United States
Environmental Protection
Agency
-------
-------
U.S. Environmental Protection Agency
Office of Water (4303T)
1200 Pennsylvania Avenue, NW
Washington, DC 20460
EPA-821-R-03-002
-------
-------
Economic Analysis of the Final Revisions to the
National Pollutant Discharge Elimination System Regulation
and the Effluent Guidelines for
Concentrated-Animal Feeding Operations
Christine Todd Whitman
Administrator
0. Tracy Mehan HI
Assistant Administrator, Office of Water
Sheila E. Frace
Director, Engineering and Analysis Division
Renee Selinsky Johnson
Project Co-Lead/Economist
Engineering and Analysis Division
Office of Science and Technology
U.S. Environmental Protection Agency
Washington, DC 20460
EPA-821-R-03-002
-------
11
-------
ACKNOWLEDGMENTS AND DISCLAIMER
This document was prepared by EPA's Office of Water's Office of Science and Technology with
the support of Eastern Research Group Incorporated.
Neither the United States government nor any of its employees, contractors, subcontractors, or
other employees make any warranty, expressed or implied, or assume any legal liability or
responsibility for any third party's use of, or the results of such use of, any information, apparatus,
product, or process discussed in this report, or represent that its use by such a third party would
not infringe on privately owned rights. '
m
-------
IV
-------
CONTENTS
EXECUTIVE SUMMARY
ES.l Introduction - ES-1
ES.2 Data and Methodology . : ES-2
ES.2.1 Data Sources : ES-2
ES.2.2 Methodology ; ES-3
ES.3 Regulated Cpximunity ES-6
ES.4 Annual Incremental Costs ES-7
ES.4.1 Costs to Regulated CAFOs ES-7
ES.4.2 Costs to the NPDES Permitting Authority ES-10
ES.5 Financial Effects ».. . ES-10
ES.5.1 Existing CAFOs ES-10
ES.5.2 SmallBusiness CAFOs ES-13
ES.5.3 New CAFOs ES-16
ES.5.4 National Markets ES-16
ES.6 Cost-Benefit Analysis '; ES-17
ES.7 Other Information , , ES-18
ES.8 Organization of the Report ..', '. ES-19
SECTION ONE REQUIREMENTS OF THE FINAL CAFO REGULATIONS
1.1 Summary of Existing Regulatory Framework 1-2
1.1.1 NPDES Permit Regulation of CAFOs 1-2
1.1.2 Effluent Limitations Guidelines for Feedldts 1-4
1.1.3 Industries Affected by the Final CAFO Regulations 1-4
1.2 Summary of the Proposed Rulemaking 1-6
1.2.1 The 2001 Proposal! 1-6
. 1.2.1.1 NPDES Permit Regulation 1-6
1.2.1.2 Effluent Limitations Guidelines and Standards 1-7
1.2.2 The 2001 Notice of Data Availability 1-8
1.2.3 The 2002 Notice of Data Availability 1-8
1.3 Summary of the Final Revisions : 1-8
1.3.1 NPDES Permit Regulation 1-8
1.3.2 Effluent Limitations Guidelines and Standards 1-10
-------
SECTION TWO
DATA AND METHODOLOGY FOR ESTIMATING COMPLIANCE
COSTS AND ECONOMIC EFFECTS
2.1 BACKGROUND AND OVERVIEW 2-1
2.1.1 Overview of Analytical Framework 2-1
2.1.2 Overview of Sources of Data 2-2
2.1.3 Overview of EPA's Economic Model (2001 Proposal) 2-4
2.1.4 Overview of Changes to EPA's Economic Model (Final Rule) 2-5
2.2 ESTIMATES OF ANNUAL COMPLIANCE COSTS 2-6
2.2.1 Development of Representative Model CAFOs 2-6
2.2.2 Compliance Assumption under Existing Regulations 2-7
2.2.3 Method for Estimating CAFO Compliance Costs 2-10
2.2.4 Cost Annualization Methodology 2-13
2.3 BASELINE FINANCIAL DATA FOR EPA MODEL CAFOs 2-14
2.3.1 Sources of Data 2-15
2.3.1.1 USDA's Agricultural Resource Management Study 2-15
2.3.1.2 Data from Various Land Grant Universities 2-17
2.3.1.3 Data from National Cattlemen's Beef Association ..... 2-18
2.3.2 Data Selection and Modification for EPA's Financial Models 2-19
2.3.2.1 Cattle Sector 2-20
2.3.2.2 Dairy Sector 2-23
2.3.2.3 Hog Sector 2-25
2.3.2.4 Poultry Sector 2-28
2.3.3 Matching of EPA Cost Models and EPA Financial Models 2-30
2.4 METHODOLOGY TO ASSESS IMPACTS ON MODEL CAFOs 2-39
2.4.1 Assessment Criteria and Financial Data Variables 2-39
2.4.1.1 Sales Test Using Gross Cash Income 2-40
2.4.1.2 DCF Analysis Using Net Cash Income 2-43
2.4.1.3 Debt Test Using Debt-Asset Ratios 2-47
2.4.2 Criteria for Assessing Financial Effects 2-48
2.4.2.1 Decision Matrix for "Economic Achievability" 2-49
2.4.2.2 Analysis of Effects at Multiple Business Levels 2-53
2.4.2.3 Basis for Benchmark Values for Assessment Criteria 2-57
2.4.3 Supplemental Analyses 2-61
2.4.3.1 Market Impacts on Facility Income 2-61
2.4.3.2 Cost-Share Assistance 2-65
2.4.3.3 Value of Manure as Cost Offsets 2-68
2.5 METHODOLOGY TO ASSESS BROADER MARKET LEVEL EFFECTS 2-71
2.5.1 Market Model Methodology and Input Data 2-71
2.5.2 Public Comments on EPA's Market Analysis 2-73
-------
SECTION THREE
TOTAL COSTS AND ECONOMIC IMPACTS OF THE PROPOSED
CAFO REGULATIONS (ALL SUBCATEGORIES)
3.1 Identification and Number of Affected CAFOs 3-1
3.1.1 Identification of Affected Industry Sectors 3-1
3.1.1.1 Beef Subcategory 3-1
3.1.1.2 Dairy Subcategory 3-2
3.1.1.3 Hog Subcategory 3-2
3.1.1.4 Poultry Subcategory 3-3
3.1.2 Estimated Number of AFOs and Regulated CAFOs 3-3
3..2 Estimated Annual Costs of the Final CAFO Regulations '. 3-7
3.2.1 Compliance Costs to CAFOs Under the Final Regulations 3-7
3.2.2 Comparison with the Proposed Regulations 3-9
3.3 Estimated Financial Effects on Existing Operations (BAT Analysis) 3-13
3.3.1 Baseline Financial Health of Model CAFOs 3-13
3.3.2 Financial Effects under the Final Regulations 3-13
3.3.3 Sensitivity Analysis Under Alternative Cash Flow Calculations 3-14
3.3.4 Supplemental Analyses 3-17
3.3.4.1 Market Impacts on Facility Income 3-17
3.3.4.2 Cost Share Assistance 3-19
3.3.5 Comparison with the Proposed Regulations 3-19
3.4 Estimated Financial Impacts to New Operations (NSPS Analysis) 3-21
3.4.1 Beef and Dairy Subcategories 3-23
3.4.2 Swine, Veal, and Poultry Subcategories 3-24
3.4.3 Comparison with the Proposed Regulations 3-26
3.5 Market Impacts 3-26
3.5.1 . Market Analysis Results Across All Subcategories 3-27
3.5.1.1 Commodity Prices and Quantities 3-27
3.5.1.2 Aggregate Employment and National Economic Output 3-29
3.5.1.3 Regional and Community Impacts 3-31
3.5.1.4 Foreign Trade Impacts 3-34
3.5.2 Market Analysis Results Across Individual Subcategories 3-34
3.5.2.1 Beef Sector 3-35
3.5.2.2 Dairy Sector 3-35
3.5.2.3 Hog Sector 3-36
3.5.2.4 Poultry Sector '.. 3-37
VII
-------
SECTION FOUR INITIAL REGULATORY FLEXIBILITY ANALYSIS
4.1 THE REGULATORY FLEXIBILITY ACT AS AMENDED BY THE SMALL
BUSINESS REGULATORY ENFORCEMENT FAIRNESS ACT 4-1
4.2 INITIAL ASSESSMENT 4-1
4.2.1 Definition of Small CAFO Businesses , 4-2
4.2.2 Number of Small Businesses Affected 4-4
4.2.3 Results of the Initial Assessment for the 2001 Proposal 4-8
4.3 EPA COMPLIANCE WITH RFA REQUIREMENTS 4-9
4.3.1 Outreach and Small Business Advocacy Review 4-9
4.3.2 EPA's Final Regulatory Flexibility Analysis 4-10
4.3.2.1 Need for and Objectives of the CAFO Regulations 4-10
4.3.2.2 Significant Comments in Response to the IRFA 4-11
4.3.2.3 Description and Estimate of Number of
SmallEntities Affected 4-13
4.3.2.4 Description of the Reporting, Recordkeeping,
and Other Requirements 4-15
4.3.2.5 Steps Taken to Minimize Significant Economic
Impacts on Small Entities 4-17
4.4 EPA'S ANALYSIS OF SMALL BUSINESS IMPACTS 4-18
4.4.1 Data and Methodology 4-18
4.4.2 Economic Analysis Results 4-21
SECTION FIVE OTHER REGULATORY ANALYSIS REQUIREMENTS
5.1 Additional Administrative and Regulatory Analyses 5-1
5.1.1 Requirements of Executive Order 12866 5-1
5.1.2 Requirements of the Unfunded Mandates Reform Act (UMRA) 5-2
5.2 Need for the Regulations 5-3
5.3 Total Social Costs 5-4
5.3.1 Costs to Regulated CAFOs 5-4
5.3.2 Costs to the Permitting Authority (Federal and State Governments) 5-5
5.3.3 Other Social Costs 5-6
5.4 Pollutant Reductions 5-9
5.5 Comparison of Cost and Benefits Estimates 5-10
SECTION SIX
REFERENCES
Vlll
-------
APPENDIX A
COST ANNUALIZATION MODEL
A.1 Input Data Sources A-l
A.1.1 Marginal Tax Rate A-2
A.1.2 Depreciation Method A-3
A.2 Sample Cost Annualization Spreadsheet A-4
APPENDIX B SUMMARY TABLES:
ANNUALIZED COSTS PER FACILITY AND PER ANIMAL
APPENDIX C METHODOLOGY TO ASSESS MARKET EFFECTS ON CAFO
REVENUE
C.I Methodology to Estimate Changes in Farm Revenue C-l
C.2 Application to Discounted Cash Flow Analysis C-3
C.3 Use of Alternative Revenue Scenario in Impact Estimation C-5
APPENDIX D SUMMARY TABLES:
ESTIMATED CAFO FINANCIAL EFFECTS
APPENDIX E COST-EFFECTIVENESS ANALYSIS
E.I Pollutants of Concern E-2
E.I.I Introduction .. E-2
E.I."2 Pollutant Concentrations in Animal Manure and Wastewater E-3
E.2 Estimated Pollutant Removals E-6
E.3 Cost-Effectiveness Analysis: Nutrients and Sediments E-8
E.3.1 Review of Literature E-8
E.3.2 Cost-Effectiveness Results , E-12
E.4
Cost-Effectiveness Analysis: Toxic Pollutants E-14
IX
-------
TABLES AND FIGURES
Table
ES-1 Number of Potential Operations Defined or Designated as CAFOs, 1997 ES-7
ES-2 Annual Pre-tax Cost of the Rule, $2001 (Option 1 & Option 2) ES-9
ES-3 Financial Effects of the ELG on CAFOs (>1,000 ALT), Option 1 and Option 2 ES-12
ES-4 Results of EPA's Small Business Analysis, Option 1 and Option 2 ES-15
ES-5 Total Annual Monetized Social Costs and Benefits (millions $2001), >1,000 AU ES-18
1-1 Number of Animal Feeding Operations (1997) 1-6
1-2 Summary Description of Options/Scenarios Considered by EPA 1-9
2-1 Model CAFO Assumption by Sector, Size, and Region
(Size Range and Average Inventory) '.... 2-33
2-2 Financial Input Data, Farm Level 2-34
2-3 Financial Input Data, Enterprise Level 2-35
2-4 Baseline Projections, Returns Per unit, 1997-2006 2-36
2-5 Net Cash Income Components from Available Data 2-36
2-6 Projected Cash Stream for Farms (1997-2006) 2-37
2-7 Projected Cash Stream for Enterprises (1997-2006) 2-38
2-8 Economic Achievability Criteria for the Final CAFO Regulations 2-52
2-9 Selected Elasticity Estimates and Estimated Regulatory Price Effect 2-65
2-10 Market Model Baseline Values (1997) 2-77
2-11 RIMS n Multipliers for Secondary Impact Analysis 2-78
3-1 Number of AFOs and Potential CAFOs (1997) 3-5
3-2 Number of Potential Operations Defined, as CAFOs (1997) 3-6
3-3 Number of Potential Operations Designated as CAFOs (1997-2001) 3-6
3-4 Annual Pre-tax Cost of the Rule, $2001 (Option 1 & Option 2) 3-8
3-5 Pre-tax ELG Option Costs, by Sector and Size Group ($2001) 3-10
3-6a Per Head ELG Option Costs (Minimum and Maximum), by Sector and Size Group ($1997). 3-11
3-6b Costs as a Share of Model CAFO Total Operating Costs (Minimum and Maximum), ($1997) ., 3-12
3-7 Financial Effects of the ELG on CAFOs (>1,000 AU), Option 1 and Option 2 3-15
3-8 Financial Effects on CAFOs: Changes to Cash Flow Calculations (Option 2) 3-16
3-9 Financial Effects to CAFOs: Partial Cost Passthrough (Option 2) 3-18
3-10 Financial Effects on CAFOs: Partial Cost-Share Assistance (Option 2) 3-20
3-11 Model CAFOs where Compliance Costs result hi Financial Stress (Alternative Options) .. 3-22
3-12 Percent Difference hi Costs between NSPS and BAT Costs, Beef and Dairy Sectors 3-24
3-13 Percent Difference between NSPS and BAT Costs, Hog and Poultry Sector 3-25
3-14 Facility Level Cost Comparison - New versus Existing Sources (>1000 AU) 3-26
3-15 Post-Compliance Farm Level Price Changes 3-28
3-16 Post-Compliance Retail Level Price Changes 3-28
3-17 Post-Compliance Farm Production Changes 3-29
3-18 Post-Compliance Changes in Total National Employment (FTEs) 3-30
3-19 Post-Compliance Changes in Total National Economic Output (GDP) 3-31
3-20 Regional Distribution of Predicted National Employment Reductions 3-32
3-21 Farm Production Region Distribution of Predicted Changes hi (Direct)
National Employment 3-33
3-22 Post-Compliance Retail Product Import and Export Changes 3-34
3-23 Summary of Market Model Results for the Beef Sector 3-38
3-24 Summary of Market Model Results for the Dairy Sector 3-39
3-25 Summary of Market Model Results for the Hog Sector 3-40
-------
3-26 Summary of Market Model Results for the Broiler Sector 3-41
3-27 Summary of Market Model Results for the Egg-Laying Sector .... 3-42
3-27 Summary of Market Model Results for the Turkey Sector 3-43
4-1 SBA Revenue Size Standards for Small Livestock and Poultry Operations 4-3
4-2 Number of Small CAFOs That Might Be Affected by the Proposed Regulations 4-6
4-3 Total Number of Small CAFO Businesses Subject to Regulation 4-8
4-4 Numbers of Small CAFO Business by Sector, Size Grouping and Region, 4-14
4-5a Results of EPA's Small Business Analysis (Option 1) 4-23
4-5b Results of EPA's Small Business Analysis (Option 2) 4-25
5-1 Annual Pre-tax Cost of the Rule, $2001 (Option 2) 5-7
5-2 Number of CAFO Permits by Region, State, and Sector (1997) 5-8
5-3 Edge of Field Loading Reductions for CAFOs (Option 2, >1,OOOAU), All Sectors 5-9
5-4 Edge-of-Field" Loading Reductions (All Contributions), Nitrogen 5-11
5-5 Edge-of-Field Loading Reductions (All Contributions), Phosphorus 5-11
5-6 Edge-of-Field Loading Reductions (All Contributions), Sediment 5-12
5-7 Total Annual Monetized Social Costs and Benefits (7% Rate): CAFOs >1,OOOAU 5-13
5-8 Total Annual Monetized Social Costs and Benefits (3% Rate): CAFOs >1,OOOAU 5-14
A-l State Tax Income Rates A-6
A-2 IRS Asset Class Lives and Recovery Periods for the Annualization of Capital Costs' A-8
A-3. Cost Annualization Model A-9
C-l Selected Elasticity Estimates and Estimated Regulatory Price Impact C-3
C-2 Selected High and Low Elasticity Estimates and Estimated Regulatory Price Effect... C-6
E-l Leading Sources and Pollutants of Water Quality Impairment in the United States, 1998 ... E-4
E-2 Summary of Statistics from the National U.S. Water Quality Impairment Survey, 1998 E-4
E-3 Nutrients, Metals, and Pathogens in Livestock and Poultry Manures E-5
E-4 Summary of Pollutant Removal Cost Estimates and Benchmarks E-ll
E-5 Cost-Effectiveness Results: Nutrients ($2001), Option 1 & Option 2 E-13
E-6. Cost-Effectiveness Results: Sediments ($2001), Option 1 & Option 2 E-14
E-7. Total Metal Removals ("At Stream" Concentrations) E-16
Figure ,,
2-1 Schematic of EPA's Decision Matrix of "Economic Achievabilityv 2-53
C-l Impact of the Effluent Guideline on Market for Livestock/Poultry Type i C-7
C-2 Effect of Price Elasticity of Demand on Change in Market Price Due to Impact of Effluent
Guideline on Market for Livestock/Poultry C-8
XI
-------
ACRONYMS
AFO animal feeding operation
ARMS Agricultural Resource Management
Study
ASAE American Society of Agricultural
Engineers
AU animal unit
BAT Best Available Technology
BATEA Best Available Technology
Economically Achievable
BLS Bureau of Labor Statistics
BMP best management practice
BNR biological nutrient removal
BOD biological oxygen demand
BPJ best professional judgment
C-E cost-effectiveness
CAFO concentrated animal feeding
operation
CARD Center for Agriculture and Rural
Development
CC/Q compliance costs per unit sold
CCI Construction Cost Index
CE Central
COD chemical oxygen demand
CWA Clean Water Act
DCF discounted cash flow
EA economic analysis
EBITDA earnings before interest, taxes,
depreciation, and amortization
ELG effluent limitations guidelines
EMS environmental management system
EO Executive Order
EPA Environmental Protection Agency
EQIP Environmental Quality Incentives
Program
ERS Economic Research Service
FAPRI Food and Agricultural Policy
Research Institute
FF farrow-finish and farrowing
FFSC Farm Financial Standards Council
FRFA final regulatory flexibility analysis
FTE full-time equivalent
GDP Gross Domestic Product
GF grow-finish
ICR Information Collection Request
IRFA initial regulatory flexibility analysis
IRS Internal Revenue Service
LCBP Lake Champlam Basin Program
MA Mid-Atlantic
MACRS Modified Accelerated Cost
Recovery System
MW Midwest
NAICS North American Industry
Classification System
NASS National Agricultural Statistics
Service
NCBA National Cattlemen's Beef
Association
NCSU North Carolina State University
NEWWT Northeast Wisconsin Waters for
Tomorrow, Inc.
NFI net farm income
NMPF National Milk Producers
Federation
NOI Notice of Intent
NPDES National Pollutant Discharge
Elimination System
NPPC National Pork Producers Council
NRCS Natural Resources Conservation
Service
NRDC Natural Resources Defense Council
NSPS New Source Performance
Standards
O&M operation and maintenance
OSHA Occupational Safety and Health
Administration
PA Pacific
POTW publicly owned treatment works
RFA Regulatory Flexibility Act
XII
-------
RIMS II Regional Input-Output Modeling
System
SBA Small Business Administration
SBAR Small Business Advisory Review
SBREFA Small Business Regulatory
Enforcement Fairness Act
SER Small Entity Representative
SIC • Standard Industrial Classification
SO South
TIAER Texas Institute for Applied
Environmental Research
TSS total suspended solids
TWF toxicity weighting factor
UMRA Unfunded Mandates Reform Act
USDA United States Department of
Agriculture
WASDE World Agricultural Supply and
Demand Estimates
WWTP wastewater treatment plant
xm
-------
-------
EXECUTIVE SUMMARY
ES.1 INTRODUCTION
The U.S. Environmental Protection Agency (EPA) is revising and updating the two primary
regulations that ensure that manure, wastewater, and other process waters generated by concentrated
animal feeding operations (CAFOs) do not impair water quality. EPA's final regulatory changes affect
the existing National Pollutant Discharge Elimination System (NPDES) provisions and the existing
effluent limitations guidelines (ELG) for "feedlots." The NPDES provisions define and establish permit
requirements for CAFOs, and the ELG establish the technology-based effluent discharge standard that is
applied to CAFOs. Existing regulations were originally promulgated in the 1970s. EPA is revising the
regulations to address changes that have occurred in the animal industry sectors over the past 25 years, to
clarify and improve implementation of CAFO requirements, and to improve the environmental protection
achieved under these regulations. Final revisions to the NPDES and ELG regulations are referred to in
this report as the final CAFO regulations.
On January 12, 2001, EPA published a proposal to revise and update these regulations (66 FR
2959), referred to in this report as the "2001 Proposal." The Economic Analysis that supports the 2001
Proposal contains information on EPA's estimates of the cost, financial effects, and monetized benefits
of the proposed revisions. That analysis, titled Economic Analysis of the Proposed Revisions to the
National Pollutant Discharge Elimination System Regulation and the Effluent Guidelines for
Concentrated Animal Feeding Operations, is referred to in this report as the "Proposal EA" (USEPA,
2001a). EPA also published two Notices of Data Availability in the Federal Register (66 FR 58556 and
67 FR 48099). These Notices present new data and information EPA has received since the 2001
Proposal, soliciting further public review and comment.
The revisions EPA is promulgating affect who must apply for a permit under the NPDES
program, who is subject to the ELG, and what the ELG requires. A summary of the current, proposed,
and final NPDES and ELG regulations for CAFOs is presented in Section 1 of this report. See Section 4
of the final rule preamble for a discussion of the final regulations.
This Economic Analysis (EA) summarizes EPA's analysis of the estimated annual compliance
costs and the economic impacts that may be incurred by affected operations that are subject to the final
revisions. Additional information on the regulatory alternatives considered by EPA for the 2001
Proposal are presented in the EA supporting the proposed regulations (USEPA, 200la). The report
covers financial impacts to CAFOs, potential impacts on processors of livestock and poultry products,
and market and other secondary impacts such as impacts on prices, quantities, trade, employment, and
output. It also responds to requirements for small business analyses under the Regulatory Flexibility Act
(RFA) as amended by the Small Business Regulatory Enforcement Fairness Act (SBREFA) and for cost-
benefit analyses under Executive Order 12866 and the Unfunded Mandates Reform Act (UMRA).
This EA summarizes EPA's analysis of the estimated annual compliance costs and the economic
impacts that may be incurred by affected operations that are subject to the final revisions. EPA also
provides additional material on the final CAFO regulations in the Development Document for the Final
Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent
Guidelines for Concentrated Animal Feeding Operations, which discusses how the Agency estimated the
compliance costs of the final regulations. EPA's detailed benefit analysis, titled Environmental and
ES-1
-------
Economic Benefit Analysis of the Final Revisions to the National Pollutant Discharge Elimination
System Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations, provides
information about existing water quality impairments associated with animal production operations and
estimates the extent to which these impairments might be mitigated by the final CAFO regulations.
ES.2 DATA AND METHODOLOGY
ES.2.1 Data Sources
EPA did not conduct an industry-wide survey of all CAFOs. Rather, the Agency is relying on
existing data sources and expertise provided by numerous government agencies, state agricultural
extension service agencies, and land grant universities, as well as information from industry trade
associations, agricultural professionals, and environmental groups. This data collection effort is
described in the 2001 Proposal (66 FR 2960) and detailed in the Proposal EA. Major data sources are
discussed in detail where they are used to conduct the analyses presented in this report or reference other
supporting documents in the rulemaking record.
For its engineering cost analysis, EPA uses industry and cost information from various sources,
Including USDA, the land grant universities, state agricultural extension agencies, and industry. EPA
uses these data to develop its model CAFOs and to extrapolate CAFO level costs to all operations
nationwide. A key source of data used to estimate compliance costs and economic impacts on the
regulated community is the 1997 Census of Agriculture. The Census is conducted by the National
Agricultural Statistical Service (NASS) every five years and provides information on the number of
feedlots, their geographic distributions, the amount of cropland available to land apply animal manure
generated from animal confinement operations, and other information. These data are compiled by
NASS, with the assistance of personnel at USDA's Natural Resources Conservation Service (NRCS), •
who developed a methodology to identify information specific to animal confinement operations. All
Census data provided to other government agencies, including EPA, are aggregated to preserve
confidential business information. As detailed in the 2001 Notice, EPA has received additional data and
information since proposal that have been incorporated into the Agency's analysis for the final
regulations. EPA's Development Document supporting the proposed and final rule (USEPA, 2001 and
2002) presents the Census data used along with other USDA data and other source data that EPA uses for
its cost analysis.
For EPA's economic impact analysis, the Agency obtained financial data for livestock and
poultry operations from a variety of sources, including USDA, the land grant universities, and industry.
EPA uses these data to depict baseline financial conditions at representative model CAFOs and to
extrapolate CAFO level impacts to all operations nationwide. As detailed in both the 2001 Notice and
the 2002 Notice, EPA received additional data and information since proposal that have been
incorporated into the Agency's analysis for the final regulations. To assess broader market changes from
the CAFO regulations, EPA compiled additional industry and market data from a wide range of USDA
data and land grant university research. A detailed summary of the data and citations of the sources of
these data are provided in the Proposal EA, supplemented by data and other information presented in this
report,
A key source of financial data is USDA's Agricultural Resource Management Study (ARMS).
This study is compiled by NASS and USDA's Economic Research Service (ERS) and provides complete
ES-2
-------
financial accounting data for U.S. farms for each of the major commodity sectors affected by the final
CAFO regulations. These data are used to depict farm financial conditions and to evaluate regulatory
impacts. ERS provided data for representative farms that were obtained through special tabulations of
the available survey data, conducted by ERS, that differentiate the financial conditions among operations
by commodity sector, facility size (number of animals onsite), and major farm producing region. As with
the Census data, USDA aggregated these data in a manner that preserves both the statistical
representativeness and confidentiality of the respondent survey data. EPA also obtained financial data
from various land grant universities, including enterprise budgets that portray financial conditions for an
operation's livestock or poultry enterprise. In particular, the University of Missouri's Food and
Agricultural Policy Research Institute (FAPRT) submitted financial data for several sectors that had been
collected as part of their evaluation of EPA's Proposal EA. EPA also obtained financial data from the
National Cattlemen's Beef Association (NCBA) based on a survey of its membership to obtain financial
statistics specific to cattle feeding operations. Section 2.3 and other sections of this report discuss these
data in more detail and describe how these data sources contribute to EPA's analyses.
ES.2.2 Methodology
EPA assessed financial effects on regulated CAFOs based on predicted changes to.select
financial criteria. The economic model that EPA used to evaluate financial impacts on CAFOs uses a
representative farm approach. Under this general framework, EPA constructed a series of model
facilities ("model CAFOs") that reflect EPA's estimated compliance costs and readily available financial
data. EPA used these model CAFOs to develop an average characterization for a group of operations
based on certain distinguishing characteristics for each sector, such as facility size and production region,
that can be shared across a broad range of facilities.
EPA developed two sets of models for determining economic impacts at animal confinement
operations—cost models and financial models. EPA evaluated compliance costs based on more than 170
farm level cost models that were developed to depict conditions at and to evaluate compliance costs for
select representative CAFOs. The cost models are differentiated by commodity sector, farm production
region, facility size, and land availability for application of manure. EPA's cost models provide the
estimated compliance costs, which are compared to corresponding financial models that characterize
financial conditions across different types of operations. (Like the cost models, the financial models are
also differentiated by sector, facility size, and production region.) Economic impacts under a post-
regulatory scenario are approximated by extrapolating the average impacts for a given model CAFO
across the larger number of operations that share similar production characteristics and are identified by
that CAFO model. A summary of this overall approach is provided in Section 2.
For the purpose of estimating the costs that would be incurred by CAFOs to comply with the
regulations, EPA estimated costs associated with four broad cost components: nutrient management
planning, facility upgrades, land application, and technologies for balancing on-farm nutrients. Nutrient
management planning costs include manure and soil testing, record-keeping, and plan development.
Facility upgrades reflect costs for additional or improved manure storage, mortality handling, runoff
controls, reduction of fresh water use where appropriate, and additional farm management practices.
Land application costs address agricultural application of nutrients, including hauling of excess manure
off-site and adjusting for changes in commercial fertilizer needs, and reflect differences among
operations based on cropland availability for manure application.
ES-3
-------
EPA evaluated compliance costs using a representative facility approach based on approximately
1,600 farm level cost models to depict conditions and to evaluate compliance costs for select
representative CAFOs. The major factors used to differentiate individual model CAFOs include the
commodity sector, the farm production region, and the facility size (based on herd or flock size or the
number of animals on-site). EPA's model CAFOs primarily reflect the major animal sector groups,
including beef cattle, dairy, hog, broiler, turkey, and egg laying operations. Practices at other subsector
operations are also reflected in the cost models, such as replacement heifer operations, veal operations,
flushed-cage layers, and hog grow-finish and farrow-finish facilities.
Another key distinguishing factor incorporated into EPA's cost models is information on the
availability of cropland and pastureland for land application of manure nutrients. For this analysis,
nitrogen and phosphorus rates of land application were evaluated for three categories of cropland
availability: (1) CAFOs with sufficient cropland for all manure generated on-site; (2) CAFOs with some,
but not enough, cropland to accommodate all of the manure produced at the facility; and (3) CAFOs with
no cropland. EPA used USDA data to determine the number of CAFOs within each of these categories.
This information takes into account which nutrient (nitrogen or phosphorus) is used as the basis to assess
land application and nutrient management costs. Additional information on this costing approach is
provided in Section 2 of this report.
For the purpose of estimating costs and financial effects to CAFOs with between 300 and 1,000
AU, EPA assumes that costs that will be incurred by those sized operations to comply with BPJ-based
limitations under the revised NPDES regulations are similar to the estimated costs that would be incurred
if operations with between 300 and 1,000 AU had to comply with the ELG.
To estimate the impacts of the final regulations, EPA examined the economic effects on
regulated CAFOs and national markets. Estimated financial impacts on regulated entities cover both
existing and new CAFOs that will be affected by the final regulations. Results presented here focus on
economic effects from the CAFO regulations affecting CAFOs with more than 1,000 AU because only
large facilities will be subject to the effluent guidelines and NSPS. EPA's analysis also presents the
estimated effects on existing operations that are small businesses.
EPA evaluated the economic achievability of the rule on existing operations based on changes in
representative financial conditions across three financial criteria: (1) an initial screening comparing
incremental post-tax costs to total gross revenue ("sales test"), (2) projected post-compliance cash flow
over a 10-year period ("discounted cash flow analysis"), and (3) an assessment of an operation's debt-to-
asset ratio under a post-compliance scenario ("debt-asset test").
EPA used the results from these analyses to divide affected CAFOs into three financial impact
categories: Affordable, Moderate, and Stress. CAFOs experiencing affordable or moderate impacts are
considered to have some financial impact on operations, but EPA does not expect the costs of complying
with this rule to make these operations vulnerable to closure. EPA considers that for CAFOs in both the
"Affordable" and "Moderate" impact categories the final requirements are likely to be economically
achievable. Operations experiencing financial stress, however, are considered to be vulnerable to closure
because of the costs of this rule. EPA considers that for CAFOs in the "Stress" impact category, the final
requirements are likely not economically achievable. EPA believes that there may be mitigating factors
that could reduce the number of facilities experiencing financial stress, such as the availability of cost-
, share assistance and long-run market adjustment.
ES-4
-------
EPA conducted its analysis first at the farm level based on data reflecting financial conditions for
the entire farm operation (e.g., reflecting incoine and cost information spanning the entire operation, thus
considering the operation's primary livestock production, along with other income sources such as
secondary livestock and crop production, government payments, and other farm-related income). Based
on the farm level results, EPA also assessed the financial effects on CAFOs.at the enterprise level (e.g.,
limiting the scope of the assessment to the operation's livestock or poultry enterprise, and excluding
other non CAFO-related sources of income from the analysis). By evaluating the financial criteria at
both the farm level and the enterprise level, EPA's analyses address comments expressed by many
commenters, including FAPRI, other land grant university researchers, and industry, as well as USD A.
Starting with the farm level analysis, EPA considers the regulations to be economically
achievable for a representative model CAFO if the average operation has a post-compliance sales test
estimate within an acceptable range, a positive post-compliance cash flow over a 10-year period, and a
post-compliance debt-to-asset ratio not exceeding a benchmark value. Specifically, if the sales test
shows that compliance costs are less than 3 percent of sales, or if post-compliance cash flow is positive
and the post-compliance debt-to-asset ratio does not exceed a benchmark (depending on the baseline
data) and compliance costs are less than 5 percent of sales, EPA considers the options to be "Affordable"
for the representative CAFO group. (Although a sales test result of less than 3 percent does indicate
"Affordable" in the farm level analysis, further analysis is conducted to determine the effects at the
operation's livestock or poultry enterprise.) The benchmark values assumed for the debt-asset test are
sector-specific. EPA assumes a 70 percent benchmark value for the debt-asset test to indicate financial
stress in the hog and dairy sectors, and an 80 percent benchmark for the debt-asset test to indicate
.financial stress in the beef cattle sector. These benchmark values address public comment received and
alternative debt and asset data submitted for the livestock sectors. For the poultry sectors, however, EPA
did not obtain alternative debt and asset data and continues to evaluate data used for proposal against a
40 percent benchmark value. .
A sales test of greater than 5 percent but less than 10 percent of sales with positive cash flow and
a debt-to-asset ratio of less than these sector-specific debt-asset benchmark values is considered
indicative of some impact at the CAFO level, but at a level not as severe as those indicative of financial
distress or vulnerability to closure. These impacts are labeled "Moderate" for the representative CAFO
group. EPA considers both the "Affordable" and "Moderate" impact categories to be economically
achievable by the CAFO, subject to the enterprise analysis (see below). If, with a sales test of greater
than 3 percent, post-compliance cash flow is negative or the post-compliance debt-to-asset ratio exceeds
these sector-specific debt-asset benchmarks, or if the sales test shows costs equal to or exceeding 10
percent of sales, EPA considers the final regulations to be associated with potential financial stress for
the entire representative CAFO group. In such cases, each of the operations represented by that group
might be vulnerable to closure. For operations that are determined to experience financial "Stress" at the
farm level, the final requirements are likely npt economically achievable.
The enterprise level analysis builds'on the farm level analysis, evaluating effects at a farm's
livestock or poultry enterprise. If the farm level analysis shows that the regulations impose "Affordable"
or "Moderate" effects on the operation, the enterprise level analysis is conducted to determine whether
the enterprise's cash flow is able to cover the cost of regulations. This analysis uses a discounted cash
flow approach similar to that used to assess the farm level effects, in which the net present value of cash
flow is compared to the net present value of the total cost of the regulatory options over the 10-year time
frame of the analysis. Over the analysis period, if an operation's livestock or poultry enterprise
maintains a cash flow stream that both exceeds the cash costs of the rule (operating and maintenance
ES-5
-------
costs plus interest) and covers the net present value of the principal payments on the capital, EPA
concludes that the enterprise will likely not close because of the CAFO rule. This analysis is conducted
on a pass/fail basis. If the net present value of cash flow minus the net present value of the rule's costs is
greater than zero, the enterprise passes the test and the enterprise is assumed to continue to operate. EPA
considers these results to indicate that the final requirements are economically achievable. If the net
present value of cash flow, is not sufficient to cover the net present value of the cost of the rule, EPA
assumes that the CAFO operator would consider shutting down the livestock or poultry enterprise. That
is, if an operation fails the enterprise level analysis, these operations are determined to experience
financial "Stress" and the final requirements are likely not economically achievable.
In response to comments, EPA conducted additional supplemental analysis to determine the
effects of the regulation under two different scenarios. One scenario takes into consideration the effects
of long-run market adjustment following implementation of the final regulations. This analysis is
conducted using simulated changes in producer revenue given changes in market prices as depicted by
EPA's market model, which uses estimates of price and quantity response in these markets. A second
scenario takes into consideration potential cost share assistance under Federal arid State conservation
programs, assuming that a portion of costs are covered by cost sharing subject to programmatic
constraints. Given the uncertainty of whether CAFO income will rise in response to long-run market
adjustment or whether available cost share dollars will effectively offset compliance costs at regulated
CAFOs, EPA's analysis to determine whether the regulation is "economically achievable" does not rely
on such assumptions as part of its regulatory analysis and therefore reflects the highest level of impacts
projected. However, EPA presents the results of this analysis assuming both some degree of cost
passthrough and no cost passthrough, as well as some degree of cost share assistance and no cost share
assistance, along with the results of its lead analysis. More information on this decision framework is
provided in Section 2.
EPA's market analysis evaluates the effects of the final regulations on national markets. This
analysis uses a linear partial equilibrium model adapted from the COSTBEN model developed by
USDA's Economic Research Service. The modified EPA model provides a means to conduct a long-run
static analysis to measure the market effects of the final regulations in terms of predicted changes in farm
and retail prices and product quantities. Market data used as inputs to this model are from a wide range
of USD A data and land grant university research. Once price and quantity changes are predicted by the
model, EPA uses national multipliers that relate changes in sales to changes in total direct and indirect
employment and also to national economic output. These estimated relationships are based on the
Regional Input-Output Modeling System (RIMS E) from the U.S. Department of Commerce. The details
of the market analysis are described in Section 2 and also in the Proposal EA.
Additional information on how EPA developed the cost models is provided in the Development
Document. See also EPA's detailed responses to public comments received on proposal and both Notices
of Data Availability published on this rule. These comments and the Agency's response are in the
Comment Response Document that is available in the rulemaking record.
ES3 REGULATED COMMUNITY
The animal sectors covered in this analysis include the cattle, veal, heifer, dairy, hog, broiler, egg
layer, and turkey sectors. Not all confinement operations (animal feeding operations or AFOs) in these
sectors may be CAFOs and thus subject to the final regulations. Table ES-1 presents the estimated
ES-6
-------
number of operations that would be defined or designated as a CAFO under the final revisions. CAFOs
in the 300 to 1,000 animal units (AU)1 size category that EPA expects would be defined as CAFOs under
the existing NPDES regulation are labeled in table as "Status Quo."
Section 2 of the Proposal EA (USEPA, 200 la) presents more detailed information on the
regulated community, including a profile of the various CAFO sectors and meat and poultry processors.
Table ES-1. Number of Potential Operations Defined or Designated as CAFOs (1997)
Sector
Cattle
Veal
Heifers
Dairy
Hogs
Broilers
Layers-dry
Layers-wet
Turkeys
Total CAFOs
Total Operations Defined as CAFOs
>1,OOOAU
300-1,000 AU
"Status Quo"
Designated
CAFOs
<1,000 AU
(number of operations)
1,766
12
242
1,450
3,924
1,632
729
383
388
10,526
174
230
7
1,949
1,485
520
26
24
37
4,452
15
0
3
30
52
52
8
2
10
172
Source: USEPA (see Section 3). "Layers: wet" are operations with liquid manure systems. "Layers: dry" are
operations with dry systems. Number of designated facilities shown over 5 year period.
ES.4 ANNUAL INCREMENTAL COSTS
ES.4.1 Costs to Regulated CAFOs
EPA estimates the annual incremental costs of compliance using the capital and recurring costs
derived in the Development Document. EPA converts these costs to incremental annualized costs, as
described in Appendix A. Annualized costs better describe the actual compliance costs that a model
As defined for the final CAFO regulations, one animal unit (AU) is equivalent to one slaughter or feeder
cattle, calf or heifer; 0.7 mature dairy cattle; 2.5 hogs (over 55 pounds) or 5 nursery pigs; 55 turkeys; 30 egg-laying
chickens (where a wet manure management system is used), and 125 broilers and 82 egg-laying chickens, regardless
of the animal waste system used.
ES-7
-------
CAFO would incur, allowing for the effects of interest, depreciation, and taxes. EPA uses these
annualized costs to estimate the total annual compliance costs and to assess the economic impacts of the
final requirements to regulated CAFOs by taking the annualized costs for each CAFO model and
aggregating them on the basis of the number of affected CAFOs represented by each model. Section 2
and Appendix A provide more details on the cost annualization methodology and results.
This EA presents the results of two technology options where EPA has estimated the cost of land
application based on nitrogen-based application rates only (Option 1) and also the cost of land
application based on nitrogen-based application rates, except hi those instances where EPA believes that
phosphorus-based rates are likely to be appropriate (Option 2). The final rule specifies that the
determination of application rates is to be based on the technical standards established by the Director
and EPA expects that these standards will require phosphorus-based application, where appropriate. The
rule also provides for these standards to include appropriate flexibilities in the use of phosphorus-based
rates, such as multi-year phosphorus application, but the potential costs savings resulting from these
flexibilities are not reflected in the analysis. As a result, the cost and economic impacts of this rule may
have been overestimated.
EPA evaluated the costs of these technology options for all operations defined as CAFOs with
more than 1,000 AU and for those operations that are defined as CAFOs with between 300 and 1,000
AU. EPA calculates these costs using the data and approaches described in the Development Document
(USEPA, 2002) and in Section 2 of this report. For the purpose of estimating total regulatory costs of the
final CAFO regulations, EPA assumes that the individual per-CAFO costs to comply with the effluent
guideline regulations are similar to the costs that will be incurred by operations with between 300 and
1,000 AU to comply with the revised NPDES requirements (although these smaller-sized operations will
be subject to BPJ and not the ELG requirements). These cost estimates, therefore, may further be
overstated for this size category.
Table ES-2 summarizes EPA's estimates of the total annualized costs to existing CAFOs due to
the regulations. The table shows these costs broken out by sector and broad facility size category.
Results are shown for both Option 1 and Option 2. As shown in the table, EPA estimates the total
estimated costs to CAFOs range from $141 million (Option 1) to $326 million annually (Option 2),
expressed as pre-tax, 2001 dollars. Roughly one-half of this cost is incurred by the dairy sector, with
another roughly 30 percent incurred within the cattle sectors (including the beef, veal, and heifer sectors).
(Total estimated social costs include an additional $9 million to Federal and State governments; see
Section 5.)
Of this total, EPA estimates that the cost to operations with more than 1,000 AU range from $119
million (Option 1) to $273 million annually (Option 2). Total estimated costs to facilities defined as
CAFOs with between 300 and 1,000 AU range from $19 million (Option 1) to $39 million annually
(Option 2). EPA estimates that of the total cost to additional operations that may be designated as
CAFOs ranges from about $3 million to $4 million annually, depending on the regulatory option. More
information on these costs is provided in Section 3, along with cost information on alternative regulatory
options EPA considered.
ES-8
-------
Table ES-2. Annual Pre-tax Cost of the Rule, $2001 (Option 1 & Option 2)
Sector
Number of Operations
CAFOs
>1,000 AU
CAFOs
300-1,000 AU
(number)
Aggregate Incremental Costs
Total
CAFOs
>1,000 AU
CAFOs
300-1,000 AU
Designated
CAFOs
($2001, millions, pre-tax)
ELG Option 1
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
1,766
12
242
1,450
3,924
1,632 ,
729
383
388
10,526
174
230
7
1,949
1,485
520
26
24
37
4,452
$19.2
-------
These aggregated cost estimates reflect pre-tax costs. However, EPA's model calculates both
pre-tax and post-tax costs (see Section 2.2.4). The post-tax costs reflect the fact that a CAFO would be
able to depreciate or expense these costs, thereby generating a tax savings. Post-tax costs thus are the
actual costs the CAFO would face. Pre-tax costs reflect the estimated total social cost of the regulations,
including lost tax revenue to governments. Pre-tax dollars are used when comparing estimated costs to
monetized benefits that are estimated to accrue under the final regulations (see Section 5). All costs
presented in this section are presented hi terms of pre-tax 1997 dollars and do not account for annual tax
savings to CAFOs. However, post-tax costs are also used to evaluate impacts on regulated facilities
using a. discounted cash flow analysis, as presented in Section 3.3. EPA's estimated compliance costs
presented in the Development Document are also estimated in 1997, dollars because 1997 is the base year
of the analysis (USEPA, 2002). Estimated costs have been converted from 1997 dollars to 2001 dollars
using the Construction Cost Index (ENR, 2002).
ES.4.2 Costs to the NPDES Permitting Authority
The NPDES permitting authority would incur additional costs to alter existing State programs
and obtain EPA approval to develop new permits, review new permit applications, and issue revised
permits that meet the final regulatory requirements. EPA expects that NPDES permitting authorities will
incur administrative costs related to the development, issuance, and tracking of general or individual
permits.
State and Federal administrative costs to issue a general permit include costs for permit
development, public notice and response to comments, and public hearings. States and EPA might also
incur costs each time a facility operator applies for coverage under a general permit due to the expenses
associated with aNOI. These per-facility administrative costs include initial facility inspections and
annual record-keeping expenses associated with tracking NOIs. Administrative costs for an individual
permit include application review by a permit writer, public notice, and response to comments. An initial
facility inspection might also be necessary.
EPA assumes that under the final regulations more than 15,500 CAFOs would be permitted.
This estimate consists of about 15,000 CAFOs covered by State permits and about 500 CAFOs covered
by Federal permits. Administrative costs incurred by State permitting authorities are expected to be $8.5
million. EPA permitting authorities will incur the remaining $0.3 million. EPA has expressed these
costs in 2001 dollars, annualized over the 5-year permit term using a 7 percent discount rate. A summary
of this analysis is available in section 10 of the preamble to the final rule. More information is is
available in Section 5 of this report. See also the NPDES Support Document (USEPA, 2002n) and in the
Development Document (USEPA, 2002).
ES.5 FINANCIAL EFFECTS
ES.5.1 Existing CAFOs
Table ES-3 presents the results of EPA's analysis of the estimated CAFO financial effects in
terms of the number of operations that will experience affordable, moderate, or stress impact because of
this rule. Results are shown by sector for CAFOs with more than 1,000 AU only. The analysis evaluates
the regulatory impacts on existing CAFOs with more-than 1,000 AU only because this size of operation
ES-10
-------
only would be subject to the ELG regulations (and, therefore, EPA has determined whether the final ELG
requirements reflect Best Available Technologies Economically Achievable or BATEA. Operations with
fewer than 1,000 AU would be subject to "Best Professional Judgement" [BPJ]).
EPA's analysis results are shown in Table ES-3. For Option 1, the analysis indicates that, among
all CAFOs with more than 1,000 AU in the veal, heifer, dairy, hog, turkey, and egg-laying sectors, the
impacts due to this rule can be characterized as "Affordable" or "Moderate." Therefore, EPA considers
this option to be economically achievable for existing facilities in these animal sectors. EPA estimates
that a total of 15 existing CAFOs (less than Ipercent of all CAFOs with more than 1,000 AU) would
experience financial stress and might be vulnerable to closure. By sector, EPA estimates that 12 beef
operations (1 percent of affected beef CAFOs) and 3 broiler operations (less than 1 percent of affected
broiler CAFOs) might close as a result of complying with the final regulations.
For Option 2, the analysis indicates that, among all CAFOs with more than 1,000 AU in the veal,
dairy, turkey, and egg-laying sectors, the impacts due to this rule can be characterized as "Affordable" or
"Moderate." Therefore, EPA considers this option to be economically achievable for existing facilities
in these animal sectors. (Moderate impacts mijght be incurred by operations in some sectors, but these
impacts are not considered to result in facility closure.) In the beef cattle, heifer, hog, and broiler sectors,
however, EPA's analysis indicates that the final rule would cause some existing CAFOs to experience
financial stress, making these operations vulnerable to facility closure. Across all sectors, EPA estimates
that 285 existing CAFOs (about 3 percent of all all CAFOs with more than 1,000 AU) would experience
financial stress and might be vulnerable to closure. By sector, EPA estimates that 49 beef operations (3
percent of affected beef CAFOs), 22 heifer operations (9 percent), 204 hog operations (5 percent of
affected hog CAFOs), and 10 broiler operations (1 percent) might close as a result of complying with the
final regulations. See Section 3 of this report for more information.
These estimates of the number of potential CAFO closures are cumulative and reflect the results
of both the farm level analysis and the enterprise level analysis. These estimated closure rates are
generally consistent with the findings of economic achievabiliry of previous effluent guidelines for other
industrial point source categories. Based on the results of this analysis, EPA concludes that both Option
1 and Option 2 would be considered economically achievable for existing CAFOs.
These results are based on an analysis that does not consider the longer term effects on market
adjustment and also available cost-share assistance from Federal and State farm conservation programs.
EPA believes that such adjustments could lessen the economic impacts of the final regulations over time.
Sections 3.3.5 show the results of this analysis under assumptions of long-run market adjustment and
cost-share assistance. !
These results reflect estimated costs for two technology options where EPA has estimated the
cost of land application based on nitrogen-based application rates only (Option 1) and also the cost of
land application based on nitrogen-based application rates, except in those instances where EPA believes
that phosphorus-based rates are likely to be appropriate (Option 2). Given that the final rule provides for
appropriate flexibilities in the use of phosphorus-based rates, such as multi-year phosphorus application,
EPA has not accounted for the potential costs savings resulting from these flexibilities in its analysis. As
a result, the economic impacts presented here may be overestimated. Also, for the purpose of this
analysis, EPA assumes that small business CAFOs with between 300 and 1,000 AU would incur costs •
similar to those estimated for CAFOs with more than 1,000 AU (although these smaller-sized operations
will be subject to BPJ and not the ELG requirements under the revised NPDES requirements). These
upper end cost estimates could, therefore, overstate the financial effects for this size category.
ES-11
-------
Table ES-3. Financial Effects of the ELG on CAFOs (>1,000 AU), Option 1 and Option 2
Sector
Number
CAFOs
(>1,OOOAU)
Affordable
Moderate
Stress
(Number)
Affordable
Moderate
Stress
(Percent of Total Operations)
ELG Option 1
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
1,766
12
242
1,450
3,924
1,632
729
383
388
10,526
1,754
12
242
1,232
3,924
1,334
729
383
388
9,998
0.
0
0
218
0
294
0
0
0
512
12
0
0
0
0
3
0
0
0
15
99%
100%
100%
85%
100%
82%
100%
100%
100%
95%
0%
0%
0%
15%
0%
18%
0%
0%
0%
5%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
ELG Option 2
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
1,766
12
242
1,450
3,924
1,632
729
383
388
10,526
1,717
12
220
1,019
3,249
1,032
729
383
388
8,749
0
0
0
431
470
590
0
0
0
1,491
49
0
22
0
204
10
0
0
0
285
97%
100%
91%
70%
83%
63%
100%
100%
100%
83%
0%
0%
0%
30%
12%
36%
0%
0%
0%
14%
3%
0%
9%
0%
5%
1%
0%
0%
0%
3%
Source: USEPA. May not add due to rounding.
"Layers: dry" are operations with dry manure systems.
"Layers: wet" are operations with liquid manure systems.
ES-12
-------
Section 3 of this report also presents the results of alternative regulatory options considered in
the 2001 Proposal. Also presented are potential closures assuming that operations with fewer than 1,000
AU might have been subject to the ELG, as was proposed by EPA.
ES.5.2 Small Business CAFOs
j
Table ES-4 shows EPA's estimate of the number of small businesses that would be affected by
the final regulations. EPA's analysis indicates; that the final rule could cause financial stress to some
small businesses, making these businesses vulnerable to closure (assuming no cost passthrough and cost-
share assistance). Section 4 of this report provides more detailed information.
The Small business Administration (SBA) defines a "small business" in the livestock and poultry
sectors in terms of average annual receipts (or !gross revenue). SBA size standards for these industries
define a "small business" as one with average annual revenues over a 3-year period of less than $0.75
million for dairy, hog, broiler, and turkey operations; $ 1.5 million for beef feedlots; and $9.0 million for
egg operations. EPA defines a "small" egg laying operation for purposes of its regulatory flexibility
assessments as an operation that generates less than $1.5 million in annual revenue. EPA consulted with
SBA on the use of this alternative definition. A summary of EPA's rationale and supporting analyses
pertaining to this alternative definition is provided in the record and in Section 4.
Given these considerations, EPA defines a "small business" for this rule as an operation that
houses or confines less than 1,400 fed beef cattle (includes fed beef, veal, and heifers); 300 mature dairy
cattle; 2,100 market hogs; 37,500 turkeys; 61,000 layers; or 375,000 broilers. The approach used to
derive 'these estimates is described in Section 4 and in the record.
EPA estimates that of the approximately 238,000 animal confinement facilities in 1997, roughly
95 percent are small businesses. Not all of these operations would be affected by the final rule. Table
ES-4 shows EPA's estimates of the number of small business CAFOs that would be affected by this rule.
For this analysis, EPA estimates that about 6,200 affected CAFOs across all size categories are small
businesses, accounting for more than 40 percent of the estimated 14,515 affected facilities. EPA
estimates that among CAFOs with more than 1,000 AU about 2,330 operations are small businesses
(accounting for about one-fourth of all CAFO$ in this size category). Most affected small businesses are
in the broiler sector. Among CAFOs with between 300 and 1,000 AU, EPA estimates about 3,830
operations are small businesses (accounting for the majority of operations in this size category), and most
of the affected small businesses are in the hog, dairy, and broiler sectors.2 :
For the 2001 proposal, EPA conducted a preliminary assessment of the potential impacts on
small business CAFOs based on the results of a costs:to-sales test (66 FR 3101). This screen test
indicated the need for additional analysis to characterize the nature and extent of impacts on small
entities. Based oh the results of this initial assessment, EPA projected that it would likely not certify that
the proposal, if promulgated, would not impose a significant economic impact on a substantial number of
entities. Therefore, EPA convened a SBAR Panel and prepared an Initial Regulatory Flexibility Analysis
(IRFA) pursuant to §§609(b) and 603 of the PJFA, respectively. The 2001 proposal provides more
For reasons noted in the record, EPA believes that the number of small broiler operations is
overestimated and might actually include a number of medium and large broiler operations that should not be
considered small businesses. |
; ES-13
-------
information on EPA's small business outreach and the Panel activities during the development of this
rulemaking (66 FR 3121). Section 10 of the preamble to the final rule summaries EPA's Final
Regulatory Flexibility Analysis (FRFA), as required under §604 of the RFA. This analysis is provided in
Section 4.
In examining the effects on small businesses for the final rule, EPA followed the same approach
used to evaluate the impacts on existing CAFOs, as described hi Section ES.2. For the purposes of this
analysis, EPA assumes that small business CAFOs with between 300 and 1,000 AU would incur costs
similar to those estimated for CAFOs with more than 1,000 AU (although these smaller-sized operations
will be subject to BPJ and not the ELG requirements under the revised NPDES requirements). These
upper end cost estimates could, therefore, overstate the financial effects for small businesses in this size
category. For past regulations, EPA has often analyzed the potential impacts to small businesses by
evaluating the results of a costs-to-sales test, measuring the number of operations that will incur
compliance costs at varying threshold levels (including ratios where costs are less than 1 percent,
between 1 and 3 percent, and greater than 3 percent of gross income). EPA conducted such an analysis at
the time of the 2001 proposal, indicating that about 80 percent of the estimated number of small
businesses directly subject to the rule as CAFOs might incur costs in excess of three percent of sales.
EPA believes that its more refined analysis used for its general analysis (presented here) better reflects
the potential impacts to regulated small businesses.
Using the approach used to evaluate the impacts on existing CAFOs, EPA's analysis indicates
that the final rule could cause financial stress to some small businesses, making these businesses
vulnerable to closure. These results are presented in Table ES-4.
For Option 1, the analysis indicates that, among all small business CAFOs hi the veal, dairy, hog,
turkey, and egg-laying sectors, the impacts due to this rule can be characterized as "Affordable" or
"Moderate." EPA estimates that a total of 172 small businesses (3 percent of all small business CAFOs
with more than 300 AU) would experience financial stress and might be vulnerable to closure. By sector,
these closures are comprised of about 131 small businesses in the beef sector, 38 businesses hi the heifer
sector, and 3 businesses in the broiler sector. Most of these (nearly 90 percent) are operations with fewer
than 1,000 AU. For Option 2, the analysis indicates that, among all small business CAFOs hi the veal,
dairy, hog, turkey, and egg-laying sectors, the impacts due to this rule can be characterized as
"Affordable" or "Moderate." EPA estimates that a total of 262 small businesses (4 percent of all small
business CAFOs with more than 300 AU) would experience financial stress and might be vulnerable to
closure. By sector, these closures are comprised of about 183 small businesses in the beef sector, 50
businesses hi the heifer sector, and 19 businesses in the broiler sector. Nearly 90 percent of these
potential closures are operations with fewer than 1,000 AU. See Section 4 of this report for more
information.
These estimates of the number of potential CAFO closures are cumulative and reflect the results
of both the farm level analysis and the enterprise level analysis. These results are based on an analysis
that does not consider the longer term effects on market adjustment and also available cost-share
assistance from Federal and State farm conservation programs. EPA believes that such adjustments
could lessen the economic impacts of the final regulations over time.
ES-14
-------
Table ES-4. Results of EPA's Small Business Analysis, Option 1 and Option 2
Sector
Option 1
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
Number of
Small
Business
CAFOs
Affordable
Moderate
Stress
(Number)
Affordable
Moderate
Stress
(Percent of Total Operations)
712
12
327
1330
1485
1823
24
407
31
6151
58L
12
289
1330
1485
1395
24
407
31;
5554
0
0
0
0
0
424
0
0
0
424
131
0
38
0
0
3
0
0
0
172
82%
100%
88%
100%
100%
77%
100%
100%
100%
90%
0%
0%
0%
0%
0%
23%
0%
0%
0%
7%
18%
0%
12%
0%
0%
0%
0%
0%
0%
3%
Option 2
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
712
12
327
1330
, 1485
1823
24
407
31
6151
529
12
277,
1306
1483
1026:
24
407|
31i
5129
0
0
0
24
2
780
0
0
0
806
183
0
50
0
0
19
0
0
0
262
74%
100%
85%
98%
100%
56%
100%
100%
100%
83%
0%
0%
0%
2%
0%
43%
0%
0%
0%
13%
26%
0%
15%
0%
0%
. 1%
0%
0%
0%
4%
Source: USEPA. See Economic Analysis. May not add due to rounding. Does not includes the number of CAFOs
includes designated facilities. Assumes that the costs that will be incurred by those sized operations to comply with
BPJ-based limitations under the revised NPDES regulations are similar to the estimated costs that would be incurred
if Medium CAFOs had to comply with the ELG. '
"Layers: dry" are operations with dry manure systems. "Layers: wet" are operations with liquid manure systems.
ES-15
-------
ES.5.3 New CAFOs
EPA evaluated impacts on new source CAFOs by comparing the costs borne by new source
CAFOs to those estimated for existing sources. That is, if the expected cost to new sources is similar to
or less than the expected cost bome by existing sources (and that cost was considered economically
achievable for existing sources), EPA considers that the regulations for new sources do not impose
requirements that might grant existing operators a cost advantage over new CAFO operators and further
determines that the NSPS requirements are affordable and do not present a barrier to entry for new
facilities. In general, costs to new sources from NSPS requirements are lower than the costs for
retrofitting the same technologies at existing sources since new sources are able to apply control
technologies more efficiently than existing sources that might incur high retrofit cost. New sources will
be able to avoid the retrofit costs that will be incurred by existing sources. Furthermore, new sources
might be able to avoid the other various control costs facing some existing producers through careful site
selection. The requirements promulgated in today's rule do not give existing operators a cost advantage
over new CAFO operators; therefore, the NSPS do not present a barrier to entry for new facilities.
Examples of avoided retrofit costs and costs of total containment systems and waste management,
including land application, for both existing and new sources, are provided in Section 4 of the preamble
to the final regulations. More detailed information is provided in the Development Document (LJSEPA,
2002) and related cost reports, as well as in Section 3.
ES.5.4 National Markets
EPA's market analysis evaluates the effects of the final regulations on commodity prices and
quantities at the national level. The analysis also presents EPA's estimate of national and regional
employment changes, net trade, and changes in economic output, among other supplemental analyses.
Section 3 of this report provides more detailed information.
EPA expects that predicted changes in animal production might raise producer prices as the
market adjusts to the final regulatory requirements. For most sectors, EPA estimates that producer price
changes will rise by less than one percent compared to the pre-regulation baseline price. At the retail
level, EPA estimates that poultry and red meat prices will rise about one cent per pound. EPA also
estimates that egg prices will rise by about one cent per dozen and that milk prices will rise by about one
cent per gallon. Trade and employment effects are also expected to be modest.
EPA also considered whether the final rule could have community level and/or regional impacts
if it substantially altered the competitive position of livestock and poultry production across the nation,
or led to growth or reduction in farm production (in- or out-migration) in different regions and
communities. Ongoing structural and technological changes in these industries have influenced where
farmers operate and have contributed to locational shifts between the traditional production regions and
the emergent, nontraditional regions. Production is growing rapidly in the emergent regions because of
competitive pressures and because specialized producers tend to have the advantage of lower per-unit
costs of production. This is especially true in hog and dairy production.
To evaluate the potential for differential impacts among farm production regions, EPA examined
employment impacts by region. EPA also evaluated whether the final requirements could result in
substantial changes in volume of production, given predicted facility closures, within a particular
production region. EPA concludes from these analyses that regional and community level effects are
ES-16
-------
estimated to be modest, but do tend to be concentrated within the more traditional agricultural regions.
This analysis is discussed in Section 3.
EPA does not expect that this rule will have a significant impact on where animals are raised.
On one hand, on-site improvements in waste management and disposal, as required by the final rule,
could accelerate recent shifts in production to more nontraditional regions as higher-cost producers in
some regions exit the market to avoid the relatively high retrofitting costs associated with bringing
existing facilities into compliance. On the other hand, the final regulations might favor more traditional
production systems where operators grow both livestock and crops, since these operations tend to have
available cropland for land application of manure nutrients. These types of operations tend to be more
diverse and less specialized and, generally, smaller in size. Long-standing farm services and input supply
industries in these areas could likewise benefit from the final rule, given the need to support on-site
improvements hi manure management and disposal. Local and regional governments, as well as other
nonagricultural enterprises, would also benefit.
ES.6 COST-BENEFIT ANALYSIS
As Table ES-5 shows, the economic value of the environmental benefits EPA is able to monetize
(i.e., evaluate in dollar terms) is comparable to the estimated costs of the rule. EPA has estimated the
monetized benefits of the final rule for all operations with more than 1,000 AU. For Option 1, total
monetized benefits for CAFOs with more than 1,000 AU range from $141 million to $224 million. For
Option 2, total monetized benefits for CAFOsiwith more than 1,000 AU range from $204 million to $340
million annually. These benefit estimates are expressed as pre-tax, 2001 dollars and have been calculated
assuming .a 7 percent discount rate. Monetized benefit categories are primarily in the areas of improved
surface water quality (measured in terms of enhanced recreational value), reduced nitrates in private
wells, reduced shellfish bed closures from pathogen contamination, and reduced fish kills from episodic
events. EPA also identified a number of benefits categories that could not be monetized, including
reduced euthrophication of estuaries, reduced pathogen contamination in private wells, reduced health
and environmental risks associated with episodic pollutant discharge events, drinking water treatment
cost savings, reduced odor and air emissions, and avoided loss in property value near CAFOs, among
other benefits. These benefits are described in more detail the Benefits Analysis and other supporting
documentation provided in the record. ,
These estimated benefits compare to EPA's estimate of the total social costs covering.both
industry and permit authority costs for operations with more than 1,000 AU only. These costs range
from $125 million (Option 1) to $289 million (Option 2) annually for all CAFOs with more than 1,000
AU, as was estimated in the Agency's Benefit'Analysis. These costs include compliance costs to all
CAFOs, as well as administrative costs to Federal and State governments. EPA estimates of the
administrative cost to Federal and State governments to implement this rule is $9 million per year. There
may be additional social costs that have not been monetized. However, these costs are estimated based
on the cost of land application based on nitrogen-based application rates, except in those instances where
EPA believes that phosphorus-based rates are likely to be appropriate. As discussed previously, the final
rule includes provisions for appropriate flexibilities in the use of phosphorus-based rates, such as multi-
year phosphorus application, but the potential costs savings resulting from these flexibilities are not
reflected in the analysis. Therefore, the costs of this rule may have been overestimated.
ES-17
-------
Table ES-5 Total Annual Monetized Social Costs and Benefits (millions $2001), CAFO >1,000 AU
Category
Option 1
Option 2
Total Monetized Social Costs
Industry Compliance Costs (pre-tax):
State/Federal Administrative Costs:
Total Social Costs
$119
$6
$125
$283
$6
$289
Total Monetized Benefits
Improved Surface Water Quality
Reduced Incidence of Fish Kills
Improved Commercial Shell Fishing
Reduced Contamination of Private Wells
Reduced Contamination of Animal Water Supplies
Reduced Eutrophication of Estuaries
Reduced Water Treatment Costs
Reduced eutrophication & pathogen contamination
of coastal & estuarine waters
Reduced pathogen contamination of private & public
underground sources of drinking water
Reduced human & ecological risks from antibiotics,
hormones, metals, salts
Improved soil properties
Reduced cost of commercial fertilizers for non-
CAFO operations
Total Benefits
$102.4-5182.6
$0.0 -$0.1
$0.1 -$2.0
$33.3
$4.7
$0.1
$0.7 -$1.0
not monetized
not monetized
not monetized
not monetized
not monetized
$141.3 + [B]
- $223.8 + [B]
$166.2 -$298.6
$0.1
$0.3 - $3.4
$30.9
$5.3
$0.2
$1.1 -$1.7
not monetized
not monetized
not monetized
not monetized
not monetized
$204.1 + [B]
- $340.2 +fBl
bource: USEPA. May not add due to rounding. [B] represents the non-monetized benefits of the rule.
These cost and benefit estimates are also expressed as pre-tax, 2001 dollars and have been
calculated assuming a 7 percent discount rate. See Section 5 for more information.
ES.7 OTHER INFORMATION
This report presents a summary of estimated per-animal and per-facility costs by animal sector
(Section 3 and Appendices B and D). It also presents an overview of the cost annualization approach
ES-18
-------
(Appendix A), details on the model used to estimate changes in producer prices associated with the final
regulations (Appendix C), and the results of a cost-effectiveness analysis (Appendix E).
Section 2 of the Proposal EA (USEPA, 2001 a) provides a detailed industry profile of the affected
regulated livestock and poultry sectors and meat and poultry processors. The Proposal EA also details
the model used to estimate economic impacts on CAFOs and national level markets (Section 4 and
Appendix B). Appendix D of the Proposal EA also shows the results of sensitivity analyses EPA
conducted for the 2001 Proposal.
This report does not include a detailed presentation of the economic benefits that are expected to
accrue as a result of the final CAFO regulations. That analysis is provided in the Benefits Analysis
(USEPA, 2002k) that supports this rulemaking. The Development Document (USEPA, 2002) provides
more detailed information on the farm level costs that EPA estimates for this analysis.
ES.8 ORGANIZATION OF THE REPORT
This report is organized to allow those interested in the impacts on a specific industry sector to
find information easily. The sections of the report are as follows:
• Section 1 provides a summary of the existing, proposed, and final regulations affecting
CAFOs. I
• Section 2 describes the data and methodologies EPA uses to estimate the total annual
incremental costs and the economic impacts that would be incurred by the livestock and
poultry industry as a result of the final CAFO regulations, highlighting changes EPA has
made since the 2001 Proposal in response to public comments,
• Section 3 presents a summary of the estimated national, annual costs and the economic
impacts on regulated facilities of the final CAFO regulations.
• Section 4 presents the results of EPA's Final Regulatory Flexibility Analysis and describes
the possible financial effects on small businesses.
• Section 5 presents a discussion of the regulatory costs and benefits pursuant to Executive
Order 12866 and the Unfunded Mandates Reform Act (UMRA).
• Section 6 presents the references used throughout the report and its appendices.
f
• Appendix A presents a description of EPA's method to annualize costs and more detailed
information on the annualized costs used as inputs to EPA's CAFO level economic analysis.
• Appendix B shows EPA's annualized compliance cost estimates for the ELG technology
option chosen for the final regulations.
« Appendix C describes EPA's methodology for estimating changes in farm revenue based on
predicted changes in market prices and quantities attributable to the final regulations.
ES-19
-------
Appendix D shows EPA estimates of financial effects on operations with more than 300 AU
for the ELG technology option chosen for the final regulations.
Appendix E presents EPA's analysis of the cost-effectiveness of the final CAFO regulation,
hi terms of pollutant removal effectiveness for nutrients and other priority pollutants, and
background information on the methods EPA used for the C-E analysis.
ES-20
-------
SECTION ONE
REQUIREMENTS OF THE FINAL CAFO REGULATIONS
The U.S. Environmental Protection Agency (EPA) is revising and updating the two primary
regulations that ensure that manure, wastewater, and other process waters generated by concentrated
animal feeding operations (CAFOs) do not impair water quality. EPA's final regulatory changes affect
the existing National Pollutant Discharge Elimination System (NPDES) provisions and the existing
effluent limitations guidelines (ELG) for "feedlots." The NPDES provisions define and establish permit
requirenaents for CAFOs, and the ELG establish the technology-based effluent discharge standard that is
applied to CAFOs. Existing regulations were originally promulgated in the 1970s. EPA is revising the
regulations to address changes that have occurred in the animal industry sectors over the past 25 years, to
clarify and improve implementation of CAFO requirements, and to improve the environmental protection
achieved under these regulations. Final revisions to the NPDES and ELG regulations are referred to hi
this report as the final CAFO regulations.
On January 12, 2001, EPA published a proposal to revise and update these regulations (66 FR
2959), referred to in this report as the "2001 Proposal." The Economic Analysis that supports the 2001
Proposal contains information on EPA's estimates of the cost, financial effects, and monetized benefits
of the proposed revisions. That analysis, titled Economic Analysis of the Proposed Revisions to the
National Pollutant Discharge Elimination System Regulation and the Effluent Guidelines for
Concentrated Animal Feeding Operations, is referred to in this report as the "Proposal EA" (USEPA,
2001a). EPA also published two Notices of Data Availability in the Federal Register (66 FR 58556 and
67 FR 48099). These Notices present new data and information EPA has received since the 2001
Proposal, soliciting further public review and comment.
This Economic Analysis (EA) summarizes EPA's analysis of the estimated annual compliance
costs and the economic impacts that might be incurred by affected operations that are subject to the final
revisions. Additional information on the regulatory alternatives that EPA considered for the 2001
Proposal is presented in the EA supporting the proposed regulations (USEPA, 200la). The report covers
financial impacts on CAFOs, potential impact^ on processors of livestock and poultry products, and
market and other secondary impacts such as impacts on prices, quantities, trade, employment, and output.
It also responds to requirements for small business analyses under the Regulatory Flexibility Act (RFA),
as amended by the Small Business Regulatory; Enforcement Fairness Act (SBREFA), and for cost-benefit
analyses under Executive Order 12866 and the Unfunded Mandates Reform Act (UMRA).
. i
EPA also provides additional material on the final CAFO regulations in the Development
Document for the Final Revisions to the National Pollutant Discharge Elimination System Regulation
and the Effluent Guidelines for Concentrated Animal Feeding Operations, which discusses how EPA
estimated compliance costs of the final regulations. EPA's detailed benefit analysis, titled
Environmental and Economic Benefit Analysis of the Final Revisions to the National Pollutant
Discharge Elimination System Regulation and the Effluent Guidelines for Concentrated Animal Feeding
Operations, provides information about existing water quality impairments associated with animal
production operations and estimates the extent to which these impairments might be mitigated by the
final CAFO regulations.
1-1
-------
This section begins with a discussion of the current regulatory framework. In the course of this
discussion, the section also defines and describes animal feeding operations (AFOs) and CAFOs
(Section 1.1). The reasons why EPA is revising these regulations are also discussed. Section 1.2
discusses EPA's proposed revisions to existing CAFO requirements in the 2001 Proposal (66 FR 2959).
Section 1.3 reviews the final revisions promulgated by EPA.
1.1 SUMMARY OF EXISTING REGULATORY FRAMEWORK
In 1972 Congress passed the Federal Water Pollution Control Act, also known as the Clean Water
Act (CWA), to "restore and maintain the chemical, physical, and biological integrity of the nation's
waters." 33 U:S.C. [United States Code] § 125l(a). Hjj? CWA establishes a comprehensive program for
protecting the nation's waters. Among its core provisions, the CWA prohibits the discharge of pollutants
from a point source to waters of the United States except those authorized by an NPDES permit. The
CWA also provides for the development of technology-based effluent limitations that are imposed
through NPDES permits to control direct discharges of pollutants.
In response to the CWA, EPA established several regulatory programs, of which two pertain to
livestock and poultry operations that confine animals (commonly referred to by EPA as animal feeding
operations, or AFOs). These regulations include the requirements for discharge permits for CAFOs
under the NPDES program (40 CFR Part 122.23) (see Section 1.1.1) and the ELG for animal feeding
operations, of "feedlots" (40 CFR Part 412) (see Section 1.1.2).
1.1.1 NPDES Permit Regulation of CAFOs
The NPDES permit program controls pollution from identifiable discharge points or sources (e.g.,
discharge pipes or ditches). Under the NPDES permit program, all point sources that directly discharge
pollutants to waters of the United States must apply for an NPDES permit and may discharge pollutants
only under the terms of that permit. Such permits must include nationally established effluent discharge
limitations. In the absence of national effluent limitations, NPDES permit writers must establish
limitations and standards on a case-by-case basis, based on their "best professional judgment (BPJ)/'
Effluent limitations guidelines and BPJ provide the basis for technology-based effluent limits in NPDES
permits.
Under the CWA, CAFOs are defined as point sources of pollution and are thus subject to NPDES
permitting requirements (33 U.S.C. § 1362). The ejdsting NPDES provisions that define which
operations are CAFOs and establish permit requirements for CAFOs (40 CFR Part 122.23) were
promulgated on March 18, 1976 (41 FR 11458).
Before an operation may be defined as a CAFO, it must first meet the definition of an AFO.
AFOs are agricultural enterprises where animals are kept and raised in confined situations for a specified
time during the year and where animals, feed, manure, dead animals, and production operations are
congregated on a small land area. As defined by federal regulation, AFOs are lots or facilities where
animals
....have been, are, or will be stabled or confined and fed or maintained for a total of 45
days or more in any 12 month period and crops, vegetation forage growth, or post-harvest
1-2'
-------
residues are not sustained in the normal growing period over any portion of the lot or
facility. (40 CFR 122.23(b)(l)). ;
In 1976 EPA issued regulations defining which AFOs met the definition of a CAFO under the
NPDES permit program. CAFOs are AFOs that confine a specified number of animals and in some cases
meet specific discharge criteria. The specified number of animals is determined using the concept of an
"animal unit" (AU). The term "animal unit" refers to a metric established in the 1970 regulations in an
attempt to equate the characteristics of the wastes produced by different animal types. For each animal
type, EPA's regulations identify the number of animals that is equivalent to 1 AU.
As defined in the existing regulation (40 CFR Part 122), 1 AU is equivalent to any of the
following:
• 1 slaughter or feeder beef cattle.
• 0.7 mature dairy cows. ;
• 2.5 swine weighing more than 55 pounds.
• 55 turkeys.
• 100 laying hens or broilers (facility with continuous-flow watering system); 30 hens or
broilers (facility with liquid manure handling system).
• 0.5 horses.
• 10 sheep or lambs.
• 5 ducks.
For the purpose of this analysis, the 1,000-AU threshold that EPA assumes for broiler and egg
laying operations with dry manure systems (not covered under the existing regulations) is 125,000 meat
chickens or broilers and 82,000 egg laying chickens. For veal and heifer operations, also not currently
covered under the existing regulations, EPA assumes a 1,000-AU threshold consistent with that for cattle
feeding operations (i.e., 1,000 AU equals l.OGJO head).1 EPA also assumes a 1,000-AU threshold for
stand-alone nursery pig operations of 5,000 nursery pigs.
The existing NPDES regulation definds AFOs with 1,000 AU or more as CAFOs. These facilities
are not CAFOs if they discharge only in the event of a 25-year, 24-hour storm. The existing regulation
also states that AFOs with between 300 and 1000 AU are CAFOs if they meet certain conditions. These
conditions include the discharge of pollutants into waters through a ditch, flushing system, or other man-
made device. An AFO with between 300 and 1000 AU may also be defined as a CAFO if pollutants are
discharged to waters that originate outside of and pass over, across, or through the facility or come into
contact with confined animals. The state agency or other authority that issues NPDES permits may also
designate AFOs with fewer than 1,000 AU as CAFOs if they are considered to have discharges that could
1 The final rale preamble refers to operations in this size category as "Large" CAFOs.
1-3
-------
significantly impair surface water. (Operations with between 300 AU and 1,000 AU are referred to in the
final rule preamble as "Medium" CAFOs; operations with fewer than 300 AU are referred to as "Small"
CAFOs.)
All NPDES permits for CAFOs with more than 1,000 AU must include requirements equivalent
to or more stringent than the established ELG. As noted above, certain smaller operations can also be
defined or designated as CAFOs, but the ELG does not apply to these CAFOs. In these cases, the permit
writer must develop technology-based limitations based on BPJ for inclusion in the NPDES permit.
1.1.2 Effluent Limitations Guidelines for Feedlots
The CWA authorizes EPA to establish restrictions on the types and amounts of pollutants
discharged from various industrial, commercial, and public sources of wastewater. Effluent guidelines
define the types and amount of pollutants an NPDES permitted facility is allowed to discharge. Direct
dischargers must comply with ELG and new source performance standards (NSPS). These limitations
and standards are established by regulation for categories of industrial dischargers, and they are based on
the degree of control that can be achieved using various levels of pollution control technology. These
guidelines base the discharge (or effluent) amount on the best available technology that is economically
achievable. Under the Clean Water Act, EPA has an obligation to promulgate effluent guidelines that
achieve "best available technology economically achievable" (BATEA).
The existing national ELGs for the feedlots category, including the beef, dairy, swine, and poultry
subcategories (40 CFR Part 412), were established on February 14, 1974 (39 FR 5704). The feedlot ELG
allow for no discharge of process wastewater pollutants into the Nation's waters except when chronic or
catastrophic storm events cause an overflow from a facility designed, constructed, and operated to hold
process-generated wastewater plus runoff from a 25-year, 24-hour storm event. As a result, the current
effluent guidelines for feedlots are usually referred to as "zero discharge" requirements. Many feedlots
meet the "zero discharge" requirement by containing wet manure in lagoons and by land applying
manure. The current ELG are applicable to NPDES permits issued to CAFOs with more than 1,000 AU.
Discharge Limits for facilities with fewer than 1,000 AU are established using BPJ.
1.1.3 Industries Affected by the Final CAFO Regulations
In this EA, information is organized by sector rather than by subcategory. This report focuses on
the major livestock and poultry industries affected by the ELG and the NPDES program requirements.
By North American Industry Classification System (NAICS)2 code, these include:
• Cattle feedlots, NAICS 112112 [includes veal] (SIC 0211, beef cattle feedlots).
• Beef cattle ranching and farming, NAICS 112111 (SIC 0241, dairy heifer replacement
farms).
2 NAICS recently replaced the SIC (Standard Industrial Classification) system.
1-4
-------
• Dairy cattle and milk production, NAICS 11212 (SIC 0241, dairy farms).
• . Hog and pig fanning, NAICS 11221 (SIC 0213, hogs).
• Broilers and other meat-type chickens, NAICS 11232 (SIC 0251, broiler, fryer, and
roaster chickens).
• Turkey production, NAICS 1123 3 (SIC 0253, turkey and turkey eggs).
» Chicken egg production, NAICS 11231 (SIC 0252, chicken eggs).
In some cases, information is limited to analyze some sectors individually. For example, the
analysis often aggregates information for the "cattle" sector presenting an aggregated review on fed
cattle, heifer, and veal operations because sector-specific financial data and other industry information is
limited. Under the regulations, however, beef cattle and heifer operations are covered under the same
subcategory but veal operations are covered under a separate subcategory. Information on the types of
operations in the poultry sector (broiler, egg layer, and turkey operations) is also presented together, in
some cases depending on best available data. The dairy and swine subcategories are evaluated
separately.
The ELG andNPDES permit requirements also affect other types of animal confinement
operations, including operations that raise sheep, lambs, goats, horses, and other miscellaneous animal
species. For some of these sectors (horses, ducks, etc.), EPA is updating the NPDES permit requirements
as part of this rulemaking. Because EPA is not revising the ELG for these other sectors, however, these
sectors are not covered in this analysis because EPA is not required to perform an economic achievability
analysis for NPDES requirements (economic achievability analysis is only required for effluent guideline
requirements). Also, EPA's cost and benefit analysis is focused only on those livestock and poultry
operations that account for a majority of both number of animals produced and manure nutrients
generated (cattle, dairy, hog and poultry sectors). EPA's national level analysis does not specifically
account for other types of operations covered under the NPDES regulation since relatively few such
operations exist. (See also response to comment DCN CAFONODA-600059-4.)
The U.S. Department of Agriculture (USDA) reports that there were 1.1 million livestock and
poultry operations in the United States in 1997, corresponding to these affected industry sectors
(USDA/NASS, 1999a). This number includes both confinement and non-confinement (grazing and
rangefed) production, as well as both commercial and noncommercial operations. Of these operations,
USDA estimates that there are about 240,000 Operations raise animals in confinement (Kellogg, 2002).
Table 1-1 summarizes the estimated total number of AFOs of all sizes in each of the four major livestock
categories in 1997. EPA estimates that only a small subset of these AFOs would be regulated as CAFOs,
because most would not meet the size definitions or other criteria. More information is provided in
Section3 of this report. ',
1-5
-------
Table 1-1. Number of Total AFOs and AFOs Defined as CAFOs (1997)
Sector
Beef operations, including both cattle, veal, and heifer operations
Dairy operations (milk production operations only)
Hog operations, including both "farrow-finish" and "grow-finish" operations ^
Poultry operations, including broilers, layers (wet and dry operations), turkeys w
Total AFOs
Total
AFOs
21,807
94,787
51,772
27,530
237,821 tf
Defined
CAFOs
2,431
3,399
5,409
3,739
14,978
See Section 3.
"'Grow-finish operations finish more mature pigs while farrow-finish operations handle all stages of production
from breeding to finishing.
"Use either liquid or dry manure handling systems present at the facility.
^ USDA estimate of the total number of AFOs is adjusted for specialty cases. Specialty cases (estimated at 2,291
operations) are dairies that went out of business in 1997, swine operations with feeder pigs only, and egg-hatching
operations.
1.2 SUMMARY OF THE PROPOSED RULEMAKING
1.2.1 The 2001 Proposal
On January 12, 2001 (66 FR 2959), EPA published proposed revisions to the existing effluent
guidelines for CAFOs (40 CFR Part 412) and to certain provisions of the NPDES regulations applicable
to CAFOs. Effluent guidelines and standards for CAFOs establish the technology-based effluent
discharge and performance standards for both existing and new sources for each of the beef, dairy, swine,
and poultry subcategories. The NPDES permit program for CAFOs defines which AFOs are CAFOs and
need to obtain NPDES permits, and it establishes the specific requirements that must be complied with
under a permit. These two existing interrelated regulations affecting CAFOs were originally
promulgated in the 1970s.
An overview of the ELG options and NPDES scenarios is provided in Table 1-2. For more
detailed information, see Sections 7 and 8 of the preamble to EPA's proposed rule (66 FR 2993-3061).
1.2,1.1 NPDES Permit Regulation
Under the current NPDES regulations for CAFOs, a three-tier structure is used to determine
which AFOs also meet the criteria under which they are considered CAFOs. Under the current NPDES
structure, (1) all AFOs with more than 1,000 AU are automatically defined as CAFOs; (2) AFOs with
301 to 1,000 AU are defined as CAFOs only if they meet certain conditions; and (3) AFOs with 301 to
1,000 AU that do not meet these conditions, and all AFOs with fewer than 300 AU are CAFOs only if
they are designated as such by the permitting authority. (See 40 CFR 122.23 and Part 122, Appendix B).
EPA proposed several alternatives for revising the existing CAFO definition. Under one scenario,
the current three-tier structure would be retained, but there would be certain changes to the conditions
1-6
-------
that define an operation as a'CAFO in the middle tier (300 AU to 1,000 AU). EPA also proposed an
alternative regulatory approach that would replace the existing three-tier structure with a two-tier
scenario for defining operations as CAFOs. Under the "two-tier" scenario, all AFOs with more than a
specified number of animals would be define^ as a CAFO. EPA considered several potential thresholds
that could be set under the two-tier scenario. •.
EPA also proposed to revise the definition of a CAFO to expressly include chicken operations
using dry litter management techniques, swine nurseries, and heifer operations. EPA proposed to
explicitly address manure application on land under the control of a CAFO and considered alternatives
for collecting information regarding manure transferred to off-site locations. The proposed rule included
certain changes affecting which entities would be required to obtain NPDES permits. It also contained
provisions requiring that a CAFOs that ceases operation must retain its NPDES permits until all wastes
generated by the operation no longer have the potential to reach waters of the United States.
Table 1-2 summarizes the scope options that EPA considered during the development of the 2001
Proposal. For more information on the proposed changes to the NPDES regulations, see Section 7 of the
proposed rule preamble (66 FR 2993-3050). ,
1.2.1.2 Effluent Limitations Guidelines and Standards
Under the current effluent guidelines regulations, CAFOs are prohibited from discharging process
wastewater, except when rainfall events cause an overflow from a facility designed, constructed, and
operated to contain all process-generated wastewater plus the runoff from a 25-year, 24-hour rainfall
event.
EPA proposed requiring all existing and new CAFOs spreading manure on cropland to limit the
application rate to the nitrogen needs of the crops and, for those fields where additional constraints are
considered necessary, to ensure that the manure application rate would not exceed the phosphorus needs
of the crops. ' ' - '
EPA also proposed requiring all existing beef and dairy operations to implement controls
(retrofitting of lagoons and ponds with impervious liners) to minimize leaching to ground water if the
ground water beneath the production area has a direct hydrologic connection to surface water. EPA
proposed requiring all existing swine, veal, and poultry CAFOs to eliminate all discharges from the
animal production area (thereby eliminating for these sectors the effluent guidelines provision that allows
for certain overflows due to chronic or catastrophic rainfall).
EPA proposed that newly constructed
-------
1.2.2 The 2001 Notice of Data Availability
On November 21,2001, EPA published a Notice of Data Availability (referred to as the "2001
Notice") that presented a summary of new data and information submitted to EPA during the public
comment period on the proposed CAFO regulations, including data received from the U.S. Department of
Agriculture (66 FR 58556). There were four main components to the Notice: (1) discussion of new data
and changes EPA was considering to refine its cost and economics model; (2) discussion of new data and
changes EPA was considering to refine its nutrient loading and benefits analysis; (3) new data and
changes EPA was considering to the proposed NPDES permit program regulations; and (4) new data and
changes EPA was considering to the proposed ELG regulations. See USGPO, 2001b. The 2001 Notice
also discussed options that the Agency considered to enhance flexibility for the use of State NPDES and.
non-NPDES CAFO programs, including implementation of environmental management systems (EMS).
1.2.3 The 2002 Notice of Data Availability
On July 23, 2002, EPA published a Notice of Data Availability (referred to in this report as the
"2002 Notice") that presented a summary of new data and information submitted to EPA during the
public comment period on the proposed CAFO regulations, including data received from the 2001 notice
(67 FR 48099). There were three main components of the 2002 Notice: (1) establishing alternative
regulatory thresholds for chicken operations using dry litter management practices; (2) the potential
creation of alternative performance standards to encourage CAFOs to implement new technologies; and
(3) financial data and changes EPA considered to refine its economic analysis models. See USGPO,
2002. The 2002 Notice made these data and potential changes available for public review and comment.
1.3 SUMMARY OF THE FINAL REVISIONS
Below is a brief summary of the major elements of this final rule and a brief index on where each
of the requirements is located in the final regulations. Part 122 of the Code of Federal Regulations (Title
40) contains the regulations for the National Pollutant Discharge Elimination System (NPDES) permit
program. These NPDES Regulations include requirements that apply to all point sources, including
CAFOs. Part 412 is the location in the Code of Federal Regulations where the national effluent
guidelines are located for CAFOs. This summary is not a replacement for the actual regulations and is
not for interpretive purposes. More information is in the preamble to the final rule.
1.3.1 NPDES Permit Regulations
Overall, the final rule maintains many of the basic features and the overall structure of the 1976
NPDES regulations with some important exceptions. First, all CAFOs have a mandatory duty to apply
for an NPDES permit, which removes the ambiguity of whether a facility needs an NPDES permit, even
if it discharges only in the event of a large storm. In the event that a Large CAFO has no potential to
discharge, the final rule provides a process for the CAFO to make such a demonstration in lieu of
obtaining a permit. The second significant change is that large poultry operations are covered, regardless
of the type of waste disposal system used or whether the litter is managed in wet or dry form. Third,
under this final rule, all CAFOs covered by an NPDES permit are required to develop and implement a
nutrient management plan. The plan would identify practices necessary to implement the ELG and any
1-8
-------
other requirements in the permit and would include requirements to land apply manure, litter, and process
wastewater consistent with site specific nutrient management practices that ensure appropriate
agricultural utilization of the nutrients. '.
Table 1-2. Summary of Options and Scenarios Considered by EPA
Technology Options
Option 1:
Option 2
Option 3
Option 4
Option 5
Option 6
Option 7
N-based land application controls and inspection and recordkeeping requirements
for the production area
Same as Option 1, but restricts the rate of manure application to a P-based rate
where necessary (depending on specific soil conditions at the CAPO)
Adds to Option 2 by requiring the operation to perform ground water monitoring
and controls unless ijt can show that the ground water beneath manure storage areas
or stockpiles does not have a direct hydrologic connection to surface waters
Adds to Option 3 by'requiring sampling of surface waters adjacent to the production
area and/or land under control of the CAFO to which manure is applied
Adds to Option 2 by i establishing a zero discharge requirement that does not allow
for an overflow fronj the production area under any circumstances
Adds to Option 2 by'requiring that large hog and dairy operations install and
implement anaerobic digestion and gas combustion to treat their manure
Adds to Option 2 by prohibiting manure application to frozen, snow-covered or
saturated ground j
Regulatory Scope Options ; '
Scenario 1
Scenario 2
Scenario 3
Scenario 4a
Scenario 4b
Scenario 5
Scenario 6
Retains existing 3-tier framework and establishes additional requirements
Same as Scenario 1, [except that operations with 300-1,000 AU would be subject to
the regulations based on a revised set of conditions at the feedlot site
Same as Scenario 2, but allows an operation with 300-1,000 AU to either apply for
an NPDES permit or to certify to the permit authority that it does not meet any of the
conditions and thus is not required to obtain a permit
Establishes 2-tier framework and applies ELG standard to all operations with more
than 500 AU !
Establishes 2-tier framework and applies ELG standard to all operations with more
than 300 AU :
Establishes 2-tier framework and applies ELG standard to all operations with more
than 750 AU ,
Retains existing 3-tier framework and establishes a simplified certification process
1-9
-------
1.3.2 Effluent Limitations Guidelines and Standards
The final ELGs will continue to apply to only CAFOs with more than 1,000 AU, although the
requirements for existing sources and new sources are different for certain animal sectors. In the case of
existing sources, the ELGs will continue to prohibit the discharge of manure and other process
wastewater pollutants, except for allowing the discharge of process wastewater whenever rainfall events
cause an overflow from a facility designed, constructed, and operated to contain all process wastewaters
plus the runoff from a 25-year, 24-hour rainfall event. The ELGs also require land application at the
CAFO must be at rates that minimize phosphorus and nitrogen transport from the field to surface waters
in compliance with technical standards for nutrient management established by the Director. The ELGs
also establish certain best management practice (BMP) requirements that apply to the production and
land application areas. .
For new large beef and dairy operations, the ELGs establish production area requirements that are
the same as those for existing sources. In the case of large swine, veal, and poultry operations that are
new sources, a new zero discharge standard is established. The rule also clarifies that where waste
management and storage facilities are designed, constructed, operated and maintained to contain all
manure, litter and process wastewater, including the runoff and direct precipitation from a 100-year, 24-
hour rainfall event, and is operated in accordance with certain other requirements, this will satisfy the
new standard. Land application requirements for both groups are identical to those established for
existing sources.
1-10
-------
SECTION TWO
DATA AND METHODOLOGY FOR ESTIMATING
COMPLIANCE COSTS AND ECONOMIC EFFECTS
This section presents the data and methodology EPA uses to estimate the total annual
incremental costs and the economic impacts that would be incurred by the livestock and poultry industry
as a result of the final CAFO regulations. Thip analysis examines potential compliance costs and
financial effects on regulated CAFOs (e.g., feedlots and.feedyards) as well as effects on consumer
markets.
Section 2.1 identifies the regulated industry sectors and provides an overview of EPA's data and
model framework using a representative "model CAFO" approach. Section 2.2 describes the methods
and assumptions used to estimate annual CAFO level compliance costs (described in greater detail in
other rulemaking support documents). Section 2.3 summarizes the development and characterization of
EPA's financial models for each sector, incorporating changes to EPA's model and input data used for
the 2001 Proposal. These models provide the basis for calculating the total annual costs of the final
regulations and are used to evaluate potential financial impacts on regulated CAFOs. This section also
presents the financial data that EPA assumes to depict baseline conditions and assess regulatory changes.
Section 2.4 describes the financial criteria and general approach that EPA assumes to evaluate regulatory
effects on model CAFOs. Section 2.5 summarizes the methodology EPA uses to assess additional market
impacts, including national level changes-in prices and available quantities, as well as changes hi national
aggregate employment and economic output. •
More detail on the data and model framework that EPA uses to evaluate economic effects of the
rule is provided in EPA's Economic Analysis supporting the 2001 Proposal (see: USEPA, 2001a, referred
to as the "Proposal EA"), with updates as documented in the two Notices of Data Availability presenting
new data and information EPA has received since the 2001 Proposal (see: USGAO, 2001b, 66 FR 58556,
and USGAO, 2002, 67 FR 48099; referred to as the "2001 Notice" and "2002 Notice," respectively).
More information on EPA's compliance cost estimates is presented hi EPA's Development Document
supporting both the proposed and final rulemaking (USEPA, 200 Ib; 2002).
2.1 BACKGROUND AND OVERVIEW
2.1.1 Overview of Analytical Framework
As discussed in greater detail in the Proposal EA, EPA estimates incremental costs and
regulatory impacts using a representative farm approach. For this analysis, EPA developed "model
CAFOs" for each sector to assess the average costs and economic impacts of the revised regulations
across differently sized, differently managed, and geographically distinct operations.
A representative farm approach is consistent with past research conducted by USDA and the land
grant universities and then: affiliated research organizations, including the Food and Agricultural Policy
Research Institute (FAPRI), the Center for Agriculture and Rural Development (CARD), Texas A&M's
Agriculture and Food Policy Center, the Texas Institute for Applied Environmental Research (TIAER),
and the University of Missouri's Commercial Agriculture Program. These organizations and others have
i 2-1
-------
widely adopted the representative farm approach to assess a broad range of policy issues, including
changes in Federal agricultural policy and pricing programs, domestic food programs, environmental
legislation, and international trade. This approach has been used to assess agricultural market changes
for both livestock and crop commodities, as well as to evaluate the financial impact of implementing
management measures and installing animal waste systems at livestock and poultry operations. More
detailed information is provided in Section 4 of the Proposal EA. Since proposal, EPA has also
conducted an in-depth literature review of the types of approaches used in the academic community to
assess the economic effects of public policy on agricultural operations, which further validates use of this
approach. This review is available in the rulemaking record (DPRA, 2001).
A representative approach provides a means to assess average impacts across numerous facilities
by grouping facilities into broader categories to account for the multitude of differences among animal
confinement operations. This approach allows a means to account for differences in performance among
farming operations.
Using a representative farm approach, EPA constructs a series of model facilities that reflect the
Agency's estimated compliance costs and available financial data. EPA uses these model CAFOs to
develop an average characterization for a group of operations (described in Section 2.3 of this report).
From these models, EPA estimates total annualized compliance costs by aggregating the average facility
costs across all operations that are identified for a representative group. As with EPA's cost models, its
financial models are grouped according to certain distinguishing characteristics for each sector, such as
facility size and production region, that might be shared across a broad range of facilities. Economic
impacts under a post-regulatory scenario are approximated by extrapolating the average impacts for a
given model CAFO across the larger number of operations that share similar production characteristics
and are identified by that CAFO model. EPA compares its estimated compliance costs at select model
CAFOs to corresponding financial conditions at these model facilities (discussed in Section 2.4).
Follow-up analysis assesses the broader market level effects of the final regulations (Section 2.5).
As detailed in the Proposal EA and in EPA's record, EPA presented its proposed methodological
approach to USDA personnel and to researchers at various land grant universities for informal review
and feedback at various stages in the development of these regulations.
2.1.2 Overview of Sources of Data
EPA has undertaken an expedited approach to this rulemaking effort and did not conduct an
industry-wide survey of all CAFOs using a Clean Water Act Section 308 questionnaire. This decision is
described in the 2001 Proposal (66 FR 3079) and detailed in the Proposal EA. EPA is relying on existing
data sources and expertise provided by numerous government agencies, state agricultural extension
agencies, land grant universities, industry trade associations, and agricultural professionals. Major data
sources are discussed in detail where they are used to conduct the analyses presented in this report or
reference other supporting documents in the rulemaking record.
The majority of the data EPA used to support development of the final CAFO regulations are
from existing sources. As defined in the Office of Water 2002 Quality Management Plan, which is
provided as part of the Development Document (USEPA 2002), existing (or secondary) data are data tha.t
were not directly generated by EPA to support the decision at hand.
2-2
-------
In keeping with the graded approach to quality management embodied in the quality management
plan, EPA must assess the quality of existing data relative to their intended use. The procedures EPA
used to assess existing data for use in developing effluent guideline limitations for CAFOs varied with
the specific type of data. In general, EPA's assessment included:
Reviewing a description of the existing data that explains how the data were collected or
produced (e.g., who collected the data, what data were collected; why were the data originally
collected; when were the data collected; how were they collected; are the data part of a long-
term collection effort, or was this a one-time effort; who else uses the data; what level of review
by others have the data undergone, etc.)
Specifying the intended use of the existing data relative to the CAFO final rule
• Developing a rationale for accepting data from this source, either as a set of acceptance criteria,
or as a narrative discussion
• Describing any known limitations with the data and their impact on EPA's use of the data.
Brief descriptions of the data and their limitations are presented later in this document, as each data
source is introduced.
In searching for existing data sources and determining their acceptability, EPA generally used a
hierarchical approach designed to identify and utilize data with the broadest representation of the
industry sector of interest. EPA began by searching for national-level data from surveys and studies by
USDA and other federal agencies. When survey or study data do not exist, EPA considered other types
of data from federal agencies.
Where national data do not exist, as the second tier, EPA searched for data from land grant
universities. Such data are often local or regional in nature. EPA assessed the representativeness of the
data relative to a national scale before deciding to use the data. When such data came from published
sources, EPA gave greater consideration to publications in peer-reviewed professional journals compared
to trade publications that do not have a formal review process.
• The third tier was data supplied by industry. Prior to proposal, EPA requested data from a
variety of industry sources, including trade associations and large producers. The level of review applied
to data supplied by industry depended on the level of supporting detail that was provided. For example,
if the industry supplied background information regarding how the data were collected, such as the
number of respondents and the total number of potential respondents, EPA reviewed the results,
compared them to data from other potential sources to determine their suitably for use hi this rulemaking.
If the data provided by industry originated from an identifiable non-industry source (e.g., a state
government agency), EPA reviewed the original source before determining the acceptability of the data.
In a limited number of instances, EPA conducted site visits to substantiate information supplied by
industry. In contrast, data supplied by industry without any background information were given much
less weight and generally were not used by EPA. Further, some data that were supplied by industry prior
to the proposal were included in the proposal for comment. In the absence of any negative comments,
such data were relied on to a greater extent than data submitted by industry during the comment period
itself.
2-3
-------
For its engineering cost analysis, EPA uses industry and cost information from various sources,
including USDA, the land grant universities, state agricultural extension agencies, and industry. EPA
uses these data to develop its model CAFOs and to extrapolate CAFO level costs to all operations
nationwide. A key source of data used to estimate compliance costs and economic impacts on the
regulated community is the 1997 Census of Agriculture. The Census is conducted by the National
Agricultural Statistical Service (NASS) every five years. It provides information on the number of
feedlots, their geographic distributions, the amount of cropland available to land apply animal manure
generated from animal confinement operations, and other information. NASS compiles these data, with
the assistance of personnel at USDA's Natural Resources Conservation Service (NR.CS) who developed a
methodology to identify information specific to animal confinement operations. All Census data
provided to other government agencies, including EPA, are aggregated to preserve confidential business
information. As detailed in the 2001 Notice, EPA has received additional data and information since
proposal that have been incorporated into its analysis for the final regulations. EPA's Development
Document supporting the proposed and final rule (USEPA, 2001, 2002) presents the Census data used
along with other USDA data and other source data that EPA uses for its cost analysis.
For the economic impact analysis, EPA obtained financial data for livestock and poultry
operations from, a variety of sources, including USDA, the land grant universities, and industry. EPA
uses these data to depict baseline financial conditions at representative model CAFOs and to extrapolate
CAFO level impacts to all operations nationwide. As detailed in both the 2001 Notice and the 2002
Notice, EPA received additional data and information since proposal that have been incorporated into the
analysis for the final regulations. To assess broader market changes from the CAFO regulations, EPA
compiled additional industry and market data from a wide range of USDA data and land grant university
research. A detailed summary of the data and citations of the sources of the data are provided in the
Proposal EA, supplemented by data and other information presented in this report.
A key source of financial data is USDA's Agricultural Resource Management Study (ARMS).
This study is compiled by NASS and USDA's Economic Research Service (ERS) and provides complete
financial accounting data for U.S. farms for each of the major commodity sectors affected by the final
CAFO regulations. These data are used to depict farm financial conditions and to evaluate regulatory
impacts. ERS obtained data for representative farms through special tabulations of the ARMS data,
conducted by ERS, that differentiate the financial conditions among operations by commodity sector,
facility size (number of animals on site), and major farm producing region. As with the Census data,
USDA aggregates these data in a manner to preserve both the statistical representativeness and
confidentiality of the respondent survey data. EPA also obtained financial data from various land grant
universities, including enterprise budgets that portray financial conditions for an operation's livestock or
poultry enterprise. In particular, the University of Missouri's Food and Agricultural Policy Research
Institute (FAPRI) submitted financial data for several sectors that were collected as part of its evaluation
of EPA's Proposal EA. EPA also obtained financial data from the National Cattlemen's Beef
Association (NCBA) based on a survey of its membership to obtain financial statistics specific to cattle
feeding operations. Section 2.3 and other sections of this report discuss these data in more detail and
describe how these data sources contribute to EPA's analyses.
2.1.3 Overview of EPA's Economic Model (2001 Proposal)
For the proposed rulemaking, EPA developed an economic model to assess financial impacts on
regulated CAFOs based on predicted changes to select financial criteria. This approach is documented in
2-4
-------
the 2001 Proposal (66 FR 3079-3103) and the Proposal EA (USEPA, 2001a). Additional information is
available in the Development Document supporting the regulations (USEPA, 2001b, 2002).
To assess regulatory impacts on CAF0s, EPA developed an economic model to assess financial
effects based on predicted changes to select financial criteria. This model consists of a series of
representative model CAFOs that EPA used to evaluate estimated compliance costs against assumed
baseline financial conditions. EPA evaluated the economic achievability of the proposed regulatory
options at existing operations based on changes in representative financial conditions across three
financial criteria: (1) an initial screening comparing incremental pre-tax costs to total gross revenue
("sales test"), (2) projected post-compliance cash flow over a 10-year period ("discounted cash flow
analysis"), and (3) an assessment of an operation's debt-asset ratio under a post-compliance scenario
("debt-asset test"). These criteria were evaluated using 1997 data from USDA reflecting financial
conditions at the whole-farm level (i.e., reflecting income and cost information spanning an operation's
primary livestock production, as well as secondary livestock and crop production, government payments,
and other farm-related income). Based on estimated changes to these select criteria, EPA divided the
impacts of the proposed regulations into three financial impact categories: Affordable, Moderate, and
Stress. Operations experiencing affordable or. moderate impacts are considered to experience some
financial impact on operations at the affected CAFOs, but EPA does not consider these operations to be
vulnerable to closure as a result of compliance. Operations experiencing financial stress impacts are
considered to be vulnerable to closure post-compliance. Section 4 of the Proposal EA provides more
information about EPA's justification for using this approach and the assumptions in the model.
To assess economic effects on national markets, EPA used an approach adapted from a model
developed by ERS to evaluate various policy scenarios in terms of changes in farm and retail prices and
product quantities. Once price and quantity changes were predicted by the model, EPA used national
multipliers that relate changes in sales to chan'ges in total direct and indirect employment and also to
national economic output. The approach and data used for this analysis are described in Section 4 and
Appendix B of the Proposal EA.
2.1.4 Overview of Changes to EPA's Economic Model (Final Rule)
As detailed in the 2001 Notice (see 66 FR 58577-58591), EPA received many public comments
on its economic analysis regarding the appropriateness of the financial data and the assessment criteria
used for the analysis, as well as other aspects of EPA's model. The 2001 Notice details the major
comments received on EPA's proposal, including recommendations that EPA (1) expand the range of
cost estimates per representative farm to account for variability across operations (based on expected
capital and management improvements needed); (2) add assessment criteria to measure changes in net
farm income (profits) in addition to criteria considered in the analysis; (3) consider financial data to
depict baseline conditions that consider revenue from an operation's livestock or poultry enterprise level
only, rather than consider income available to;an operation from all enterprises at that operation ("farm
level" data); (4) revise the baseline data and the criteria threshold used to analyze the debt-asset test
(which would reflect higher baseline debt levels in industry); (5) consider debt feasibility to evaluate an
operation's ability to incur new debt; and (7) consider other available financial data for multiple years to
supplement EPA's analysis based on a single year of data. Other comments include recommendations on
EPA's assumptions on cost offsets, such as income from manure sales and cost-sharing and technical
assistance. Additional information is presented in the 2002 Notice (see 67 FR 48110-48105).
2-5
-------
Both Notices describe ways in which EPA would address these concerns and also present
alternative financial data that the Agency is considering to perform its analysis. Comments received by
EPA from industry and the land grant universities on both Notices largely support these efforts and
provide additional recommendations. However, EPA also received comments that challenge the
methodological changes presented in the 2001 Notice. These comments claim that EPA failed to
consider societal costs and industry impacts accounting for various cost offsets, including cost savings of
converting from confined to pasture-based systems as well as cost passthrough from farm to processor.
See Waterkeepers Alliance, etal. (2001) and Sierra (Club (2001), and other supporting comments (Bcerd
2001; Weida, 2001).
The EA supporting the final regulations retains the general modeling framework that the Agency
used to assess economic effects for the 2001 Proposal, with the modifications discussed in both EPA
Notices. Section 2.3 of this-report presents financial data that EPA uses for its final analysis. Section
2.4 describes changes to the approach EPA uses to assess financial effects to CAFOs.
2.2 ESTIMATES OF ANNUAL COMPLIANCE COSTS
2.2.1 Development of Representative Model CAFOs
To evaluate regulatory impacts on CAFOs, EPA has developed a series of model CAFOs to
conform to a representative farm approach. This approach consists of two major modeling components:
cost models and financial models. This section describes EPA's cost models; Section 2.3 describes
EPA's financial models. Section 4 of the Proposal EA provides additional information on the
development and interface of the cost and financial models.
Model CAFOs developed for EPA's analysis reflect average conditions for selected groups of
livestock and poultry operations. Three factors are recognized to affect the way CAFOs operate: (1)
commodity sector (beef, veal, heifers, dairy, hogs, broilers, layers, turkeys); (2) farm production region;
and (3) facility size (based on herd or flock size or the number of animals on site). EPA's cost models '
and financial models are therefore differentiated by sector, select region, and size group.
The CAFO models EPA uses for this analysis represent the interface between a large number of
cost models and a smaller number of financial models. Fewer financial models are developed because of
data availability issues (as discussed in detail in Section 4 of the Proposal EA). The cost models are able
to account for greater variability among operations, as compared to the financial models. This variability
includes differences in production types, geographic conditions and production region, land availability,
technology needs, and so forth. For example, EPA is able to account for individual costs to veal and
heifer operations; however, financial data are not available for these individual sectors. Data are
available to reflect cost differences between egg-laying operations that use liquid manure management
systems and dry systems, but financial data do not capture these differences in cost and returns. The cost
models can account for the type of animal production facility, the availability of cropland and
pastureland to land apply manure nutrients, farmland, geography, and existing state regulatory
requirements. They can also reflect cost differences within sectors based on manure composition,
bedding use, and process water volumes. For more detailed information, refer to the Development
Document (USEPA, 2002). As discussed in Section 2.4, however, the financial models are able to
account for certain other factors, such as business type and legal structure, which could affect an
assessment of whether an operation is able to afford the estimated cost of compliance.
2-6
-------
For its cost analysis, EPA has developed representative models that account for variability
among the different types of operations, accounting for differences based on available cropland for
manure application, differences by production region and by facility type, and an operation's current
manure management practices and technology needs. As described in more detail in the Development
Document (USEPA, 2002), estimated compliance costs distinguish between three categories of land
availability: Category 1 CAFOs (sufficient cropland for all manure nutrients generated), Category 2
CAFOs (insufficient cropland), arid Category 3 CAFOs (no cropland). EPA's estimated costs also
distinguish between three categories of technology needs based on the types of manure management
practices already in place: "Average Needs" (assumed for 50 percent of all operations), and "Least
Needs" and "Most Needs" (assumed to account for 25 percent each of all operations). In addition, EPA's
cost models account for production area differences in costs that are critical to an assessment of
incremental compliance costs. See Section 2.2.3 of this report.
EPA's cost models aggregate USDA's regions into five broad production regions for the
purposes of estimating costs: Midwest (MW); Central (CE); Pacific (PA); Mid-Atlantic (MA); and South
(SO) (see USEPA, 2002). The financial models, however, are not distinguishable by this many regions
because available financial data do not allow for aggregation at this level of detail. Where financial data
are not available by region, national data are used. To match up with fewer regional models in the
financial analysis, EPA collapses the total number of regions evaluated in some cases. To do this,
estimated number of CAFOs in regions other than the major production regions are allocated to the major
regions on an equally weighted basis. That is,! within each sector, 50 percent of CAFOs in regions other
than the two primary production regions are assigned to one major production region and the other 50
percent are assigned to the other. • , . •
Finally, EPA's cost models are developed across a broad range of facility size groups, including
CAFOs with more than 1,000 AU2 (Large 1 and Large 2 CAFOs) and operations with between 300 AU
and 1,000 AU (Medium 1,2, and 3 model CAFOs). Facility size categories vary by sector; the average
number of animals represented by each model: CAFO is based on typical inventory estimates that are
common for that size range in a particular sector. Data limitations restrict the number of facility size
categories available for EPA's financial models. In some cases, available financial data generally cover
operations with more than 1,000 AU and operations with fewer than 1,000 AU. In cases where available
data do not match this size breakout, EPA uses national average data. Because the cost and financial
models are both expressed in terms of per-animal (inventory) basis, this approach allows EPA to link the
available data on baseline financial conditions to estimated compliance costs across representative
CAFOs, thus capturing differences in facility size. See the discussion in Section 2.4.
Table 2-1 shows the range of facility sizes and the average number of animals associated with
each size range that EPA assumes for each model CAFO. See the Development Document (USEPA,
2002) for more information on the development of the model sizes shown in the table.
2.2.2 Compliance Assumption Under Existing Regulations
For the 2001 Proposal, EPA estimated only the costs of the new requirements attributable to the
proposed regulations. All operations with more than 1,000 AU that are defined as CAFOs by the existing
As defined for the final regulations, one AU is equivalent to one slaughter or feeder cattle, calf, or heifer;
0.7 mature dairy cattle; 2.5 hogs (over 55 pounds) !or 5 nursery pigs; 55 turkeys; 30 egg-laying chickens (wet
manure systems); and 125 meat chickens and 82 egg-laying chickens (regardless of waste system used).
2-7-
-------
regulations are currently required to be in compliance with the existing regulatory program. As a result,
all existing CAFOs with more than 1,000 AU—except poultry operations with dry manure management
systems, which are not covered by the existing regulations—were costed for full compliance since they
are covered by the existing regulations. This includes the NPDES regulations and the effluent limitations
guidelines and standards for feedlots. For those operations with less than 1,000 AU, EPA used available
data regarding current waste treatment practices under existing State laws and regulations to estimate the
incremental cost they would incur to comply with the requirements of the proposed regulations.
EPA acknowledges comments claiming that many CAFOs do not have the necessary waste
management components in place to comply with the existing CAFO regulations promulgated in 1974.
Although the existing regulations were issued over 25 years ago, these commenters claim that many
operations with 1,000 or more AU are not currently in compliance with these baseline requirements and
would therefore incur substantial costs just to meet the 1974 requirements, in addition to any additional
costs that would be incurred to comply with the new requirements of the proposed rule. Limited
supporting data and information has been provided to EPA support these claims. However, EPA believes
that it should consider only the costs attributable to the revised requirements and assume that existing
CAFOs are in compliance with current requirements that were issued over 25 years ago. See also
response to comment DCN CAFO400177-27 in EPA's COmment Response Document.
It is EPA's longstanding practice to attribute to a revised rule only the incremental cost of new
requirements when revising existing regulations. EPA's methodology is authorized by the Clean Water
Act (CWA). Under Section 301(b)(2)(B), EPA is required, when identifying BAT, to take into account a
variety of factors, including the cost of achieving effluent reductions attainable through the application of
BAT. The existing regulations identify BAT and require a certain level of effluent reduction. The
effluent reductions attributable to the final revised regulation are those which are a result of new
requirements. Therefore, EPA must evaluate the cost of achieving those additional reductions. The cost
to implement Part 412 was considered when Part 412 was promulgated hi 1974. If EPA were to now
account for the cost to bring existing CAFOs into compliance with the 1974 requirements, the Agency
would therefore bear the cost and impact of the 1974 regulation a second time. There should be no
reward for non-compliance.
Not only is it statutorily required but reasonable to assume full compliance twenty-five (25) years
after promulgation. The Clean Water Act (CWA), in Section 301(b)(3) states "for effluent limitations ...
promulgated after January 1,1982..., compliance as expeditiously as practicable but in no case later than
three years after the date such limitations are promulgated (Part 412 was promulgated in 1974)...and in
no case later than March 31, 1989..." Furthermore, the National Pollution Discharge Elimination System
(NPDES) permits regulation at Part 122.47(a)(l) states, "Any schedules of compliance under this section
shall require compliance as soon as possible, but not later than the applicable statutory deadlines under
the CWA." 40 CFR 122.63(13) further states under compliance schedule "...In no case shall the
compliance schedule be modified to extend beyond an applicable CWA statutory deadline for
compliance." The statutory deadline for full compliance for Part 412 has long passed.
EPA believes that the Agency is well within any test of reasonableness to assume full compliance
25 years after the rule was promulgated. The practice of assuming compliance is consistent with EPA's
published guidance for conducting regulatory analysis, outlined hi EPA's "Guidelines for Preparing
Economic Analyses, USEPA, 2000." EPA's guidance is available online at
http://www.epa!gov/economics/. In accordance with EPA practice and guidance, EPA assumes that
operations with 1,000 or more AU are hi compliance with existing requirements promulgated hi 1974;
,2-8
-------
these operations are assumed to have akeady incurred whatever costs were necessary to achieve
compliance with these existing requirements. ,
As discussed in the 2001 Notice, guidance from the Office of Management and Budget (OMB),
as outlined in "Economic Analysis of Federal Regulations Under Executive Order 12866," recommends
that the baseline for assessing the costs and benefits of a regulation be, "... the best assessment of the way
the world would look absent the proposed regulation." OMB's guidance goes on to discuss various
factors that may be considered in choosing an appropriate baseline, including existing regulations and the
likely degree of compliance with these regulations, and recommends that, "when more than one baseline
appears reasonable or the baseline is very uncertain, and when the estimated benefits and costs of
proposed rules are likely to vary significantly with the baseline selected, the agency may choose to
measure benefits and costs .against multiple alternative baselines as a form of sensitivity analysis."
OMB's guidance is available online at http://www.whitehouse.gov/omb/inforeg/riaguide.html.
EPA did consider ways to evaluate the possibility that there may be noncompliance with the
existing regulations and the additional potential costs of compliance as a supplement to its cost and
economic analyses. To evaluate the cost of the existing regulations, EPA requested additional data and
information on current rates of non-compliance in a 2001 Notice of Data Availability ("2001 Notice" at
66 FR 58556). Information was requested on the number or share of operations with more than 1,000
AU that are not in compliance with the existing regulations. During the development of the proposed
CAFO rulemaking, EPA requested additional data and information to substantiate industry claims of
widespread non-compliance with the existing regulations. In the 2001 Notice, EPA requested
information on current rates of non-compliance with the existing regulation, differentiated to the extent
possible by production type or facility size for each of the major livestock and poultry sectors. This
information would be needed to account for animal waste management systems and practices that are
akeady being implemented at the CAFO to manage manure and wastewater, including practices
associated with various voluntary programs as well as practices to assist with basic day-to-day production
needs at the facility.
EPA considered using any information submitted to conduct an evaluation of the combined
additional cost to comply with the existing regulations plus the incremental costs of the proposed
regulations. In the 2001 Notice, EPA also solicited comment on an approach that would be conducted in
two stages, which is outlined as follows. j
The first stage of this analysis would assess the cost to CAFOs to comply with current
requirements—specified for the production area—promulgated under the existing 1970s regulations and
further evaluate the expected financial impacts of these costs. Using a representative farm approach,
where the Agency determines that compliance with the existing regulations would have resulted in
financial stress and potential closure of a representative facility, this operation would be removed from
the analysis under the assumptions that this operation would not have remained in business. This
representative facility would now constitute a baseline closure for purposes of evaluating the proposed
revisions to the existing rule. This approach by which baseline closures are removed from any
subsequent analyses is consistent with longstanding Agency practice to assess only the incremental costs
associated with a specific regulatory action.
The second stage of this analysis would evaluate costs and financial impacts to comply with the
revised requirements. These costs and impacts would be assessed for operations within the assumed
remaining CAFO universe based on the number of operations assumed to have remained in business
2-9
-------
while complying with the existing regulations (i.e., excluding assumed baseline closures determined to
close under the existing regulations in the first stage of this analysis). This alternative approach likely
would have resulted in a reduced total CAFO population for the purposes of EPA's regulatory analysis,
since those CAFOs determined to be unable to absorb the costs of the existing 1974 effluent guidelines
requirements would have been eliminated from the analysis prior to assessing the financial effects of the
final revised requirements. This alternative approach might have allowed EPA to consider more
stringent and more costly requirements for this rulernaking had EPA been focusing primarily on those
more financially secure CAFOs that have already been successful in absorbing the costs of the existing
requirements.
EPA solicited comment on this approach and requested data and information in order to conduct
this supplemental analysis. Subsequent to the proposal and the 2001 Notice, EPA received no
substantive data to document the claim of substantial non-compliance and associated compliance cost in
the CAFO industry. Minimal data was submitted for two segments of the industry but the basis of these
data were not included. Neither stage of this assessment could be addressed; therefore, EPA was unable
to calculate a reasonable alternative cost estimate because no substantive and useful information is
available or was provided by comtnenters.
Due to the lack of substantiation of the baseline compliance claims, EPA's final analysis
continues to assume that operations with 1,000 or more AU are hi compliance with existing regulations
(not including poultry operations with dry manure management systems). Accordingly, EPA's estimates
of the incremental costs attributable to the final regulations take into account information regarding
current Federal and State requirements for animal feeding operations and calculate compliance costs of
the final requirements that exceed the current requirements. Operations located in states that currently
have requirements that meet or exceed the proposed regulatory changes would already be hi compliance
with the final regulations and would not incur any additional cost.
EPA's final analysis also accounts for current structures and practices, assumed to be hi place
already at operations, that may contribute towards compliance with the regulations. However, EPA has
made significant improvements to its analysis to better estimate the types of practices and controls at
existing facilities. EPA's analysis now provides an expanded range of cost estimates that accounts for
greater variability across operations based on expected capital and management improvements needed.
This approach is discussed in the following section Section 2.2.3 of this report. More detailed
information is provided hi the Development Documents (USEPA, 2002, 2001b).
2.2.3 Method for Estimating CAFO Compliance Costs
Section 4 of the Proposal EA summarizes EPA's approach to estimate compliance costs to
CAFOs and to non-CAFO recipients of manure generated at CAFOs. EPA's Development Documents
for the proposed and final rule provide detailed information on EPA's cost analysis (USEPA, 2001b
2002).
For the purpose of estimating total costs and economic impacts, EPA calculates the costs of
compliance for CAFOs to implement the final regulatory options being promulgated. EPA estimates
costs associated with four broad cost components: nutrient management planning, facility upgrades, land
application, and technologies for balancing on-farm nutrients. Nutrient management planning costs
2-10
-------
include manure and soil testing, record keeping, and plan development, among other costs. Facility
upgrades reflect costs for manure storage, mortality handling, storm water and field runoff controls,
reduction of fresh water use, and additional farm management practices. Land application costs address
agricultural application of nutrients, including hauling of excess manure off-site and adjusting for
changes in commercial fertilizer needs, and reflect differences among operations based on cropland
availability for manure application at a representative CAFO. Specific information on the capital costs,
annual operating and maintenance costs, startup or first-year costs, and also recurring costs that EPA
uses to estimate impacts of the final regulations is provided in the Development Document (USEPA,
2002). EPA also uses these model CAFOs to estimate total aggregate incremental costs to the CAFO
industry. _ ]
EPA evaluates compliance costs using a representative facility approach based on about 1,600
farm level cost models to depict conditions and to estimate compliance costs for select representative
CAFOs (USEPA, 2002). The major factors used to differentiate individual model CAFOs include the
commodity sector, the farm production region, and the facility size (based on herd or flock size or the
number of animals on-site). EPA's model CAFOs primarily reflect the major animal sector groups,
including beef cattle, dairy, hog, broiler, turkey, and .egg-laying operations. Practices at other subsector
operations are also reflected in the cost models, such as replacement heifer operations, veal operations,
operations with flushed caged layers, and grow-finish and farrow-finish hog operations (USEPA, 2002,
200 lb).3 EPA bases its analysis on results for model facilities with similar waste management and
production practices to depict operations in regions that are not separately modeled.
Another key distinguishing factor incorporated into EPA's model CAFOs is information on the
availability of cropland and pastureland for land application of manure nutrients. For this analysis,
nitrogen and phosphorus rates of land application are evaluated for three categories of cropland
availability: Category 1 CAFOs are assumed to have sufficient cropland for all on-farm nutrients
generated, Category 2 CAFOs are assumed to have insufficient cropland, and Category 3 CAFOs are
assumed to have no cropland (USEPA, 2002). EPA uses 1997 information from USD A to determine the
number of CAFOs in each category. This information takes into account which nutrient (nitrogen or
phosphorus) is used as the basis to assess land application and nutrient management costs.
For Category 2 and Category 3 CAFOs, EPA evaluates additional technologies that may be
necessary to balance nutrients. Such technologies reduce off-site hauling costs associated with excess
on-farm nutrients, as well as address ammonia redeposition, pathogens, trace metals, and antibiotic
residuals. These technologies may include BMPs and various farm production technologies, such as feed
management strategies, solid-liquid separation, composting, anaerobic digestion, and other retrofits to
existing technologies. EPA considers all of these technologies for identification of "best available
technologies economically achievable" (BAIJEA) under the various regulatory options described in the
preamble for the final rulemaking. ;
For the proposal, EPA estimated compliance costs for a model CAFO facility by first estimating
the total cost to an individual facility to employ a given technology including the full range of necessary
capital, annual, start-up, and recurring costs. ;EPA then weights the average facility level cost to account
for current use of the technology or management practice nationwide based on certain weighting factors,
3Grow-fmish operations finish more mattire pigs, while farrow-finish operations handle all stages of
production from breeding to finishing. !
t
1 2-11
-------
referred to in the analysis as "frequency factors," that the Agency assumes for each individual cost (each
technology) and cost component (capital and annual costs) in each of its CAFO models (USEPA, 2002).
Average costs were obtained by multiplying the total cost of a particular technology or practice by the
frequency factor for that costing category, expressed as the percent of operations that are believed to use
this particular technology or practice, to derive the average expected cost that could be incurred by a
model CAFO. More information on how EPA developed and tested the frequency factors used for this
analysis is provided in the Development Documents (USEPA, 2002,2001b). These documents also
provide additional information on the data and assumptions EPA uses for its cost models.
EPA received public comments that challenge this general approach because it fails to account
for variability among operations. To address this concern, the 2001 Notice presents an alternative way to
characterize the variability of costs that might be incurred by increasing the number of representative
models used to assess compliance costs (66 FR 58572-58573). The 2001 Notice presents data and
information from USDA that support this approach (see USEPA, 2002). This approach would first
define a set of model CAFOs that represent typical or dominant production practices. Second, it would
identify the expected compliance costs associated with the proposed CAFO rule requirements. Finally, it
would adjust these costs according to how many CAFOs are expected to need upgrades to their facilities
or practices to meet requirements. Compared to EPA's analysis for the 2001 Proposal, this approach
further breaks out these costs into three categories of farms based on the "average" operation and also
operations with "least needs" and "most needs." For the purpose of this analysis, EPA uses USDA's
simplifying assumption for this approach: 50 percent of all operations within each representative farm
group represent the average, while each representative group representing operations outside the average
accounts for 25 percent of all operations. More information on this approach is presented in the 2001
Notice (66 FR 58556) and the Development Document supporting the final rale (USEPA, 2002).
EPA's cost models also account for other differences among operations, including soil type and
other production factors, such as climate and farmland geography, land application and waste
management practices, and other major production practices typically found in the key producing regions
of the country. Model facilities reflect major production practices used by confinement operations with
more than 300 AU. More information on EPA's cost models is provided in the Development Document
(USEPA, 2002).
Where costs are not estimated for operations with fewer than 300 AU (e.g., for operations
designated as CAFOs because they are determined to contribute to water quality impairment), EPA uses
available compliance costs for other model CAFOs. EPA approximates costs to expected designated
facilities using estimated costs for the smallest size model CAFO among operations with between 300
and 1,000 AU ("Medium 1" operations),4 with the added assumption that these potential costs and effects
are represented by costs developed to depict operations in the more traditional production regions
(Midwest for the livestock and turkey operations and Southeast for the broiler and egg laying operations).
For analysis purposes, EPA further assumes that these operations are characterized as having available
land for land application of manure (Category 1 model facilities) and high technology needs ("most
needs"). More detailed cost information is provided in the Development Document (USEPA, 2002) and
related cost reports. See also EPA's Comment Response Document available in the rulemaking record.
The smallest model for wet layer is Medium 3, which were used for this analysis (see Tale 2-1).
2-12
-------
2.2.4 Cost Annualization Methodology
EPA develops CAFO compliance costs from estimated start-up (first-year) costs, recurring
3-year and 5-year costs, and annual operating and maintenance costs. To compare estimated costs to
available farm financial data in any one year, EPA annualizes these costs using the approach described
below. A 1997 time frame is used for comparison with available USDA data on livestock and poultry
farms, as reported in the 1997 Census of Agriculture and other related databases. The inputs and
assumptions of the cost annualization model are summarized as follows.
Annualized costs account for the tune value of money and reflect the annual repayment amount
of an on-farm capital investment by spreading the initial costs over the expected life of the structure.
EPA calculates both pre-tax and post-tax annual costs. Pre-tax costs are used to estimate the total cost of
the final regulations to society (social costs). Post-tax costs are used to measure the economic impacts at
CAFOs and to account for the reduction in a CAFO's tax liability. This reduction in taxes paid ("tax
shield") offsets the expected compliance costs incurred by a facility. This portion of costs is borne by
Federal and State governments through a reduction in tax revenue. Accordingly, the economic impacts
of the final regulations are measured as the impact of the expected compliance cost incurred by a CAFO
minus an appropriate tax shield. \
The major inputs to and assumptions used in the cost annualization model are (1) the discount
rate, (2) the life of the asset, and (3) tax rates. \ EPA uses the discount rate to calculate the present values
of the cash flows. This rate is analogous to ah interest rate used to compute a mortgage payment. The.
annualization model uses a real discount/interest rate of 7 percent, as recommended by the Office of
Management and Budget (OMB, 1992), which does not have to be adjusted for inflation. EPA also
evaluates costs assuming an alternative discount/interest rate of 3 percent to compare monetary benefit
estimates using a range of rates (see the Benefits Analysis (USEPA, 2002k). Cost estimates assuming an
alternative 3 percent discount rate are also presented hi Section 5, comparing estimated costs and benefits
assuming this rate. ,
The life of the asset is the tune period over which the costs are to be annualized (like a mortgage
time period) and is determined according to the Internal Revenue Code's classes of depreciable property.
The time period over which the annualization is made depends on the serviceable life of the structure as
well as on the depreciable life, which affects what portion of a capital cost can be used each year to
reduce taxable income. The Internal Revenue Service (IRS) rules govern the designation of depreciable
life, which is assigned on the basis of serviceable life. Most of the types of capital investments required
under these regulations are typically depreciated over 10 years (IRS, 1999c).5 The cost annualization
model thus incorporates a 10-year annualization period to compute both pre-tax and post-tax annual
costs. The equation EPA uses to calculate annual cost operates from mid-year to mid-year (mid-year
convention); therefore, the entire time frame of the analysis begins in Year 1 and concludes in Year 11
but is discussed here as a 10-year time frame (see Appendix A).
The assumed tax rates are used to determine a facility's tax benefit or tax shield. Estimated tax
savings are subtracted from the actual outlay in each year and are used to calculate the annual post-tax
Many of the types of investments would jbest be classified as single-purpose agricultural structures, which
IRS defines as enclosures or structures specifically designed, constructed, and used for housing, raising, and feeding
a particular kind of livestock, including structures ito contain produce or equipment necessary for housing, raising,
and feeding livestock. .;
2-13
-------
cost of compliance. The tax shield calculation uses three inputs: marginal tax rates (composed of Federal
tax rates and an assumed State tax rate); an estimate of CAFO taxable income (net cash minus
depreciation plus value of inventory change, assuming the CAFO is using the accrual method of
accounting); and a depreciation schedule.
EPA calculates compliance costs to CAFOs under both pre-tax and post-tax scenarios. The pre-
tax costs reflect the estimated total social cost of the final regulations, including lost tax revenue to
governments. EPA uses calculated pre-tax dollars when comparing estimated costs to monetized benefits
that are estimated to accrue under the final regulations. (EPA also uses pre-tax costs to conduct an
initial screener of CAFO level financial effects; see Section 2.4.) Post-tax costs reflect the fact that a
CAFO would be able to depreciate or expense these costs, thus generating a tax savings. Post-tax costs
thus are the actual costs the CAFO would face. For this reason, EPA evaluates cash flow changes at
CAFOs over time taking into account the tax savings to facilities, according to estimated post-tax costs,
using available Federal and State tax information to compute the expected tax shield for a representative
model facility (see Section 2.4).
Appendix A provides a description of how the tax rates are assigned to each model CAFO. The
depreciation schedule is dictated by IRS rules, but there are several choices of depreciation schedule
within those rules. For reasons outlined in Appendix A, EPA has chosen the Modified Accelerated Cost
Recovery System (MACRS), which is a commonly used and generally advantageous depreciation
schedule for tax minimization purposes. The tax shield is calculated using the depreciable capital cost in
each year plus any recurring expenditures allowed to be expensed in each year. Each model CAFO is
assigned a tax rate (marginal Federal rate plus an assumed State tax rate) based on the estimated amount
of taxable income. The tax rate times the depreciated and expensed compliance cost in each year equals
the estimated tax shield.
Appendix A of this report also provides more detailed information on the cost annualization
approach used for this analysis and presents a sample spreadsheet that shows how all of the computations
are made. The appendices also document all annualized incremental costs estimated by EPA (pre-tax,
expressed in 1997 dollars) by model facility and by animal inventory (Appendix B) for each of the major
livestock and poultry sectors. Section 3 presents the aggregated, national level annualized compliance
costs (pre-tax, 2001 dollars) for the final regulations. Input costs used for this analysis are provided in
the Development Document (USEPA, 2002).
2.3
BASELINE FINANCIAL DATA FOR EPA MODEL CAFOs
This section describes the data that EPA uses to depict baseline financial conditions at regulated
CAFOs. Section 2.3.1 describes the sources of data used for the 2001 Proposal and alternative data that
EPA received during the comment period to address public comments on the data and approach that the
Agency uses to assess regulatory impacts for the final regulations. Section 2.3.2 discusses the process
EPA uses to select among the available data to build baseline financial models for each of the affected
sectors and also describes, in some cases, any adjustments that EPA made to these data. Section 2.3.3
briefly restates how EPA matches these financial models to the cost models developed to represent model
CAFO facilities, which is described in more detail in the Proposal EA (USEPA, 200la).
2-14
-------
I
The financial data presented in this section reflect consideration of alternative data for use in
EPA's analysis based on comments received during the public comment period. During this period, EPA
received many comments on the financial data used to estimate CAFO level effects in the 2001 Proposal.
In many cases, these comments were accompanied by alternative financial data for consideration by EPA.
Among the principal comments that EPA received on its Proposal EA is the need to separately evaluate
effects on an individual operation's livestock lor poultry enterprise. This recommendation originated
from USDA, various land grant universities, and some industry representatives. The comments
recommend that EPA evaluate impacts using livestock enterprise level data that do not include revenue
from other farm-related sources (e.g., secondary livestock, crops, government payments). This approach
differs from the approach EPA used to evaluate effects for the 2001 Proposal, where only farm level
financial data were used to evaluate regulatory impacts on CAFOs using financial data that include
revenue from other farm-related sources. This change in the approach and underlying data for the
analysis was presented uvthe 2001 Notice. This section describes these data for EPA's final analysis and
describes additional adjustments that EPA made to respond to other public comments received on the
2001 Proposal, the 2001 Notice, and the 2002 Notice.
2.3.1 Sources of Data
To evaluate the regulatory impacts of the final regulations, EPA uses both farm level and
enterprise level financial data compiled from a variety of sources, including USDA, various land grant
universities and academic research organizations, as well as data provided by the regulated industry.
The financial data that EPA uses for its analysis of the final CAFO regulations depict baseline
conditions at both the farm level and enterprise level. At the farm level, for most sectors, EPA will
continue to use available 1997 farm level data from USDA, which EPA used for proposal. For the cattle
feeding, dairy, and hog sectors, EPA substitutes the financial data used for proposal with alternative data
obtained since proposal, as discussed later in this report. For the poultry sectors, EPA continues to use
the 1997 USDA farm level data used for proposal, but also uses additional enterprise level data obtained
from USDA and various land grant universities. All alternative data used by EPA were presented in both
the 2001 Notice and the 2002 Notice. More information is provided in the rulemaking record.
i
2.3.1.1 USDA's Agricultural Resource Management Study
A key source of financial data used by EPA to evaluate the regulatory impacts of the final
regulations is USDA's ARMS data. The ARMS is USDA's primary method for collecting data covering
a broad range of issues about agricultural production practices and costs. These data provide the only
national perspective on annual changes in the (financial conditions of production agriculture (USDA/ERS,
2000a). The ARMS is an annual survey conducted using a probability sample, which in 1997 included
information from 11,724 surveyed farms nationwide. The sample survey is hand-enumerated by trained
personnel. USDA extrapolates the data from the sample survey to represent farming and ranching
operations in the 48 contiguous states. These jnational level data are published in a series of annual and
periodic reports, such as USDA ERS's annual compendiums on farm costs of production and on farm
financial performance (data formerly identified as the Farm Costs and Returns Survey data).
Data on both family and nonfamily farms are included in the ARMS data (USDA/ERS, 2000b,
1999a). USDA's farm typology data also provide information on animal ownership based on the
2-15
-------
percentage of animals raised at the farm site that are owned or not owned by the farmer (e.g., raised
under contract for another business entity) (USDA/ERS, 1999a). This information is useful for
understanding the average data, which include all the different farm structure types that are captured in
the aggregated ARMS data for each livestock and poultry sector. The ARMS revenue data are separable
by enterprise (livestock and crops), as well as by other farm-related income and government payments.
Off-farm revenue is not included in the ARMS data used by EPA for this analysis, as described
previously under revenue definitions for "Income Statement Information." However, the ARMS
operating expense data are not separable by enterprise (e.g., buildings, labor and equipment for crop
versus livestock production), but instead represent average production costs for an operation as a whole.
This generally limits the types of analyses that EPA can conduct using these data for its economic impact
analysis. Also, USDA information on off-farm revenue is not included in this analysis.
Aggregated ARMS data are readily available through periodic compendiums published by
USDA. To depict financial conditions for selected representative farm groups, EPA requested that USDA
provide these data on a more disaggregated basis than that found in the published data. As noted
extensively throughout the 2001 Proposal and various support documents, USDA periodically publishes
summary data from its farm level databases and provides customized analyses of the data to the public
and other government agencies. The requested ARMS data summaries were compiled with the assistance
of staff at USDA's ERS, who performed special tabulations of the data to differentiate the financial
conditions among farms by selected facility size categories and by primary producing region for each
sector. ERS developed a methodology for identifying farms likely to be CAFOs based on reported
survey information, and developed estimates of animal units on these operations based on reported data.
Given these estimates, farms were grouped into animal unit size categories and data were provided to
EPA and other government agencies. All data provided to EPA are sufficiently aggregated to ensure the
confidentiality of an individual farming operation and to maintain the statistical representativeness of the
sample data.
In general, the published data provide financial information on a total, national basis across all
farms for only four aggregated sectors: beef, dairy, hogs, and poultry. These data are reported across all
production types and businesses, and in the poultry sector thus combine information across all broiler,
turkey, and egg laying operations. However, the underlying ARMS database provides information on the
financial conditions within individual sectors. These data can also be grouped to show differences
among farms by facility size and production region, among other factors.
For the purposes of EPA's analysis, the Agency requested more detailed data from USDA for the
poultry sector (1997 data), the hog sector (1998 data), and the dairy sector (2000 data). In some cases,
USDA data are not available for each level of aggregation because of confidentiality and nondisclosure
requirements, requiring that EPA use national level data. For the poultry sectors, the 1997 ARMS, which
was conducted in conjunction with USDA efforts to collect the 1997 Census, contains more detailed
information and allows for the breakout of financial conditions across the poultry category, including
broiler, turkey, and egg-laying operations. EPA uses the farm level data to estimate financial effects on
poultry operations for the 2001 Proposal. Since the 2001 Proposal, EPA has obtained additional
financial data for the hog and dairy sectors from a special ARMS compilation of these sectors. These
data provide a means for USDA to break out enterprise level operating revenues and costs to depict
financial conditions at an operation's livestock or poultry enterprise separate from the revenues and costs
for the whole facility. The 1997 ARMS operating expenses data are not distinguishable by business
enterprise, but are the total for the business. For the hog sector, these data allow for greater breakout of
financial conditions across the different production types (farrowing, farrow-finish, and grow-finish) as
2-16
-------
well as across different business types (contract grower and independent owner-operator). The
rulemaking record documents how EPA worked with USDA to obtain additional data since the 2001
Proposal (see: USEPA, 2002a, 2002b, 2002c, 2002d, 2002f, 2001c, and 2001d; USDA/ERS 2002a
2002b, 2002c, 2002d, 2001,2001a, 2001b, 20;01c, and 2001d; ERG, 2002c; ERG and DPRA, 2001). A
detailed summary of how EPA uses the available hog data obtained from USDA is available in the record
(ERG, 2002c—DCN 375083). i
Financial data obtained by USDA from its ARMS and related databases are based on average
end-of-year farm inventories. 1997 ARMS data obtained by USDA include information on the total
number of farms and the total number of animals in the sample set. These data correspond exclusively to
the average income statement and balance sheet information for representative farms compiled by ERS
for each aggregated data grouping by commodity, production region, and facility size groups
(USDA/ERS, 1999a). EPA uses these data to Calculate financial data on a per-animal inventory. (See
Section 4.2.4 of the Proposal EA [USEPA, 20Qla], which also describes how EPA compiled its financial
models using the 1997 ARMS data.) Data obtained from USDA by special compilation of recent hog and
dairy financial data were translated on a per-animal inventory basis by USDA (USDA/ERS 2002a
2002b, 2002c). '
2.3.1.2 Data from Various Land Grant Universities
To supplement EPA's farm level assessment of regulatory impacts conducted for the 2001
Proposal with an assessment of impacts at an operation's livestock or poultry enterprise, EPA obtained
enterprise level financial data or "enterprise budgets" from a variety of land grant universities and
academic research organizations. ''•
Enterprise budgets are useful tools for examining the potential profitability of an enterprise
before actually making an investment. To create an enterprise budget, an analyst gathers information on
capital investments, variable costs (such as labor and feed), and fixed costs (e.g., interest and insurance),
combined with price information and typical production yields, to estimate annual revenues, costs, and '
returns for a project. By varying different input parameters, enterprise budgets can be used to examine
the relative importance of individual parameters to the financial return of the project or to identify break-
even prices required to provide a positive return.
. As part of EPA's public comment period, FAPRI submitted enterprise budgets developed by a
panel of industry experts (PAPRI, 2001a). (See: DCN 235619.) For its study, FAPRI convened a panel
of experts "to provide a snapshot of each enterprise at a given point in time" (FAPRI, 2001a, 2001b).
These experts developed information on the financial characteristics of each model farm at the enterprise
level for 2000. FAPRI did not provide corresponding revenue and cost data at the farm level, which
would have allowed EPA to appropriately conduct its discounted cash flow analysis at the farm level.
Enterprise data submitted are in the form of full financial statements and include other information such
as beginning cash reserves, productivity measiires, and feed efficiency. These data cover cattle, dairy,
and hog (farrow-finish independent) operations, and they vary by select facility size grouping and
production region for each sector (FAPRI, 20Qla). Although the data are for a single year, other
information provided by FAPRI allows for a more extensive analysis of expected changes over a 10-year
period (2001 to 2011) based on FAPRI's projections, taking into account pricing cycles. Other available
timeline data are from FAPRI's periodic U.S. Baseline Briefing Book (FAPRI, 2001c, 2001d). FAPRI's
reports are provided in EPA's record and are also available at FAPRI's web site.
! 2-17
-------
Since the publication of the 2001 Proposal, EPA has collected other published "enterprise
budget" data from various land grant university sources to further evaluate the availability of usable
enterprise level data and information. Given the lack of other available financial data for the poultry
sectors, EPA uses published enterprise budgets to depict enterprise level financial conditions for broiler,
egg, and turkey operations (as discussed in Section 2.4.2). As part of EPA's overall effort, however,
enterprise budgets were compiled for beef feedlots (14 budgets), farrow-finish hog operations (10
budgets), grow-finish hog operations (5 budgets), dairy operations (7 budgets), heifer operations (4
budgets), and broiler operations (3 budgets). Since the publication of the 2001 Notice, EPA also
obtained enterprise budgets for the egg and turkey sectors, which were provided when the 2002 Notice
was published. The range of sources includes the University of Idaho, Iowa State University, Ohio State
University, Oklahoma State University, Kansas State University, North Carolina State University, Ohio
State University, Clemson University, and University of Arkansas. The enterprise budgets span a wide
range of assumptions, including size and type of operation; type, age, or sex of animal raised; and feed
and operating efficiency. The budgets vary greatly with respect to line items, which items were
considered variable or fixed, whether depreciation and interest were reported separately, and whether a
capital recovery item or building and equipment charge was reported. The years represented by data in
these budgets varies, tending to be within the period from 1997 to 2000, with some exceptions. A
summary of all the enterprise budget data collected for the purpose of identifying alternative financial
data is provided hi the record (see: ERG, 200Id), along with additional citations on poultry data used by
EPA (see: DCN 175024, DCN 375036, DCN 375048, and DCN 375049).
2.3.1.3 Data from National Cattlemen's Beef Association
As discussed in the 2001 Notice, during the development of the proposed rulemaking EPA
received alternative enterprise level data for the cattle feeding sector from NCBA based on a survey of its
membership. For reasons described in the Proposal EA and the 2001 Notice, EPA decided not to base its
economic analysis on NCBA's data for the proposal. Instead, given the lack of other statistically
validated survey data for this sector, EPA used USDA's 1997 ARMS data for beef operations despite
recognition of the limitations of these data for assessing cattle feeding operations. Both before EPA's
proposal and during the comment period, NCBA expressed concern that the ARMS data are more
reflective of cow-calf operations and represent few feedlots and, therefore, might not be representative of
operations hi this sector. USDA also indicated to EPA that the available ARMS data are more reflective
of cow-calf operations and might not be suitable for evaluating impacts on cattle feeding operations. In
public comments on the 2001 Proposal, researchers at Iowa State University also suggested that the use
of ARMS data to represent beef feedlots is inappropriate (see: DCN 201602).
As part of EPA's public comment period, NCBA submitted additional financial data and
information for cattle feeding operations (NCBA, 2001). (See: DCN 201165.) This new data submission
addresses many of EPA's initial concerns about NCBA's previously submitted survey data. It provides
additional details about how these data were collected and includes additional information that allows
EPA to more fully evaluate these survey data. NCBA's data submission also includes projections by
NCBA based on these baseline data over the time frame of EPA's analysis (NCBA, 2001, 2002).
The 2001 Notice presents data provided by NCBA, representing results of surveys of NCBA's
membership. These data consist of a total of 66 surveys with 1997 financial data, 72 surveys with 1998
data, and 73 surveys with 1999 data returned by respondents. Of these, 54, 60, and 58, respectively, were
used by NCBA to characterize the finances of the beef feedlots represented by these survey data. These
2-18
-------
data are enterprise level data but include information on both company-owned cattle and cattle that are
not owned by the feedlot but are fed on-site (e.jg., custom operations). For the purpose of this analysis,
EPA assumes that these data are representative of both the enterprise and farm because the data are more
inclusive of a range of revenue sources. These' data are used to depict conditions at larger beef
operations based on NCBA survey results, which represent operations marketing an average of 52,000
cattle annually. Regional breakouts are not provided. NCBA presented gross receipts, total operating
costs, interest payments and receipts, net cash income, depreciation, pre-tax net income, current assets,
total assets, current liabilities, total liabilities, and total equity. NCBA also provided a variety of ratios,
including debt-assets. These key parameters represent an average over a 3-year period from 1997 to
1999. !
The next section of this report further describe the NCBA survey data submitted to EPA and
discuss the Agency's rationale for choosing these data. These data are available in EPA's record
(NCBA, 2001—DCN 201165), along with the ;an assessment comparing NCBA's data against
information available from other sources (see ERG, 200 Ib). Also see EPA's response to comments on
the data used to depict financial conditions at cattle feeding operations in the Comment Response
Document available in the rulemaking record (see response to comment DCN CAFO 201602-22).
i
2.3.2 Data Selection and Modification for EPA's Financial Models
This section discusses EPA's process to select among the available data to build baseline
financial models for each of the affected industry categories—cattle, dairy, hog, and poultry sectors—and
also describes, in some cases, any adjustments made to these data by EPA. Data tables are presented at
the end of this section. All financial variables used for EPA's analysis conform to established practices
and standards for specifying commodity cost and returns, consistent with those used by USDA and set by
American Agricultural Economics Association, guidelines (AAEA, 2001).
For the some sectors, EPA continues to use available 1997 data from USDA reflecting financial
conditions at the farm level, which the Agency used for proposal. For the livestock (cattle feeding, dairy,
and hog) sectors, EPA has replaced the 1997 USDA data used for proposal with other farm level and
enterprise level data, which were presented in both the 2001 Notice and 2002 Notice. For cattle
v operations, EPA uses financial data provided by NCBA and FAPRI. For dairy and hog operations, EPA
uses alternative data from USDA. For the poultry (broiler, egg, and turkey) sectors, EPA continues to
use USDA's farm level data used for proposal, but supplements these data with with limited available
enterprise level data obtained since proposal, i
t
As discussed in both the 2001 Notice and the 2002 Notice, among the principal comments that
EPA received on its Proposal EA is the recommendation to separately evaluate effects on an individual
operation's livestock or poultry enterprise. This recommendation originated from USDA, various land
grant universities, and some industry representatives. It was suggested that EPA evaluate impacts using
livestock enterprise level data that do not consider revenue from other farm-related sources (e.g.,
secondary livestock, crops, government payments). This approach differs from the 2001 Proposal, where
only farm level financial data were used to evaluate regulatory impacts on CAFOs, using financial data
that include revenue from other farm-related sources. To support this comment and to encourage EPA to
use alternative data for its analysis, many commenters submitted enterprise level data to the Agency
during the comment period, which are presented in the 2001 Notice.
2-19
-------
To address comments that criticize EPA's use of a single year of financial data to reflect baseline
conditions, the Agency adjusts financial data for the cattle, hog, and dairy sectors (using other available
published data from USD A, FAPRI, and the land grant universities) to average out conditions over
multiple years. This approach involves incorporating other available data into the analysis to obtain
average conditions over a multiple year tune frame, as discussed in the 2001 Notice (see 66 FR 58590-
58591). Because of the lack of multiple years of financial data for the poultry sectors, EPA is not able to
use this approach for those types of operations and is instead continuing to use a single year of data.
Other recommended changes to the data that EPA uses for its analysis include the use of alternative data
to project conditions over the tune frame of the analysis (1997-2006), which is also discussed in both of
EPA's published Notices.
For more information, see EPA's response to comments received during the public comment
period regarding the financial data and the analytical, approach that the Agency uses compile aggregate
costs and to assess regulatory effects on CAFOs. These response to comments address alternative data
and recommended changes to EPA's assessment approach. Relevant response to comments in the
Comment Response Document include EPA's use of alternative data EPA uses (DCNs 201602-22,
400158-91,400165-36,202013-2,201605-13 and 201352-108,201352-136-4) and related adjustments
using best available data to modify EPA's assessment approach (see, for example, 202402-35 regarding
its enterprise analysis, 400158-92 regarding adjustment to average out single year of data, 201352-101 on
projections used, and adjustments and clarification on the assessment criteria used in 201352-35,
201335-104,201438-207-1, 201335-104,210352-106, and 201438-207-1), among other Agency
comment responses. The Comment Response Document available in the rulemaking record.
2.3.2.1 Cattle Sector
Because of USDA's concerns that the financial data for this sector might be more reflective of
cow-calf operations and not suitable for evaluating impacts to cattle feeding operations (see: 2001
Notice, 66 FR 58585-58587), EPA is replacing the financial data for this sector used in the Proposal EA.
Instead, for its final analysis of impacts on the cattle feeding sector, EPA uses financial data submitted by
NCBA and FAPRI, along with available enterprise level data for heifers from the University of Idaho. A
summary of the input data that EPA uses for its analysis is presented in Tables 2-2 and 2-3.
For operations with more than 1,000 AU, EPA uses data provided by NCBA for operations with
an average of 52,000 head (see: DCN 175044). For operations with between 300 and 1,000 AU, EPA
uses data submitted by FAPRI for a 500-head feedlot enterprise (DCN 175038). For the purposes of this
analysis, and because of the lack of additional available data, EPA assumes that these data reflect
baseline financial conditions for operations with fed cattle and veal. For operations rasing heifers, EPA
uses enterprise budget data for heifer replacements given the availability of 1998 data from the
University of Idaho (DCN 175033 and DCN 175034). EPA presented those data in the 2001 Notice (66
FR 58589). Each of these data sources represent enterprise level conditions. Farm level data are not
available; therefore, EPA's analysis assumes that farm and enterprise conditions are the same.
EPA has evaluated the reasonableness of both the NCBA and FAPRI data (ERG, 2001a).
Because of limited financial data on cattle feeding operations, little additional information is available
for this sector to conduct an in-depth comparison. The use of these data is supported by information
cited by Koontz et al. (2000), reporting average industry returns of $10 to $15 per head, along with high-
end returns of SI 1 to $25 per head (assuming certain production equipment). Assuming returns reported
2-20
-------
by Koontz et al. (2000) are primarily cash-based returns, they compare to the calculated midpoint of $10
to $12 per head based on the ranges assumed by EPA for its analysis (EPA assumes values for net cash
income ranging from a $7 per head loss to earnings of $30 per head, depending on facility size). This
information generally supports the level of net cash per head that EPA assumes for its discounted cash
flow analysis for cattle feedlots. EPA selected'the NCBA survey data for large feedlots because these
data are more representative of larger operations. EPA has evaluated NCSA's financial data against
those provided by FAPRI, and they compare closely. EPA also provided initial review and input to
NCBA on each of its survey questionnaires developed for this rulemaking. For more information, see
Section 8.1.3 of the Proposal EA. ;
EPA selected to use the alternative NCBA and FAPRI data over other more limited available
data and information, including data submitted by Iowa State University (ISU, 2001) and enterprise
budgets obtained from various land grant universities (see ERG, 200Id). EPA also chose NCBA and
FAPRI data because all key data for the analysis were provided in one data source (revenues, net cash,
total liabilities and total assets). Other advantages of these data are as follows.
Because nearly all operations responding to NCBA's survey are significantly larger than
operations with fewer than 1,000 AU, EPA us£s the FAPRI enterprise data for operations in this size
category. FAPRI's data, which EPA uses for operations with fewer than 1,000 AU, were compiled using
an "expert panel" approach. Some commenterjs object to the use of FAPRI-supplied financial data
because these data were developed using a panel approach, which they perceive as potentially biasing the
data. EPA disagrees with these comments. Use of an expert panel approach to obtain information about
a representative facility's financial conditions is a longstanding and common practice used by FAPRI and
other land grant university researchers to assess the implications of public policy on the agricultural
sectors. Such an approach allows researchers jo compile data and other information to address policy
questions where other statistically valid data are not available. Even statistical survey data can vary,
depending on what data are used (e.g., time period captured, sample size and representativeness, etc.).
Although EPA recognizes that expert panel-generated data may be variable across different panels,
statistical data are also variable, since each value generated by a statistical survey is subject to statistical
variance and the same survey of a different group of respondents will not yield exactly the same results.
In the past, the courts have upheld EPA's use of data, even though not perfect, as long as EPA uses the
best data available in the best way the Agencyjcan. Moreover, FAPRI data and analyses span decades of
ongoing research work and are well-recognized within the agricultural research community and among
land grant university researchers. Evidence of the community's regard for FAPRI's research contribution
is shown by a 2002 nomination by the American Agricultural Economics Association (AAEA), the
organization that publishes the leading agricultural economics research journal, for the AAEA
Distinguished Policy Contribution Award—a nomination supported by the U.S. House of
Representatives' Committee of Agriculture for FAPRI's contribution during the 2002 congressional farm
bill debate (see AAEA, 2002—DCN 375112).|
EPA decided to use available NCBA and FAPRI financial data instead of other available
I
"enterprise budget" data that are have been developed by various land grant universities (see ERG,
200Id) for the following reasons. Enterprise budgets are developed to characterize possible revenues and
costs that might be encountered by a farm that, is interested in developing that enterprise. The revenues
and costs are presented as examples, and typically the source indicates that the farmer should develop the
budget using his or her best estimates of revenues and costs specific to that operation because, as many
budgets note, "your costs or revenues may vary from those shown" (ERG, 200Id). Thus, farmers often
use enterprise budgets as a template, not as the final word on whether to undertake the enterprise at a
2-21
-------
specific operation. Enterprise budgets are very dependent on detailed assumptions and conditions, some
of which are documented but some of which are not. Therefore, enterprise budgets might not truly
represent conditions across a broad range of facilities. FAPRTs budgets are compiled using an "expert
panel" approach to develop a representative financial model, which is a common and established practice
in the field of agricultural policy research. Enterprise budget data are also not straightforward and easily
interpreted because these data are not presented in terms of a standard income statement or balance sheet.
Additional interpretation of line items is often required to determine whether they constitute actual cash
items, opportunity costs, or noncash items (e.g., operating interest or labor). FAPRI data are more
explicit and are presented in terms of a standard income statement or balance sheet line items.
Furthermore, the FAPRI data explicitly provide asset and liability assumptions specific to the models,
whereas many enterprise budgets do no explicitly provide such data.
As discussed in the 2001 Notice, to address recommendations that EPA average out baseline
conditions to better account for year-to-year variability and pricing cycles (see 66 FR 58590), EPA uses
the 3 years of survey data (1997 to 1999) provided by NCBA to calculate an average gross revenue value
for its analysis using the sales test (NCBA, 2001). From the FAPRI data, which include a 2000 base year
along with several years of projected data (2000 to 2011), EPA uses the first 3 years of reported revenue
(2000 to 2002) to obtain an average total revenue value. EPA uses average values to address
recommendations expressed during the public comment period. These comments suggest that EPA
consider ways to depict financial conditions ove'r multiple years, despite the availability of only a single
year of data in some cases (see 66 FR 58590).
Tables 2-2 and 2-3 show the resultant average gross revenue values that EPA assumes for this
analysis. At operations with more than 1,000 AU, the estimate is $475 per head revenue. This estimate
compares to the average value of $945 per head assumed for operations with fewer than 1,000 AU.
These average values reflect revenue per head sold (or, in the case of the NCBA data, revenue per head
marketed, which includes the number of head sold plus the number of head fed under contract that were
sent to market). The NCBA data highlight two distinct operations at large feedlots: custom feeding
operations and company-owned cattle operations. The difference in revenue per head between these two
size categories is attributable to the inclusion of information for custom cattle feeding operations hi the
NCBA data. The custom feeding portion of a feedlot operation has a different revenue and cost structure
than the company-owned portion of the business because the feedlot does not buy or sell these cattle;
rather, a price for keeping and feeding these cattle is paid, leading to lower revenues, but also lower
costs. The NCBA revenue figure of $475 per head reflects the weighted average of per-head revenues
for the company owned cattle enterprise and per-head revenues for the custom feeding enterprise.
Because these data are for EPA's sales test, which is used principally as an initial screener to indicate the
need for further analysis (see Section 2.4), the revenue data EPA uses for this analysis do not
substantially affect the overall results of the Agency's analysis. Moreover, differences hi the financial
data among production types are less stark once revenues and costs are jointly considered, resulting in
more comparable net cash income values.
EPA's discounted cash flow (DCF) analysis already accounts for variability and changing
conditions over multiple years. This analysis spans a 10-year time frame (1997 to 2006) and uses time
series projections. This approach is consistent with that used for the 2001 Proposal. For this analysis,
EPA obtains net cash income estimates at both the farm and enterprise level for the base year (1997)
from the available data. EPA uses NCBA data from 1997 for cattle operations with more than 1,000 AU
(NCBA, 2001); EPA derives a base year estimate from available FAPRI data for 2000 (FAPRI, 2001),
back-calculated to 1997 using the NCBA time series data (NCBA, 2001).
2-22
-------
EPA projects out the 1997 baseline data using NCSA-reported data on costs and returns to
feedlot enterprises, expressed as dollars per marketed head, to obtain a cash flow stream over the analysis
period (1997 to 2006). NCBA's projection coyers the 10-year analysis period, relying on historical data
and pricing trends in the cattle cycle that correspond to the 3 years of data in the association's survey.
EPA uses projected returns made by NCSA that were submitted to EPA (NCSA, 2001). See Table 2-4.
Alternative projections by FAPRI and USDA report net returns to cow-calf operations only, which might
not correspond to trends in the cattle feeding sector that will be subject to the revised regulations. The
FAPRI projections for its 500-head feedlot model also do not cover the 1997 to 2006 time period used for
EPA's analysis. The method EPA uses to project the baseline data follows the approach used to support
the 2001 Proposal (see Section 4 of the Proposal EA). From this projected cash stream, EPA estimates
the net present value estimates for use in its DCF analysis. Table 2-5 shows specific line item
definitions. A summary of these values at both the farm level and enterprise level is presented in Tables
2-6 and 2-7. ;
For the debt-asset test, EPA uses both )SfCBA and FAPRI data on total assets and total liabilities
for operations of similar size in this sector (FAPRI, 200la), replacing the USDA asset and liability data
used for proposal. As with the other financial data, EPA uses NCBA data for operations with more than
1,000 AU andFAPRI data for operations withbetween 300 and 1,000 AU.6 See Table 2-2. Use of the
alternative data addresses concerns expressed (luring the public comment period about EPA's
assumptions of baseline debt and equity conditions at CAFOs and the data on debts and assets assumed
for the proposed rulemaking (see: 2001 Notice., 66 FR 58582-58583). These data exclude smaller sized,
typically older, operations that may carry less debt, and focus on larger sized facilities that are often more
capital-intensive or might be seeking to expand, thus requiring additional capital investment. EPA uses
these alternative debt and asset data for its deb^-asset test—instead of USDA data—since these data are
likely more representative of the debt load and, size of operation affected by the final regulations.
i .
For more information, refer to EPA's Comment Response Document available in the record for
the Agency's response to comments on the financial data used to depict financial conditions for this
sector, as well as other responses to comments about the financial tests used to evaluate this rule.
2.3.2.2 Dairy Sector
i " -
For dairy operations, EPA replaces the 1997 USDA farm level data that were used for the
proposal analysis with alternative data provided by USDA based on a special USDA survey of the dairy
sector in 2000 (USDA/ERS, 2002c—DCN 37^085). A summary of the farm level and enterprise level
input data that EPA uses for its analysis is presented in Tables 2-2 and 2-3.
I
The alternative 2000 USDA data for dairies have the advantage of providing both farm level and
enterprise level data from a single data sourcei Another advantage of using USDA's data is that these
data are based on an actual producer survey. As with all other data provided by USDA, these data were
compiled by USDA's ERS for EPA's use andjwere sufficiently aggregated to mask any confidential
business information. Given the availability of this single and up-to-date data source, EPA decided to
use these data instead of a compilation of farm level data from the 1997 ARMS data set from USDA used
6 The resultant ratio using these alternative NCBA and FAPRI data provide an identical debt-asset ratio of
68 percent for use in EPA's debt-asset test, although the representative model debt and asset data may differ.
i
I 2-23
-------
for the proposal analysis (USDA/ERS, 1999a), along with enterprise level data submitted by FAPRI
(FAPRI, 2001a—DCN 175038) and/or enterprise budget data from various land grant universities (see
ERG, 2001d). EPA's evaluation of each of these data sources, however, indicate that these data compare
favorably to one another. The alternative FAPRI and. enterprise budget data were presented in the 2001
Notice (66 FR 58588-58589), soliciting further public comment on their use for this analysis. The
alternative 2000 USDA data were discussed in the 2002 Notice (see 67 FR 48108 and DCN 375084) and
available for public review in the rulemaking record.
EPA conducted additional sensitivity analyses of these data by comparing the results of the
Agency's main analysis using new farm level and enterprise level data from USDA for the year 2000
against the results of an alternative analysis using the 1997 USDA farm level data used for proposal and
other enterprise data submitted by FAPRI. The results of this analysis indicate that EPA's analysis
results are stable across a range of input data (ERG, 2002c—DCN 375111).
To address recommendations that EPA average out baseline conditions to better account for year-
to-year variability and pricing cycles (see: 2001 Notice, 66 FR 58590), EPA adjusts the available 1997
gross income data prior to evaluating these data. This evaluation is done as part of EPA's sales test using
published USDA cost and returns data for U.S. dairy operations, spanning 1993 to 2000. These national
level data are used to create an index of 8 years of farm level financial data from which to project 1997
gross sales data, producing an average 8-year revenue value.
EPA's DCF analysis, which spans a 10-year time frame (1997 to 2006) and uses time series
projections, already accounts for variability and changing conditions over multiple years. This approach
is consistent with that used for the 2001 Proposal. For this analysis, EPA obtains net cash income
estimates at both at the farm level and enterprise level for the base year (1997) from the available data.
At the farm level, EPA projects the 1997 baseline data using USDA-reported net returns for the dairy
sector to obtain a cash flow stream over the analysis period (1997 to 2006). At the enterprise level, EPA
uses the 2000 net cash income for representative dairy operations submitted by FAPRI. The 2000 data
are back calculated to 1997 and projected from 2000 to 2006 using the same USDA-reported net returns
for the dairy sector that are used to adjust the farm level data. EPA continues to use the same USDA
projections that were used for the 2001 Proposal (USDA/WAOB, 1999, 2000, 2002; see Table 2-4)
because other available projections do not regularly report net returns per milk cow. They also do not
cover the 1997 to 2006 time period for EPA's analysis. The method that EPA uses to project the baseline
data follows the approach used for the Proposal EA. From this projected cash stream, EPA estimates the
net present value for use in its DCF analysis. (Table 2-5 shows specific line item definitions.) A
summary of these values at both the farm level and enterprise level is presented in Tables 2-6 and 2-7.
For the debt-asset test, EPA uses FAPRI data on total assets and total liabilities for operations of
similar size in this sector (FAPRI, 2001a), replacing the USDA asset and liability data used for proposal.
Use of the alternative data addresses concerns expressed during the public comment period about EPA's
assumptions of baseline debt and equity conditions at CAFOs and the data on debts and assets assumed
for the proposed rulemaking (see: 2001 Notice, 66 FR 58582-58583). These FAPRI data exclude
smaller sized, typically older, operations that may carry less debt, and focus on larger sized facilities that
are often more capital-intensive or might be seeking to expand, thus requiring additional capital
investment. EPA uses the FAPRI debt and asset data for its debt-asset test, instead of USDA data, since
FAPRI's data are likely more representative of the debt load and size of operation affected by the final
regulations.
2-24
-------
For more information, refer to EPA's Comment Response Document available in the record for
the Agency's response to comments on the financial data used to depict financial conditions for this
sector, as well as other responses to comments about the financial tests used to evaluate this rule.
2.3.2.3 Hog Sector
As discussed in the 2001 Notice, EPA! is replacing the 1997 USDA data for hog operations used
for proposal with other data obtained by the Agency since proposal (see 66 FR 58587-58588). For the
hog sector, EPA is not using the financial data, that it used for the proposal analysis because of concerns
expressed by USDA and others through public comment on the 2001 Proposal. Such comments suggest
that the 1997 data are not representative because they reflect conditions where hog prices were unusually
high. For the final analysis, EPA uses alternative farm level and enterprise level data from USDA based
on a special USDA survey of the hog sector in 1998 (USDA/ERS, 2002a—DCN 375064), with
modifications by EPA as summarized here. A summary of the farm level and enterprise level input data
that EPA uses for its analysis is presented in Tables 2-2 and 2-3.
The alternative 1998 USDA data for the hog sector have the advantage of providing both farm
level and enterprise level data from a single data source. Another advantage of using USDA's data is
that these data are based on an actual producer survey. As with all other data provided by USDA, these
data were compiled by USDA's ERS for EPA[s use and were sufficiently aggregated to mask any
confidential business information. Given the availability of this single and up-to-date data source, EPA
decided to use these data instead of a compilation of farm level data from the 1997 ARMS data set from
USDA used for the proposal analysis (USDA/ERS, 1999a), along with enterprise level data submitted by
FAPRI (FAPRI, 2001a—DCN 175038). The alternative USDA and FAPRI were presented in the 2001
Notice (66 FR 58588-58589), soliciting further public comment on their use for this analysis. The
alternative 1998 USDA data were further discussed in the 2002 Notice (see 67 FR 48108 and DCN
375084) and available for public review in the rulemaking record.
The 1998 USDA data have the added jadvantage of providing broader coverage of the hog sector
because these data cover a broader range of hog production types, including both farm and enterprise
level conditions across three types of operations: independent owner-operator farrow-finish and
farrowing operations, contract grow-finish operations, and independent grow-finish operations.
(Financial data for farrow-finish contract operations are not available from USDA because of small
sample size.) By contrast, the 1997 USDA hog data represent average conditions across all types of
operations; the FAPRI reflect independent farrow-finish operations only. FAPRI's data also do not
include farm level financial data. Although the USDA data reflect national and not regional conditions,
other data from USDA are available to distribute the types of operations—contract versus independent
operations—by major production region (USDA/ERS, 1999a). EPA is therefore able to provide region-
specific model breakouts that account for the different proportions of contract versus independent
operations across two of its CAFO model regijons (Mid-Atlantic and Midwest).
i
As EPA had anticipated in its 2001 Notice, initial data obtained by the Agency from USDA
could not be readily analyzed. Since the publication of the Notice, EPA has been working with USDA to
resolve these issues and obtain additional data. Since the publication of the 2001 Notice, EPA has
obtained data from USDA that report farm income excluding non-cash items, which USDA had included
in the original submittal of these data. USDAfs new submittal also includes corresponding farm level
data. These data are available in the rulemaking record (USDA/ERS, 2002a—DCN 375064). The
! 2-25 '
-------
rulemaking record also contains additional information documenting how EPA has worked with USDA
to obtain alternative data since the 2001 Proposal (see: USEPA, 2002b, 2002c, 2002d, 2002f, 2001c,
2001d; USDA/ERS, 2002a, 2002b, 2002c, 2002d, 2001, 2001a, 2001b, 2001c, 2001d; ERG, 2002c; ERG
and DPRA, 2001).
Because of persistently negative net cash income due to 1998 market conditions in the hog
sector, EPA is unable to readily analyze these data for its analysis and considered additional
modifications to the data obtained by USDA. Modifications to these data by EPA include (1) averaging
conditions over 5 years using available USDA data on farm costs and returns at hog farms; (2) adjusting
these data to reflect expected price rather than actual price for 1998 and 1999; and (3) making
assumptions about farrow-finish operations in the Mid-Atlantic region that are counter to USDA's
database. Other adjustments, consistent with those performed on data for each of the other livestock and
poultry sectors analyzed, include projection of the base-year data across EPA's 10-year analysis period.
First, to average the available baseline farm level financial data over multiple years, EPA adjusts
the 1998 data using published USDA cost and returns data for both farrow-finish and grow-finish
operations. These data cover 1995 to 1999. For this analysis, EPA uses national level data to create an
index to develop 5 years of farm level financial data from which to extrapolate the 1998 farm data. The
1998 data are extrapolated over the time frame by apportioning costs and revenues on the basis of
changes in costs, revenues, and returns reported for 1995 through 1999. This type of adjustment is
discussed in the 2001 Notice (66 FR 58590-58591) and it addresses comments received on the Proposal
EA. This adjustment is made by averaging baseline conditions to better account for year-to-year
variability and pricing cycles. Using this approach and USDA data, EPA obtains the average farm level
revenue values that it uses for its sales test.
EPA's DCF analysis already incorporates changes over multiple years, spanning a 10-year time
frame (1997 to 2006). This approach is consistent with that used for the 2001 Proposal. However, net
cash income reported by USDA for hog enterprises in 1998 continues to be negative in some cases.
When these 1998 values are extrapolated to the 1995 to 1999 tune period, as is done for the farm level
data, cash flow on average over this 5-year period continues to be negative for some representative
facilities. The primary reason for these negative income values is that 1998 was a year in which hog
prices dropped dramatically. At the farm level, USDA-reported net cash income is positive, although
likely low when compared to other years.
Second, the principal modification to these enterprise data by EPA is the adjustment of the data
to reflect expected price rather than actual price for 1998 and 1999. (EPA does not adjust USDA-
reported farm level data since the Agency can analyze these data without adjustment.) EPA assumes this
resultant expected price to adjust the 1998 data provided to the Agency by USDA. The method EPA
uses is based on an approach recommended by USDA ERS personnel. This recommended approach uses
price projections from USDA's World Agricultural Supply and Demand Estimates (WASDE) published
in 1997 as an indicator of expected 1998 price levels in the hog sector (USDA, 2001). Applying this
approach provides an expected price of about $47 per hundredweight (cwt.) across all hog operations for
that year, compared to the actual price of less than $35 per hundredweight reported in 1998. Another
approach suggested by USDA uses historical data to compile a ratio of hog prices to corn prices (see
ERG, 2002c). This approach adjusts reported 1998 hog revenues upward by roughly 15 percent, but
applying this approach results in consistently negative net cash income values for enterprises with fewer
than 1,000 AU. A detailed summary of how EPA adjusts the available hog data obtained from USDA is
available in the record (ERG, 2002a—DCN 375083).
2-26
-------
EPA uses the resultant expected price for 1998 to adjust the enterprise level data provided by
USDA. Once the 1998 enterprise level data arp adjusted, EPA derives a base year estimate by back-
calculating to 1997 using a 5-year index that EPA created based on the same USDA national level cost
and returns data for farrow-finish and grow-finish operations from 1995 to 1999 as are used to
extrapolate farm level revenues. EPA replace^ the USDA-reported data for 1998 and 1999 with EPA-
adjusted values based on the expected market prices during this period. The adjusted base-year
enterprise level net cash income values are presented in Table 2-3 and are the data EPA assumes for its
analysis. (Table 2-5 shows specific line item definitions.) EPA presented the results of these
adjustments of the original data to USDA ERS personnel, who reviewed the approach and resultant
adjustments to these data (USEPA, 2002f; USDA/ERS, 2002d).
i
EPA defends its decision to adjust tie 11998 USDA hog financial data to reflect expected price
rather than actual price for 1998 and 1999. As! discussed in the Proposal EA, hog prices during this
period were uncharacteristically low and the result of excess supplies due to overproduction and
overcapacity in this sector. Since this time, hog prices have recovered to more closely reflect average
historical price levels. Adjustments for "expected price" are also consistent with economic theory and
are generally recognized as valid techniques among economists, and are commonly employed hi applied
research to obtain representative average and Usable data for conducting policy analysis. The techniques
employed by EPA are consistent with those employed by researchers at USDA, industry, and the land
grant universities, in fact, the approaches used by EPA to adjust these data are precisely those
recommended by researchers at USDA and were reviewed by USDA prior to use in the Agency's
economic model (see DCN DCN 375083 AND DCN 375094). The approach used by EPA is consistent
with previous data adjustments made by the Agency to adjust data for use in other regulatory analyses to
make data reflect average and, in some cases, more realistic conditions, where other data are not
available. Finally, adjustment of the original USDA data is necessary since without such adjustments,
these data show persistently negative net cash income due to 1998 market conditions in the hog sector
and EPA is unable to readily analyze these data for its analysis. No other data are available for EPA to
conduct its analysis (see response to comment [DCN CAFO400165-36). Without EPA's adjustments to
these data, these data show persistently negative net cash income due to 1998 market conditions in the
hog sector and EPA is unable to readily analyze these data for its analysis. Without these adjustments or
other available data, this would require that EPA regard these operations as "baseline closures" and
remove them from the analysis. As discussed in the 2001 Notice (66 FR 58579), where data show that a
regulated facility would not normally be financially viable, it is EPA's longstanding practice to assume
the operation is a baseline closure for purpose 'of its analysis and remove the facility from subsequent
analysis! Because EPA is using a representative farm approach and grouping several operations under a
certain representative model groupings, the Agency decided not to assume that any existing CAFOs
would constitute baseline closures and thus bejremoved from the analysis.
EPA conducted two sensitivity analyses using alternative hog sector data and assumptions. One
analysis compares the results of the Agency's plain analysis using new farm and enterprise level data
from USDA (as adjusted by EPA using WASIJ)E data) against the results of an alternative analysis using
other enterprise level data submitted by FAPRL A second sensitivity analysis compares the results of its
main analysis against USDA's data under alternative expected price adjustments based on the ratio of
hog to com prices (using the approach discussed previously; see also ERG, 2002a). The results of the
analysis using alternative data for operations with more than 1,000 AU indicate that EPA's analysis
results are stable across a range of input data. [The results of the sensitivity analysis using alternative
adjustments for expected price are indeterminate among operations with fewer than 1,000 AU since the
baseline data for many of these operations indicate negative cash flow and would likely be considered as
baseline closures by EPA (ERG, 2002c—DCl^f 375111).
i
! 2-27
-------
EPA projects the 1997 baseline data using FAPRI timeline data of net returns for the hog sector
to obtain a cash flow stream over the analysis period (1997 to 2006). See Table 2-4 (FAPRI, 2001c,
2001d). From these data, EPA estimates the net present value of expected cash flow for use in its DCF
analysis. A summary of these values at both the farm level and enterprise level is presented in Tables 2-6
and 2-7.
Finally, USDA's financial data indicate that there are few (less than 4 percent) farrow-finish
independent operations in the Mid-Atlantic region. This means that USDA is unable to provide financial
data, given too small a sample size. Because these data are not available, EPA uses available national
level data for farrow-finish independent operations to depict conditions for these types of operations in
this region. However, EPA's interpretation of other USDA information, which the Agency uses to
develop its engineering cost estimates, indicates that there is potentially a much greater share of farrow-
finish operations in this region. Because this issue cannot be readily clarified, EPA uses the available
financial data for farrow-finish independent operations, which is matched up against cost model data and
information depicting the number of farrow-finish contract operations in this region.
For the debt-asset test, EPA uses FAPRI data on total assets and total liabilities for operations of
similar size in this sector (FAPRI, 200la), replacing the USDA asset and liability data used for proposal.
Use of the alternative data addresses concerns expressed during the public comment period about EPA's
assumptions of baseline debt and equity conditions at CAFOs and the data on debts and assets assumed
for the proposed rulemaking (see: 2001 Notice, 66 FR 58582-58583). These FAPRI data exclude smaller
sized, typically older, operations that may carry less debt, and focus on larger sized facilities that are
often more capital-intensive or might be seeking to expand, thus requiring additional capital investment.
EPA uses the FAPRI debt and asset data for its debt-asset test, instead of USDA data, since FAPRI's data
are likely more representative of the debt load and size of operation affected by the final regulations.
For more information, refer to EPA's Comment Response Document available in the record for
the Agency's response to comments on the financial data used to depict financial conditions for this
sector, as well as other responses to comments about the financial tests used to evaluate this rule.
2.3.2.4 Poultry Sector
For the poultry sectors, EPA continues to use the 1997 USDA farm level data for broiler, egg-
laying, and turkey operations, which the Agency used for the proposal analysis. Since proposal, additional
farm level data for these sectors have not been made available. EPA also continues to use 1997 USDA data
on total assets and total liabilities for the debt-asset test, which were used for proposal, since the Agency
was unable to obtain alternative debt and asset data for these sectors. A summary of the farm level and
enterprise level input data that EPA uses for its analysis is presented in Tables 2-2 and 2-3.
For the enterprise level analysis, EPA uses enterprise budget data compiled by various land grant
universities. For broiler operations, EPA uses enterprise budgets reported by Oklahoma State University
(1997), presented in the 2001 Notice (DCN 175024). These budgets reflect conditions at a contract
grower operation. The data compare favorably to enterprise budget data published by other land grant
universities for a contract broiler operation. See Georgia University (Cunningham, 2001), North
Carolina State University (1993), and University of Arkansas (2000). EPA uses the 1997 data from
Oklahoma State University because these data correspond to the base year of the Agency's analysis-time
frame (1997).
2-28
-------
f
The 2001 Notice presented enterprise budget data for broiler operations. As anticipated by EPA
in its 2001 Notice, the Agency compiled additional enterprise level data for egg-laying and turkey
operations. Despite an extensive search of available land grant university data, EPA was able to locate
only a single source for enterprise budgets forithe egg-laying and turkey sectors. For turkey operations,
EPA identified two enterprise budgets (one foi: hens and one for toms, which EPA averaged) for a
contract grower operation (North Carolina Stajte University, 1997). For egg-laying operations, EPA
identified an enterprise budget for an independent-owner operation (Iowa State University, 1999).
These data are available in the rulemaking record (see: DCN 375036, DCN 375048, and DCN 375049).
Available enterprise data do not capture each of the possible types of poultry operations,
including whether an operation is independently-owned and operated or whether the operation raises
animals under contract. Given that EPA has been unable to locate additional financial data for all types
of operations, the Agency is unable to directlylevaluate regulatory impacts at each type of operation. The
enterprise data for broiler and turkey operatiorls are for contract operations only; data are not available
for independent owner-operators in these sectors. Enterprise data for layer operations are for an
independent owner operations only; data are not available for operations that raise eggs under contract.
i
As noted in the Proposal EA, the overall financial conditions might differ depending on whether
the operations raises animals independently orjunder contract. Gross farm revenues generated by
contract growers tend to be lower than those of independent operators because the contract price is often
lower than the market price received by independent operators; however, the contract grower typically
faces lower production costs because the processor supplies much of the contract grower's production
input. Also, a grower operation's current assets might be lower because these operations do not own the
chickens they grow or produce crops requiring1 storage (Perry et al., 1999). Because production costs at
contract operations are typically lower compared to independent operations, cash flow per bird is likely
not substantially different. Thefefore, EPA believes that the results of its cash flow analysis at either the
farm level or the enterprise level will not be different in terms of number of number of business closures
under a post-regulation scenario. Debt-to-assej: ratios are also expected to be similar between contract
and independent operations of similar size, since most contract operations own their own infrastructure.
EPA has further evaluated the potential implications of using the available data despite their
limitations. EPA believes that lack of contract [grower information for broiler and.turkey operations does
not substantially affect the results of its analysijs of these sectors. First, the use of data for a contract
operation to evaluate independent-owner operations may generally be considered a conservative source
of data for assessing potential effects. Second,jthe available data reflect the dominant operation type in
these sectors. USDA data indicate that nearly all broilers are raised under contract. This is based on data
showing that 98 percent of birds produced are not owned by the farmer. Similar data for the turkey
sector indicate that 70 percent of turkeys are prpduced under contract. Because EPA's analysis assumes
that all (100 percent) broiler and turkey operations are contract grower operations, the results of EPA's
analysis might be overstated. Because contract: operations tend to have less available income to pay for
compliance costs, as compared to independents, EPA's analysis might show a greater number of potential
closures than is actually the case.
For the egg-laying sector, however, EPA uses enterprise budgets for independent operations
across all operation, including contract grower operations, which could understate regulatory impacts to
those operations that raise eggs under contract using the Agency's sales test (if these contract operations
generate lower revenue per bird than independent operations). Information from USDA indicate that 87
percent of operations with more than 1,000 AUJare independent operations and 60 percent of operations
i 2-29. . ' .
-------
with more than 300 AU are independent operations.7 Although EPA believes that use of these data
would not substantially affect its cash flow analysis results because production costs at contract
operations are typically lower compared to independent operations (and, therefore, cash flow per bird
might not be substantially different between independent and contract operations), the Agency has
conducted further review of these data.
To evaluate how limited data in the egg-laying sector might influence the results of EPA's
analysis, the Agency conducted additional sensitivity analyses of these data by comparing the results of
its analysis using available data with adjustments to approximate conditions at contract grower
operations (ERG, 2002c—DCN 375111). This sensitivity analysis uses enterprise budget data for
independent-owner operations, which are adjusted by USDA information on the share of operations that
are contract growers versus independents and by USDA information about the livestock portion of total
farm revenue generated at egg operations (USDA/ERS, 1999a).
EPA conducts this analysis as follows. Among larger-sized operations with dry manure systems,
EPA assumes that contract growers account for 13 percent of all operations and generate 10 percent of
the reported livestock portion of total farm revenue for egg operations. Among smaller-sized operations
with wet manure systems, EPA assumes that contract growers account for 40 percent of all operations
and also generate 10 percent of the reported livestock portion of total farm revenue for egg operations.
More information is available in the rulemaking record (see ERG, 2002c—DCN 375111). The results of
this sensitivity analysis show that under these assumptions no egg operations would go out of business,
which is consistent with the results of the main analysis (see Section 3.3 of this report). This analysis
shows that use of these alternative data and assumptions should not affect the results of EPA's analysis.
EPA believes that this finding would not change its assessment of the economic achievability of the
CAPO regulations.
Because only limited poultry data are available, EPA has not been able to locate multiple years
of financial data to average available data over a multiple year time frame. Therefore, EPA's analysis of
the financial effects on broiler, egg, and turkey operations is based on a single year of input data. Using
available data, EPA obtains net cash income estimates at both the farm and enterprise levels. EPA
projects out the 1997 baseline data using FAPRI timeline data of net returns for the broiler, egg-laying,
and turkey sectors to obtain a cash flow stream over the analysis period (1997 to 2006). See Table 2-4
(FAPRI, 2001c, 2001d). From these data, EPA estimates the net present value of expected cash flow for
use in its DCF analysis. A summary of these values at both the farm level and enterprise level is
presented in Tables 2-6 and 2-7. ;
For more information, refer to EPA's Comment Response Document available in the record for
the Agency's response to comments on the financial data used to depict financial conditions for this
sector, as well as other responses to comments about the financial tests used to evaluate this rule.
2.3.3 Matching of EPA Cost Models and EPA Financial Models
To facilitate the linking of the cost and financial models developed for this analysis, EPA
expresses all cost model outputs and financial variable inputs on a per-animal (inventory) basis. This
7 Assessed by USDA assuming 100,000 birds equals 1,000 AU.
2-30
-------
allows EPA to compare estimated costs and baseline financial conditions across representative CAFO
models that reflect varying facility sizes, producing regions, land availability, and facility types. This
process is described in greater detail in the Proposal EA. EPA's cost models are described in Section
2.2, and more detail is provided hi EPA's Development Document (USEPA, 2002).
To match up and establish consistency between the cost and financial models, EPA scales the
financial data using the same number of animals assumed for each of the cost models, whose estimated
compliance cost outputs also are expressed on a per-animal (inventory) basis. This intersection of
financial models and cost models forms the basis for EPA's regulatory analysis using the representative
farm approach. Table 2-1 shows the underlying assumptions of the average animal inventory for each
CAFO model. Multiplying the average animal inventory estimates (shown in Table 2-1) by the financial
data derived on a per-animat basis (shown in Tables 2-2 and 2-3) allows EPA to match up available cost
and financial models for the purposes of this analysis. The baseline financial models that EPA uses for
its analysis assume gross facility revenue andjnet present value of cash flow. This baseline depiction
reflects the product of the average inventory assumptions and financial data derived on a per-animal basis
shown in the tables. j
This approach allows for greater accuracy by aligning the compliance costs incurred and
revenues generated at a facility, allowing EPA to account for .the single largest variable in its
analysis—the number of animals raised at the facility. This approach also allows for greater flexibility
because EPA can readily use available financial data for one CAFO model as a substitute for another
where data are not available simply by adjusting the number of animals at a facility (assuming that per-
unit costs and revenues between these representative facilities may be considered similar).
Agriculture sector research routinely expresses costs and revenues as a unit metric, such as
dollars per animal or dollars on a unit weight basis. Expressing an increase in production costs on a per
unit basis provides a quick assessment of the potential effects of such increases on a farming operation,
often without further analysis. For example, {o evaluate a range of technology options to regulate hog
producers in North Carolina, researchers at North Carolina State University (NCSU) have established a
cutoff of $3 to $5 per marketed hog as being "economically feasible," implying that per-head costs in
excess of that threshold might be prohibitive (NCSU, 1999). EPA's estimates of per-animal costs for the
final regulations are provided in Appendix B £or each of the commodity sectors.
t
As noted in Section 2.2.1, the CAFOJmodels EPA uses for this analysis represent the interface
between a large number of cost models and a Ismaller number of financial models. The cost models are
able to account for greater variability among operations, compared to the financial models, including
differences by production types, geographic conditions and production region, land availability,
technology needs, and the like. In some cases, available financial data do not match each possible
permutation among all possible production ccjst structures (as discussed in Section 2.2.1).8 Fewer
financial models are developed because of limited data on financial conditions across all CAFOs. In
other cases, however, the available financial data might more precisely reflect an operation's business
type, including whether the operation is a contract grower or independent owner-operator, as well as (in
more limited cases) whether the operation is reflective of a corporate structure. These types of
o i
In some cases, EPA decided to use natibnal average available data despite limited available regional data,
for reasons explained in Section 4 of the Proposal! EA.
2-31
-------
circumstances might have more bearing on the regulatory effects on an operation than the operation's
cost structure.
Given that EPA has accounted for the single largest variable in its analysis—the number of
animals raised at the facility—and given the use of available average financial data differentiated by
sector and in some cases by size and business type, EPA believes that this approach reasonably
approximates average financial conditions across all types of operations.
Alternative data obtained by EPA since proposal represent an important improvement to the
economic analysis. EPA has obtained additional information differentiating between independent owner-
operation and contract grower operations in the hog and poultry sectors. At proposal, EPA used
available financial data for an entire sector that did not, in some cases, refleet differences in financial
conditions across different business types, including whether the operation markets animals it owns (e.g.,
independently owned and operated farms) or raises animals on behalf of a corporate entity that typically
retains ownership of the animals (e.g., contract grower). New data obtained for the hog sector also depict
differing conditions among farrow-finish and grow-finish operations. Other new data depict enterprise
budgets for replacement heifer operations. EPA's model still is unable to reflect conditions specific to
veal operations. EPA's model also is not able to account for possible financial differences among egg
laying operations (wet versus dry manure management systems). Other limitations regard the availability
of data for the poultry sector to fully indicate all cases of whether the operation is an independent-owner
operation or raises animals under contract (see discussion in Section 2.3.2.4).
As described in Section 2.4 of this report, EPA uses additional alternative data to expand upon its
analysis to further evaluate regulatory effects at an operation's livestock or poultry enterprise. This
approach builds upon the 2001 Proposal analysis, which evaluates financial effects at regulated CAFOs
using financial data for an operation as a whole. That is, the analysis now includes revenue generated at
a facility from other non-livestock and farm-related enterprises at the operation, and it counts among an
operation's total farm income the revenue from the sale of livestock, crops, and other farm-related
income, as well as government payments. Historically, most effluent guideline regulations have used
broader facility level data, with the exception of only a limited number of cases (e.g., see USEPA, 1996).
Given the availability of additional data that EPA has obtained since proposal, the Agency is able to
account for potential facility closures as well as potential product line closures, as represented by the
representative model CAFOs developed by EPA for this analysis.
2-32
-------
Table 2-1. Model CAFO Assumptions by Sector, Size, and Region (Size Range and Average Inventory)
Sector
Fed
Cattle
Veal
Heifers
Dairy
Hog:
FF
Hog:
GF
Hog:
FF
Hog:
GF
Layers:
Wet
Layers:
Dry
Broilers
Turkeys
Region
MW,CE,
PA,SO,MA
MW,CE,
PA,SO,MA
MW,CE,
PA,SO,MA
MW,CE,
PA,SO,MA
MA
MW
MA '
MW
CE
CE
SO
MW
SO
MA
SO
MA
MW
Medium 1
t Medium 2
Medium 3
300-1000 AU
300-499
(370)
300-499
(400)
300-499
(400)
200-349
(250)
750-1249
(940)
750-1249
(921)
750-1249
(940)
750-1249
(921)
r^'X t"i ,zT-,r>
•m. -jbj^^j
""» (* « -i
•"nL *™ &- "~ $ %\//
~mMi i INI nun 11^1 mi i r mil* A i mfiniTi mi mi i
^ *"*
" ™^v^*- d~*» a fy iy~,
^^i^/5-^"Xc3^
sfc w ~ > *
30,000-49,999
(38,209)
30,000-49,999
(38,209)
30,000-49,999
(37,248)
30,000-49,999
(36,792)
16,500-27,499
(22,246)
16,500-27,499
(22,246)
| 500-749
! (552)
! 500-749
! (540)
500-749
1 (625)
1 350-524
1 (425)
i 1250-1874 ,
1 d,439)
i 1250-1874
1 (1,415)
i 1250-1874
i (1,439)
1 1250-1874
I (1,415)
^1?" ^ v-'Wfe ^ * ' s
/
^ " """ ,. &
"\ " -- ' "*•'
.*'*".*, -"
-SS%-^S 1~ -^rl .
\ 50,000-74,999
! (61,734)
; 50,000-74,999
I (61,734)
i 50,000-74,999
I (56,469)
j 50,000-74,999
j (56,130)
1 27,500-38,499
) (34,640)
| 27,500-38,499
j (34,640)
750-999
(766)
750-999
(1,080)
750-999
(875)
525-699
(600)
1875-2499
(2,004)
1875-2499
(1,987)
1875-2499
(2,004)
1875-2499
(1,987)
-_ V J^_f *"~
~ ^ ™ ^"^
y ^
i i ^
9,000-29,999
(19,500)
75,000-99,999
(90,367)
75,000-99,999
(90,367)
75,000-99,999
(79,454)
75,000-99,999
(79,364)
38,500-54,999
(47,534)
38,500-54,999
(47,534)
Large 1
Large 2
>1,000 AU
1,000-8,000
(1,839)
>=1,000
(1,080)
>=1,000
(1,500)
>=700
(1,430)
2500-5000
(3,686)
2500-5000
(3,280)
2500-5000
(3,686)
2500-5000
(3,280)
2500-5000
(3,601)
2500-5000
(3,601)
>= 30,000
(146,426)
100,000-600,000
(349,999)
100,000-600,000
(349,999)
100,000-180,000
(126,565)
100,000-180,000
(124,448)
>=55,000
(127,396) .
>=55,000
(127,396)
>8,000
(25,897)
-"»•..
»v *•-%,
H^ *W ^ ?~^ -r
•:, „ ^
• " -5 ' •"•"""
"r^s fS«
v^^ s ^ V
^™ J* <~
•'.x^SH&'JKzX
;ff^*;-^'^|
iS&fS^M^sSw
>5,000
(11,231)
>5,000
(10,300)
>5,000
(11,231)
>5,000
(10,300)
>5,000
(16,946)
>5,000
(16,946)
S *• ^> > \
,v, ^~
>600,000
(856,367)
>600,000
(856,367)
> 180,000
(254,390)
>180,000
(228,091)
tVi $4. % „* VS.
^ -, - <&,<&*&•
-^\^^~
"*y 7* -.
k rf^-S ^ *^f
"* ^ * *>} ****** "•
" 33" v^- — ~
Source: USEPA, 2002. Values shown in parentheses are the average number of animals (inventory) assumed for
each model CAFO. Values shown are averaged apross all cost categories (based on land use and technology needs)
for the P-based land application standard. See Development Document (USEPA, 2000). Shaded cells indicate
model CAFO not developed. EPA's model regions: Midwest (MW); Central (CE); Pacific (PA); Mid-Atlantic
(MA); South (SO) (vary by sector, see USEPA, 2002). FF: farrow-finish; GF: grow-finish.
2-33
-------
Table 2-2. Financial Input Data, Farm Level
Sector
Size
(AU)
Reg.
Gross
Revenue
Net Cash
Income
Deprec.
Operating
Cost
($ tier head inventory)
Debt-
Asset
(%)
Source/
Description
Beef, Veal, & Heifers Operations
>1000
<1000
All
All
$475
'$945
$9
$2
$5
$5
$461
$913
68%
68%
NCSA 2001 (1997-1999)
U.S. 52,000 head.
FAPRI 2001a (2000-2002).
Midwest 500-head.
Dairy Operations
>1000
<1000
MW
PA
MW
PA
$1,746
$1,764
$2,492
$1,841
$269
$230
$631
$405
$144
$202
$158
$117
$1,319
$1,374
$1,635
$1,269
64%
64%
62%
62%
USDA 2002 (2000 data)
Revenues avg. 1991-2000
using USDA/ERS 2002b.
Debt/asset:
FAPRI 2001 (2000).
Hog Operations (GF/contract)
>1000
<1000
All
All
$32
$244
$9
$38
$6
$15
$20
$192
65%
49%
Hog Operations (GF/independent)
>1000
<1000
All
All
$163
$251
$29
$42
$9
$16
$124
$194
65%
49%
Hog Operations (FF & farrowing/independent)
>1000
<1000
All
All
$143
$204
$18
$42
$12
$17
$112
$141
65%
49%
USDA 2002a (1998 data)
U.S. >1,OOOAU; 300-1,000
AU.
Averaged 1995-1999 using
USDA ERS, 2002b
Debt/asset:
FAPRI 2001a (2000).
Broiler Operations (average all operations, independent and contract)
>1000
<1000
MA
SO
MA
SO
$1.13
$1.16 .
$1.47
$1.42
$0.50
$0.50
$0.60
$0.60
$0.17
$0.17
$0.18
$0.18
$0.44
$0.47
$0.67
$0.64
30%
26%
21%
19%
USDA 1999a (1997)
Layer Operations (average all operations, independent and contract)
All
All
$24.63
$4.10
$2.60
$16.74
11%
USDA 1999a (1997)
Turkey Operations (average all operations, independent and contract)
>10QO
<1000
All
All
$20.08
$11.24
$1.80
$2.60
$0.88
$0.90 .
$17.29
$7.20
15%
23%
USDA 1999a (1997)
2-34
-------
Table 2-3. Financial Input Data, Enterprise Level
Sector
Size
(AU)
Reg.
Net Cash
Income
Depr./Cap.
Recoy.
Operating
Cost
i
($ per head inventory)
Source/
Description
Beef & Veal Heifer Operations I
>1000
<1000
All
All
$9
$2
Heifer Operations
All
All
$136
Dairy Operations
>1000
<1000
MW
PA
MW
PA
$433
$295
$356
$372
$5
$5
.
$63
|
di?i
$222
$525
$232
$461
$913
Same as farm level (see Table 1)
Same as farm level (see Table 1)
$903
University of Idaho (1998 data)
Average of Jersey and Holstein budgets.
$904
$1,136
$1,100
$1.006
USDA 2002 (2000)
Two regions:
North (assumed for MW)
& South (assumed for PA)
Hog Operations (GF contract)
>1000
<1000
All
All
$35
$14
Hog (GF independent)
>1000
<1000
All
All
$18
$6
Hog (FF/farrowing , independent)
>1000
<1000
All
All
$33
$4
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
$86
$94
$104
$94
$67
$73
USDA, 2002a (1 998 data)
U.S., >l,OOOAUand300AU-l,OOOAU
(Adjusted-see text and ERG, 2002a)
Broiler Operations (contract) j
All
All
, $0.15
Layer Operations (independent)
All
Turkey O
All
All
$2.85
Derations (contract)
All
$0.57
$0.05
1
$0.60
t
$0.19
$0.09
Oklahoma State University, 1997
$10.19
Iowa State University, 1999
$0.14
NCSU, 1997
Average of turkey torn and hen budgets
2-35
-------
Table 2-4. Baseline Projections, Returns Per Unit, 1997-2006
Sector/
Year
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Beef
($/cow)
$21.78
($4.48)
$9.52
$4.36
$14.82
$30.08
($4.36)
$26.59
$29.20
($6.54)
Dairy
($/cwt)
$11.62
$12.41
$9.85
$9.83
$10.46
$10.89
$11.05
$11.28
$11.48
$11.69
Hogs
($/cwt)
$10.62
$2.20
$1.79
$13.93
$15.33
$13.78
$9.06
$10.93
$12.09
$13.05
Broilers
(fW)
5.81
14.26
11.81
9.21
11.99
12.21
11.87
11.68
11.54
10.87
Egg Layers
(0/doz)
9.10
10.12
3.21
5.63
4.89
0.65
3.61
5.45
6.94
7.15
Turkeys
(0/lb)
(3.80)
0.08
11.83
12.11
7.89
7.90
8.49
8.98
8.87
8.37
Sources: Cattle (NCBA, 2001); Dairy (USDA/WAOB, various years), and Hog/Poultry (FAPRI, 2001c, 2001d).
Table 2-5. Net Cash Income Components from Available Data
Data source
1997 ARMS
(USDA/ERS,
1999a)
1998 ARMS
(USDA/ERS,
2002a, 2002c)
FAPRI (2001a)
NCBA (2001)
Enterprise
budgets
(various)
Sector
Poultry
sectors
Hog and dairy
sector
Cattle sectors
(<1000AU)
Cattle sectors
(>1000 AU)
Heifer,
broiler, layer,
and turkey
sectors
Data Type
Farm
Farm and
enterprise
Enterprise
Enterprise
, Enterprise
Nef Cash Income Components
Computed by USDA as gross cash income less variable and
fixed cash expenses (see Proposal EA, USEPA, 2001a)
Farm net cash income computed by USDA as net cash farm
income (gross cash income minus total cash expenses);
enterprise net cash income computed as USDA-provided
gross sales minus USDA-provided cash expenses (excl.
operating interest, considered an opportunity cost by USDA).
Computed by FAPRI using revenues minus operating costs,
operating and fixed interest, and cash overhead items such as
office supplies and property taxes.
Computed by NCBA-as revenues minus operating costs plus
interest income minus interest expenses.
All cash items, both fixed and variable (including operating
interest) identified and subtracted from revenues.
Depreciation excluded.
2-36
-------
it Returns
i
£
CM
O
1
o
Jased on 1
1
Cfl
A
fe
=2
-M
CO
s
U
•e
cu
"5
£
CN
S
E2
^
z
vo
0
OS
OS
1-H
hi
£
JS
n
U
VO
O
o
i
s
CN
i
o
o
o
o
o
«N
OS
OS
os
*H
OS
OS
OS
1
^"*
l||
&£s
0>
.£j
V}
c
0
w>
K
i
oo
69
f-
Os
CN
69
t-
I
0
CO
69
in
69
69
0
69
S
CN
CN
CN
69
>-J
•%
%
U
m
vo
69
Os"
r—
CN
69
CN
69
§
00
CN
CN
69
CN
69
r-
69
69,
OS
t»H
CM
. ,
^
%
0>
u
oa
s
69
69
f-
69
T— t
r-
o
69
i
§
69
OS
1
CN
69
S
69
OS
VO
69
I-J
^
1
2
CN"
69
CO
69
OO
69
g
69
OO
VO
CO
69
O
CO
69
S
CO
69
0
a
CO
CO
CN
VD
69
CN
CO
-J
£
1
VO
69
CO
r-
69
OS
00
69
CO
O
OO
69
OS
t--
69
69
rt-
69
I
VO
69
VO
VO
69
CO
OS
69
VD
69
2
^
1
•a
p
t--
69
VO
O
in
69
CO
VO
69
69
CO
69
O
69
OO
E
i
69
00
O
OO
69
r-
69
1
69
S
2i
D
OO
69
69
69
69
VO
CO
69
OO
CN
69
OO
69
f-
69
OO
69
69
OO
69
l-J
CO
§>
1
vS
69
VO
69
VO
69
f-
69
OS
VD
69
69
O
•f-
69
OO
69
i
OS
OS
69
69
2
CO
60
ffi
o\
69
69
§
OS-
69 •;.
5!
vo
CO
69 '
1
VD
CO
69
69
os.;
si
i
00
"n !
69 ;
Os
CN !
69 i
J i
S:
lit
t-
CN
69
CO
69
CO
69
O
CO
69
>n
CN
69
r-
co
69
69
f-
co
69
vb
69
69
f-
OO
69
E
s
00
o
00 13
ffi £
CO
r-
69
CO
69
CO
69
OO
CM
69
69
VO
CO
69
s.
69
VO
CO
69
69
£
69
69
I—I
OO
60 US
0 0
ffi u
OO
69
CM
CO
69
O
CO
69
f-
CM
69-
CM
S
CO
69
OO
CO
69
CO
69
CO
69
OO
CO
69
O
OO
69
OO
CO
69
§
CO
D
$ £
o §
ffi O
r—t
69
00
69
69
m
C-;
*— t
69
69
VO
OO
69
OO
69
CM
69
v— 4
69
O
CO
CN
69
O
in
O
69
O
w-i
0
69
i-J
00
M
1
CQ
Os
i— 1
69
OO
vq
69
CN
00
69
OO
*— 1
69
OS
OO
69
VO
OS
T-H
69
OS
69'
CM
CO
69
OO
OO
69
O
CN
69
O
VO
O
69
O
VD
0
69
£
CO
1
CQ
n
00
69
OS
oq
i— i
69
»— • i
69
OS
»— i
69
CM
CO
69
00
oq
69
o
CN
69
O
VO
o
69
S
o
69
§
O
00
1
ro
OS
CO
CN
69
CO
69
vq
CO
69
CO
CO
69
OS
CN
69
CO
CM
69
CN
CO
69
CO
69
00
S
'CO
69
5
69
*-H
<|
00
,1
OO
69
69
in
69
>n
69
CO
69
CO
69
IN
in
69
iri
69
VO
S
oq
69
oq
69
,J
CO
D
I
C-;
CO
CO
69
CN
in
69
CO
in
69
CO
in
69
CM
in
i— i
69
in
69
O
VO
69
OS
>o
69
CO
69
VO
CM
•69
VO
S
^
B
1
O
G E?
•Si4
n b
"o S
d> ™
J2 o
si
O A
•^ **
g'a
i?3-
|f
III
§ "e S
^ S "
S o .SJ,
S ^ ^
OS O O
OS O »O
OS CN
CO lr?^ t-t
III
1 11
•3 O »C3
1 CN «
|g|
cfl W
>% ca
-------
§
u.
—
1
§
s
0
Projecti
a
e
•a
I
(S
^
2
G\
ci
V)
.a
t-i
a
i*
f°
n
w
18
y
ra
•11
ft
j=
O
•a
25
_
>?
0
g
cr\
»•*
S
R
S
t/l
tn
u
g
*"*
in
o
fN
|
i
fS
O
CM
I—I
§
g
o
i
OO
OS.
OS
i
„_,
QJ O
« 2 U e
.a
00
e
.0
o
1
cn
oo
69
_,
&
Os
CN
69
r--
£
S
o
CO
69
m
« — i
69
69
O
69
, — ,
4
CN
69
CN
69
j
OO
CM
CO
in
vo
69
ST1
69,
a
Tj-
s
g
OO
CN
69
CN
•-H
69
cN
69
69
,— ^
69,
O\
69
CN
69
^
OO
*§
m
S
69
^j.
CO
»— i
69
O
69
(^
VO
69
VO
CO
69
_
f-
69
in
in
69
69
o
in
69
VO
CO
69
CN
VO
69
VO
CO
69
^
OO
1
•5J-
c-
69
^j.
CO
m
69
m
69
«-H
f-
m
69
CO
CO
m
69
S
in
69
CO
69
VO
69
OO
vo
OO
69
m
CO
r—
69
CO
CO
69
1
S
b
1
m
H
cn"
69
VO
OS
cn
69
s
in
69
f^.
69
cn
g
m
OS
cn
69
00
VO
cn
69
69
OO
OS
£9
o
69
f^.
m
69
m
OS
CN
69
,
2
1
cn
cn"
69
t—
vo
in
69
OO
CN
in
69
I
VO
m
69
OS
5?
69
VO
cn
69
.OS
m
•— «
69
OO
VO
69
VO
m
cn
69
^
S
1
VO
en"
69
cn
E
o
OO
69
,.,.
69
O
69
CN
69
i
69
CN
f-
en
69
f-
en
69
r-
g
69
-fr
r-
VO
69
CN
t—
cn
69
^!
£
i
cn
cn
69
r—
69
69
CN
Tf
69
r—
cn
69
OS
S
cn
in
69
O
in
69
OO
69
en
CO
69
Os
VO
69
CO
cn
69
,
OO
!=»
OA
OO
CN
»— i
69
Tt-
CN
69
»— i
CN
69
OO
69
CO
69
VO
8
o
CO
69
VO
CN
69
frT
69,
^j.
69
,
cn
69
^j.
69
^
OO
bo
£
C3N
OS
69
to
to
€i9
S
OO
IN
f/9
IN
69
in
i-o
69
Os
CO
&9
CO
69
69
OO
Ii9
t—t
69
06
,
•S
e
$-*
i^-l I-H
OS
CN
69
m
CN
69
CN
CN
69
OS
69
69
r-
CN
69
CO
69
C-
CN
69
g
VO
69
CO
CN
69
VO
69
. §
S
m's
o
CO
69
OO
69
69
CN
69
f-
CO
69
ON
S
CO
69
O
in
69
OS
69
in
CO
69.
CO
69
•n
eo
69
l_l
%
on a
o 5
K U
t-
69
t
cn
69
OO
CN
69
in
69
§
en
en
69
r—
cn
69
en
en
69
CN
69
^j.
69
m
cn
69
Tl-
69
^
00
S -•
o°l
K 0
OS
t-;
OO
69
cn
CN
69
p-
CO
69
,-j
S
T— 1
69
_
in
69
VO
T—t
69
r-
oo
C5
69
69
in
69
•n
0
69
m
O
69
53
S
1
'§
PQ
•n
in
69
in
CN
69
CN
69
|
CN
69
r-;
69
^H
69
O
CN
69
CN
CN
69
t-;
r-H
69
,
CO
69
OS
cs
69
Os
CN
69
3
S
!
vo
OS
69
CN
CO
eo
69
CO
eo
69
cs
CO
69
,_,
S?
eo
69
o
69
OS
CO
69
^j.
69
VO
O
69
VO
O
69
5S
00
1
^^
0) O
•~ N*^
2 <
ap
!•§
Z ea
OS •-<
Os O
,-^CN
'88
? CJ-
II
« n<
OO ,_^
° ^>
•S P
^« KJ t>H
II!
& Q "g
^ I-J tt>
0 g C
3W /M*
S j»S
^ sl
11*1
S"tl
S ST "
|82
^ ^ "
"i 's 1
n > ^^
2 -| ^
1 t§ 8"
•a _g „
" ^ •§
K S t<~<
l|i
•< ^i;^
Si ON •§
>^ Os *j
f ^ 0
S3 ^ P
Source: D
State Uni\
Rounded t
OO
CO
-------
2.4 METHODOLOGY TO ASSESS IMPACTS ON MODEL CAFOs
For the 2001 Proposal, EPA developed a scheme to evaluate financial effects using 1997 USDA
data based on a combination of farm's net income and debt-asset ratios to classify a representative farm's
overall financial position based on annual earnings and solvency (USDA/ERS, 1997a 1997e) See 66 FR
3079-3103. The analytical framework for the final rule retains the general modeling framework that EPA
used to assess economic effects for proposal, with the modifications discussed in both the 2001 Notice
and the 2002 Notice. Both Notices describe the range of methodological changes and financial data EPA
has considered to improve its analysis.
This section describes the methodology that EPA uses to assess financial effects on regulated
CAFOs, highlighting changes to this analysis since proposal. Section 2.4.1 presents the assessment
criteria and key financial variables that EPA uses to assess post-compliance effects. Section 242
describes how EPA evaluates these assessment criteria to determine whether the estimated compliance
costs are affordable, thus demonstrating the "economic achievability"9 of the final regulations Section
2 4.3 discusses additional analyses performed by EPA, including an assessment of the regulatory effects
that takes into consideration long-run market price adjustments, Federal and State cost-share assistance
and other cost offsets. '
2.4.1 Assessment Criteria and Financial Data Variables
EPA's choice of criteria in any economic assessment of a regulation is variable and highly
dependent on the industry being regulated. EPA recognizes that each industry has its own special
attributes and requires an individual assessment of appropriate financial criteria. Therefore EPA does not
advocate a "one size fits all" benchmark for all industries but instead assesses each industry's general
conditions and uses generally accepted analytical approaches for identifying economic impacts in each
industry, if available, among other factors. Where appropriate, these other factors include criteria that
have been developed to analyze other industries.
Federal agencies like EPA and USDA have been analyzing the impacts of regulatory requirements
on regulated communities for many years. For example, the CWA, with its requirement to assess
economic achievability, has prompted EPA since the early 1970s to analyze the economic and financial
impacts of effluent guidelines on affected industries. Generally, EPA measures impacts using a variety of
approaches that attempt to assess post-compliance changes in key financial variables. In many cases a
benchmark is developed. This benchmark may be based on, for example, the lowest quartile performance
of firms in the industry (e.g., USEPA, 1998b) or on an assessment of what has been generally accepted in
past analyses or by the financial community, tempered by any specifics of the industry. Usually EPA uses
more than one financial variable in an assessment because a single variable is rarely sufficient to fullv
describe the relative financial health of an affected entity.
For this rulemaking, EPA has selected 9riteria based on those commonly used in the agricultural
sector to measure financial stress, in conjunction with criteria that the Agency has used in the past to
9 The Clean Water Act requires EPA to establish effluent limitations for point sources based on the "best
avauable technology economically achievable" (Sections 301(b)(2)(A) and 304(b)(2)). Factors that EPA shall
' oy include the cost of achieving effluent reductions»
2-39
-------
determine the affordability of effluent guidelines developed for other industries. This analysis focuses on
three financial criteria to assess whether the final CAFO regulations are affordable to affected businesses:
(1) an initial screening comparing incremental pre-tax costs to total gross revenue ("sales test"), (2)
projected post-compliance cash flow over a 10-year period ("discounted cash flow" [DCF] analysis), and
(3) an assessment of an operation's debt-asset ratio under a post-compliance scenario ("debt-asset test").
Financial data used for this assessment include total gross revenue for the sales test, net cash income for
the DCF analysis, and debt-asset ratios for the debt-asset test. Each of these tests is conducted using
available farm level financial data, with the exception of the DCF analysis, which is evaluated based on
both farm level and enterprise level net cash income. Input data that EPA uses for this analysis are
presented in Section 2.3 of this report.
For more information, see EPA's response to comments regarding the financial data and the
analytical approach that the Agency uses compile aggregate costs and to assess regulatory effects on
CAFOs. These response to comments address recommended changes to EPA's assessment approach, as
well as the use of alternative data. Relevant response to comments in the Comment Response Document
include adjustments to EPA's assessment approach (see, for example, 202402-35 regarding its enterprise
analysis, 400158-92 regarding adjustment to average out single year of data, 201352-101 on projections
used and adjustments and clarification on the assessment criteria used in 201352-35,201335-104,
201438-207-1 201335-104,210352-106, and 201438-207-1) and EPA's use of alternative best available
data related to'these adjustments (DCNs 201602-22,400158-91,400165-36,202013-2,201605-13 and
201352-108,201352-136-4), among other Agency comment responses. The Comment Response
Document available in the EPA's rulemaking record.
2.4.1.1 Sales Test Using Gross Cash Income
EPA uses gross cash income to measure the ratio of compliance costs to sales ("sales test"). EPA
uses pre-tax costs to evaluate a sales test because this approach is more consistent with the majority of
previous analyses that use the threshold values assumed for this analysis (although previous ELG analyses
have evaluated cost-to-sales ratios using both post-tax and pre-tax costs).10 The use of pre-tax revenue for
the sales test represents a change from what EPA did for the Proposal EA, where post-tax revenues were
analyzed for this criterion. This change addresses public comments received by EPA on the Proposal EA,
as discussed in the 2001 Notice (see: 66 FR 58584-58585).
*
For this analysis, EPA uses average gross cash income expressed at the farm level. This measure
includes total farm income from an operation's livestock business as well as income from other sources,
such as sales of crops and other secondary livestock on-site. Other farm-related revenue and government
payments are also included. Table 2-2 lists the farm level revenue values that EPA assumes for this
analysis.
EPA has often used a sales test to evaluate post-compliance impacts in previous regulatory
analyses (USEPA, 1987, 1994, 1995, 1996, 1997, 1998a, 1998b, 1999a, 1999b, 2000b, 2000c, 2002h,
10Effluent guideline regulations that have been evaluated using post-tax costs include the Landfills,
Commercial Hazardous Waste Combustors, and Centralized Waste Treatment industries. Pre-tax costs were used
to evaluate the Pulp, Paper, and Paperboard, the Pesticide Formulating, Packaging and Repackaging, and the Metal
Products and Machinery industries. EPA used both pre- and post-tax costs to evaluate the Transportation
Equipment Cleaning industry.
2-40
-------
2002g, 20021; DPRA, 1993, 1995; USGPO, 1999). EPA's use of a sales test is also common practice
when evaluating small business impacts for most regulatory development. Other agencies, including the
Occupational Safety arid Health Administration, also use a sales test (e.g., OSHA, 1999). USDA has also
considered cost-to-sales impacts to evaluate impacts on animal confinement operations (Heimlich and
Barnard, 1995). As noted in the Proposal EA, however, the sales test is not widely used to measure
impacts in the agricultural sector (Foster, 2000). During the comment period, several commenters claimed
that the sales test is not a useful measure of whether producers can afford the regulations. They suggested
that it should be replaced with a rate of return measure, such as return on assets, equity, or investment.
One commenter suggested a criterion based on cost as a percent of profit margin (measured as revenue
less cost of goods sold) or gross margin (measured as returns to labor and overhead before taxes) (Iowa
State University, 2001). Another commenter recommended evaluating profits measured as earnings
before interest, taxe^v depreciation, and amortization (EBITDA) (NCBA, 2001). Others indicated that the
sales test, if retained, should be measured against a lower threshold value due to the lower profit margins
on sales in agriculture. In general, commenters asserted that potential impacts, even at lower cost-sales
ratios, can result in proportionately large reductions in net returns and erode the attractiveness of
reinvestment in animal agriculture (NPPC, 2001). The 2001 Notice solicited comment on these and other
alternative assessment criteria. More information is available in the record (ERG, 200 Ib). Overall,
commenters expressed a preference that EPA evaluate compliance cost impacts using other income and
profitability measures instead of a sales test. In part, this is already part of EPA's overall analysis, which
includes an analysis of changes in discounted cash flow. See Section 2.4.1.2.
The Proposal EA describes as an alternative and common metric the examination of earnings
before taxes as a percentage of gross income or revenues ("profit test"), where the change in ratio post-
compliance is used as an indicator of the impact that compliance costs might have on profits. USDA's
analysis (Heimlich and Barnard, 1995) measured economic achievability by comparing estimated
regulatory costs with gross cash income (a sales test) and net farm income (a profit test), as well as cash
operating expenses. In recent years, however, EPA has tended to move away from using net income
analysis and profit tests as an indicator of the flnancial strength of a regulated entity for a number of
reasons. First, many financial analysts now acknowledge that a net income analysis is a less accurate
measure of financial health than a cash flow analysis because net income includes depreciation as a cost
even though depreciation is not a cash outlay (see, e.g., Brigham and Gapenski, 1997). Also, for valuing
corporate loans, the Financial Analysis Standards Board considers discounted cash flow the best estimator
for assessing fair value for enterprises lacking a quoted market price (Jarnagin, 19961; FFSC, 1997, 2001).
Second, profitability can be highly variable because a firm has a certain amount of leeway in calculating
earnings in any given year to minimize tax liability. Privately held entities (which predominate in the
livestock and poultry industries, for example) have few incentives to show large profits but every
incentive to show minimal earnings for tax purposes. Third, if a large segment of an industry is showing
negative net income, it is difficult to assess the impact of a regulation on profitability.
t
The problem with analyses based on profitability is especially important in the agricultural sector.
Heimlich and Barnard (1995) point .out that niany farms "may be motivated by noneconomic
considerations and should be considered hobby or recreational activities, rather than businesses,
particularly when net farm income is negative." They further contend that most farm operators reporting
negative net income have nonfarm sources of income and that they might be using the farm losses to offset
off-farm income to reduce income tax liability. They also find, as does EPA, that when net farm income is
2-41
-------
negative, costs as percentages of net income are difficult to interpret.u EPA, therefore, considers a sales
test to be a more analytically useful tool than a profit test for assessing impacts in the livestock and
poultry industries. First, EPA has concerns that proifit-based measures might overstate vulnerability.
Second, revenues are generally not as sensitive to incentives to show minimum values for tax purposes as
profits and thus are not as likely as profits to be understated. Third, sales are never negative and thus a
comparison between costs and sales can be adequately interpreted.
Given the boom and bust conditions common in the agricultural sectors, available financial data
often show negative returns to risk, management, and unpaid labor. Consequently, the only way for EPA
to conduct its analysis using these data is either to assume it is a baseline enterprise closure (i.e., it should
not be considered in the regulatory analysis because the operation would be discontinued even without
considering the impact of the regulations) or to determine that the operation cannot be analyzed at this
level (i.e., the operation is remaining in business because of certain mitigating factors).I2 Information
provided in the 2001 Notice indicates that some sectors would likely show large numbers of baseline
closures given available data using a profit test with USDA definitions of net farm income (which
includes depreciation and nonmoney expenses). Therefore, if the financial data for a certain
representative group show negative returns under EPA's traditional approach, the Agency would need to
consider all operations within a group as a baseline closure. For example, as discussed in the Notice, if
EPA were to use alternative 1998 hog data from USDA, its traditional approach would assume that all
operations in each of the representative groups are baseline closures. However, EPA recognizes that when
available data show large numbers of baseline closures (including even whole sectors), this may indicate
limitations with the underlying data or methodologies rather than a realistic picture of the industry. EPA
is further aware that facilities identified as baseline closures under its traditional approach might be the
very facilities likely to experience stress as a result of additional compliance costs and that it is therefore
important to account for these facilities in the analysis.
For these reasons, EPA is maintaining use of the sales test and is not considering an alternative
profitability measure for this criterion. However, to address comments on EPA's use of a sales test for the
analysis, the Agency is clarifying that this test is primarily used as a first-level screen, indicating the need
for further analysis, as discussed in more detail in Section 2.4.2.
EPA has made a number of changes in the way it evaluates this criterion. First, to address public
comments on the use of financial data for this test, EPA uses alternative revenue data for the cattle and
hog sectors (see Section 2.3). Second, EPA uses a sales test based on estimated pre-tax incremental cost,
as opposed to costs that take into account potential tax savings (post-tax), which was assumed at proposal.
More information is in EPA's response to comment DCN CAFO 201438-182. These pre-tax costs are
1' Typically, EPA considers that if a regulated entity is not profitable before pollution control investments
are made, the entity "may not claim that substantial impacts would occur due to compliance..." (USEPA, 1995). In
some cases EPA has used the concept of "baseline closure" if only a few entities have negative net income and
cannot be analyzed (see, for example, USEPA, 2002h, 2001e, 2000c, 1998a, 1998b, 1997, and 1995). These
entities might not necessarily close prior to implementation of a rule, but they cannot be analyzed within a profit test
or net income analysis framework.
I2Assumption of baseline closures is common practice in cases where EPA encounters such problems when
analyzing certain multi-facility manufacturing or service firms using actual facility level data. In such cases the
facility is removed from the analysis because it cannot be analyzed and is considered a baseline closure (see, for
example, USEPA, 2002h, 2001e, 2000c, 1998a, 1998b, 1997,1995).
2-42
-------
compared to total farm level revenues, and that ratio is used as an initial screener to determine the need for
additional analysis using EPA's discounted cash and debt-asset tests. Third, EPA's use of gross revenue
now considers multiple years of data, where data are available, to derive a more representative average
sales value for this test, rather than being based on a single year of data, as assumed at proposal. This
approach uses available time series data from USDA to compile an index to project data over a longer
time frame, linking up available financial data with other market and financial data for preceding and
subsequent years (also for example, see: ERG and DPRA, 2001; ERG, 2002a). This approach, discussed
in both of EPA's published Notices, is further discussed in Section 2.3 and documented in the record
(ERG, 2002c; ERG and DPRA, 2001). More information is in EPA's response to comment DCN CAFO
400158-92. The DCF analysis spans a 10-year time frame (1997-2006) and uses time series projections,
as discussed in Section 2.4.1.2, and thus already accounts for variability and changing conditions over
multiple years. EPA is also expanding its DCF analysis to take into consideration enterprise Fe'vel changes
in profitability in addition to farm level effects (see Section 2.4.1.2).
For additional information about EPA's sales test, see response to comment DCN CAFO201352-
35 in the Comment Response Document in the rulemaking record.
2.4.1.2 DCF Analysis Using Net Cash Income
The financial position of a farm can be calculated using either net cash income or net farm
income. Net farm income is an effective measure of long-term profitability because it accounts for capital
replacement costs and noncash business income (land, capital, and labor services). Net cash income
reflects current or short-term cash earnings. For the purposes of this analysis, EPA uses cash-based
measures (that is, the analysis is a net cash income-type analysis). The reported net cash income, or gross
income less cash expenses, is used as an estimate of cash flow to construct a baseline per-animal annual
cash flow. EPA conducts this analysis using both farm level and enterprise level financial data. Tables 2-
2 and 2-3 list the baseline net cash income estimates for each sector that EPA assumes for this analysis.
(See Table 2-5 for line item components assumed to define net cash income based on available data.)13
Tables 2-6 and 2-7 present the discounted cash flow values computed for this analysis.
A net cash income-type analysis is consistent with current views on the use of cash flow analysis
in preference to net income analysis among financial analysts (Brigham and Gapenski, 1997; Jarnagjn,
1996). Net cash income corresponds to total farm cash revenues minus cash expenses; that is, it is the
agricultural term corresponding to the financial term "cash flow." A net cash income-type analysis differs
from an evaluation of net farm income, which includes both noncash income and noncash expenses (e.g.,
depreciation) and corresponds to the term "net income" in accounting. This methodology estimates the.
long-term reduction in earnings that results from the costs of complying with the final regulations. If the
post-regulatory status is less than or equal to zero, it does not make economic sense for the owner to
upgrade the farm. Under these circumstances, the average farm represented by that model might be
vulnerable to closure. (As explained in the Proposal EA, unlike previous regulatory analyses conducted
by EPA, this approach does not consider the salvage value of liquidated assets at a CAFO.)
To account for changes in an operation's cash flow post-compliance, EPA estimates the present
value of projected farm earnings, measured asja future cash flow stream in 1997 dollars. The present
13 This analysis does not consider noncash income and depreciation.
: 2-43
-------
value of cash flow, also known as the discounted cash flow, or DCF, represents the value (in terms of
today's dollars) of a series of future receipts. EPA calculates baseline cash flow as the present value of a
10-year stream of farm cash flow.
EPA projects future earnings over the period of the analysis (1997 to 2006) using net cash flow
values derived on a per-animal basis. These values are measured at both the farm level and the enterprise
level using available data, along with available projections of enterprise level earnings from 1997 through
2006, and other market data to translate projected per-unit returns to per-animal returns. EPA
approximates future earnings using FAPRI's, NCSA's, or USDA's projected changes (expressed in
dollars per unit) by applying the equivalent incremental change (expressed in dollars per animal) for each
year during the forecast period (as presented in Section 4.2). EPA uses the resultant tune series data to
calculate the present value of net cash income used for this analysis. This approach is outlined below.
EPA projects the available base year (1997) farm level and enterprise level data (Tables 2-2 and
2-3) using projections from USD A, FAPRI, and NCBA. To translate available projections in net returns
by sector (Table 2-4) on a per-animal basis, EPA uses available market information, such as average per-
animal yields reported by USD A and/or annual marketing cycles based on industry data. For dairy, the
1997 average output of 16,781 pounds of milk per cow is assumed (USDA/NASS, 1999c). An average
weight of 257 pounds per finished hog is assumed, based on reported weights for "swine for slaughter"
and "farrow-finish" (NPPC, 1998) averaged according to the market share of each (USDA/APfflS,
1995b). The average number of 255 eggs per egg-laying chicken in 1997 is assumed (USDA/NASS,
1998b, 1998f). An average broiler weight of 5.5 pounds per bird is assumed, derived from the total
number of animals and pounds of production, reported in 1997 (USDA/NASS, 1999d). For turkeys, EPA
assumes an average weight of 23.8 pounds per bird derived from weight estimates and market share
information for turkey toms and hens (USEPA, 1999J; USDA/NASS, 1999d). No translation is needed for
projections for the beef cattle sector because NCBA reports projected returns per occupancy, which EPA
converts to per-marketed head using a ratio of occupancy to marketed head calculated using NCBA's data.
Once the available projections are expressed on a per-animal basis, future earnings are
approximated by applying the incremental national average change (dollars per animal) between each year
during the forecast period to the baseline financial data for each representative model CAFO. This is the
same approach used for the Proposal EA. The revised cash streams over the forecast period for EPA's
final analysis are shown in Tables 2-6 (farm level) and 2-7 (enterprise level).
Using these per-animal values, EPA calculates the net present value of future earnings for each
model CAFO (also shown in Tables 2-6 and 2-7). This approach assumes a 7 percent discount rate over
the 10-year period of the analysis (1997 to 2006). The equation EPA uses to calculate the net present
value of cash flow is
NPV =
n
z
v,-
'=2 (i+r)'"1
where:
v,...vn = series of cashflows
r = interest rate
n = number of cash flow periods
i — current iteration
2-44
-------
EPA's adjustment of the DCF analysis to represent post-compliance conditions for each model
CAFO is measured based on present value of cash flow less present value of compliance costs.
EPA frequently uses negative post-compliance cash flow calculated over the period of the impact
analysis to identify regulated entities that are vulnerable to closure. Several economic analyses for other
effluent guidelines have used this measure as the only criterion or as part of a group of criteria for a
closure analysis (see USEPA, 1995, 1996, 1997, 1998b, 1999a, 2000c, 2002h, 2002g). In these analyses,
EPA has considered negative cash flow over the period of analysis as at least one indicator that a facility
might be likely to close post-compliance.
To address public comments on EPA's proposal analysis, the Agency has made a number of
changes in the way it evaluates this criterion. The changes EPA has made or considered to its general
approach for this assessment criterion to address public comments are as follows. For more information,
see EPA's response to comment DCN CAFO 201352-104 and other related comment responses (noted
below) in the Comment Response Document in the rulemaking record.
First, EPA has expanded its DCF analysis, which now considers both farm level changes and
enterprise level changes in cash flow—the latter which, is based on an assessment of the financial effects
on an operation's livestock or poultry enterprise. This change addresses comments expressed by many
commenters, including FAPRI, other land grant university researchers, and industry, as well as USD A, to
principally consider enterprise level effects for EPA's regulatory analysis. The analysis supporting the
2001 Proposal considers farm level effects only. This issue was discussed in the 2001 Notice (66 FR
58580-58582). It is also documented in the rulemaking record (see, for example, USEPA, 2001d;
FAPRI, 2001a, 2001b; NPPC, 2001, NCBA, 2001, NMPF, 2001). Many of these comments were
supported by alternative enterprise level data that were submitted to EPA since proposal and were
presented in the 2001 Notice (USDA/ERA, 2002a and 2002c; FAPRI, 2001a; NCBA, 2001). An
enterprise level analysis recognizes that a farm might be unwilling to cross-subsidize a continually failing
livestock operation. Also, this approach recognizes that a failing enterprise with continuous cash flow
problems would have limited access to financing for capital replacement and/or expansion, despite the
health of the overall business. This analysis is conducted using the enterprise level financial data
presented in Table 2-3 of this report. Section 2-4.2 provides more information and describes how EPA
evaluates enterprise level changes in profitability. More information is in EPA's response to comment
DCN CAFO 202402-35.
Second, EPA is using alternative time series data to project available financial data onto a 10-
year time horizon for the discounted cash flow analysis. For the proposed rule, EPA used data
projections developed by USDA (USDA/WAOB, various years). The 2001 Notice discussed comments
that disagree with EPA's use of USDA's data series as the basis for projecting 1997 data, criticizing
USDA projections on various grounds. Some comments suggested that EPA replace use of USDA's
projections with alternative projections from FAPRI. In making the decision to use alternative
projections for some sectors, EPA did not determine that USDA's projections were, in fact, inferior to
projections compiled by other sources. EPA has reviewed the alternate projections recommended by
commenters, comparing these to other published information. The data that EPA uses for the final
analysis are based on a determination that these alternative data provide a better source from which to
project out baseline financial conditions over ;the time period for some sectors. Based on this review,
EPA is using alternative timeline data from FAPRI (hog and poultry sectors) and NCBA (cattle sector) to
project future earnings from the baseline data. EPA justifies its decision to use alternative FAPRI
projections given that FAPPJ's publication of its annual projections are well-established and span
: 2-45
-------
decades of ongoing research work; also, FAPRI's work is well-recognized within the agricultural
research community and among land grant university researchers.14 EPA was unable to use FAPRI
projections for the cattle sector since these data do not cover the 1997 to 2006 tune period of EPA's
analysis. Other FAPRI and USDA projections report net returns to cow-calf operations only (and do not
correspond to regulated cattle feeding operations). Therefore, EPA uses NCBA's projections for the
cattle sector. Both FAPRI's and NCBA's projections compare well with USDA projections. For the
dairy sector, EPA continues to use USDA's projections because alternative projections either do not
regularly report net returns per milk cow or do not cover the 1997 to 2006 time period of EPA's analysis.
Section 2.3 provides more detailed information on these data and EPA's selection process; see also
EPA's response to comment DCN CAFO 201352-101. Projections that EPA uses for this analysis are
shown in Table 2-4 and are expressed on a per-unit basis (i.e., cash returns per animal or per-unit output).
The method EPA uses to project the baseline data follows the approach used for the proposal analysis, as
discussed in the Proposal EA.
Third, the 2001 Notice discusses comments received by EPA that oppose the use of post-tax
costs to assess financial impacts on the grounds that it is not appropriate to factor tax savings into the
cost of compliance for producers. Commenters recommend that EPA not include expected tax offset in
its financial tests because operations whose survival is in question would have no positive income against
which to offset these ".tax benefits." Instead, such operations would be forced to bear the full "pre-tax"
costs of implementation. As discussed in the Notice, previous regulatory impact analyses conducted by
EPA have evaluated compliance cost impacts on a post-tax basis using a standard cash flow model,
incorporating an annualization approach that accounts for tax savings as well as depreciation at a
business. This has been done because these "costs are more reflective of the costs that are actually
incurred by that business. Given this longstanding practice, which follows standard business and
accounting practices, EPA continues to account for tax savings in its discounted cash flow analysis. As
discussed in Section 2.4.1.1, however, EPA is using pre-tax costs instead of post-tax costs in the sales
test for its final analysis. For more information, see EPA's comment-response document on this topic.
More information is in EPA's response to comment DCN CAFO 201438-182.
Fourth, although other measures of farm earnings are discussed in the 2001 Notice, EPA decided
not to use these other earnings measures, including EBITDA. This alternative measure of earnings
would have been used to calculate return on assets and internal rate of return. However, EPA's analysis
results using net cash income after taxes and a measure based on EBITDA for earnings are not
substantially different for most sectors. Because EPA uses the present value of the total cost of the rule
(the present value of operating expenses and capital), the Agency is able to determine whether cash flow
is sufficient to cover the cash expenses of the regulations. This approach also provides for capital
replacement at the end of the analysis period (or alternatively to cover the principal and interest payments
over the period of the analysis). Although a "pass" result indicates that cash flow is positive over the 10-
year period of the analysis, it also indicates that there is a cash flow cushion equal to the net present
value of the capital expenditure (including the real cost of that capital) over that time frame. As
discussed in the 2001 Notice, other possible financial indicators, such as return on assets or equity, were
ultimately not used because those measures would involve 1 year of data or a single calculated average
over a few years of data. EPA's use of discounted cash flow over the 10-year period of the analysis
provides a better indication of whether an enterprise would be likely to remain viable. Indicators such as
14 Evidence of the community's regard for FAPRI's research contribution is provided in the rulemaking
record (see AAEA, 2002). See also EPA's response to comments on FAPRI's daat at DCN CAFO 201352-136-4.
2-46
-------
return on assets are not ideal indicators of the financial health of an operation's enterprise because assets
are rarely assessed at that level. More information is provided in EPA's record (see: ERG, 200 Ib) and in
EPA's response to comment DCN CAFO 201352-104-182.
Some commenters (see, for example, NMPF, 2001) further recommended that EPA incorporate
uncertainty into the analysis, pointing to FAPRTs parallel analyses of the 2001 Proposal (FAPRI, 2001a,
2001b). EPA did investigate the possibility of adopting a similar approach for its analysis that would
incorporate a probabilistic approach (i.e., one that places probability distributions about available average
data, similar to that adopted by FAPRI for its parallel analysis) and discontinue use of a deterministic
approach (i.e., one that uses point estimates without any probability distributions, as EPA did for the
proposed rule analysis). Information about FAPRI's baseline model is available in the rulemaking record
at DCN 175038. EPA is not able to use a probabilistic approach because of dkta limitations and the
challenges inherent to such an approach. For the 2001 Proposal, the financial data used were USDA's
1997 ARMS data, which are reported as average estimates from a statistical survey. Variance analysis of
these data are limited. Strict confidentiality requirements on the outside use of USDA's databases also
limited EPA's direct access to these and other USD A databases. Therefore, EPA uses average single
point estimates for input into its models, as opposed to a broader range of data that would depict financial
conditions at operations that are not necessarily represented by the average, such as operations at either
end of the distribution (e.g., higher cost, less efficient operations at one end and lower cost, more
efficient operations at the other end). Following the 2001 Proposal, EPA did evaluate the possibility of
constructing probability distributions about the available financial data using uncertainty analysis
techniques. Based on this investigation, EPA does not believe a probabilistic model would have best
served the needs of its analysis for the CAFO rule. EPA's efforts demonstrate that such an approach may
yield results that are overly dependent on a large number of critical assumptions that may be difficult or
impossible to obtain. In general, EPA has concerns about probabilistic models based on its experience in
trying to develop a such a model for another regulation of a farming sector (aquaculture or fish farming
sectors). For that rulemaking, EPA decided not to pursue this approach, given the complexity and
additional information needs to support such an approach. More information is available in the
rulemaking record (ERG, 200le—DCN 375013). See also EPA's response to comment DCN CAFO
201352-136-4.
Many commenters also criticize EPA for not considering impacts in a way that takes into account
all of the cash outlays for an operation, including principal payments on loans to purchase the required
technology. For reasons outlined in the 2001 Notice, EPA does not include a debt feasibility test as part
of its analysis of the final rule because a down payment assumption is not necessary given the Agency's
joint analysis of debt-asset ratios and cash flow (see 66 FR 58583-58584). More information is provided
in the record (ERG, 2001c; USEPA, 2001c). See also response to comment DCN CAFO201352-104.
2.4.1.3 Debt Test Using Debt-Asset Ratios
The debt-asset ratio is a measure of a company's solvency and its ability to finance regulatory
. costs through additional debt. USDA calculates this measure as the ratio of business debt to business
assets and considers it to reflect the share of assets owed to lenders (USDA/ERS, 1997a, 1997e).
To model the regulatory baseline for the representative model CAFOs, EPA uses available debt
and asset data to compare changes in the ratio of baseline debt to assets under a postregulatory scenario.
EPA calculates the postregulatory debt-asset ratio using the underlying data as follows:
2-47 . . '
-------
_ .. T-k i x x » x T. x- debt + capital compliance cost
Postcomphance Debt-to-Asset Ratio = -
asset + capital compliance cost
For the 2001 Proposal, EPA used 1997 USDA-reported total farm assets and liabilities
(USDA/ERS., 1999a) to evaluate changes in the debt-asset ratio for representative facilities. Changes in
these ratios were evaluated based on USDA considerations that an operation facing potential financial
stress were with debt-asset ratios exceeding 40 percent (USDA/ERS, 1997a, 1997e). More information is
provided in Section 2.4.2.3; see also the discussion in Section 4 of the Proposal EA.
Comments received during the public comment period indicated general approval of EPA's use
of debt-asset ratios in the economic analysis. However, many comments expressed concern about the
baseline data assumptions and concern about the threshold value assumed to assess regulatory impacts.
These comments noted that USDA's debt and asset data that EPA used for the proposal do not represent
the current state of borrowing in many of these sectors, particularly among larger operation subject to
EPA's regulations that tend to carry more debt than that reflected by USDA's data.
To address comments about the baseline date, EPA uses alternative debt and asset data for the
livestock sectors (cattle, dairy, and hog). These data were submitted by FAPRI and NCSA. These
alternative debt and asset data were presented in Section 2.3 and are available in the record (see: DCN
175044 and DCN 175038). These alternative data translate to the baseline debt-asset ratios shown in
Table 2-2. These data indicate that confinement operations tend to have baseline debt-asset levels
ranging from 60 percent to more than 70 percent in the beef, dairy and hog sectors, thus exceeding the
USDA-recommended 40 percent threshold for indicating financial stress. The use of these alternative
data for the livestock sectors has implications for the debt-asset benchmark for indicating financial stress.
as part of EPA's analysis. This issue is described in more detail in Section 2.4.2.3.
Because of data limitations, EPA continues to use USDA-reported average debt and asset data
for the poultry sectors used for proposal. EPA also continues to evaluate these data using USDA
recommendations that a 40 percent threshold indicates financial stress.
For more information, see EPA's response to comment DCN CAPO 210352-106 and also DCN
CAFO 201438-207-1.
2.4.2 Criteria for Assessing Financial Effects
EPA uses its financial models, incorporating the data presented in Section 2.3 and the assessment
criteria described in Section 2.4.1, to assess financial effects on select representative model CAFOs. The
analysis for the final rule retains the general modeling framework that EPA used to assess economic
effects for the 2001 Proposal (see 66 FR 3079-3103), with the modifications discussed in both the 2001
Notice and the 2002 Notice. Both Notices describe a range of methodological changes and financial data
EPA considered for its analysis.
For the 2001 Proposal, the three assessment criteria described in Section 2.4.1 (sales test,
discounted cash flow, and debt-asset ratios) were evaluated using USDA data reflecting financial
conditions at the whole-farm level (reflecting income and cost information spanning an operation's
2-48
-------
primary livestock production, as well as secondary livestock and crop production, government payments,
and other farm-related income). For the final regulations, EPA conducts its discounted cash flow
analysis using both farm level and enterprise level financial data. EPA still evaluates changes in the
debt-asset levels using farm level data. EPA's sales test is also based on an evaluation of farm level
revenue data, but it is primarily used as an initial screen of potential impacts that indicates the need for
further evaluation. •
2.4.2.1 Decision Matrix for "Economic Achievability"
For the 2001 Proposal, EPA's basis for determining economic achievability for the proposal was
measured in terms of potential facility level (farm) closures and not potential product line (enterprise)
closures. For the final regulations, economic achievability is determined based on an analysis measured
both in terms of potential farm closures and potential enterprise closures.
The farm level analysis that supports the final rulemaking retains the same general framework
used for the 2001 Proposal. Specifically, financial impacts are assessed using a sales test, discounted
cash flow analysis, and debt-asset test. This evaluation is conducted using the farm level financial data
presented in Table 2-2. These farm level data reflect income and cost information spanning an
operation's primary livestock production, as well as secondary livestock and crop production,
government payments, and other farm-related income.
As was done for the proposed rule, EPA divides the impacts of the final regulations into three
financial impact categories: Affordable, Moderate, and Stress. The first category is the "Affordable"
category, which means that the regulations have little or no financial impact-on CAFO operations. The
second category is the "Moderate" impact category, which means that the regulations would have some
financial impact on operations at the affected CAFOs, but EPA does not consider these operations to be
vulnerable to closure as a result of compliance. EPA considers that for CAFOs in both the "Affordable"
and "Moderate" impact categories the final requirements are economically achievable. Operations
experiencing financial stress, however, are considered to be vulnerable to closure because of the costs of
this rule.15 EPA considers the "Stress" impact| category to indicate that the final requirements might not
be economically achievable by the CAFO, subject to other considerations. Table 2-8 shows a summary
of how EPA assesses these criteria using farm level data. Figure 2.1 illustrates the decision matrix
graphically. Additional information on this approach is provided in the Proposal EA.
In general, EPA considers the regulations to be economically achievable for a representative
model CAFO if the average operation has a post-compliance sales test estimate within an acceptable
range, positive post-compliance cash flow over a 10-year period, and a post-compliance debt-asset ratio
not exceeding a benchmark value. The benchmark value on the debt-asset test assumed for this analysis
varies depending on the baseline conditions reported in the financial data used to conduct the analysis
(discussed in Section 2.4.2.3) based on new data and recommendations submitted to EPA during the
public comment period.
15 Commonly used measures of "farm fiiiancial stress" include bankruptcies, foreclosures, and net exits
(Stam et al., 1991). Indicators of stress in agriculture as reported by farm banks include delinquent loans,
discontinued financing, farm closures, liquidation,, and bankruptcy (Stam et al., 1991,2000).
2-49
-------
EPA conducted its analysis first at the farm level based on data reflecting financial conditions for
the entire farm operation (e.g., reflecting income and cost information spanning the entire operation, thus
considering the operation's primary livestock production, along with other income sources such as
secondary livestock and crop production, government payments, and other farm-related income). Based
on the farm level results, EPA also assessed the financial effects on CAFOs at the enterprise level (e.g.,
limiting the scope of the assessment to the operation's livestock or poultry enterprise, and excluding
other non CAFO-related sources of income from the analysis).
Starting with the farm level analysis, EPA considers the regulations to be economically
achievable for a representative model CAFO if the average operation has a post-compliance sales test
estimate within an acceptable range, a positive post-compliance cash flow over a 10-year period, and a
post-compliance debt-to-asset ratio cut exceeding a benchmark value. Specifically, if the sales test
shows that compliance costs are less than 3 percent of sales, or if post-compliance cash flow is positive
and the post-compliance debt-to-asset ratio does not exceed a benchmark (depending on the baseline
data) and compliance costs are less than 5 percent of sales, EPA considers the options to be "Affordable"
for the representative CAFO group. (Although a sales test result of less than 3 percent does indicate
"Affordable" in the farm level analysis, further analysis is conducted to determine the effects at the
operation's livestock or poultry enterprise.) The benchmark values assumed for the debt-asset test are
sector-specific. EPA assumes a 70 percent benchmark value for the debt-asset test to indicate financial
stress in the hog and dairy sectors, and an 80 percent benchmark for the debt-asset test to indicate
financial stress in the beef cattle sector. These benchmark values address public comment received and
alternative debt and asset data submitted for the livestock sectors. For the poultry sectors, however, EPA
did not obtain alternative debt and asset data and continues to evaluate data used for proposal against a
40 percent benchmark value.
A sales test of greater than 5 percent but less than 10 percent of sales with positive cash flow and
a debt-to-asset ratio of less than these sector-specific debt-asset benchmark values is considered
indicative of some impact at the CAFO level, but at a level not as severe as .those indicative of financial
distress or vulnerability to closure. These impacts are labeled "Moderate" for the representative CAFO
group. EPA considers both the "Affordable" and "Moderate" impact categories to be economically
achievable by the CAFO, subject to the enterprise analysis (see below). If, with a sales test of greater
than 3 percent, post-compliance cash flow is negative or the post-compliance debt-to-asset ratio exceeds
these sector-specific debt-asset benchmarks, or if the sales test shows costs equal to or exceeding 10
percent of sales, EPA considers the final regulations to be associated with potential financial stress for
the entire representative CAFO group. In such cases, each of the operations represented by that group
might be vulnerable to closure. For operations that are determined to experience financial "Stress" at the
farm level, the final requirements are likely not economically achievable.
The enterprise level analysis builds on the farm level analysis, evaluating effects at a farm's
livestock or poultry enterprise. If the farm level analysis shows that the regulations impose "Affordable"
or "Moderate" effects on the operation, the enterprise level analysis is conducted to determine whether
the enterprise's cash flow is able to cover the cost of regulations. This analysis uses a discounted cash
flow approach similar to that used to assess the farm level effects, in which the net present value of cash
flow is compared to the net present value of the total cost of the regulatory options over the 10-year time
frame of the analysis. Over the analysis period, if an operation's livestock or poultry enterprise
maintains a cash flow stream that both exceeds the cash costs of the rule (operating and maintenance
costs plus interest) and covers the net present value of the principal payments on the capital, EPA
concludes that the enterprise will likely not close because of the CAFO rule. This analysis is conducted
2-50
-------
on a pass/fail basis. If the net present value of cash flow minus the net present value of the rule's costs is
greater than zero, the enterprise passes the test and the enterprise is assumed to continue to operate. EPA
considers these results to indicate that the final requirements are economically achievable. If the net
present value of cash flow is not sufficient to cover the net present value of the cost of the rule, EPA
assumes that the CAFO operator would consider shutting down the livestock or poultry enterprise. That
is, if an operation fails the enterprise level analysis, these operations are determined to experience
financial "Stress" and the final requirements are likely not economically achievable.
The enterprise level analysis builds on! the farm level analysis, evaluating effects at a farm's
livestock or poultry enterprise. If the farm level analysis shows that the regulations impose "Affordable"
or "Moderate" effects on the operation, the enterprise level analysis is conducted to determine whether
the enterprise's cash flow is able to cover the cost of regulations. This analysis uses a discounted cash
flow approach similar to that used to assess the farm level effects, where the net present value of cash
flow is compared to the net present value of the total cost of the regulatory options over the 10-year time
frame of the analysis. Over the analysis period, if an operation's livestock or poultry enterprise
maintains a cash flow stream that both exceeds the cash costs of the rule (operation and maintenance
costs plus interest) and covers the net present value of the principal payments on the capital, EPA
concludes that the enterprise would likely not £lose because of the CAFO rule. This analysis is
conducted on a pass/fail basis. If the net present value of cash flow minus the net present value of
estimated compliance costs is greater than zero, the enterprise passes the test and is assumed to continue
to operate. EPA considers these results to indicate that the final requirements are economically
achievable. If the net present value of cash flow is not sufficient to cover the net present value of
estimated compliance costs, EPA assumes that the CAFO operator would consider shutting down the
livestock or poultry enterprise. In such cases, JEPA conducts further analysis before making a final
assessment of whether the final requirements are economically achievable.
Table 2-8 shows a summary of how EPA assesses these criteria using enterprise level data,
providing additional analysis of the farm level assessment. Figure 2.1 illustrates the decision matrix
graphically. The following section provides more information on the enterprise level analysis and how it
builds on the farm level analysis.
In response to comments, EPA has conducted additional supplemental analysis to determine the
effects of the regulation under two different scenarios. One scenario takes into consideration the effects
of long-run market adjustment following implementation of the final regulations. This analysis is
conducted using simulated changes hi producer revenue given changes in market prices as depicted by
EPA's market model, which uses estimates of price and quantity response in these markets. A second
scenario takes into consideration potential cost share assistance under Federal and State conservation
programs, assuming that a portion of costs are;covered by cost sharing subject to programmatic
constraints. Given the uncertainty of whether JCAFO income will rise in response to long-run market
adjustment or whether available cost share dollars will effectively offset compliance costs at regulated
CAFOs, EPA's analysis to determine whether'the regulation is "economically achievable" does not rely
on such assumptions as part of its regulatory analysis and therefore reflects the highest level of impacts
projected. EPA presents the results of this analysis assuming both some degree of cost passthrough and
no cost passthrough, as well as some degree of cost share assistance and no cost share assistance, along
with the results of its lead analysis. More information on these supplemental analyses is provided in
Section 2.4.3 of this report. The results of this analysis are provided in Section 3.3.
2-51
-------
Table 2-8. Economic Achievability Criteria for the Final CAFO Regulations
Criteria
Affordable
Moderate
Stress
Farm Level Analysis
Sales test < 3%
Sales test > 3% AND negative farm cash flow OR
debt-asset > benchmark value "
Sales test < 5% AND positive farm cash flow AND
debt-asset < benchmark value"
Sales test > 5% but < 10% AND positive cash flow
AND debt-asset < benchmark value"
Sales test > 10%
X
X
X
X
X
Enterprise Level Analysis
"Affordable" farm level effects with negative
enterprise cash flow
"Affordable" farm level effects with positive
enterprise cash flow
"Moderate" farm level effects with negative
enterprise cash flow
"Moderate" farm level effects with positive
enterprise cash flow
Economically Achievable
X
X
X
X
X
X
2-52
-------
FARM LEVEL ANALYSIS
ENTERPRISE LEVEL ANALYSIS
Affordable/Moderate
(Farm level)
yes
.
profitability, post-tax, long-run)
•
Economic
ichievable'H
(Farm) / "Affordable"
(Sales test: 0%-5%)
"Moderate"
(Sales test: 5%-10%)
CDCF analysis'
(Eriterprise profitability.
post-taxj long-run) <~«\
"Economically
k.chievable'j
(Enterprise)
Supplemental analyses:
•Cttstpassttarougfr"' "^
XCost-share assistances'
Figure 2-1. Schematic of EPA's Decision Matrix of "Economic Achievability"
2.4.2.2 Analysis of Effects at Multiple Business Levels
For the 2001 Proposal, EPA evaluated financial impacts using USDA data aggregated at the
whole-farm level because data obtained fron^USDA did not allow for an enterprise level analysis.
Therefore, EPA's basis for determining economic achievability for the proposal was measured in terms
of potential farm closures and not potential enterprise closures.16 Both of EPA's Notices present
additional data received since proposal that EPA uses to assess financial impacts at multiple business
levels within a representative facility (presented in Section 2.3 of this report). Using these data, EPA
evaluates financial impacts both at the farm level and the enterprise level for the final regulations.
16
EPA typically conducts its analyses of regulated entities using data for a business as a whole as opposed
to an individual product line because of data limitations. The only recent ELG regulation to evaluate product line
closures is that for the Pesticide Formulating, Packaging and Repackaging industry, for which enterprise level
financial data were collected through a CWA Section 308 survey (USEPA, 1996, or 61 FR 57518).
2-53
-------
Perhaps the principal concern raised by researchers at various-land grant universities and USDA
is that EPA should evaluate financial impacts on regulated CAFOs using an enterprise level analysis
only. As discussed in the 2001 Notice, many commenters claim that EPA's use of farm level financial
data raises questions as to whether a CAFO would willingly subsidize one of an operation's enterprise
with dollars from another enterprise at the business. These commenters question whether producers at
more diversified operations would choose to cross-subsidize an unprofitable enterprise for long periods
or whether they would instead shift assets toward other, more profitable enterprises at their operation;
these producers might not quit farming but would remove the nonproductive enterprise from their
fanning mix (FAPRI, 2001a, 2001b; NPPC, 2001). This criticism was also raised before and after the
2001 Proposal (USEPA, 200Id). Other commenters point out that larger operations are normally
enterprise-specific and tend to specialize. Therefore, an enterprise approach might be more appropriate
for EPA's analysis. Other commenters also note that the use of enterprise level data in the form of
"enterprise budgets" is more consistent with a representative farm approach, which was the general
approach EPA adopted for evaluating financial impacts for the 2001 Proposal (NMPF, 2001). FAPRI
(200 la) has also noted that although an evaluation of impacts at the farm level has merit, it is also prone
to confounded results because enterprise-specific costs are spread over a larger share of the business
(e.g., non-livestock enterprises bear the cost of regulations affecting the livestock portion of the
operation). Some commenters, however, disagree with an approach that would consider an assessment at
the enterprise level only (see, for example, Weida, 2002; Dcerd, 2002).
For the 2002 Proposal, EPA acknowledged many of the concerns expressed in public comments
about the need to consider enterprise level financial effects. In the industry profile and data sections of
the Proposal EA (see Section 2 and Section 4, respectively), EPA readily acknowledged limitations of
these data stating that data were not available to evaluate an operation's livestock or poultry enterprise
separate from the whole business operation. EPA also agrees with comments stating use of farm-level
financial data raises questions of whether a CAFO would willingly subsidize one enterprise with dollars
from other farm enterprises (e.g., whether producers at more diversified operations would choose to
cross-subsidize an unprofitable enterprise for long periods or whether they would instead shift assets
towards other, more profitable enterprises at their operation). Such producers might not quit farming but
would only remove the non-productive enterprise from their farming mix. EPA recognizes that larger
operations are normally enterprise specific and tend to specialize, focusing on a single enterprise;
therefore, an enterprise approach may be more appropriate for EPA's analysis. EPA also recognizes that
the use of enterprise level data in the form of "enterprise budgets" is more consistent with a
representative farm approach, which was the general approach adopted by EPA for evaluating financial
impacts for the 2001 Proposal. These concerns were noted by EPA in the 2001 Notice (66 FR 58580-
58582). Because alternative enterprise level financial data were submitted to or obtained by EPA during
the comment period, EPA has responded to these comments by including an analysis of the enterprise
level effects as part of its overall assessment. Both of the Notices of Data Availability that EPA has
published on this rule presented alternative enterprise level financial data and discussed options for
evaluating enterprise level effects as part of the analysis, soliciting further review and comment on this
issue. See: "2001 Notice" (November 21,2001, 66 FR 58556) and the "2002 Notice" (July 23,2002, 67
FR 48099), as well as DCN 375084 in the rulemaking record.
Although EPA agrees with comments that an evaluation of impacts at the farm level might be
susceptible to confounded results because enterprise-specific costs are spread over a larger share of the
business (including non-livestock enterprises), the Agency notes the merit in including an analysis of the
fam level effects as well, since an analysis focused at the enterprise level only would ignore the
interdependency among related enterprises at an operation. Comments by Dcerd (2002) noted that an
enterprise level analysis would:
2-54
-------
"ignore the fact that, on many diversified fanning operations, the output of one
enterprise becomes the input of another and the waste of one enterprise becomes
a resource for another." Enterprise analysis treats separate enterprises as if they
were 'independent,' whereas, on diversified farms enterprises are instead
"interdependent" In addition, on well-managed, diversified farms, the different
enterprises are complements, not substitutes—i.e. the enterprises 'cross-
subsidize' each other by nature. Enterprise analysis quite simply is not
appropriate to address issues where diversification is a logical management
strategy —as is most clearly the case in dealing with environmental issues."
EPA recognizes the importance of considering financial impacts at multiple levels within a
business because this is consistent with economic theory and is a technically sound approach. This
approach is also consistent with how businesses make decisions because most businesses would be
unwilling to cross-subsidize a failing enterprise over a long period rather than simply discontinuing it.
Also, a failing enterprise might have Limited access to available financing for capital replacement or
expansion of the operation because lenders typically look at expected cash flow for an operation's
enterprise in making loan decisions (ERG, 200 Ic). Focusing on the enterprise level further addresses
changes in an operation's ability to diversify and manage risk, and it might also affect industry
concentration and consolidation trends. Therefore, for the final rule analysis, although EPA's primary
level for evaluating financial effects remains the farm level, the Agency has supplemented this approach
with an assessment of the potential enterprise level effects of the regulation. EPA's final analysis
approach using both farm level and enterprise level financial data for this effort.
EPA believes that both levels of analysis have merit in evaluating the financial effects of
regulation in an industry. EPA has used this multi-level approach in other economic analyses it has
performed for effluent guidelines. In the manufacturing sectors the key components of an impact
analysis are the firm and the facility. EPA looks at whether a facility can absorb the costs of compliance
while still remaining viable (typically, if cash flow is negative post-compliance, the facility is considered
nonviable). The facility may be able to absorb the cost of compliance, but the firm may not be able to
obtain the necessary capital to meet requirements or may fail as a result of incurring the costs of
compliance at multiple facilities. Thus a firm level analysis is also performed. Impacts on both firms
and facilities are considered in EPA's assessment of economic achievability. This approach supports
observations noted in some comments on the CAFO rule, pointing out that farmers may support an
enterprise because the output of one enterprise is used as input to another apply to analyses of firms and
facilities. These facilities may be considered ^'captive" facilities, in that they are not stand-alone or the
output of one is the input to another facility. Only an analysis at the firm level would reveal whether the
firm can afford to keep going even if one or more facilities does not appear viable. Thus, EPA believes
that an analysis covering both the farm level and the enterprise level is appropriate for this rulemaking.
For these reasons EPA is expanding its analysis to include an assessment of enterprise level
effects. Other comments, however, challenge EPA's assessment of financial effects at the regulated
entity, claiming that this assessment should be made for the "industry as a whole" and that economic
factors be given only minimal consideration in setting effluent guidelines (Water Keepers Alliance, et al.,
2001). Related comments presented by various groups during the development of the rulemaking further
support conducting this analysis based on financial effects measured at the processor and consumer level
(see, for example, USEPA, 2001f, and notes from other EPA meetings during the development of the
rulemaking). As noted in the 2001 Notice, EPA has not modified its economic models to consider •
financial data for processing firms (66 FR 58581), as described below.
2-55
-------
EPA continues to consider farm level impacts in addition to other assessed effects at the
enterprise level because of concerns about evaluating impacts at the enterprise level only, as discussed
in the 2001 Notice (see discussion starting at 66 FR 58580). As a practical matter, EPA recognizes
that often the individual enterprises at an operation are highly interdependent, such as in the case of
integrated production systems where there may be considerable cost savings due to shared production
and labor costs among multiple enterprises. This is also true where one enterprise (e.g., grain crop
production) serves as an input to another (e.g., livestock production). An analysis using, enterprise
level data might also fail to account for the range of assistance to the farming operation available
through various government programs, which are often noted as a separate source of farm level income
in USDA's data compendiums. Also, as pointed out by one lender questioned by EPA, lenders usually
look at the debt-carrying capacity of the farm operation as a whole, except in the unusual instance
when the lien is on only the enterprise (ERG,-2001c). Finally, farms are commonly noted to be
motivated by noneconomic factors, which might influence an operation's decision to weather the boom
and bust cycles that are commonplace hi agricultural markets (USEPA, 2001, Heimlich and Barnard,
1995).
For additional information, EPA's response to comment DCN CAFO202402-35 in the Comment
Response Document in the rulemaking record.
The issues described above raise questions about whether a decision to conduct EPA's analysis
strictly at the enterprise level has merit. Also, previously published academic research by both the land
grant universities and USDA has typically evaluated impacts using data and methods specified at the
farm level or has, at least, taken into consideration information for the larger business concern (DPRA,
2001). This is all consistent with EPA's long-standing practice and consistent with Agency guidance to
assess impacts on small businesses at the broader business level (USEPA, 1999i; SBA, 1998; USGPO,
2000).
Since the publication of the 2001 Notice, EPA has evaluated ways to incorporate an enterprise
level analysis as part of its assessment. How EPA incorporates its enterprise level analysis into its
overall decision-making framework was described in Section 2.4.2.1.
EPA conducts its enterprise level profitability test on a cash basis, which excludes both the
noncash income and noncash expenses (depreciation). In agricultural accounting, net cash income
measures the difference between gross cash income and cash expenses, including net rent to non-operator
landlords. It does not include depreciation. This approach is consistent with Farm Financial Standards
Council (FFSC) guidance. FFSC makes several recommendations concerning the role of unpaid labor
and management hi the income statement: "For analysis purposes, the FFSC recommends the following:
(a) the general income statement should include a calculation of gross revenues and farm income, both on
an accrual adjusted basis; (b) a charge for unpaid family labor and management should not [emphasis, as
underlined, in the original] be included on the income statement;...." (FFSC, 1997, p. H-3). Other FFSC
recommendations that support EPA's approach include the following: "For the purpose of analysis, the
FFSC recommends the following on the issue of NFI (net farm income): NFI will continue to be defined,
as the return to operator and unpaid family labor, management and equity capital. No estimate of a
charge for unpaid labor and management should be included on the income statement" (FFSC, 1997, p.
It-22). Based on this guidance, EPA decided not to use net farm income as the profitability measure for
this analysis. Net farm income is the difference between gross farm income and total production
expenses, whereas gross farm income includes noncash income such as the value of home consumption
and the rental value of dwellings. Also, in many cases the farm operation is also the owner-operators'
2-56
-------
home; operator returns are calculated by excli
operators' dwellings from net farm income.
the income and expenses associated with farm
2.4.2.3 Basis for Benchmark Values for Assessment Criteria
For the 2001 Proposal, the principal basis for EPA's economic achievability criteria for this
rulemaking is USDA's financial classification of U.S. farms. In its analyses of the financial performance
of U.S. commercial farms, USDA uses a combination of a farm's net income and debt-asset ratio to
classify the overall financial position of a farm based on annual earnings and solvency (USDA/ERS,
1997e). Net farm income is an effective measure of long-term profitability; the debt-asset ratio is a
useful measure of a farm's financial risk. Together these two measures provide an indicator of the farm's
long-term financial health and viability (Sommer et al., 1998). For example, if a farm earns enough
income to service debt and meet its other financial obligations, a high debt-asset ratio might be
acceptable, while a farm carrying a low debt load might be able to weather periods of low or negative.
farm income (Sommer et al., 1998). USDA considers net income and debt-asset ratio jointly to classify
farm performance by financial position, ranging from "favorable" to "unfavorable" (Sommer et al., 1998;
USDA/ERS, 1997a, 1997e). USDA's classification scheme broadly identifies an operation with negative
income and a debt-asset ratio hi excess of 40 percent as "vulnerable." An operation with positive income
and a debt-asset ratio of less than 40 percent is considered "favorable."
EPA adopts this scheme as part of its economic achievability criteria, using net cash flow to
represent income and assuming a debt-asset threshold value of 40 percent. More information is presented
in Section 4 of the Proposal EA. ;
As presented in the 2001 Proposal, USDA's debt-asset ratio threshold of 40 percent, which
defines whether a farm is highly leveraged, is consistent with other recommendations (Ohio State
University, 1999). Although a higher ratio usually indicates financial risk, debt-asset ratios tend to be
higher for large farms and for those specializing in livestock feeding (Iowa State University, 1999b). For
example, ratios of 30 to 40 percent are common among Iowa farms, although many operate with little or
no debt (Iowa State University, 1999b). Another caution when considering debt-asset ratios is that a high
debt load does not make farms less efficient; high-efficiency farms are able to service a higher debt load
and maintain a higher debt-asset ratio with less risk than low-efficiency farms (Iowa State University,
1999b). As noted in the Proposal EA, the range of acceptable values for an operation's debt-asset ratio
will vary depending on income variability, the proportion of owned land (or other assets) used in the
farming operation, risks associated with normal production, and fluctuations hi farm asset values that
might occur due to changes in demand for agricultural assets (FFSC, 1997). For more information, see
Section 4 of the Proposal EA.
EPA received several comments on the debt-asset test. Criticism of EPA's debt-asset test fall
into two interrelated groupings, one criticizing the baseline data assumptions and the other criticizing the
threshold value chosen to assess regulatory impacts. These comments noted that USDA's debt and asset
data that EPA used for the proposal do not represent the current state of borrowing in many of these
sectors, particularly for the size of operation subject to EPA's regulations which tend to carry more debt
than that reflected by USDA's data. Comments challenging the baseline debt and asset data used for the
2001 proposal further raise questions the appropriateness of using USDA's recommended 40 percent
benchmark value for assessing these larger-sized confinement operations. The 2001 Notice (November
21, 2001, 66 FR 58556) presented some of these concerns and described alternative data and approaches
2-57
-------
that EPA was considering (see 66 FR 58585-58589). The 2002 Notice of Data Availability (July 23,
2002, 67 FR 48099) discussed additional considerations, providing further details and discussions of data
pertaining to EPA's analysis for the final rule, thus soliciting further comment on this issue (see 67 FR
48105). Other information supporting the 2002 Notice was provided in DCN 375084 in the rulemaking
record. For additional information, see EPA's comment-response document on this topic.
Commenters generally claimed that USDA's 40 percent threshold value, used by EPA in its
baseline model to assess post-regulatory debt-asset ratios, does not reflect the financial reality of today's
livestock or poultry industry. They also claimed that this debt level does not represent the current state
of borrowing in many of these sectors (see, for example, NPPC, 2001; NMPF, 2001). These comments
noted that the USDA 1997 data fail to account for the wide range of variability among farm operations,
based on various factors, including facility size and the age of the farm operators. Alternative data.
submitted along with these comments support these claims.
To address comments about the baseline data, EPA uses alternative debt and asset data for
several livestock sectors (cattle, dairy, and hog), which were submitted by FAPRI and NCBA.17 These
data indicate that larger, more intensive, or expanding operations tend to carry more debt than that
reflected in data used by EPA for the proposal. This fact is supported by information EPA obtained from
major agricultural lenders following the proposal; EPA's own discussions with farm lenders indicate a 60
percent debt level for "typical" operations (ERG, 20()lc). See data presented in Table 2.2 in Section 2.3.
By contrast, average USDA-reported data tend to cover a broader range of farm types and sizes,
including small farms and non-confinement operations that are not subject to the regulations. EPA
believes that alternative debt and asset data submitted by commenters and presented in both Notices are
more appropriate for this analysis than data used for the proposal analysis. (EPA did not obtain
alternative data for the poultry sectors; therefore, the Agency continues to use the same USDA-reported
average debt and asset data and USDA's 40 percent threshold to indicate financial stress, as was done for
proposal.)
The use of these alternative data, however, has implications for the debt-asset benchmark for
indicating financial stress for these sectors. As shown in Table 2.2, these data translate to the baseline
debt-asset ratios ranging from 60 percent to more than 70 percent and exceed the USDA-recommended .
40 percent benchmark indicating financial stress. Therefore, USDA's recommended 40 percent
benchmark is not suitable for assessing changes in debt at operations using these alternative debt and.
asset data. Use of alternative data submitted during the comment period (indicating that baseline debt-
asset levels at some representative facilities exceed 40 percent and often exceed 70 percent) point to the
need for EPA to consider an alternative benchmark to evaluate this test.
Since USDA's recommended 40 percent benchmark is not suitable for assessing operations using
these alternative data, both of EPA's'Notices and related supporting documentation requested
information about alternative benchmark assumptions to evaluate changes in the baseline debt and asset
data, soliciting further comment on this issue. In general, commenters claim that financial stress would
occur at operations facing debt-asset ratios of roughly 60 percent to 80 percent. One commenter
suggested that a ratio of more than 60 percent would, be indicative of stress and that a ratio of more than
70 percent would result in bankruptcy (NMPF, 2001). The basis for this recommendation is farm credit
information from the American Bankers Association's Farm Financial Standards Task Force suggesting
17 These alternative debt and asset data are available in the record (see: DCN 175044 and DCN 175038)
2-58
-------
that debt-asset levels in excess of 60 percent act as "red light" indicators to lenders (USEPA, 200 Ic;
Cryan, 2001). The 2002 Notice solicited comment on an assumption of an 80 percent benchmark value
to indicate financial stress for these sectors. This alternative benchmark is based on recommendations by
NCBA (NCBA, 2002— DCN 375047). EPA's own discussions with farm lenders indicate a 60 percent
debt level for "typical" operations (ERG, 2001 c). Most lenders require an operation to retain a 40
percent equity base in the operation, although lower bases may be acceptable, particularly where the
majority of debt is in short-term livestock loans or at very large operations. Therefore, debt-asset ratios
of nearly 70 percent (reflecting a 30 percent equity stake) at very large operations represented in the
NCBA survey may reflect both of these factors (NCBA, 2001).
In response to the 2002 Notice, EPA received comments recommending alternative benchmarks
ranging from 50 percent to 70 percent for all sectors. One commenter representing the hog industry
provided information from university researchers recommending a benchmark of 70 percent for larger
hog operations and 50 percent for smaller hog operations; information provided suggests that an 80
percent benchmark is too high for a farrow finish operation since neither the animals or the facilities in
this sector is as marketable as beef cattle (DCN 600031). EPA disagrees with the use of this lower bound
benchmark given that the alternative debt-asset ratios that EPA presented in the 2002 Notice already
exceed this level; however, EPA's "economic achievability" analysis is focused on larger-sized
operations with more than 1,000 AU and therefore does not require that EPA establish an appropriate
benchmark for smaller-sized operations. Other comments presented information from agricultural
lenders supporting a benchmark of 70 percent for all sectors (DCN 600060 and DCN 400158). Because
this recommendation originated from university staff and agricultural lenders, EPA generally recognizes
that it should consider a lower benchmark for some sectors. Given these considerations and because
USDA's recommended 40 percent benchmark is not suitable for evaluating the alternative debt and asset
data that EPA is now using to reflect baseline; conditions at regulated CAFOs, EPA is assuming for the
final rule analysis a 70 percent benchmark value for the debt-asset test to indicate financial stress in the
hog and dairy sectors and an 80 percent benchmark for the debt-asset test to indicate financial stress in
the beef cattle sector.
To further evaluate these data and alternative benchmark values, and the implications for EPA's
analysis, the Agency conducted additional sensitivity analyses. This analysis indicates that the use of the
alternative 70 percent benchmark does not change the overall results of EPA's analysis for these sectors,
compared to an analysis assuming an 80 percent threshold value for the debt-asset test. This finding
holds for each of the cattle, dairy, or hog sectors. For each of the affected livestock sectors, EPA's
sensitivity analysis compares the results of the economic analysis assuming two alternative benchmark
values for its debt-asset test: one debt-asset benchmark assesses the results of this test assuming that
financial "stress" occurs if the ratio of debt to assets exceeds 80 percent ("main" analysis); another debt-
asset benchmark assesses the results of this test assuming that "stress" occurs if the ratio exceeds 70
percent ("alternative" analysis). This test is used in conjunction with EPA's two other assessment
criterion for this analysis sales test and DCF analysis, with no change from the main analysis. The
results of these analyses indicate that EPA's analysis results are stable across a range of input data (ERG,
2002c—DCN 375111). For more information, see EPA's response to comments DCN CAFO 210352-
106 and DCN CAFO 201438-207-1.
The threshold values EPA uses for its sales test (3 percent, 5 percent, and 10 percent) are those
the Agency has determined to be appropriate for this rulemaking and are consistent with threshold levels
used by EPA to measure impacts of regulations for other point source dischargers. See Section 4 of the
Proposal EA. EPA has used 1 percent and 3 percent sales test benchmarks to screen for potential impacts
2-59
-------
in many small business analyses (e.g., USEPA, 2000c, 1999a). These benchmarks are only screening
tools, but do support EPA's contention that a sales test of less than 3 percent generally indicates minimal
impact (Snyder, 2000). Heimlich and Barnard (1995) do not define a threshold where the management
measures would be considered economically achievable because "...there are no hard and fast guidelines
for what is economically achievable, any appraisal of overall acbievability... is subjective."
The 5 percent benchmark is consistent with threshold values established by EPA in previous
regulations for other point source dischargers. Generally, EPA's analyses have assumed that sales tests
less than 5 percent indicate compliance costs that are achievable (see, for example USEPA 1987 and
1994). Other analyses have assumed the same threshold but have further assumed that ratio values in
excess of 5 percent may constitute moderate impacts, taking into consideration other factors (USEPA
2000b, 1999b, and 1996). This analysis adopts this framework to analyze regulatory impacts to CAFOs.
In another analysis, a sales test result of greater than 5 percent was labeled a "sales impact" (USEPA,
1987). Sales impacts were assessed separately from those impacts that may make a facility vulnerable to
closure.
EPA uses an upper limit for a sales test result of 10 percent (whereby this result alone indicates
financial stress), rather than assuming that there is no upper limit on a sales test percentage if other
financial variables are also analyzed (such as in USEPA, 1996). EPA believes, in this case, that if a sales
impact is very high, this result should be considered a substantial impact and might make an operation
vulnerable to closure in spite of positive cash flow and an adequate debt-asset ratio. EPA thus uses the
10 percent benchmark to ensure that potential vulnerability will not be underestimated. In fact, relatively
few operations could incur costs greater than 10 percent of revenues while continuing to show positive
cash flow.
Because EPA does not use a sales test alone as a measure of financial vulnerability, the sales test
operates more as a screening tool. In most cases (results between 3 percent and 10 percent), a finding of
financial stress is driven by cash flow and debt burden considerations. Thus, over the key range of sales
impacts, EPA's methodology is consistent with many USDA analyses, which very frequently use net
income and debt-asset ratios to assess impacts (e.g., USDA/ERS, 1997e). The exception is that EPA
does not consider noncash income and depreciation (that is, EPA uses a net cash income-type analysis
rather than a net farm income analysis). This is consistent with current views on the use of cash flow
analysis, which is preferred over net income analysis among financial analysts (Brigham and Gapenski,
1997; Jarnagin, 1996).
Finally, as noted hi the 2001 Notice, EPA has not modified its economic models to take into
consideration financial data for processing firms (66 FR 58581). Such an approach has been suggested
because of the affiliation between some CAFOs (e.g., contract growers) and processing firms through
various contractual arrangements in some sectors. Data are not available to conduct such an analysis:
EPA does not have market information on which processors and CAFOs participate in such contract
agreements; financial data for processing firms that contract out the raising of animals to CAFOs are also
not available. Consistent with how EPA conducted its analysis for the 2001 Proposal, EPA will continue
to assume that an assessment of the regulatory impacts of the final regulations is more accurately
conducted for the regulated CAFO that incurs the cost of the final requirements. EPA solicited
comments on this approach and requested additional financial data to conduct such an analysis in its •
2001 Proposal and Notice. EPA continues, however, to evaluate expected broader market level changes
using the assumptions of cost passthrough that were developed for the proposal as a surrogate for more
complex market level models that would take into account structural adjustment among farmers as well
as market adjustment hi the long run.
2-60
-------
2.4.2 Supplemental Analyses
This section discusses supplemental analyses performed by EPA to evaluate financial effects on
CAFOs. Section 2.4.3.1 describes how EPA evaluates the effects of long-run market adjustments under a
post-compliance scenario, assuming that eventual higher prices and facility revenue might partially offset
the estimated financial effects on regulated CAFOs. This analysis modifies a similar analysis conducted
for the 2001 Proposal in which EPA assumed a portion of the costs are passed up through the food
marketing chain under assumptions of long-run market adjustment. Section 2.4.3.2 describes how EPA
evaluates the effects of the final regulations in conjunction with increased funding of available cost-share
assistance programs, assuming that these program monies might partially offset the estimated compliance
costs to regulated CAFOs. Section 2.4.3.3 describes other supplemental analyses considered by EPA.
Although EPA conducts various supplemental analyses of alternative assumptions in its analysis
(for example, analyzing the potential CAFO closures assuming both no long-run market adjustment or
cost passthrough, or assuming both some degree of cost share assistance and no cost share assistance),
the Agency decided not to base its statutory analysis of "economic achievability" on such assumptions.
The reason for this decision is continued uncertainty about how to incorporate such assumptions into its
analysis. Therefore, EPA's analysis reflects the highest level of financial effects projected. The basis for
EPA's decision is discussed hi the Comment Response Document in the rulemaking record. Response to
comment DCN CAFO201717-32 discusses how EPA addresses long-run market adjustment as part of its
analysis, as well as the potential for operations to pass on costs incurred to comply with the final
regulations. Response to comment DCN CAFO200139-4 discusses how EPA addresses available cost
share assistance from Federal and State farm conservation programs as part of its economic analysis.
Response to comment DCN CAFO202615-21 discusses how EPA's analysis accounts the nutrient value
of manure and potential income from manure sales as part of its economic analysis.
2.4.3.1 Market Impacts on Facility Income
For the 2001 Proposal, EPA presented the results of its economic impact analysis both assuming
no long-run market adjustment or cost passthrough (i.e., the highest level of financial effects projected)
and some degree of cost passthrough. However, because of uncertainties regarding how and when much
market adjustments would occur and whether this would actually offset estimated compliance costs
incurred by CAFOs, EPA's determination of whether the regulation is "economically achievable" did not
rely on assumptions of cost passthrough an offset to estimated compliance costs as part of its regulatory
analysis and therefore reflects the highest level of impacts projected.
In general, EPA measures the financial effects of the final regulations on the basis of the
estimated compliance costs incurred at the CAFO. However, other mitigating factors could influence
what costs the CAFO ultimately incurs because a portion of these costs might eventually be passed on
through the food marketing chain. Passthrough of compliance costs might occur in the long run through
market adjustment (higher prices through changes in supply and demand) or in the shorter term as
processors take steps to ensure a steady and continued supply of raw farm input (raise production prices
for live animals or animal products produced by CAFOs). For the purpose of this analysis, EPA
examines regulatory impacts on producers in the livestock and poultry sectors under the assumption that
they will experience increased revenues due to long-run market adjustment and resultant higher market
prices. This section presents an overview of)this analysis.
2-61
-------
Individual farms may be considered competitive and may not individually be able to raise prices.
Collectively, however, if production costs rise across the industry as a whole, economic theory indicates
that prices will rise. Essentially, if farmers cannot earn a sufficient return to cover all long-run costs of
production, they will leave the market. This action, in turn, will force customers to pay a higher price to
purchase the quantity of the product they desire. (This is illustrated in Figure C-l of Appendix C of this
report). As the final regulations result in an increase in production costs, the supply curve for the market
shifts upward. The magnitude of this shift is equal to annualized compliance costs per unit sold (CC/Q).
Because the supply curve reflects long-run production costs, this change represents the minimum price
necessary to ensure adequate supply of the product. Market price will rise from P° to P1 in the long run.18
Intuitively, the effect of the final regulations on market prices can be measured (as shown in Figure C-l)
as the increase in market price (P1 - P°) relative to compliance costs per unit of production (e.g., head of
cattle):
market price increase as percent of unit compliance costs = APCC =
_ (pi _ pO)
CC
Table 2-9 shows, for example, that the measured price increase as a percent of unit compliance costs
equals 70.7 percent for beef cattle. That means if the final regulations cause farmers to incur compliance
costs of $1.00 per head of cattle, then the resulting decrease in cattle supply causes the market price to
increase by about $0.71 per head. In general, the magnitude of this effect will vary according to market-
specific conditions.
EPA thoroughly examined this issue during the development of the proposed rulemaking, as
documented in Section 10 of the proposed rule preamble as well as in the Proposal EA (Sections 2 and 4
and Appendices B and C). In the industry profile and data sections of the Proposal EA, EPA readily
acknowledged limitations of incorporating assumptions of cost passthrough in the analysis, given
existing dynamics in these industries. EPA's industry profile in the Proposal EA acknowledged many of
the reasons why farmers may be limited from passing on higher operating costs, including the perception
that farmers are price takers and have limited negotiating power to pass on costs or negotiate higher
product prices, attributable in part to imperfect market conditions characterized by conditions of
oligopsony/monopsony (i.e., few buyers, many sellers).
To further examine this issue, EPA conducted an extensive review of the agricultural literature
on market power and price transmission in each of the livestock and poultry sectors and concluded that
there is little evidence to suggest that markets will not adjust to at least partially offset increased
production costs to producers. Although there is a potential for market power in each of the animal
products industries, and although vertical integration has squeezed the rents out of many farming
activities, EPA believes that the literature generally supports the conclusion that the degree of market
power in these sectors is not sufficient to prevent increased production costs from being partially offset
Under highly unusual circumstances, market price will not rise in response to increased production
costs. First, if demand for a product is perfectly elastic (the demand curve in Figure C-l in Appendix C is
horizontal), consumers, including processors or packers, are not willing to pay more for a product regardless of
scarcity. Second, if the supply of a product is perfectly inelastic (the supply curve in Figure C-l is vertical), the
quantity supplied by the producer will not change regardless of price. In the real world, even nearly perfectly elastic
demand or nearly perfectly inelastic supply at the sector or industry level for most products in the long run is rare.
2-62
-------
by increased market prices for these products, particularly in the long-run, such that prices and quantities
will adjust to a post-regulatory equilibrium. A summary of this research is in the rulemaking record
(ERG, 2000c—DCN 70640).
Despite EPA's general conclusions based on the empirical research about long-run market
adjustment, EPA presented the results of its economic impact analysis both assuming no long-run market
adjustment or cost passthrough for the 2001 Proposal, and based its determination of whether the
regulation is "economically achievable" without assuming cost passthrough of costs. As noted in the
preamble and Proposal EA, many industry representatives opposed assumptions that producers will be
able to pass on costs or that compliance costs would be partially offset by higher producer prices,
including prices paid to contract growers who raise animals under contract with a meat packer or
slaughtering/processing facility. Similar concerns were expressed by many small entity representatives
during the Agency's small business outreach process and by members of the Small Business Advisory
Review (SBAR) Panel.19
EPA received several comments on the 2001 Proposal recommending that the Agency not
consider cost passthrough as part of its analysis, particularly for its analysis of whether the regulation is
economically achievable. (See, for example, NPPC, 2002, NMPF, 2002, National Center, 2002) EPA
acknowledges comments pointing out that individual farmers might be unable to influence market or
producer prices. EPA also acknowledges, however, comments focused on the relationship between
processing firms and producers that raise animals under contract for these firms, citing expectations that
future contract negotiations would result in compliance costs will be fairly allocated over time
(Wisconsin Department of Natural Resources, 2002). Some stakeholder?, support assumptions of cost
passthrough. During the development of the rulemaking, the Natural Resources Defense Council
(NRDC) and interest groups continually requested that EPA consider the financial ties linking processors
and contract growers, and the ability within these markets to pass on costs to consumers (see: Weida,
2002; Ikerd, 2002; USEPA, 20021f, NRDC, 1999). Dcerd (2002) notes that "EPA CAFO regulations
might logically result in more, smaller, and more-profitable farms" since the regulations "could cause
price, increases that would more than offset any increase in production costs."
In response to comments on this issue hi the 2001 Proposal, the Agency's 2001 Notice of Data
Availability (November 21,2001, 66 FR 58556) EPA restated its intention to consider such analyses for
the final regulations as part of its economic analysis, expecting to obtain additional comment on this
issue (66 FR 58581). The 2002 Notice of Data Availability (July 23, 2002, 67 FR 48099) further
discusses adjustments to the Agency's approach to conduct this analysis (67 FR 48107). The approach
presented would alter the Agency's analysis from an approach that assumes costs are passed on by farmer
through the marketing chain to an approach that would instead evaluate financial effects based on
assumed changes hi prices received by producers as a result of long-run market adjustment.
Appendix C of this report describes EPA's approach to evaluate the effects of long-run market
adjustment and changes in facility level income under a post-compliance scenario for this analysis. To
conduct this analysis, EPA estimates changes in farm level prices using its market model analysis
(described in Section 2.5 of this report). EPA's market model uses baseline equilibrium price and
quantity, as well as equations representing estimated supply and demand responses to changes in price.
These comments note that integrators have a bargaining advantage in negotiating contracts, which might
ultimately allow mem to force producers to incur all compliance costs, as well as allow them to pass down to
growers any additional costs that might be incurred by the processing firm.
2-63
-------
This model is specified for each livestock and poultry industry affected by the final regulations. The
market model uses estimated compliance costs per unit of production for the final regulations to measure
the vertical shift in the supply curve. Given the vertical shift in the supply curve, the model solves for
the post-regulatory equilibrium price. Thus, all components of this supplemental analysis are baseline
parameters, inputs, or outputs of EPA's market model. This approach reflects an adjustment to what was
done for the 2001 Proposal by using predicted price changes from the market model analysis to calculate
the effect of this change on the CAFO level financial analysis (focusing on the revenue rather than the
cost side of the analysis). Such an approach is more consistent with previous regulatory analyses
conducted by EPA's effluent guideline program (e.g.,USEPA, 1999a—65 FR 49686). This change was
noted in the 2002 Notice (67 FR 48106-48107).
Table 2-9 shows the selected price elasticities of supply and demand that EPA assumes for each
sector, along with the resultant estimate of the price increase as a percent of per unit compliance costs
based on these estimates using the approach outlined in this section.
Section 4.4 and Appendix B of the Proposal EA describe EPA's market model for this analysis,
providing a detailed overview of the data and the methodology underlying this approach. Section 4.2.6
and Appendix C of the Proposal EA provide additional information on the supply and demand elasticities
compiled to evaluate long-run market conditions following promulgation of the final regulations.
Although many comments generally concurred with EPA that long-run market adjustment will
occur, EPA agrees with concern expressed by these commenters about short-run impacts at regulated
CAFOs and agrees that the results of a cost passthrough analysis must be interpreted cautiously. Given
the uncertainty of whether CAFO level income will rise in response to long-run market adjustment,
however, EPA presents the results of this analysis assuming both some degree of cost passthrough and no
cost passthrough (the highest level of impacts projected).
EPA agrees that over the long-run the aggregate effect of many individual farmer's response to
the regulations will cause market prices and quantities to adjust. This long-run market adjustment will
lessen the economic impacts of the final regulations over time. EPA also agrees with comments that
predict contract price negotiations between processing firms and their contract growers that will ensure
continued and steady supply of animals for further processing. However, EPA decided not to base its
statutory analysis of "economic achievability" on assumptions of long-run market adjustment because
continued long-run changes are difficult to predict and therefore cannot be readily incorporated into
EPA's regulatory analysis as an offset to estimated compliance costs at all regulated facilities. EPA also
agrees with comments noting that an analysis that takes into account broader long-run market
adjustments might mask severe financial effects at regulated CAFOs in the short-run. Accordingly, EPA
has undertaken its mam analysis as a short run analysis of the financial effects at regulated CAFOs. The
results of this analysis are available in Section 3.3.2 of the Final EA and presents the results of EPA's
economic achievability analysis before any longer-run revenue effects are realized. See Section 3.3 of
this report. Although EPA's short-run model provides a reasonable means to approximate CAFO level
effects taking into account market changes associated with long-run adjustment (when coupled with
results from a market model analysis and other published information from various land grant
universities), this model is not specifically designed to precisely capture such long-term effects.
To the extent that EPA's analysis considers assumptions of long-run market adjustment as part of
a supplemental analysis, the Agency agrees with comments that the results of this analysis must be
interpreted cautiously. Because long-run market adjustment will likely lessen the economic impacts of
2-64
-------
the final regulations over time (in conjunction with offsetting cost share and technical assistance) EPA
believes that the results of its analysis to determine "economic achievability" is sufficiently conservative
and depicts the highest level of potential effects. The results of the Agency's supplemental analysis
assuming some degree of long-run market adjustment is viewed as providing a realistic lower bound
estimate of financial effects of the regulation. Section 2.4 of the Final EA discusses how EPA
incorporates these assumptions in its analysis, while addressing the constraints of such an analysis
Appendix C of this report describes EPA's approach to evaluate the effects of long-run market
adjustment and changes in facility level income under a post-compliance scenario.
EPA continues to present its analysis results both assuming no long-run market adjustment and
some degree of long-run market adjustment. EPA also continues to base its determination of whether the
regulation is "economically achievable" without relying on assumptions of long-run market adjustment as
an offset to estimated compliance costs in the short-run.
Fable 2-9. Selected Elasticity Estimates and Estimated Regulatory Price Effect
Animal
Sector
Beef
Dairy
Hogs
Broiler w
Layer
Turkey
Selected Price
Elasticity of Supply "
1.020
1.527
0.628
0.200
0.942
0.200
Selected Price
Elasticity of Demand1"
-0.621
-0.247
-0.728
-0.372
-0.110
-0.535
Price Increase as Percent of
per unit Compliance Costs
70.7%
84.8% .
69.7%
68.7%
93.7%
49.5%
------ v — »u, *-^^«j *^^^y, MAow o^n ouAiuiuu^y ni rtppcuuiA. \^ ill jTropoSal EjJ
Elasticities representing a consensus of expert opinion (Vukina, 2000; Foster, 2000a).
^Includes elasticity estimates for both broilers and chickens because studies vary between the two terms when
analyzing the markets for meat from chickens.
2.4.3.2 Cost-Share Assistance
For the 2001 Proposal, EPA presented1 the results of its economic impact analysis without
considering the potential offsetting effects of cost-share and technical assistance from various Federal,
State, and local farm conservation programs, due to uncertainties regarding who and how much cost
share and technical assistance farmers receive and whether this would actually offset estimated
compliance costs incurred by CAFOs. EPA's analysis to determine whether the regulation is
"economically achievable" also did not rely oh such assumptions as an offset to estimated compliance
costs as part of its regulatory analysis and therefore reflects the highest level of impacts projected.
EPA thoroughly examined this issue during the development of the proposed rulemakrng as
documented in Section 4.2 of the Proposal EA and in the rulemaking record (DCN 70130). Various State
and Federal programs, such as the Environmental Quality Incentives Program (EQIP) administered by
USDA, offer assistance to farmers for 6n-farm environmental improvements. For example, cost sharing
2-65
-------
for eligible producers under EQIP may cover up to 75 percent of the costs of certain conservation
practices, such as grassed waterways, filter strips, manure management facilities, capping of abandoned
wells, and other practices important to improving and maintaining the health of natural resources in the
area. 'Technical assistance is also available for formulating conservation plans. Previous regulatory
analyses by the land grant universities and USDA have included cost-share program dollars as an offset
to compliance costs associated with environmental regulation or at least consider available government
assistance as part of an overall assessment (see literature review, DCN 175100). Also, a 1995 regulatory
analysis of confined animal operations located in coastal zone areas, conducted by both USDA and EPA
assumed a maximum cost sharing amount of $3,500 per year in government cost-sharing (Heimlich and
Barnard, 1995; DPRA, 1995).
For reasons outlined in Section 4.2 of the Proposal EA (and detailed hi DCN 70130), EPA
decided not to consider cost share assistance as an offset to estimated compliance costs in determining
whether the regulation is "economically achievable." Reasons for this include the following: (formerly)
lower EQIP funding levels would be insufficient to cover all new applicants that might be affected by the
final regulations, (formerly) strict eligibility requirements would limit larger-sized operations from
participating in the program20 and limiting the types of practices covered, waiting lists to participate in
the program would be long and geographic priority areas were established, thus limiting access to some
producers, among other factors limiting participation.
EPA received several comments on the 2001 Proposal supporting the Agency's decision not to
consider include cost sharing to offset compliance costs faced by CAFOs (see, for example, DCN
201734, DCN 400158, DCN 400125, DCN 201717, DCN 400140, DCN 235769). EPA received few
comments on the 2001 Proposal that support this assumption.
The 2001 Notice discussed the possibility that EPA would consider such analyses for the final
regulations as part of its economic analysis (see: 66 FR 58585). The 2002 Notice presented additional
information and discusses options for incorporating cost sharing in EPA's analysis due to increased
appropriations and program changes broadening those eligible to participate in the program (67 FR
48106-48107). The 2002 Notice discusses new farm bill legislation passed by Congress in Spring 2002
that could significantly raise government expenditures for USDA conservation programs. Specifically,
total EQIP authorization for FY 2002-2007 is $5.8 billion, ranging from $400 million to $1.3 billion per
year over the period. The current authorized levels are about $200 million per year. The new legislation
targets 60 percent of available EQIP funds to livestock and poultry producers, including confinement and
grass-based systems (the latter accounting for about 70 percent of total livestock and poultry operations).
The new legislation also removed the previous eligibility requirements under EQIP that restricted
funding for certain structural practices to operations with fewer than 1,000 animal units (as measured by
USDA), replacing this with an overall payment limitation of $450,000 per producer over the authorized
life of the 2002 Farm Bill.
In response to the 2002 Notice, EPA received numerous comments recommending that the
Agency account for the availability of cost-share and technical assistance in its regulatory analysis as an
offset to estimated compliance costs as well as how producers might use these programs to help secure
loans for capital investment associated with regulatory compliance. These comments noted that the
debate surrounding these increased funding levels included a focus on assisting producers to comply with
20 Prior to new legislation passed in 2002, EQIP funds were not available to operations with more than
1,000 AU but only to operations with fewer than 1,000 AU (using USDA AU definitions). (See: DCN 70130).
2-66
-------
environmental regulations (House Committee on Agriculture, 2002).21 NRDC et al. (2002) also noted
that industry representative, in their lobbying messages, industry told Congress that producers would
need significant boosts in cost-share funds with no size restrictions on subsidy eligibility in order to
comply with EPA's new CAFO regulations.22 Despite these legislative changes, however, the majority of
comments received by EPA on the cost-share issue continue to oppose the use of cost share assumptions
as part of the analysis because of continued uncertainties about the availability and adequacy of funds, as
well as administrative changes being considered in USDA's conservation programs. See comments by
land grant universities (DCN 600046 and DCN 600038) and State governments and agriculture agencies
(eg., DCN 600057, DCN 201716, DCN 400165, DCN 400249, and DCN 600049-7).
EPA agrees that program changes and increased funding in EQIP and other USDA conservation
programs will benefit farmers and might offset compliance costs incurred by some facilities under the
CAFO regulations. However, EPA disagrees that these legislative and program changes can be readily
incorporated into EPA's regulatory analysis and will offset compliance costs at all regulated facilities.
EPA decided not to base its statutory analysis of "economic achievability" on assumptions of
cost sharing because of continued uncertainty about how to incorporate such assumptions into its
analysis. A number of uncertainties continue to constrain EPA's ability to simply incorporate cost share
assumptions into its economic analysis. Such factors include uncertainty about actual funding levels, the
share of program dollars allocated to confinement facilities (compared to all livestock and poultry
operations, including non-confinement and grazing operations), the share of program dollars allocated to
larger-sized operations (compared to smaller-sized operations), restrictions and eligibility requirements
on the types of waste management practices covered, and availability of USDA technical personnel to
implement the recent legislative changes in the near term. USDA is also considering administrative and
programmatic changes to its conservation programs, making it difficult to know how the program will
actually be implemented. For example, recent actions by USDA have sought to restrict cost share
assistance to 50 percent of the capital expenditure on funding levels exceeding $100,000 per facility.
Because EPA is unable to reasonably account for each of these factors and accurately incorporate
assumptions of cost sharing addressing the uncertainty surrounding these factors, EPA decide not to base
its statutory analysis of "economic achievability" on assumptions of cost sharing. EPA believes that the
uncertainty regarding actual funding levels and implementation of the recent Farm Bill make less
conservative assumptions more difficult to justify when economic achievability is assessed.
For these reasons, EPA continues to base its determination of whether the regulation is
"economically achievable" without relying on assumptions of cost share assistance as an offset to
estimated compliance costs. Because EPA recognizes that cost share assistance from Federal and State
farm conservation programs will likely lessen the economic impacts of the final regulations over time (in
conjunction with long-term market adjustment), however, the Agency now presents its analysis results
21 The Congressional record on the Farm Bill: "As legislation was developed to improve EQIP and
provide additional resources to it, Congress was specifically concerned about how the U.S. livestock industry would
meet the new Clean Water Act requirements on animal feeding operations" (Cong. Rec. at H1923, May 1,2001).
22See letter from National Cattlemen's Beef Association, National Chicken Council, National Milk
Producers Federation, National Pork Producers Council, National Turkey Federation, The Alliance of Western Milk
Producers, and United Egg Producers to U.S. Senators (NCBA et al., 2001); testimony by National Pork Producers
Council and National Cattlemen's Beef Association, Committee on Agriculture, Nutrition and Forestry, U.S. Senate
(NPPC, 2001a; NCBA, 2001a).
2-67
-------
both assuming some degree of cost share assistance and no cost share assistance (i.e., the highest level of
financial effects projected). EPA believes that the results of its analysis to determine "economic
achievability" is sufficiently conservative and depicts the highest level of potential effects. The results of
EPA's supplemental analysis assuming some degree of cost sharing is viewed as providing a realistic
probable alternative estimate of financial effects of the regulation among some operations. However,
because EPA's supplemental analysis does not consider the maximum cost-share assistance possible
(3450,000 per producer over the authorized life of the 2002 Farm Bill), this estimate should not be
regarded as the potential low bound estimate among all operations.
2.4.3.3 Value of Manure as Cost Offsets
During the development of the 2001 Proposal, EPA considered whether to assume that beneficial
uses of manure might offset incurred compliance costs as part of the Agency's economic analysis. This
analysis consists of two components: (1) the nutrient value of manure for use as a fertilizer substitute of
organic matter and (2) the potential income from manure or litter sales, particularly of relatively higher
value dry poultry litter. Research conducted by the land grant universities and USDA often provide for
some accounting of the benefits associated with efficient manure use (see a literature review conducted
by EPA at DCN 175100 in the rulemaking docket). However, because there is not an established market
for manure and the value of manure is uncertain or variable, EPA's determination of whether the
regulation is "economically achievable" does not rely on assumptions of manure sales as part of its
regulatory analysis and therefore reflects the highest level of impacts projected.
For both the proposal and final rule analysis, EPA's regulatory cost estimates take into account
the nutrient value of manure for use as a fertilizer substitute to meet the nutrient needs of crops raised by
the regulated CAFO. This analysis estimates the incremental cost of the land application requirements,
accounting for various baseline practices of what farmers are doing currently in the absence of
regulation. Because livestock and poultry operations currently use manure nutrients as a fertilizer source
on crops grown on-site as a baseline practice, this analysis incorporates assumptions of the nutrient value
of manure for use as a fertilizer substitute to meet the nutrient needs of crops raised by the regulated
CAFO. The general approach used by EPA to assess the nutrient value of manure is consistent with
approaches used by USDA (Kellogg et al., 2002; Kellogg et al., 2000). Information on EPA's approach
to assess the nutrient content of manure for use as a fertilizer substitute is available in Section 21 of the
rulemaking record and in the Development Documents and Cost Report (see: USEPA, 2002).
For the proposal, EPA also conducted a supplemental economic analysis that considered the
potential income that might accrue to regulated CAFOs should that operation be able to sell any
additional manure nutrients in excess of the nutrient needs of crops raised by the CAFO to other
agricultural businesses. This supplemental analysis presented the results of its economic impact analysis
both assuming no income from manure sales (i.e., the highest level of financial effects projected) and
income from sales of manure in excess of the crop needs at the CAFO. For this analysis, EPA did not
adjust or offset its estimated costs associated with managing, storing, hauling, processing, and
distributing excess manure nutrients off-site as part of this analysis. This analysis evaluated only the
income that might be generated from the sale of this excess manure based on the market value for
nitrogen, phosphates, and potassium in commercial fertilizer. Also, EPA conducted this analysis for the
poultry sectors only, because of the typically higher value of dry poultry manure and litter; e.g., in the
broiler sector, EPA's supplemental analysis shows that sales of dry poultry manure could offset up to 50
percent of the estimated compliance costs (see Section 6 of the Proposal EA). Although EPA does
2-68
-------
believe that the other livestock operations might also benefit from the sale of animal manure, the Agency
chose not to evaluate such a scenario because of inadequate market indicators for the wetter manures that
are common in the hog and dairy sectors and for dry manure collected at fed cattle operations. Because
there is not an established market for manure, however, EPA's determination of whether the proposed
regulation is "economically achievable" did not rely on assumptions of manure sales as part of its
analysis. Information on EPA's supplemental economic analysis of the potential income that might
accrue to regulated CAFOs should that operation be able to sell excess manure nutrients is available hi
Section 6 of the Proposal EA.
EPA received several comments that were generally opposed to EPA's consideration of the
nutrient value manure, particularly about the Agency's monetary assessment of manure's value for
consideration as an offset to estimated compliance costs of the rule. Few comments endorsed the concept
of assuming the collateral benefit of considering manure as an offset the cost of compliance with this
regulation. Following proposal, EPA further evaluated the potential income generated and/or cost
savings to an operation from the sale or use of manure by the CAFO as a fertilizer substitute. EPA's
2001 Notice discusses options to include an analysis based on the volume of manure nutrients estimated
for each representative CAFO model adjusted by the average value for these nutrients, according to, for
example, market value for nitrogen, phosphates, and potassium. The 2001 Notice solicited public
comment on these estimated values and data that EPA had considered for this analysis (see both 66 FR
58575 and 66 FR 58585), soliciting further comment on possible analytical approaches and assumptions.
EPA disagrees with comments that it should not consider the nutrient value of manure for use as
a fertilizer substitute as part of its analysis of the compliance costs associated with the regulations.
EPA's analysis estimates the incremental cost of the rule need by accounting for baseline practices based
on what farmers are doing currently in the absence of EPA's regulation. Because livestock and poultry
operations currently use manure nutrients as a fertilizer source on crops grown on-site as a baseline
practice, this analysis incorporates assumptions of the nutrient value of manure for use as a fertilizer
substitute to meet the nutrient needs of crops raised by the regulated CAFO. For this analysis, EPA
assumes that CAFOs use manure generated as a fertilizer substitute on cropland under the control of the
CAFO. This analysis fully considers all estimated costs associated with managing, storing, hauling,
processing, and distributing excess manure nutrients off-site, and does not assume that these costs are
offset by the nutrient value of the excess manure. Therefore, EPA disagrees with comments suggesting
that the Agency has not considered the increased cost of using manure due to added costs attributable to
the regulation. This analysis also accounts for the cost of additional fertilizer purchases, to the extent that
it is needed to supplement manure that may need to be applied at different rates as a result of this rule
(e.g., under a phosphorus standard, more commercial fertilizer may be needed to supply nitrogen needs to
crops).
EPA acknowledges concerns expressed in comments about the possibility that the methodology
used by the EPA for valuing manure nutrients might overstate the market value of manure. The approach
that EPA uses to approximate the nutrient value of manure—based on the value of commercial fertilizer
values of nitrogen, phosphorus, and potassium—is consistent with research conducted by USDA and
land grant universities. Other market data and approaches for approximating the nutrient content of
manure are not available and alternative data and approaches were not recommended to EPA during the
public comment period. Information was also not submitted to EPA substantiating claims that the
Agency has grossly overstated the nutrient value of manure for the purposes of its costing analysis. EPA
also received no information to support claims that some farmers can obtain spread manure at no cost
from other sources, and that therefore the CAFO's own supply of manure has zero value since it
2-69
-------
substitutes for a free input. Finally, EPA disagrees with comments that it has not appropriately
accounted for differences in the fertilizer value of manure based on the specific circumstances of each
farm; such differences are accounted for using a representative farm approach that closely approximates
the range of variability among farming operations. Use of such a representative farm approach to
approximate a range of farming conditions is consistent with and research conducted by USDA and the
land grant universities.
For more information on issues pertaining to the nutrient value of manure, see EPA's response to
comment CAFO400112-52. Also see the response to comment CAFO 201141-2 for a discussion of how
commercial fertilizer use is addressed by the nutrient management plan.
EPA agrees, however, with comments that caution against assuming that the nutrient value of
manure will provide a source of income that will offset compliance costs, particularly as part of the
Agency's analysis to assess regulatory impacts. Upon further review, EPA decided not to consider
income from manure sales as part of its analysis because of uncertainty associated with incorporating
such assumptions into the analysis. The main basis for this decision is the absence of established markets
and a cash market price for spreading manure. Manure markets are presently functional, but remain
largely under-developed and are not well established. In the absence of data under such market
conditions, the true market value for manure and manure nutrients is uncertain or variable. Other
marketing factors, such as distance from the source of manure to the application site and other site
specific conditions, regional markets conditions, manure products applied, life cycle of the feeding
operation in regards to the growing season, weather conditions, make such assumptions difficult to
measure. Because true market value for manure is unknown, EPA assumes commercial fertilizer values
(of nitrogen, phosphorus, and potassium) for approximating the nutrient value of manure. Although such
an approach is consistent with practices used by researchers at USDA and the land grant universities,
EPA recognizes that the value of manure might be misrepresented using this approach. In cases where
there might be little or no positive cash market price for spreading manure, this approach would overstate
its value. Use of this approach might also be inconsistent with the context in which manure is used; that
is, some CAFOs may spread manure as a means of disposal, with the optimal application rate being that
which satisfies crops needs at the lowest cost. Also, some operations may already be benefitting from
manure as a potential income source; therefore, this income may already be reflected in the baseline
financial data and any potential revenue from manure sales would not result in additional incremental
income to a regulated CAFO.
Although EPA disagrees with comments suggesting that it has not considered the increased cost
of using manure due to added costs associated with managing, storing, hauling, processing, and
distributing excess manure nutrients off-site to comply with the regulation, it agrees with
recommendations by USDA researchers that should EPA consider the revenue from the sale of manure as
part of the analysis, then it should also consider any additional incurred costs (e.g., payments to crop
growers to accept manure, in some cases). To date, EPA has not accounted for such additional costs.
EPA also acknowledges comments noting that because the rule will not result in an (incremental)
increase in the value of manure, it should not account for incremental offsetting costs.
Finally, EPA acknowledges concerns expressed by some commenters that the final rule might
negatively affect the market for manure and manure nutrients. These commenters believe that the
regulations will reduce or eliminate the inherent market value of manure by restricting the amount of
manure that can be applied on available land, thus reducing the demand for manure nutrients and creating
additional manure nutrient surpluses. These commenters claim that this might also increase the incentive
2-70
-------
for CAFOs to subsidize the use of such manure, thus further increasing the CAFO's disposal costs.
Many of these commenters claimed that such effects would be more pronounced under a phosphorus-
based standard than under a nitrogen-based standard. Given the possibility that the value of manure may
decline as a result of this rule, at least in the near term, EPA decided not to calculate the potential
benefits from manure sales using current available data and approaches to approximate the potential
market value of manure: Alternative market data and information to support an analysis assuming
additional income from the sale of excess manure are not available and were not recommended to EPA
during the public comment period. .
Because of the inherent difficulties of conducting such an analysis and because of the possibility
that the available data and analytical approaches might misrepresent the market value of manure
nutrients, EPA's analysis of the final rule does not consider the potential income generated from the sale
of manure as an offset to estimated compliance costs. Therefore, EPA continues to base its
determination of whether the regulation is "economically achievable" does not rely on assumptions of
manure sales as part of its regulatory analysis and therefore reflects the highest level of impacts
projected. Despite this limitation of EPA's analysis, the Agency believes that some operations will
benefit from the sale of excess manure and that the results of its analysis to determine "economic
achievability" is sufficiently conservative and depicts the highest level of potential effects.
2.5 METHODOLOGY TO ASSESS BROADER MARKET LEVEL EFFECTS
EPA's CAFO level analysis measures the economic effects on regulated facilities. As these
effects influence the decisions of farmers, processors, packers, and ultimately consumers, they translate
into changes in the price and quantity of farm commodities and retail foods and generate changes
throughout the national economy. To better understand the potential impacts, EPA conducts a market
level analysis. Section 2.5.1 provides an overview of EPA's market model and input-output model to
evaluate broader market level effects and it describes the input data and parameters for these models.
EPA did not receive comments that directly criticize the underlying data and modeling
framework used to conduct this analysis. However, comments were submitted that question the
appropriateness of EPA's modeling results, focusing on effects to regulated CAFOs and also regions and
local communities. Section 2.5.2 discusses EPA's response to these comments. For more information
see response to comments DCN CAFO 201438-186, DCN CAFO 400120-20, and DCN CAFO 201352-
101 available in the Comment Response Document.
2.5.1 Market Model Methodology and Input Data
EPA's market analysis evaluates the effects of the final regulations on national markets based on
the estimated total annual industry compliance costs (presented in Section 3.5 of this report). EPA's
market model analysis predicts the effects of the final regulations on national markets in terms of the
broader market changes that might result due to compliance with requirements. This analysis examines
changes throughout the economy as impacts are absorbed at various stages of the food marketing chain.
The analysis is intended as a long-run analysis to show impacts of the regulation's on society, including
effects on price and quantity. Other market changes examined by EPA include changes in regional
employment and changes in U.S. livestock and poultry trade (imports and exports). This analysis uses
national level production and employment impacts to approximate potential regional impacts at the
community level effects.
2-71
-------
The analysis uses a linear partial equilibrium model adapted from the COSTBEN model
developed by the USDA's Economic Research Service (Hahn, 1996a, 1996b). The modified EPA model
provides a means to conduct a long-run static analysis to measure the market effects of the final
regulations in terms of predicted changes in farm and retail prices and product quantities. Appendix B of
the Proposal EA provides a more detailed discussion of the market model's structure and operation. The
market model assesses the estimated direct impacts associated with complying with the CAFO
regulations, measured in terms of dollars of industry output per year. This approach allows EPA to
compute market level changes in terms of changes in consumer and farm level prices for the selected
products and changes in the amount of commodities produced and traded internationally (expressed as
changes in U.S. product exports and imports).
Once the changes in output (price times quantity) are estimated using EPA's market model, EPA
evaluates these changes using input-output multipliers to estimate the ripple effects as changes hi one
industry pass through its suppliers and the rest of the economy. Input-output analysis uses multipliers
that forecast how much more or less output the whole economy would produce as a result of each dollar
increase or decrease in spending by a given industry. For this analysis, EPA uses multipliers from the
Regional Input-Output Modeling System, version 2 (RIMS II) (USDC, 1997, 1996) to estimate the
impact on the national economy of changes in the animal products industry. Multiplying the original
change by the multiplier gives a measure of the total direct effects (on immediate suppliers), indirect
effects (on the suppliers' suppliers and all other industries), and induced effects (on households'
spending and labor decisions). These estimates might be driven by an original change in final demand,
output, earnings, or employment and yield results in terms of final demand, output, earniags, tax revenue,
or employment changes. Estimated effects include changes in national employment (measured in terms
of full-time equivalents) and changes in economic output (measured in terms of changes in Gross
Domestic Product).
The data EPA collected to conduct this analysis span a wide range of primary and secondary data
sources from USDA, the U.S. Department of Commerce's Bureau of Labor Statistics (BLS), various land
grant universities, industry, and other sources, as documented in the Proposal EA. EPA uses 1997 as the
base year, which is consistent with the engineering cost estimates that reflect 1997 conditions. The input
data EPA uses for this analysis are presented in Tables 2-10 and 2-11 of this report. Detailed citations
for each base year value appear in Section 4.4 and Appendix B of the Proposal EA (USEPA, 200 la).
The Proposal EA provides additional detail on this approach, explaining EPA's justification for the
approach as well as the theoretical concepts underlying the analysis.
Market data used as inputs to this model are from a wide range of USDA data and land grant
university research. In keeping with the focus of this market analysis, the supply and demand elasticities
used are long-run elasticities, rather than short-run elasticities. Short-run elasticities are not considered
appropriate for this analysis (see response to comments DCN CAFO 400120-20 in the EPA's Comment
Response Document). The approach used for EPA's market level analysis is discussed in greater detail
in Section 4.4 of the Proposal EA (USEPA, 2001a). Section 4.4.1 of the Proposal EA presents an
overview of the model and Section 4.4.2 presents the data sources used for the analysis.
In general, EPA also considered whether the final regulations could have community-level and/or
regional impacts, e.g., if they substantially alter the competitive position of livestock and poultry
production across the nation, or lead to growth or reduction in farm production (hi- or out-migration) in
different regions and communities. Ongoing structural and technological change in these industries has
2-72
-------
influenced where farmers operate and has contributed to locational shifts between traditional production
regions and the emergent, nontraditional regions. Production is growing rapidly in these regions because
of competitive pressures from more specialized producers who face lower per-unit costs of production.
This is especially true in hog and dairy production (El-Osta and Johnson, 1998; McBride, 1997; Iowa
State University, 1998; Martinez, 1999). EPA believes that the regulations would not have a
disproportionate effect on regions and communities.
The general market model framework EPA uses does provides a means to evaluate regional and
community level effects. To do this, EPA distributes national employment estimates on a regional basis
using state level production data for larger-sized livestock and poultry operations for each sector. The
data EPA uses to allocate national employment impacts in the agriculture sectors are from the 1997
Census (USDA/NASS, 1999a) with imputed values to correct for omitted values (Westat, 2000),
supplemented with other state level data from USDA (USDA/NASS, 1998b). The approach EPA used
approximates changes in regional employment by disaggregating the national employment reductions
(both direct and indirect) to indicate regions where impacts of the final regulations are most likely to
occur. For each animal sector, EPA distributes the national direct employment impacts at the CAFO and
processor/wholesale level onto a regional basis using state level data that reflect livestock and poultry
production by the largest facilities in each state. These data include the 1997 Census (USDA/NASS,
1999a) and other USDA data (USDA/NASS, 1998b), with imputed values for omitted USDA data
(Westat, 2000). EPA allocates total national indirect and induced employment changes onto a regional
basis according to each state's share of 1997 total U.S. population as reported for 1997 from U.S. Census
data (U.S. Census Bureau, 1999). The direct and indirect/induced results are summed to calculate the
total impact for each state. EPA evaluates regional impacts from these state level estimates, aggregated
to USDA's farm production regions, as shown hi Figure 2-1 of the Proposal EA.
The available approach discussed in this EA and the best available data for EPA to evaluate these
concerns, however, are not sufficient to more precisely assess community or regional impacts.
Nevertheless, EPA concludes from its broader-based analysis that regional and community level
effects are estimated to be modest, but do tend to be concentrated within the more traditional agricultural
regions. EPA does not expect that this rule will have a significant impact on where animals are raised.
On one hand, on-site improvements hi waste management and disposal, as required by the final rule,
could accelerate recent shifts hi production to more nontraditional regions as higher-cost producers in
some regions exit the market to avoid the relatively high retrofitting costs associated with bringing
existing facilities into compliance. On the other hand, the final regulations might favor more traditional
production systems where operators grow both livestock and crops, since these operations tend to have
available cropland for land application of manure nutrients. These types of operations tend to be more
diverse and less specialized and, generally, smaller hi size. Long-standing farm services and input supply
industries hi these areas could likewise benefit from the final rule, given the need to support on-site
improvements in manure management and disposal. Local and regional governments, as well as other
nonagricultural enterprises, would also benefit.
r
2.5.2 Public Comments on EPA's Market Analysis
EPA received public comments on its market model approach that question the appropriateness
of EPA's market model. These comments focus mostly on the implications of the Agency's assessment
of the potential effects to regulated CAFOs and also the broader effects of the regulations on regional
markets (especially local communities and agricultural support industries). For more information, see
2-73
-------
response to comments DCN CAFO 201438-186, DCN CAFO 400120-20, and DCN CAFO 201352-101
available in the Comment response Document.
Most commenters recognize the distinctions between prices as observed by individual farms and
prices at the aggregate level and generally concurr with EPA that over the long run, prices and quantities
will adjust to a post-regulatory equilibrium (see, for example, NMPF, 2001; FAPRI, 2001a; National
Center, 2002). However, these commenters expressed concern about short-run impacts. (Short-run
impacts on farms are assessed using the approach described in Section 2.3, which details the Agency's
approach for determining economic achievability; see Section 3.3.) Some commenters recommended
that EPA consider using a more complicated modeling approach (NMPF, 2001), such as that used by
FAPRT in its parallel analysis conducted of the proposed CAFO regulations. Other commenters noted
that EPA's model does not capture supply and demand shifts that might occur among species (e.g.,
NMPF, 2001a).
Another commenter requested that EPA perform a detailed assessment of impacts on individual
communities and regions (National Center, 2002—DCN 400159). This commenter recommended that
EPA further analyze and report results by geographic location based on the number of CAFO enterprises
and their respective volumes of animal production that are expected to experience financial stress as a
result of the final regulations. This commenter also pointed to FAPRI's analysis that indicates that
financial stress would be clustered in some regions rather than spread uniformly across the country. The
commenter recommended that EPA more closely evaluate the quantity of income, employment, and tax
base lost on those farms that are determined to go out of business to calculate the multiplier effects in the
surrounding community. See response to comment regarding EPA's analysis of the effects of the
regulation on regional or community level effects (DCN CAFO400159-26).
EPA disagrees that using an alternative modeling approach is preferable to the model EPA's
uses. Alternative modeling approaches—such as that used by FAPRI—do not produce results that are
radically different from EPA results, as confirmed by FAPRI itself (see: DCN 235619). Although EPA
uses a static model, rather than a dynamic model, this model was developed and used by USDA to
evaluate the effects of changes in policy on the U.S. economy. This model is readily available and
usable, provided at no charge by USDA, and is available in EPA's record for full public review and
comment. FAPRI's model is proprietary and access to its use is restricted; also, FAPRI has not provided
EPA the opportunity to submit their model for public review and comment in order to meet the Agency's
administrative requirements for public notice. Finally, use of USDA's standing model has the added
benefit of being simpler to operate, whereas FAPRI's model consists of a large scale econometric model
of both U.S. and world agriculture containing roughly 5,000 behavioral equations and identities. See also
response to comment DCN CAFO201352-136-4 regarding recommendations to use data and modeling
techniques similar to FAPRI.
EPA believes that comments expressing concerns about the inability of EPA model to account
for interspecies shifts in supply and demand (e.g., shifts in demand between products that might be
considered close substitutes, such as beef and pork) are overstated. EPA readily acknowledged that its
market model is not able to account for interspecies shifts hi supply and demand in Section 2 and
Appendix C of the Proposal EA. EPA decided not to account for inter-species shifts among different
sectors in order to avoid making large-scale changes to USDA's COSTBEN-type framework. As a
result, EPA's analysis may not fully capture cases where price or production costs changes hi one sector
may cause a shift in production from one commodity to another. However, EPA does not believe that
such effects, though probable, are likely to be significant and substantially alter EPA's analysis of these
2-74
-------
regulated sectors. Given the overall modest effects predicted for these final regulations (presented in
Section 3 of the Final EA) such shifts would likely be very minimal. First, available USDA estimates of
the cross-price elasticity of demand for these products tend to be small, even for close substitutes such as
beef and pork (see DCN 70336), such that a change in the price of beef will have a relatively small
impact on the demand for pork. Second, because EPA is regulating each of these sectors more or less
equally, such that changes in production costs within one sector should not cause producers to shift from
one sector to another. Also, because cross-price elasticities tend to be of similar magnitude across these
food commodities, the net effect in shifts in demand between species will likely be minimal. Finally, ,
because Americans are among the largest consumers of meat, dairy, and poultry products in the world,
EPA believes that the strength and size of the U.S. market will cause markets to adjust over time and act
to offset higher (short-term) costs. There have been ongoing changes in consumer demand trends,
however, that are independent from EPA's regulation. For example, hi the past few decades there has
been a steady shift hi the demand from the consumption of red meat to poultry products, and also shifts
away from the demand for other products, such as eggs and some types of dairy foods. Accounting for
these other factors affecting overall consumer demand—independent of the effects of EPA's
regulation—are difficult to predict. The effects of the international demand for these products are, also
uncertain, given a wide range of market factors (e.g., relative prices and exchange rate effects, acceptance
of U.S. foods abroad due to growing reluctance to U.S. hormone use and genetically modified foods,
existing international trade restrictions, etc.).
In response to comments expressing concern over the time frame of the elasticity measure that
were used to analyze market level effects, EPA disagrees with the comments that EPA should use short-
run elasticities rather than long-run elasticities for EPA's market level analysis. EPA's market model is
intended as a long-run analysis to assess potential changes hi overall supply and demand conditions from
EPA's regulations within the affected markets, including changes hi prices and produced and traded
quantities, as well as other market changes. Use of long-run elasticities are more appropriate to estimate
market equilibrium effects on the U.S. economy. In the nearer term, the regulations should have little
effect on prices and quantities. EPA believes that comments concerned about the short-run effects on
regulated CAFOs and are more appropriately directed at EPA's CAFO level analysis. By contrast,
EPA's market level analysis is intended to assess the market equilibrium effects and other effects on the
economy as an additional aspect of the Agency's regulatory impact analysis.
EPA also disagrees that use of long-run elasticities distort EPA's cost estimates for this rule. For
this rule, EPA calculates total costs by aggregating facility-level compliance costs estimated across all
regulated CAFOs (which are then expressed on an annualized basis). These total costs are based on
estimated engineering costs for select representative facilities (comprised of roughly individual 1,600
cost models). Elasticity measures and other market level parameters are not directly factored hi this
calculation. Also, EPA estimates of total social costs are calculated in terms of pre-tax costs and include
broader social costs of the rule. Based on the results of EPA's but also FAPRI's market level analysis,
the broader impact of these regulations of national markets are expected to be modest. These results
indicate that any additional costs that might be incurred given changes hi market conditions, but that are
not directly accounted for by EPA's approach, are likely relatively small. Given that the majority of
confinement operations (more than 90 percent of all animal feeding operations or AFOs) will not be
directly affected by EPA's regulations, EPA believes that any eventual changes hi market conditions
resulting in higher prices over time might benefit non-regulated AFOs and also regulated CAFOs. See
response to comment DCN CAFO 400120-20.
2-75
-------
Regarding the Agency's analysis of the regional effects of the regulation, EPA disagrees with
comments stating that this analysis does not adequately account for broad differential effects among the
animal production regions. EPA acknowledges the merits of comments noting that the size of an
operation that goes out of business—based on the number of animals raised at an operation and the
resultant change in industry production—is relevant to an assessment of the effects of this regulation on
communities and regions (see, for example, comment DCN 400159). However, the available data and
the limitations of EPA modeling approach restrict the types of analyses the Agency is able to conduct
Instead, EPA's national level framework uses a representative farm approach to depict baseline financial
conditions at representative model CAFOs and to extrapolate CAFO level impacts to all operations
nationwide. This approach is not able to precisely measure changes in animal production in conjunction
with model facilities that are predicted to close within a specific geographic location. Although EPA's
approach may not appropriate tc evaluate the potential effects at an individual affected CAFO or specific
effects within a particular production region or farming community, such a broad-based approach is often
consistent with other national level policy analyses conducted by researchers at USD A, the land grant
universities, and industry analysts.
EPA believes that its analysis meets the Agency's obligation to perform a reasonable analysis
with the best data EPA can obtain. A more in-depth and detailed study of these effects on individual
communities and regions is not feasible given limited available data and information. Data necessary for
a more detailed study would require a census or full survey of these industries, stratified by geographic
location, indicating a full range of characteristics specific to an operation's production system, including
financial status. This is the type of information that EPA gathers in its Section 308 survey. This
information, along with an engineering assessment of what would be required under alternative
regulatory options, would provide the basis to assess regional changes in income and employment
(building its analysis from the bottom-up rather than using a top-down approach used by EPA). Because
EPA did not undertake a Section 308 survey,23 data were not available to implement such an approach for
this rulemaking. The type of study this commenter recommends, however, is even more detailed and
would require additional data, requiring that data be collected from all farming operations within a
community—both regulated and non-regulated—as well as businesses and other institutions that might
be affiliated with those farms. More focused analyses are sometimes conducted by academia to examine
very narrowly-defined policy effects within a particular community or U.S. county; these analyses
require a more detailed framework and the use of specific data collected from actual businesses in that
community, including other farming and non-farming operations in that community. EPA typically does
not conduct analyses conducted at this level of detail in developing national level regulations. Data and
information were not available to support the more detailed analysis suggested by some commenters.
EPA believes that the analysis it conducted using the best data available adequately informed the
Agency's decision-making process for this rule. For more information see response to comment DCN
CAFO400159-26.
23 See discussion in the preamble to the 2001 Proposal at 66 FR 3079.
2-76
-------
Table 2-10. Market Model Baseline Values (1997)
Variable
Beef"'
Dairy b/
Hog
Broiler tf
Turkey "
Layer*
Farm Products
Price
Quantity Produced
Quantity Exported
Quantity Imported
$66.09/cwt
40,893
thous. head
282
thous. head
2,046
thous. head
$13.38/cwt
156,100
mil. Ibs
0
0
$54.30/cwt
91,960
thous. head
55
thous. head
.3,178
thous. head
370/lb
-
-
-
400/lb
-
-
—
700/doz.
6,473
mil. doz.
895
mil. doz.
0
Retail Products
Price
Quantity
Demanded
Quantity Exported
Quantity Imported
$2.80/lb
25,824
mil. Ibs
2,136
mil. Ibs
2,343
mil. Ibs
145.5
156,100
mil. Ibs
5,244
mil. Ibs
4,383
mil. Ibs
$2.45/lb
17,274
mil. Ibs
1,044
mil. Ibs.
633
mil. Ibs
1510/lb
27,551
mil. Ibs
5,048
• mil. Ibs
5
mil. Ibs
1050/lb
5,412
mil. Ibs
598
mil. Ibs
0
106e7doz.
5,578
mil. doz.
228
mil. doz.
7
mil. doz.
Elasticities
Demand Elasticity
Supply Elasticity
-0.621
1.020
-0.247
1.527
-0.728
0.628
-0.372
0.200
-0.535
0.200
-0.110
0.942
Sources: See USEPA, 200la.
^Includes veal and heifer.
b/ Consumer Price Index for Dairy Products as a composite good. Output is on a milk equivalent, total solids basis.
"^Includes various forms of chicken meat, such as broilers and mixed poultry meat. Because of coordination
between the broiler feeding and processing sectors, it is not possible to determine prices per animal at the farm level.
The chicken and turkey markets are modeled in terms of pounds of production.
*Eggs (million dozen). Layer "exports" represent the number of eggs diverted to hatcheries (assumed as fixed).
2-77
-------
Table 2-11. RIMS II Multipliers for Secondary Impact Analysis
Sector Name
Total Output
Total Employment
Own Industry
Employment"'
Farm Products
Poultry and Eggs
Meat Animals
Hogs
Cattle Feeding
Dairy Farm Products
2.8217
2.1692
-
-
2.3215
26.3665
20.8698
-
-
23.5130
12.1043
10.2072
~
-
11.5267
Food and Kindred Products'1'
Meat Packing Plants
Meat/Egg Processing
Poultry Processing
Fluid Milk Processing
Dairy Processing
2.4755
-
2.1822
2.3968
-
18.2332
-
18.0150
16.3311
-
3.3511
-
6.1750
2.6981
~
Other
Construction
Households
3.0851
2.1642
32.4816
23.8483
10.9000
0.2823
Sources: SeeUSDC, 1997,1996.
'•'Employment multipliers adjusted for inflation to 1997 values based on CPI-U.
^Processing sector multipliers adjusted to eliminate CAFO level impacts.
2-78
-------
SECTION THREE
TOTAL COSTS AND FINANCIAL EFFECTS
OF THE FINAL CAFO REGULATIONS
This section presents the national level aggregate compliance costs and economic impacts on
regulated facilities under the final CAFO regulations. Section 3.1 describes the regulated sectors and
presents EPA's estimates of the number of affected facilities. Section 3.2 presents EPA's estimates of
the expected pre-tax costs (2001 dollars) to industry as a result of the final CAFO regulations for both the
NPDES and ELG revisions. (Section 5 of this report presents additional costs of the final regulations to
Federal and State permitting authorities.) Section 3.3 and 3.4 present the results of EPA's analysis that
evaluates the financial effects on CAFOs with more than 1,000 AU under the effluent guideline
regulations. Section 3.3 examines the impact on existing facilities of complying with the final ELG
requirements for Best Available Technologies Economically Achievable (BATEA); Section 3.4 examines
the impact to new facilities on complying with the final ELG requirements for New Source Performance
Standards (NSPS). Finally, Section 3.5 presents the results of EPA's market level analysis, focusing on
the potential secondary impacts of the final NPDES and ELG regulations on both consumer and farm
level prices and quantities, as well as changes in employment and economic output at the national level.
3.1 IDENTIFICATION AND NUMBER OF AFFECTED CAFOs
3.1.1 Identification of Affected Industry Sectors
3.1.1.1 BeefSubcategory
Cattle feedlots are identified under NAICS 112112 (SIC 0211, beef cattle feedlots) andNAICS
112111, beef cattle ranching and farming (SIC 0212, beef cattle, except feedlots). This sector comprises
establishments primarily engaged in feeding cattle and calves for fattening, including beef cattle feedlots
and feed yards (except stockyards for transportation).
The beef cattle industry can be divided into four separate producer segments:
• Feedlot operations fatten or "finish" feeder cattle before slaughter and constitute the final
phase of fed cattle production. Calves usually begin the finishing stage after reaching 6
months of age or reaching at least 400 pounds. Cattle are typically held for 150 to 180
days and weigh 1,150 to 1,250 pounds (for steers) or 1,050 to 1,150 pounds (for heifers) at
slaughter.
• Veal operations raise male dairy calves for slaughter. The majority of calves are "special
fed" or raised on a low-fiber diet until about 16 to 20 weeks of age, when they weigh about
450 pounds.
• Stacker or backgrounding operations coordinate the flow of animals from breeding
operations to feedlots by feeding calves after weaning and before they enter a feedlot.
Calves are kept 60 days to 6 months or until they reach a weight of about 400 pounds.
3-1
-------
• Cow-calf producers typically maintain a herd of mature cows, some replacement heifers,
and a few bulls, and they breed and raise calves to prepare them for fattening at a feedlot.
Calves typically reach maturity on pasture and hay and are usually sold at weaning. Cow-
calf operators may also retain the calves and continue to raise them on pasture until they
reach 600 to 800 pounds and are ready for the feedlot.
APOs in this sector that might be affected by the final regulations include facilities that confine
animals. More information on the types of facilities hi this sector that might be covered by the final
regulations is provided in the Development Document (USEPA, 2002) and the rulemaking record.
3.1.1.2 Dairy Subcategory
Operations that produce milk are identified under NAICS 11212, dairy cattle and milk
production (SIC 0241, dairy farms). A dairy operation may have several types of animal groups present,
including the following:
• Calves (0 to 5 months)
• Heifers (6 to 24 months)
• Lactating dairy cows (currently producing milk)
• Cows close to calving and dry cows (not currently producing milk)
• Bulls
AFOs in this sector that might be affected by the final regulations include facilities that confine
animals. More information on the types of facilities in this sector that might be covered by the final
regulations is provided in the Development Document (USEPA, 2002) and the rulemaking record.
3.1.1.3 Hog Subcategory
Hog operations that raise or feed hogs and pigs either independently or on a contract basis are
identified under NAICS 11221, hog and pig farming (SIC 0213, hogs). Hog operations may be
categorized by six facility types based on the life stage of the animal in which they specialize:
« Farrow-to-wean operations that breed pigs and ship 10- to 15-pound pigs to nursery
operations.
• Farrowing-nursery operations that breed pigs and ship 40- to 60-pound "feeder" pigs to
growing-finishing operations.
• Nursery operations that manage weaned pigs (more than 10 to 15 pounds) and ship 40- to
60-pound "feeder" pigs to growing-finishing operations.
» Growing-finishing or feeder-to-finish operations that handle 40- to 60-pound pigs and
"finish" them to market weights of about 255 pounds.
3-2 ,
-------
• Farraw-to<-fmish operations that handle all stages of production from breeding through
finishing.
• Wean-to-finish operations that handle all stages of production, except breeding, from
weaning (10- to 15-pound pigs) through finishing.
AFOs in this sector that might be affected by the final regulations include facilities that confine
animals. More information on the types of facilities in this sector that might be covered by the final
regulations is provided in the Development Document (USEPA, 2002) and the rulemaking record.
3.1.1.4 Poultry Subcategory
Poultry operations can be classified into three individual sectors based on the type of commodity
in which they specialize. These sectors include operations that breed and/or raise the following:
• Broilers or young meat chickens that are raised to a live weight of 4 to 4.5 pounds and
other meat-type chickens, including roasters that are raised to 8 to 9 pounds.
Classification: NAICS 11232, broilers and other meat-type chickens (SIC 0251, broiler,
fryer, and roaster chickens).
» Turkeys and turkey hens, including whole turkey hens that range from 8 to 15 pounds at
slaughter, depending on market, and also turkey "canners and cut-ups" that range from 22
to 40 pounds. Classification: NAICS 11233, turkey production (SIC 0253, turkey and
turkey eggs).
• Hens that lay shell eggs, including eggs that are sold for human consumption and eggs that
are produced for hatching purposes. Classification: NAICS 11231, Chicken egg
production (SIC 0252, chicken eggs), and NAICS 11234, poultry hatcheries (SIC 0254,
poultry hatcheries).
AFOs in this sector that might be affected by the final regulations include facilities that confine
animals. More information on the types of facilities in this sector that might be-covered by the final
regulations is provided in the Development Document (USEPA, 2002) and the rulemaking record.
3.1.2 Estimated Number of AFOs and Regulated CAFOs
USDA reports that there were 1.1 million livestock and poultry farms in the United States in
1997 (USDA/NASS, 1999a). This number includes both confinement and non-confinement (grazing and
rangefed) production, as well as both commercial and noncommercial operations. As shown in Table 3-
1, USDA reports that about 240,000 operations raise animals in confinement (Kellogg, 2002). USDA
estimates the number of operations with confined animals by focusing on those operations that meet
certain minimum characteristics based on USDA assumptions in terms of the number of animals at an
operation. This approach does not specifically focus on characteristics that meet the regulatory definition
of an animal feeding operation, as codified at 40 CFR Part 122, according to the number of days animals
are confined or the amount of vegetative cover at the production area. As stated hi the 2001 Notice, EPA
believes this is a reasonable approach to estimate the potential number of confinement operations, given
best available data and other limited information.
3-3
-------
To estimate the number of AFOs and "potential" CAFOs, USDA first defines "farms with
confined livestock types" to be farms with 4 or more animal units of any combination of fattened cattle,
milk cows, swine, chickens or turkeys (Kellogg, 2002). In USDA's analysis, the use of animal units is
based on the USDA definitions of 1,000 pounds of liveweight and not EPA's regulatory definitions,
which are expressed in terms of the number of animals on-site (codified in 40 CFR Part 122). USDA
estimates of the number of "potential" CAFOs is based on EPA's regulatory definitions used for the
proposed regulations. As defined for the proposed CAFO regulations, one animal unit (AU) is equivalent
to one slaughter or feeder cattle, calf or heifer; 0.7 mature dairy cattle; 2.5 hogs (over 55 pounds) or 5
nursery pigs; 55 turkeys; 30 egg-laying chickens (where a wet manure management system is used), and
100 broilers and egg-laying chickens, regardless of the animal waste system used. (Note that the final
regulation instead defines one AU as equivalent to 125 broilers and 82 egg-laying chickens; see the final
rule preamble). The primary source of data for USDA's estimate is the 1997 Census of Agriculture
(Census). More information on these data is provided in Kellogg (2002) and the 2001 Notice (66 FR
58556).
Table 3-1 shows EPA's estimates of the number of operations that would be defined as CAFOs
under the final regulation (based on USDA's estimates). Size groups shown break out facilities by broad
AU size groups (>1,000 AU and increments among operations with between 300 AU and 1,000 AU).23
The data reflected in this table are adjusted from USDA's original estimates to account for layer facilities
(800 operations) with wet manure management systems that have a different AU scale and that were not
accounted for in USDA estimates of potential CAFOs. EPA's estimates also differ because other poultry
sector data are assessed using a different AU scale—1,000 AU equals 125,000 broilers and 82,000 egg
laying chickens—where a dry manure management system is used. EPA estimates further breakouts of
the number of egg operations by the type of manure management systems, as well as among hog
operations, by whether these are farrow-finish and farrowing operations (grouped under FF) or grow-
finish (GF) operations. More information on EPA's estimates is provided in the Development Document
(USEPA, 2002) and the rulemaking record.
As shown in Table 3-1, EPA estimates that there were about 10,500 operations that confine more
than 1,000 AU in 1997, accounting for about 5 percent of all confinement operations. Total operations
with between 300 and 1,000 AU are estimated at about 33,100 operations (Table 3-1). Table 5-2 in
Section 5 of this report shows EPA's estimate of the number of CAFOs by State and EPA region.
To assess the number of operations with between 300 and 1,000 AU that are defined as CAFOs
under the existing NPDES permit requirements, EPA uses available data to determine the share of all
operations in this size group that are affected by the final regulations. EPA uses data and information
from USDA, State extension service experts, and agricultural professionals to derive percentage
estimates of the number of operations in each sector that meet the conditions of the existing rule for
being defined as a CAFO. Table 3-2 shows the resultant number of operations with 300 to 1,000 AU that
EPA expects will be defined as CAFOs based on the existing NPDES regulations (labeled in the table as
"Status Quo"). More detailed information on EPA's estimates is in the NPDES Support Document
available hi the rulemaking record (USEPA, 2002n).
23As defined for the final CAFO regulations, one animal unit (AU) is equivalent to one slaughter or feeder
cattle, calf or heifer; 0.7 mature dairy cattle; 2.5 hogs (over 55 pounds) or 5 nursery pigs; 55 turkeys; 30 egg-laying
chickens (where a wet manure management system is used), and 125 broilers and 82 egg-laying chickens, regardless
of the animal waste system used.
3-4
-------
Table 3-1. Number of AFOs and Potential CAFOs (1997)
Sector
Cattle
Heifers
Veal
Dairy
Hogs
Hogs-FFb/
Hogs-GF "'
Chickens
Broilers
Layers: dry b/
Layers: wet b/
Turkeys
Other Cattle"
Total CAFOs
Total
AFOs
Total Operations by Size Group
>1,000 AU *
300-1,000 AU
(Number of Operations)
17,796
3,843
168
94,787
51,772
24,221
17,776
6,445
3,309
39,634
237,821*
1,766
242
12
1,450
3,924
1,939
1,985
2,744
1,632
729
383
388
0
10,526
2,682
724
57
5,780
9,901
6,112
3,789
12,372
10,402
1,170
800
1,615
0
33,131
Source: Derived by EPA from USDA estimates (Kellogg, 2002). Rounded to nearest tenth. AFO totals include
operations that raise more than a single animal type. Potential CAFOs adjusted for mixed operations. See
Development Document (USEPA, 2002) for more detailed information.
17 As defined for the final CAFO regulations, one AU is equivalent to: one slaughter or feeder cattle, calf or heifer;
0.7 mature dairy cattle; 2.5 hogs (over 55 pounds) or 5 nursery pigs; 55 turkeys; 30 egg-laying chickens (where a
wet manure management system is used), and 125 broilers and 82 egg-laying chickens (with a dry waste system).
^Estimated by EPA to break out among production system types (farrowing and farrow-finish [FF] and grow-fmish
[OF], and laying operations with wet and dry manure management systems).
3/Cattle other than fattened cattle or milk cows.
47 USDA's estimate of the total number of AFOs is adjusted for specialty cases. Specialty cases (estimated at 2,291
operations) are dairies that went out of business in 1997, swine operations with feeder pigs only, and egg-hatching
operations. USDA estimates of the total number of potential CAFOs adjusts for double counting of operations with
animal populations in one or more sectors that qualify as potential CAFOs.
Table 3-3 shows estimates of the number of facilities that EPA expects will be designated as
CAFOs by the permitting authority because they are significant contributors to water quality impairment.
EPA does not anticipate that many AFOs with fewer than 1,000 AU will be designated by the permitting
authority and subject to the final requirements. EPA is aware of very few AFOs that have been
designated as CAFOs in the past 20 years. Based on available USDA analyses that measure excessive
nutrient application on cropland in some production areas and other farm level data by sector, facility
size, and region, EPA estimates that designation might add 172 operations, expressed over the term of a
5-year permit period nationwide (or, on average, about 35 operations each year). More information on
EPA's estimates is available in the rulemaking record (USEPA, 2002n).
3-5
-------
Table 3-2. Number of Potential Operations Defined as CAFOs (1997)
Sector
Cattle
Heifers
Veal
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
TVitnl OAKOs
Total Operations Defined as CAFOs
>1,000 AU
300-1,000 AU
(number of operations)
1,766
242
12
1,450
3,924
1,632
729
383
388
10526
174
230
7
1,949
1,485
520
26
24
37
4.452
Source: EPA's Development Document (USEPA, 2002) and NPDES Support Document (USEPA, 2002n). See
notes Table 3-1.
Table 3-3. Number of Potential Operations Designated as CAFOs (1997-2001)
Sector/Size Category
Cattle
Veal
Heifers
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
Total
Operations with
Operations with
(number of operations)
15
o •
3
30
52
52
2
8
10
172
13
0
3
28
50
50
1
7
8
160
2
0
0
2
2
2
1
1
2
12
Source: EPA's Development Document (USEPA, 2002) and NPDES Support Document (USEPA, 2002n). See
notes Table 3-1. Estimates are shown projected over a 5-year period.
3-6
-------
3.2 ESTIMATED ANNUAL COSTS OF THE FINAL CAFO REGULATIONS
This section presents EPA's estimates of the compliance costs to regulated CAFOs for a range of
technology options considered by the Agency during the development of these regulations. (Section 5 of
this report presents costs of the final regulations to Federal and State permitting authorities.)
This EA presents the results of two technology options where EPA has estimated the cost of land
application based on nitrogen-based application rates only (Option 1) and also the cost of land
application based on nitrogen-based application rates, except in those instances where EPA believes that
phosphorus-based rates are likely to be appropriate (Option 2). The final rule specifies that the
determination of application rates is to be based on the technical standards established by the Director
and EPA expects that these standards will require phosphorus-based application, where appropriate. The
rule also provides for these standards to include appropriate flexibilities in the use of phosphorus-based
rates, such as multi-year phosphorus application, but the potential costs savings resulting from these
flexibilities are not reflected in the analysis. As a result, the cost and economic impacts of this rule may
have been overestimated. ,
EPA evaluated the costs of these technology options for all operations defined as CAFOs with
more than 1,000 AU and for those operations that are defined as CAFOs with between 300 and 1,000
AU. EPA calculates these costs using the data and approaches described hi the Development Document
(USEPA, 2002) and in Section 2 of this report. For the purpose of estimating total regulatory costs of the
final CAFO regulations, EPA assumes that the individual per-CAFO costs to comply with the effluent
guideline regulations are similar to the costs that will be incurred by operations with between 300 and
1,000 AU to comply with the revised NPDES requirements (although these smaller-sized operations will
be subject to BPJ and not the ELG requirements). These cost estimates, therefore, may further be
overstated for this size category.
3.2.1 Compliance Costs to CAFOs Under the Final Regulations
Table 3-4 summarizes the total annualized compliance costs to CAFOs. Results are shown as a
range of estimates between Option 1 and Option 2. The table shows these costs broken out by sector and
by broad facility size category. As shown in the table, EPA estimates the total estimated costs to CAFOs
range from $141 million (Option 1) to $326'miUion annually (Option 2), expressed as pre-tax, 2001
dollars. Most of this cost (roughly 50 percent) is incurred by the dairy sector, with another roughly 30
percent incurred within the cattle sectors (including beef, veal, and heifer sectors).
Of this total, EPA estimates that the cost to operations with more than 1,000 AU ranges from
$119 million (Option 1) to $283 million annually (Option 2). Total estimated costs to facilities defined
as CAFOs with between 300 and 1,000 AU ranges from $19 million (Option 1) to $39 million annually
(Option 2). EPA estimates that of the total cost to operations that may be designated as CAFOs ranges
from about $3 million to $4 million annually^ depending on the regulatory option.
These aggregated cost estimates reflect pre-tax costs. However, EPA's model calculates both
pre-tax and post-tax costs (see Section 2.2.4). The post-tax costs reflect the fact that a CAFO would be
able to depreciate or expense these costs, thus generating a tax savings. Post-tax costs thus are the actual
costs the CAFO would face. Pre-tax costs reflect the estimated total social cost of the proposed
regulations, including lost tax revenue to governments. Pre-tax dollars are used when comparing
3-7
-------
estimated costs to monetized benefits that are estimated to accrue under the final regulations (see Section
5). All costs presented in this section are expressed in terms of pre-tax dollars and do not account for
annual tax savings to CAFOs. However, post-tax costs are also used to evaluate impacts on regulated
facilities using a discounted cash flow analysis, as presented in Section 3.3.
Estimated compliance costs are initially evaluated hi 1997 dollars and then adjusted to 2001
dollars using Engineering News Record's Construction Cost Index (CCI) (ENR, 2002).24 The base year
for this analysis is 1997, corresponding with available data from USDA's 1997 Agriculture Census.
Estimated compliance costs presented in the Development Document are estimated in 1997 dollars
(USEPA, 2002).
Table 3-4. Annual Pre-tax Cost of the Rule, $2001 (Option 1 & Option 2)
Sector
Number of Operations
CAFOs
>1,000 AU
CAFOs
300-1,000 AU
(number)
Aggregate Incremental Costs
Total
CAFOs
>1,000 AU
CAFOs
300-1,000 AU
Designated
CAFOs
($2001, millions, pre-tax)
ELG Option 1
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
1,766
12
242
1,450
3,924
1,632
729
383
388
10,526
174
230
7
1,949
1,485
520
26
24
37
4,452
$19.2
<$0.1
$3.5
$71.5
$8.6
$18.5
$6.6
$6.4
$6.3
$140.6
$17.8
<$0.1
$1.3
$59.7
$6.4
$15.3
$6.3
$6.4
$5.9
$119.1
$1.1
<$0.1
$2.1
$11.3
$2.1
$2.1
$0.1
$0.0
$0.2
$19.0
$0.3
$0.0
$0.1
$0.5
$0.1
$1.1
$0.2
<$0.1
$0.2
$2.5
ELG Option 2
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
1,766
12
242
1,450
3,924
1,632
729
' 383
388
10,526
174
230
7
1,949
1,485
520
26
24
37
4,452
$88.2
$0.0
$6.3
$151.1
$34.8
$20.5
$7.5
$8.9
$8.7
$326.0
$85.8
<$0.1
$3.8
$128.2
$24.9
$16.8
$7.2
$8.4
$8.1
$283.2
$1.9
<$0.1
$2.4
$22.0
$9.5
$2.4
$0.1
$0.5
• $0.3
$39.1
$0.5
$0.0
$0.1
$0.9
$0.4
$1.3
$0.2
<$0.1
$0.3
$3.8
May not add due to rounding. Number of operations do not include designated facilities. See notes Table 3-1.
24 Adjustment factor = (2001 CCI)/(1997 CCI) = 6342/5825 = 1.0888
3-8
-------
3.2.2 Comparison with the Proposed Regulations
For the 2001 Proposal, EPA considered various alternative regulatory options, which are
summarized in Table 1-2 in Section 1 of this report. The proposed CAFO regulations noted that EPA's
"preferred BAT option" at the time of proposal required nitrogen-based and, where necessary,
phosphorus-based land application controls at all livestock and poultry CAFOs (Option 2), along with the
additional requirement that all cattle and dairy operations (except veal) must conduct ground water
monitoring and implement controls if the ground water beneath the production area has a direct
hydrologic connection to surface water (Option 3), and with the additional requirement that all hog, veal,
and poultry CAFOs achieve zero discharge from the animal production area with no exception for storm
events (Option 5). During the Agency's Option Selection process for the final regulations, EPA
evaluated these and other options. The results of this analysis are presented in this section; see also
USEPA, 20021 (DCN 375086) hi the rulemaking record.25 This comparison presents the results for five
technology options (see also Table 1-2): .
• Option 1 would require land application at the CAFO to be consistent with proper
agricultural practices, including limiting manure application to the nitrogen needs of the
crops grown
• Option 2 would require land application at the CAFO to be consistent with proper
agricultural practices, including lirniting manure application to the nitrogen needs of the
crops grown, or where necessary, to the phosphorus needs of the crops
• Option 3 would add to Option 2 by requiring the operation to perform ground water
monitoring and controls, unless it can show that the ground water beneath manure storage
areas or stockpiles does not have a direct hydrologic connection to surface water
• Option 5 that would add to Option 2 by establishing a zero discharge requirement from the
production area that does not allow for an overflow under any circumstances
• Option 7 that would add to Option 2 by prohibiting manure application to frozen, snow-
covered or saturated ground.
Compared to the proposed requirements, EPA is promulgating a less costly regulatory option and is
limiting the scope of the final revised regulations. See Section 4 of the final preamble for more details.
Table 3-5 summarizes the total annualized (pre-tax) costs of the alternative technology options
for each of the ELG technology options that EPA considered in developing the final CAFO regulations.
This comparison does not include estimated costs for designated facilities. As shown in the table, among
operations with more than 1,000 AU, the total estimated costs across these options range from about
$119 million and $640 million per year (pre-tax, 2001 dollars), not including the potential costs to
designated CAFO facilities. Note that estimated costs for Option 3 and Option 7 are calculated using a
previous set of engineering costs XApril 4, 2002 ) and also assume an alternative AU thresholds for
broiler and egg-laying operations (where 1,000 AU would equal 100,000 broiler and egg-laying operation
with dry manure systems). Also, EPA did not estimate costs or financial impacts within the cattle and
25 Costs for Option 3 and Option 7 are calculated using April 4,2002 engineering costs and alternative AU
thresholds for the broiler and egg-laying sector.
3-9
-------
dairy sectors tinder Option 5 because the Agency does not consider housing of large animals under this
option to be practicable in these sectors.
More cost information is provided in Tables 3-6(a) and 3-6(b). Table 3-6(a) shows estimated
compliance costs on a per-animal (inventory) basis. Table 3-6(b) compares estimated per-animal costs
to average operating costs for model CAFOs. Ranges are expressed across rninimum and maximum
values. Refer also to Appendix B and Appendix D for more detailed cost information.
Table 3-5. Pre-tax ELG Option Costs, by Sector and Size Group ($2001)
Sector
#CAFOs
Option 1
Option 2
Option 3
Option 5
Option 7
All Defined CAFOs >300 AU
Beef
Veal
Heifer
Dairy
Hog
Broiler
Layer
Turkey
Total
1,939
20
472
3,398
5,409
2,152
1,162
425
14,977
$19.0
<$0.1
$3.3
$71.0
$8.6
$17.4
$12.7
$6.1
$138.2
$87.7
<$0.1
$6.2
$150.2
$34.6
$19.2
$16.2
$8.4
$322.6
$87.7
<$0.1
$8.3
$203.5
$148.6
$53.2
$30.9
$12.9
$545.3
N/A
N/A
N/A
N/A
$144.1
$31.7
$17.3
$8.4
$201.5
$63.9
<$0.1
$7.7
$555.4
$75.3
• $43.2
$19.8
$10.2
$775.5
All Defined CAFOs >1,000 AU
Beef
Veal
Heifer
Dairy
Hog
Broiler
Layer
Turkey
Total
1,766
12
242
1,450
3,924
2,945
960
388
10,526
$17.8
$0.0
$1.3
$59.7
$6.4
$15.3
$12.7
$5.9
$119.1
$85.8
<$0.1
$3.8
$128.2
$24.9
$16.8
$15.6
$8.1
$283.3
$83.1
<$0.1
$4.9
$152.9
$132.3
$47.8
$29.3
$12.5
$462.8
N/A
N/A
N/A
N/A
$114.5
$28.2
$16.6
$8.1
$167.4
$60.0
<$0.1
$4.9
$442.6
$64.6
$39.7
$18.5
$9.9
$640.2
All Defined CAFOs 300-1000 AU
Beef
Veal
Heifer
Dairy
Hog
Broiler
Layer
Turkey
Total
173
8
230
1,948
1,485
520
50
37
4,451
$1.1
<$0.1
$2.1
$11.3
$2.1,
$2.1
$0.1
$0.2
$19.0
$1.9
<$0.1
$2.4
$22.0
$9.5
$2.4
$0.6
$0.3
$39.1
$4.6
<$0.1
$3.4
$50.6
$16.3
$5.4
$1.6
$0.4
$82.5
N/A
N/A
N/A
N/A
$29.6
$3.4
$0.7
$0.3
$34.0
$3.9
<$0.1
$2.8
$112.8
$10.7
$3.5
$1.4
$0.3
J135.3
Source: USEPA. Costs for Option 3 and Option 7 are calculated using April 4,2002 engineering costs and assume
an alternative AU thresholds for broiler and egg-laying operations; see also USEPA, 20021—DON 375086), N/A =
"not applicable" since EPA does not consider housing of large animals in some sectors to be practicable.
3-10
-------
Table 3-6a. Per Head ELG Option Costs (Minimum and Maximum), by Sector and Size Group ($1997).
Sector/
Size Group
Option 1
Min
Max
Option 2
Min
Max
Option 3
Min
Max
Option 5
Min
Max
Option 7
Min
Max
Beef
>1000 AU
300-1000AU
$0.1
$3.4
. $51.1
$54.6
$2.2
$7.4
$49.6
$69.3
$0.8
$5.3
$61.2
$108.2
N/A
N/A
•, N/A
N/A
$0.8
$5.9
$135.5
$117.0
Veal
>1000 AU
300-1000AU
$1.3
$1.3
' $1.7
$4.5
$1.3
$1.3
$1.7
$4.5
$2.2
$1.7
$3.2
$8.7
N/A
N/A
N/A
;N/A
$1.3
$1.3
$1.8
$4.9
Heifer
>1000 AU
300-1000AU
$0.9
$3.0
$17.1
$72.6
$3.4
$6.7
$50.3
$65.4
$1.7
$4.8
$63.4
$107.5
N/A
N/A
N/A
N/A
$2.5
$5.7
$124.8
$155.4
)airy
>1000 AU
300-1000AU
$0.6
$2.8
$92.7
$149.3
$3.2
$6.2
$144.0
$205.2
$3.2
$8.9
$281.0
$532.7
N/A
N/A
N/A
N/A
$46,3
$54.8
$1,018
$1,261
Hog: GF
>1000 AU
300-1000AU
$0.0
$0.4
$0.7
$2.3
$0.0
$0.7
$6.2
$6.9
$0.1
$5.4
$9.4
$18.8
$0.1
$0.5
$11.2
$14.2
$0.1
$1.6
$6.6
$12.7
Hog: FF
>1000 AU
300-1000AU
$0.0
$0.4
$0.7
$2.4
$0.0
$0.7
$6.2
$6.9
$0.1
$5,3
$9.4
$18.8
$0.1
$0.5
$11.1
$14.2
$0.1
$1.5
$9.0
$12.7
Broilers
>1000 AU
300-1000AU
$0.01
$0.01
$0.12
$0.14
$0.01
$0.01
$0.17
$0.21
$0.03
$0.05
$0.21
$0.38
$0.01
$0.01
$0.17
$0.21
$0.02
$0.04
$0.17
$0.29
Layer Wet
>1000 AU
300-1000AU
$0.01
$0.04
$0.38
$0.09
$0.01
$0.04
$0.35
$0.19
$0.15
$0.37
$0.49
$1.03
$0.01
$0.42
$0.35
$0.71
$0.02
$0.10
$0.30
$0.43
Layer Dry
>1000 AU
300-1000AU
$0.01
$0.02
$0.06
$0.12
$0.01
$0.02
$0.12
$0.18
$0.01
$0.04
$0.19
$0.38
$0.01
$0.02
$0.12
$0.18
$0.01
$0.03
$0.18
$0.25
Turkeys
>1000 AU
300-1000AU
$0.03
$0.04
$0.21
$0.25
$0.03
$0.04
$0.32
$0.48
$0.00
$0.10
$0.46
$0.85
$0.03
$0.04
$0.32
$0.48
$0.06
$0.09
$0.37
$0.57
Source: USEPA. Costs for Option 3 and Option 7 are calculated using April 4,2002 engineering costs and assume
an alternative AU thresholds for broiler and egg-laying operations; see also USEPA, 20021—DCN 375086). N/A =
"not applicable" since EPA does not consider housing of large animals in some sectors to be practicable.
3-11
-------
Table 3-6b. Costs as a Share of Model CAFO Total Operating Costs (Minimum and Maximum), ($1997).
Sector/
Size Group
Option 1
Min
Max
Option 2
Min
Max
Option 3
Min
Max
Option 5
Min
Max
Option 7
Min
Max
Beef
>1000AU
300-1000AU
0.0%
0.4%
11.1%
6.0%
0.5%
0.8%
10.8%
7.6%
0.2%
0.6%
13.3%
11.9%
N/A
N/A
N/A
N/A
0.2%
0.7%
29.4%
12.8%
Veal
>1000AU
300-10GOAU
0.1%
0.1%
0.2%
0.5%
0.1%
0.1%
0.2%
0.5%
0.2%
0.2%
0.4%
1.0%
N/A
N/A
N/A
N/A
0.1%
0.1%
0.2%
0.5%
Heifer
>1000AU
300-1000AU
0.2%
0.3%
3.7%
8.0%
0.7%
0.7%
10.9%
7.2%
0.4%
0.5%
13.8%
11.8%
N/A
N/A
N/A
N/A
0.5%
0.6%
27.1%
17.0%
Dairy . .
>1000AU
300-1000AU
0.0%
0.2%
4.7%
7.8%
0.2%
0.3%
7.3%
12.0%
0.2%
0.5%
14.2%
31.2%
N/A
N/A
N/A
N/A
2.3%
2.9%
51.2%
66.2%
Hog: GF
>1000 AU
300-1000AU
0.0%
0.2%
3.5%
1.2%
0.0%
0.4%
30.9%
3.6%
0.1%
2.8%
47.0%
9.8%
0.1%
0.2%
55.9%
7.4%
0.1%
0.8%
33.0%
6.6%
Hog: FF
>1000AU
300-1000AU
0.0%
0.3%
0.6%
1.7%
0.0%
0.5%
5.5%
4.9%
0.1%
3.8%
8.4%
13.3%
0.1%
0.3%
9.9%
10.0%
0.1%
1.1%
8.0%
9.0%
Jroilers
>1000 AU
300-1000AU
1.1%
1.8%
25.6%
22.2%
1.1%
1.8%
36.1%
32.7%
5.5%
7.5%
46.6%
59.2%
1.8%
1.1%
32.7%
36.1%
5.1%
6.5%
39.0%
42.6%
Layer Wet
>1000AU
300-1000AU
0.1%
0.2%
2.3%
0.5%
0.1%
0.2%
2.1%
1.1%
0.9%
2.2%
2.9%
6.2%
0.1%
2.5%
2.1%
4.2%
0.1%
0.6%
1.8%
2.6%
Layer Dry
>1000 AU
300-1000AU
0.1%
0.2%
' 0.4%
0.5%
0.1%
0.2%
2.1%
1.1%
0.1%
0.2%
1.1%
2.3%
0.1%
0.1%
0.7%
147°
0.1%
0.2%
1.1%
1.5%
Turkeys
>1000 AU
300-1000AU
0.2%
0.6%
1.2%
3.5%
0.2%
0.6%
1.9%
6.7°/c
0.0%
1.4%
2.7%
11.8%
0.2%
0.6%
1.9%
6.7%
0.3%
1.3%
2.1%
7.9%
Source: USEPA. Costs for Option 3 and Option 7 are calculated using April 4,2002 engineering costs and assume
an alternative AU thresholds for broiler and egg-laying operations; see also USEPA, 20021—DCN 375086). N/A =
"not applicable" since EPA does not consider housing of large animals in some sectors to be practicable.
3-12
-------
3.3 ESTIMATED FINANCIAL EFFECTS ON EXISTING OPERATIONS (BAT ANALYSIS)
Following a brief review of the baseline financial conditions depicted in EPA's model CAFOs
(Section 3.3.1), this section presents the financial effects of the regulations on CAFOs with more than
1,000 AU (Section 3.3.2). These results focus on two principal technology options (Option 1 and Option
2), as was done for estimated compliance costs in Section 3.2. Sections 3.3.3 and 3.3.4 show these
results under alternative assumptions, including alternative cash flow calculations (Section 3.3.3) and
estimates of CAFO closures under alternative assumptions of long-run market adjustment and cost-share
assistance (Section 3.3.4). Section 3.3.5 provides additional information regarding other alternative
regulatory options considered by the Agency during the development of the rule.
33.1 Baseline Financial Health of Model CAFOs
Based on financial data presented in Section 2 (see Tables 2-2 and 2-3), all representative model
CAFOs, regardless of sector or size or production region, are considered to be financially healthy in the
baseline before the impacts of the final regulations are considered. Using these data, all model CAFOs
currently are estimated to have positive discounted cash flow and debt-to-asset ratios below the
established benchmark value for this rule (depending on sector).26 Post-regulatory impacts are measured
against this baseline. EPA considers that negative cash flow or debt-to-asset ratios greater than the
benchmark value in the impact analysis can be attributed to the compliance costs associated with the
regulatory options considered.
3.3.2 Financial Effects on CAFOs under the Final Regulations
This section examines the impact on existing CAFOs with more than 1,000 AU to comply with
the final ELG requirements for Best Available Technologies Economically Achievable (BATEA).
Table 3-7 presents the results of EPA's analysis of the estimated CAFO level financial effects in
terms of the number of operations that will experience affordable, moderate, or stress impact due to the
regulations. Results are shown both for Option 1 and Option 2. Results are shown by sector for
operations with more than 1,000 AU only because these are the operations that would be subject to the
ELG regulations. Operations with fewer than 1,000 AU would be instead subject to the BPJ of the
permitting authority. Section 3.3.5 shows the results of alternative regulatory options assuming that
operations with fewer than 1,000 AU would be subject to the ELG, which EPA considered in the 2001
Proposal. - . .
For Option 1, the analysis indicates that, among all CAFOs with more than 1,000 AU in the veal,
heifer, dairy, hog, turkey, and egg-laying sectors, the impacts due to this rule can be characterized as
"Affordable" or "Moderate." Therefore, EPA considers this option to be economically achievable for
existing facilities hi these animal sectors. EPA estimates that a total of 15 existing CAFOs (less than
Ipercent of all CAFOs with more than 1,000 AU) would experience financial stress and might be
26As discussed in Section 2, EPA did adjust the available hog enterprise level data from USDA. Among
the various reasons for this adjustment were concerns about how to assess impacts for this sector given that the
reported data are unanalyzable in this framework (because of consistently negative cash flow calculations).
3-13
-------
vulnerable to closure. By sector, EPA estimates that 12 beef operations (1 percent of affected beef
CAFOs) and 3 broiler operations (less than 1 percent of affected broiler CAFOs) might close as a result
of complying with the final regulations.
For Option 2, the analysis indicates that, among all CAFOs with more than 1,000 AU in the veal,
dairy, turkey, and egg-laying sectors, the impacts due to this rule can be characterized as "Affordable" or
"Moderate." Therefore, EPA considers this option to be economically achievable for existing facilities
in these animal sectors. (Moderate impacts might be incurred by operations in some sectors, but these
impacts are not considered to result in facility closure.) In the beef cattle, heifer, hog, and broiler sectors,
however, EPA's analysis indicates that the final rule would cause some existing CAFOs to experience
financial stress, making these operations vulnerable to facility closure. Across all sectors, EPA estimates
that 285 existing CAFOs (about 4 percent of all all CAFOs with more than 1,000 AU) would experience
financial stress and might be vulnerable to closure. By sector, EPA estimates that 49 beef operations (3
percent of affected beef CAFOs), 22 heifer operations (9 percent), 204 hog operations (5 percent), and 10
broiler operations (1 percent) might close as a result of complying with the final regulations.
These estimates of the number of potential CAFO closures are cumulative and reflect the results
of both the farm level analysis and the enterprise level analysis. These estimated closure rates are
generally consistent with the findings of economic achievability of previous effluent guidelines for other
industrial point source categories. Based on the results of this analysis, EPA concludes that both Option
1 and Option 2 would be considered economically achievable for existing CAFOs.
These results are based on an analysis that does not consider the longer term effects on market
adjustment and also available cost-share assistance from Federal and State farm conservation programs.
EPA believes that such adjustments could lessen the economic impacts of the final regulations over time.
Sections 3.3.5 show the results of this analysis under assumptions of long-run market adjustment and
cost-share assistance.
As already discussed in Section 3.2, this report presents the results of two technology options
where EPA has estimated the cost of land application based on nitrogen-based application rates only
(Option 1) and also the cost of land application based on nitrogen-based application rates, except in those
instances where EPA believes that phosphorus-based rates are likely to be appropriate (Option 2). Given
that the final rule provides for appropriate flexibilities in the use of phosphorus-based rates, such as
multi-year phosphorus application, EPA has not accounted for the potential costs savings resulting from
these flexibilities in its analysis. As a result, the economic impacts presented here may be overestimated.
Also, for the purpose of this analysis, EPA assumes that small business CAFOs with between 300 and
1,000 AU would incur costs similar to those estimated for CAFOs with more than 1,000 AU (although
these smaller-sized operations will be subject to BPJ and not the ELG requirements under the revised
NPDES requirements). These upper end cost estimates could, therefore, overstate the financial effects
for this size category.
3.3.3 Sensitivity Analysis Under Alternative Cash Flow Calculations
This section presents the results of a separate sensitivity analysis where EPA calculates
alternative cash flows based on the use of other accounting data as a proxy for capital replacement
(discussed in more detail in Section 2.3.3).
3-14
-------
Table 3-7. Financial Effects of the ELG on CAFOs (>1,000 AU), Option 1 and Option 2
Sector
ELG Option 1
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
ELG Option 2
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
Number
CAFOs
(>1,OOOAU)
1,766
12
242
', 1,450
3,924
1,632
729
383
388
10,526
Affordable
Moderate
Stress
(Number)
1,754
12
242
1,232
3,924
1,334
729
383
388
9,998
1,766
12
242
1,450
3,924
1,632
729
383
388
10,526
1,717
12
220
1,019
3,249
1,032
729
383
' 388
8,749
0
0
0
218
0
294
0
0
0
512
0
0
0
431
470
590
0
0
0
1,491
12
0
0
0
0
3
0
0
0
15
Affordable
Moderate
Stress
(Percent of Total Operations)
99%
100%
100%
85%
100%
82%
100%
100%
100%
95%
49
0
22
0
204
10
0
0
0
285
97%
100%
91%
70%
83%
63%
100%
100%
100%
83%
0%
0%
0%
15%
0%
18%
0%
0%
0%
5%
0%
0%
0%
30%
12%
36%
0%
0%
0%'
14%
1%
0%
0%
0%
0%
0%
0%
0%
0%
0%
3%
0%
9%
0%
5%
1%
0%
0%
0%
3%
Source: USEPA. May not add due to rounding.
EPA's cash flow analysis uses net cash income estimates and does not consider noncash income
and expenses. To address the question of whether EPA may have understated impacts because its
discounted cash flow analysis does not include any allowance for depreciation or replacement of capital
in its definition of cash flow, the Agency has conducted further sensitivity analysis using reported
3-15
-------
accounting depreciation as a proxy for capital replacement to calculate alternative cash flow values for
EPA's financial analysis.
For the purposes of this sensitivity analysis, EPA examines the sensitivity of the results of
economic impact analysis under an alternative scenario where capital expenditures are set equal to
accounting depreciation. These results are contrasted to results in EPA's main analysis, where capital
replacement is not reflected as part of the Agency's cash flow calculation. This analysis is conducted at
the farm level. Table 2-2 reflect reported depreciation amounts corresponding to financial data obtained
for each model CAFO. These sources of financial data do not report estimated capital replacement.
Table 3-8 shows the results of this analysis. Based on this analysis, EPA has determined that the
results of the economic impact analysis are not sensitive to the alternate assumptions regarding cash
flow. The results of this analysis show that the number of estimated CAFO closures would not be
substantially different if allowances for replacement of capital are made. Table 3-9 shows that under
these alternative assumptions, the number of potential facility closures rises only slightly from 285
potential closures to 287 closures.
EPA recognizes that cash outlays for capital replacement and additions are required for a firm to
remain in business and should be reflected in the cash flows used to assess economic impacts. However,
EPA does not conclude from this analysis that accounting depreciation provides a reliable proxy for these
continuing capital expenditures. Reported depreciation is a periodic accounting charge for capital assets
acquired in the past, and it may be either larger or smaller than annual future capital expenditures for
several reasons. Depreciation is based on historical cost, which might not equal the replacement cost of
capital assets. Also, reported depreciation is based on various accounting and tax reporting conventions
that might bear little resemblance to the actual economic life and consumption of capital assets. Finally,
a firm's capital outlay decisions are influenced by the quality of its investment opportunities, the
financial health of the enterprise, and general business conditions, which vary over time.
oMo i_fi Financial F.ffprfc nn CAFOs: Chanees to Cash Flow Calculations (Option 2)
Sector
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
of
CAFOs
1,766
12
242
1,450
3,924
1,632
729
383
388
10 526
Affordable
Moderate
Stress
Zero Depreciation
Affordable
Moderate
Stress
100% Depreciation
(Number of Affected Operations)
1,717
12
220
1,019
3,249
1,032
729
383
388
8749
0
0
0
431
470
590
0
0
0
1,491
49
0
22
0
204
10
0
0
0
285
1,715
12
220
1,019
3,249
1,032
729
383
388
8,747
0
0
0
431
470
590
0
0
0
1,491
51
0
22
0
204
10
0
0
0
287
Source: USEPA. May not add due to rounding. See Table 2-8 for definitions: affordable, moderate, and stress.
3-16
-------
3.3.4 Supplemental Analyses
Results presented in Section 3.3.1 do not consider the longer term effects on market adjustment
and also available cost-share assistance from Federal and State farm conservation programs. EPA
believes that such adjustments could lessen the economic impacts of the final regulations over time. To
evaluate potential financial effects under such conditions, EPA has conducted further supplemental
analysis to assess potential effects under two different scenarios. One scenario takes into consideration
the effects of long-run market adjustment following implementation of the final regulations. This
analysis is conducted using simulated changes in producer revenue given changes in market prices as
depicted by EPA's market model, which uses estimates of price and quantity response in these markets.
A second scenario takes into consideration potential cost-share assistance under Federal and State
conservation programs, assuming that a portion of costs are covered by cost sharing subject to
programmatic constraints. Given the uncertainty of whether CAFO income will rise in response to long-
run market adjustment or whether available cost share dollars will effectively offset compliance costs at
regulated CAFOs, EPA's analysis to determine whether the regulation is "economically achievable" does
not rely on such assumptions as part of its regulatory analysis and therefore reflects the highest level of
impacts projected. However, EPA presents the results of this analysis assuming both some degree of cost
passthrough and no cost passthrough, as well as some degree of cost share assistance and no cost share
assistance, along with the results of its lead analysis. Section 2.4.3 presents an overview of how EPA
conducts these analyses and also discusses the Agency's decision not to incorporate such scenarios as
part of its determination of economic achievability.
3.3.4.1 Market Impacts on Facility Income
For the purpose of this analysis, EPA examines regulatory impacts on producers in the livestock
and poultry sectors under the assumption that they will experience increased revenues due to long-run
market adjustment and resultant higher market prices. This analysis is conducted only for the beef,
heifer, hog, and broiler sectors because these are the sectors where EPA's analysis shows there might be
facility closures (under assumptions of no cost passthrough). Table 3-10 shows that, under assumptions
of long-run market adjustment the number of potential facility closures is reduced from 210 closures
(assuming no cost passthrough) to 1 closure in the beef sector (assuming partial cost passthrough).
In this analysis, EPA examines regulatory impacts on producers in the beef, heifer, and broiler
sectors under the assumption that they will experience increased revenues due to the impact of the rule
on market price. This revenue increase occurs because the effluent guideline increases production costs,
shifting the supply curve for the market upward. Market price must then rise in the long run to ensure
adequate supply; otherwise, producers will exit the market. The increase in unit price caused by the
effluent guideline is illustrated hi Figure C-l in Appendix C of this report, where the shift in the supply
curve is shown to equal to annualized compliance costs per unit sold (CC/Q) and the increase in market
price is measured as (P1 - P°).
In general, the magnitude of the price increase resulting from the revised regulations is largely
determined by the price elasticities of supply and demand specified for the market model. Once the
market model is specified, EPA can estimate the ratio of the change in price to the per unit compliance
costs incurred: (P1 - P°)/(CC/Q). In the beef and heifer sector, EPA found this ratio to be equal to 70.7
percent; in the broiler sector this ratio is equal to 68.7 percent. This means if the regulations cause
farmers to incur compliance costs of $1.00 per head of cattle, for example, the resulting decrease in cattle
supply causes the market price to increase by about $0.71 per head (see Section 2.4.3 for details).
3-17
-------
Conceptually, applying this impact of the ELG on facility revenues to the DCF analysis is
straightforward. In its DCF analysis, EPA (1) calculates the post-regulatory cash flow for each year of
project life by subtracting operating expenses and compliance costs from operating revenues, (2)
discounts the result according to project year, and then (3) sums the stream of post-regulatory discounted
cash flows over the entire life of the project. Thus, for each year of the project's life, EPA calculates (in
simplified form) post-regulatory cash flow as equal to market price multiplied by the number of units
sold by the facility (facility revenues) minus operating costs and compliance costs. As a conservative
estimate, EPA first performs its DCF analysis assuming that equilibrium market price is unchanged by
the rule (i.e., market price is P° in Figure C-l). In this analysis, EPA adjusts facility revenues to reflect
the increase in market price resulting from the ELG (market price is P' in Figure C-l in Appendix C).
See Appendix C of this report for more information.
Table 3-9 shows the results of the supplemental analysis assuming facility revenues reflect the
increase in market price resulting from the final regulations. Only the fed cattle, heifer, hog, and broiler
sectors are analyzed because CAFOs with more than 1,000 AU in the other sectors would be able to
absorb costs associated with the final rule. As the table shows, the compliance costs would be affordable
for virtually all CAFOs in these sectors. Only one beef operation would experience financial stress. All
other operations in these sectors would be able to absorb the estimated compliance costs under an
assumption that market prices would increase hi response to regulatory revisions.
Table 3-9. Financial Effects to CAFOs: Partial Cost Passthrough (Option!)
Sector
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Wet
Layers - Dry
Turkeys
Total
Number
of
CAFOs
1,766
12
242
1,450
3,924
1,632
383
729
388
10,526
Affordable
Moderate
Stress
Zero Cost Passthrough
Affordable
Moderate
Stress
Partial Cost Passthrough
(Number of Affected Operations)
1,717
12
220
1,019
3,249
1,032
729
383
388
8,749
0
0
0
431
470
. 590
0
0
0
1,491
49
0
22
0
204
10
0
0
0
285
1,765
ND
242
ND
3,720
1,632
ND
ND
ND
7,359
0
ND
0
ND
204
0
ND
ND
ND
204
1
ND
0
ND
0
0
ND
ND
ND
1
Source: USEPA. May not add due to rounding. See Table 2-8 for definitions: attordable, moderate, and stress.
3-18
-------
3.3.4.2 Cost-Share Assistance
For the purpose of this analysis, EPA examines regulatory impacts on producers in the livestock
and poultry sectors assuming that some portion of the compliance costs will be incurred by Federal
and/or State cost-share assistance. This analysis is conducted only for the beef, heifer, hog, and broiler
sectors because these are the sectors where EPA's analysis shows there are potential facility closures
(under assumptions of no cost sharing). Although other sectors may also receive cost share assistance,
EPA has not modeled the effect of cost-share assistance on these types of operations because no stress
impacts are measured in these sectors.
For this analysis, EPA assumes that 50 percent of the capital costs of compliance hi these sectors
would be covered by cost-share assistance. EPA reduced the capital cost of compliance by>.50 percent for
each of the representative model CAFOs and ran the same economic model as that used for the main
analysis, with all other assumptions held constant.
Under an assumption that 50 percent of the capital costs are covered by cost-share assistance,
EPA's analysis would assume that total cost sharing for operations with more than 1,000 AU in these
four sectors would amount to roughly $20 million annually (1997 dollars). The majority of operations
(about 90 percent) would receive less than $ 10,000 each per year, with a smaller share of operations
receiving up to $30,000 each per year in the cattle and broiler sectors. Assuming changes under the 2002
Farm Bill legislation are implemented and there are resulting changes to USDA's farm conservation
programs, EPA believes that these are reasonable assumptions for the purposes of conducting a
sensitivity analysis.
Table 3-10 shows that, under assumptions of partial cost share assistance (assumed for this
analysis to cover 50 percent of the capital expenditure to comply with the revised regulations), the
number of potential facility closures is reduced only somewhat from 285 closures to 261 closures
(assuming partial cost share assistance). These estimated closures are comprised of 43 beef, 11 heifer,
204 hog, and 3 broiler operations. Among the reasons why these closure results indicate little change
assuming cost-share assistance is that EPA's approach applies cost-sharing to estimated capital costs
only, whereas the bulk of incurred compliance costs are likely to be annual operating and maintenance
costs associated with the land application requirements of the rule, including nutrient management and
off-site hauling of excess manure.
3.3.5 Comparison with the Proposed Regulations
EPA considered various alternative regulatory options during the development of this
rulemaking. For the Agency's Option Selection process for the final regulations, EPA evaluated these
and other options. This section presents the results of these analyses.
Table 3-11 shows the results of EPA's analysis of these alternative options in terms of the
number of operations estimated to experience financial stress under these options and that would be
vulnerable to facility closure. These results are based on an analysis that does not consider the longer-
term effects on market adjustment and also available cost-share assistance from Federal and State farm
conservation programs. Note that estimated costs for Option 3 and Option 7 are calculated using a
previous set of engineering costs (April 4,2002) and also assume an alternative AU thresholds for broiler
and egg-laying operations (where 1,000 AU would equal 100,000 broiler and egg-laying operation with
dry manure systems). Also, EPA does not estimate costs or financial impacts on the cattle and dairy
3-19
-------
Table 3-10. Financial Effects on CAFOs; Partial Cost-Share Assistance (Option 2)
Sector
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Wet
Layers - Dry
Turkeys
Total
Number
of
CAFOs
1,766
12
242
1,450
3,924
1,632
383
729
388
10,526
Affordable
Moderate
Stress
Zero Cost Passthrough
Affordable
Moderate
Stress
50% Cost Share Assistance
(Number of Affected Operations)
1,717
12
220
1,019
3,249
1,032
729
383
388
8,749
0
0
0
431
470
590
0
0
0
1,491
49
0
22
0
204
10
0
0
0
285
1,723
ND
231
ND
3,257
1,485
ND
ND
ND
6,696
0
ND
0
ND
463
144
ND
ND
ND
607
43
ND
11
ND
204
3
ND
ND
ND
261
Source: USEPA. May not add due to rounding. See Table 2-8 for definitions: Affordable, Moderate, and Stress.
sectors under Option 5 because the Agency does not consider housing of large animals under this option
to be practicable in these sectors).
Among operations with more than 1,000 AU, the expected potential CAFO closures range from
about 20 operations to 1,700 operations, depending on the technology option
Table 3-11 also presents economic impacts on all operations with between 300 and 1,000 AU
(more than 33,100 operations) and not just those operations that are expected to be defined as CAFOs
under the regulations (about 4,500 operations). The reason EPA presents its analysis for all operations in
this size category is that the Agency had considered extending the ELG regulations to operations in this
size category in the 2001 Proposal. As shown hi the table, applying these requirements to aU operations
with between 300 and 1,000 AU could potentially affect a large number of operations, ranging from
about 200 operations27 to nearly 11,000 operations, depending on the regulatory option.
Despite data and analytical changes made to EPA's financial analysis, as presented in both of
EPA's Notices (see: USGAO, 2001b, 66 FR 58556 and USGAO, 2002, 67 FR 48099), the results of the
Agency's analyses for these various regulatory options did not change much compared to that evaluated
and presented for the 2001 Proposal. In particular, these results show that the inclusion of an enterprise
level financial analysis does not significantly alter the results of EPA's overall analysis (since the
enterprise level results do not always differ substantially from the farm level results across all sectors).
27,
Since EPA does not estimate costs or financial impacts on the cattle and.dairy sectors under Option 5,
EPA would assume total closures under either Option 1 or Option 2 for those sectors.
3-20
-------
The use of alternative financial data overall in the beef and hog sectors, compared to that used for the
proposal, does result in substantial changes to EPA's analysis results compared to that conducted for the
proposed rule (although more beef operations but fewer hog operations are shown to experience financial
stress from estimated compliance costs). EPA's economic results, however, are not driven solely by
changes to EPA's financial models but are also driven by underlying changes to the Agency's
engineering cost models. As discussed in the 2001 Notice, EPA has expanded the range of cost estimates
per representative farm to account for variability across operations based on expected capital and
management improvements needed (see 66 FR 58572-58573). The cumulative effect of each of these
data and modeling refinements results in EPA's cost and financial models consistently showing that
certain types of business operations in the baseline—namely, operations without sufficient land base for
land application of manure that may incur high offsite transfer costs, high-technology and management
needs, along with higher-cost, low-performing businesses—are more vulnerable to facility closure.
3.4 ESTIMATED FINANCIAL EFFECTS TO NEW OPERATIONS (NSPS ANALYSIS)
This section examines the impacts to new facilities to comply with the final ELG requirements
for New Source Performance Standards (NSPS). For this analysis, EPA evaluated impacts on new source
CAFOs by comparing the costs borne by new source CAFOs to those estimated for existing sources.
That is, if the expected cost to new sources is similar to or less than the expected cost borne by existing
sources (and that cost is considered economically achievable for existing sources), EPA considers that
the regulations for new sources do not impose requirements that might grant existing operators a cost
advantage over new CAFO operators and further determines that the NSPS is affordable and does not
present a barrier to entry for new facilities. In general, the costs to new sources from NSPS requirements
are lower than the costs for existing sources because new sources are able to apply control technologies
more efficiently than existing sources, which may incur high retrofit costs. Not only will new sources be
able to avoid the retrofit costs incurred by existing sources, new sources might also be able to avoid the
other various control costs facing some existing producers through careful site selection. The
requirements promulgated in the final regulation do not give existing operators a cost advantage over new
CAFO operators; therefore, the new source performance standards do not present a barrier to entry for
new facilities.
Examples of avoided retrofit costs and costs of total containment systems and waste
management, including land application, for both existing and new sources, are provided in Section 4 of
the preamble. As discussed in the preamble, EPA evaluated economic impacts to new source CAFOs by
comparing the costs borne by new source CAFOs to those estimated for existing sources. That is, if the
expected cost to new sources is similar to or less than the expected cost borne by existing sources (and
that cost was considered economically achievable for existing sources), then EPA considers the
regulations for new sources not to impose requirements that might grant existing operators a cost
advantage over new CAFO operators and further determines that the NSPS is affordable and does not
present a barrier to entry for new facilities. In general, costs to new sources for complying with a given
set of regulatory requirements are lower than the costs for existing sources to comply with the same
requirements since new sources are able to apply control technologies more efficiently than existing
sources that may incur high retrofit cost. New source CAFOs will be able to avoid the retrofit costs that
will be incurred by existing sources. For example, the cost of a model total containment system for
swine that would meet the no discharge requirement (e.g., incremental cost of deep pit swine house,
including land application) typically is less than the cost for an existing source to retrofit water intensive
lagoon-based systems that are exposed to precipitation. Among the primary reasons for the capital cost
' 3-21
-------
Table 3-11. Model CAFOs where Compliance Costs result in Financial Stress (Alternative Options)
Sector
Total No.
Option 1
Option 2
Option 3"
Option 5
Option 7'1
All Defined CAFOs >300 AU
Beef
Veal
Heifers
Dairy
Fogs
Broilers
Layers
Turkeys
Total
4,448
736
299
7,230
13,825
12,034
3,082
2,003
43,657
133
0
38
0
0
3
0
0
174
216
0
63
0
204
19
0
0
502
2,885
0
322
504
990
8,293
0
0
12,994
N/A
N/A
N/A
N/A
665
108
0
0
773
2,535
0
213
1,888
674
2,732
0
0
8,042
All Defined CAFOs >1,000 AU
Beef
Veal
Heifers
Dairy
Hogs
Broilers
Layers
Turkeys
Total
1,766
12
242
1,450
3,924
1,632
1,112
388
10,526
12
0
0
0
0
3
0
0
15
49
0
22
0
204"
10
0
0
285
340
0
71
3
990
699
0
0
2,103
N/A
N/A
N/A
N/A
665
84
0
0
749
63
0
58
393
674
541
0
0
1,729
All Defined CAFOs 300-1000 AU
Beef
Veal
Heifers
Dairy
Hogs
Broilers
Layers
Turkeys
Total
2,682
57
724
5,780
9,901
10,402
1,970
1,615
33,131
121
0
38
0
0
0
0
0
159
167
0
41
0
0
10
0
0
218
2,545
0
251
502
0
7,594
0
0
10,892
N/A
N/A
N/A
N/A
0
24
0
0
24
2,472
0
155
1,495
2,191
6,313
Source: USEPA. Costs for Option 3 and Option 7 are calculated using April 4, 2002 engineering costs and assume
an alternative AU thresholds for broiler and egg-laying operations; see also USEPA, 20021—DCN 375086).
N/A - "not applicable" since EPA does not consider housing of large animals in some sectors to be practicable.
This table also reflects impacts on all operations 300-1000 AU and not just operations defined as CAFOs only.
3-22
-------
difference for a new source with total containment is that it does not include an impoundment lagoon,
and it experiences reduced operating costs because it handles less waste with substantially lower water
and higher solids content than a water-intensive lagoon-based system. New sources may be able to avoid
many of the other control costs facing some existing producers through careful site selection, such as
choosing to locate.at a site with sufficient available land nearby for applying manure. Furthermore, other
technologies are available to new sources, that have been implemented by existing sources, that are also
capable of achieving the no discharge standard. The preamble of the final rule provides further
discussion of these and other technologies. Since the new source requirements for beef and dairy
operations are the same as the corresponding existing source requirements, EPA concludes that the NSPS
requirements promulgated today do not present a barrier to entry for new facilities. For hog, poultry, and
veal operations, where the new source requirements are more stringent than the existing source
requirements, EPA concludes that the NSPS requirements do not pose a barrier to entry because of the
currently widespread use of animal confinement practices and waste management technologies that can
comply with the zero discharge standard, and because these total containment technologies and practices
are less costly to implement than water-intensive systems (e.g., such as water flush waste management)
that are exposed to precipitation.
As part of its preliminary analysis, EPA costed for zero discharge technologies and showed that
these would pose no barrier to entry (see Section 3.4.1 and Section 3.4.2 below); now that operations can
choose an alternative option that might be cheaper to implement, EPA believes there is even less
likelihood that there is a barrier to entry. More information is provided in the Development Document
and related cost supporting the final regulations (USEPA, 2002). All new source technologies are widely
demonstrated and available hi each animal sector.
3.4.1 Beef and Dairy Subcategories
As part of a preliminary analysis, EPA evaluated costs for new beef and dairy operations with
more than 1,000 AU. These costs compare the cost of land application requirements for both new and
existing source under similar technology requirements reflected by costs estimated for Option 2. The
land application requirements for new sources would be identical to those established for existing
sources.
EPA's analysis indicates that requiring Option 2 for new sources for the beef and dairy
subcategories would not create a barrier to entry because the estimated costs for new sources are less
expensive than the BAT costs for existing sources. This determination is based on a comparison of the
costs of Option 2 BAT to the costs of Option 2 NSPS on a model-by-model basis. These results are
shown in Table 3-12. Estimated Option 2 NSPS costs for new beef and dairy operations are lower than
Option 2 BAT costs since they do not include retrofitting costs that would be incurred by existing
sources. EPA's comparison of the estimated NSPS and BAT costs shows that the new source costs for
some model facilities were estimated to be more than 20 percent lower than those for existing facilities.
Furthermore, these requirements are "economically achievable" to existing facilities (see Section 3.3).
Therefore, EPA concludes that the NSPS requirements should pose no barrier to entry to new business hi
these sectors. These cost estimates are available in the record.
3-23
-------
3.4.2 Swine, Veal, and Poultry Subcategories
As part of a preliminary analysis, EPA evaluated costs for new swine, veal, and poultry
operations with more than 1,000 AU. These costs would require that all discharges of process
wastewater from the production area are prohibited and there is no allowance for discharges due to large
rainfall events (Option 5). Land application requirements would be similar to those established for
existing sources.
EPA's analysis indicates that requiring Option 5 for new sources for the hog, veal, and poultry
subcategories would not create a barrier to entry since the estimated costs for new sources are the same
as (for veal) or less expensive than the BAT costs for existing sources. This determination is based.on a
comparison of the costs of Option 2 BAT to the costs of Option 5 NSPS on a model-by-model basis.
These results are shown in Table 3-13 (results are not shown for veal, since the costs are the same for
NSPS and BAT). Estimated Option 5 NSPS costs for new swine and poultry operations are lower than
Option 2 BAT costs since they do not include retrofitting costs that would be incurred by existing
sources. EPA's comparison of the estimated NSPS and BAT costs shows that the new source costs for
some model facilities were estimated to be more than 50 percent lower than those for existing facilities.
Furthermore, these requkements are "economically achievable" to existing facilities (see Section 3.3).
Therefore, EPA concludes that the NSPS requirements should pose no barrier to entry to new business hi
these sectors. These cost estimates are available in the record.
Table 3-12. Percent Difference in Costs between NSPS and BAT Costs, Beef and Dairy Sectors
Sector
Fed Cattle
Dairy
Heifers
Facility Size
Ml
M2
M3
LI
L2
Ml •
M2
M3
LI
Ml
M2
M3
LI
Percent Difference
-14% to -21%
-13% to -28%
-12% to -27%
-10% to -18%
-9% to -15%
-1% to -19%
-0.3% to -21%
-0.7% to -14%
-0.1% to -23%
-21% to -37%
-21% to -29%
-17% to -27%
-15% to -22%
Source: USEPA. Costs for BAT and NSPS Option 2 are calculated using April 4,2002 engineering costs. Where
percentages are negative, NSPS costs are less expensive than the BAT costs. See Table 2-1 for CAFO model
definitions. Ranges shown are by region and reflect the average land availability and technology needs categories.
3-24
-------
Table 3-13. Percent Difference between NSPS & BATCosts, Hog and Poultry Sectors
Sector
Hog-GF
Hog-FF
Layers-Dry
Layers-Wet
Broilers
Turkeys
Facility Size
Ml
M2
M3
LI
L2
Ml
M2
M3
LI
L2
Ml
M2
M3
LI
L2
M3
LI
Ml
M2
M3
LI
L2
Ml
M2
M3 '
LI
Percent Difference
-4% to -12%
-4% to -16%
-3% to -18%
-7% to -15%
-6% to -12%
-4% to -11%
-4% to -15%
-3% to -17%
-8% to -15%
-6% to -12%
-42% to -43%
-44% to -46%
-34% to -36%
-55% to -58%
-58% to -63%
-60%
-92%
-22% to -59%
-24% to -65%
-26% to -70%
-28% to -74%
-34% to -81%
-33% to -36%
-41% to -45%
-40% to -44%
-50% to -56%
Source: USEPA. Costs for BAT and NSPS Option 2 are calculated using April 4, 2002 engineering costs. Where
percentages are negative, NSPS costs are less expensive than the BAT costs. See Table 2-1 for CAFO model
definitions. Ranges shown are by region and reflect the average land availability and technology needs categories.
3-25
-------
3.4.1 Comparison with the Proposed Regulations
Table 3-14 compares the Agency's preliminary aggregate, average costs to new sources to those
estimated for existing source, across a range of regulatory options considered by EPA. For the 2001
Proposal, these costs reflect new source requirements set forth in the proposal would have required
phosphorous-based land application requirements with the added requirements of ground water controls
where there is a direct hydrologic connection (Option 3, all sectors) and also total containment from the
production area with no exception for a storm event (Option 5, hogs and poultry only). This proposed
option is listed in Table 3-14 as the "Proposed Option 3/5 ." These proposed requirements would have
applied both to new operations with more than 1,000 AU and to new operations with less than 1,000 AU
that are defined as CAFOs. EPA did not consider a total containment option for the cattle and dairy
sectors since this was deemed impracticable and not affordable.
As shown hi the table, both alternative Option 1 and Option 2 would likely not pose a barrier to
entry to new operations since the average NSPS cost is estimated to be less than or equivalent to the BAT
costs (and these costs are determined to be economically achievable for existing operations; see Section
3.3). To determine "no barrier to entry" for the other alternative regulatory options that EPA considered
for new sources (Option 3, Option 7, and Option 5 for some sectors), the Agency would need to conduct
additional analysis before making such a determination. As shown, although the NSPS costs are
generally lower than the estimated BAT costs, it is unclear whether imposing similar requirements for
existing sources would be economically achievable for those operations or that these costs would not
pose a barrier to entry to new operations.
Taw* 1.14- FnriHtv T,evel Cost Comnarison - New versus Existing Sources (>1000 AU)
Sector
Cattle
Dairy
Hog
Broilers
Layers
Turkeys
Estimated NSPS Costs
Proposal
Option 3/5
$8,000
$15,400
$5,700
$5,800
$7,600
$16,100
P-based
Standards
Option 2
$5,500
$13,300
$5,700
$5,700
$7,600
$16,100
P-based &
Timing
Option 7
$10,700
$109,100
$5,700
$5,700
$7,600
$16,100
Estimated BAT Costs
N-based
Standards
Option 1
$4,700
$30,600
$7,700
$11,900
$14,200
$20,900
P-based
Standards
Option 2
$9,200
$44,900
$18,200
$13,900
$21,500
$30,800
P-based &
Timing
Option 7
$16,500
$331,000
$20,000
$13,900
$21,500
$30,800
Source: USEPA. Costs for BAT and NSPS Option 2 are calculated using April 4,2002 engineering costs.
3.5 MARKET IMPACTS
This section the results of EPA's market model to predict impacts of the final regulations on
consumer and farm level price and quantity. The market model results also form the basis for further
projecting changes to national employment, national economic output, and regional employment. EPA
3-26
-------
measures economic impacts on the livestock and poultry sectors (direct effects), on industries that
provide goods and services to livestock and poultry producers (indirect effects) and from associated
expenditures of income earned in direct and indirect activities (induced effects). EPA also predicts
impacts on U.S. trade. Section 3.5.1 presents the results of EPA's analysis across all subcategories;
Section 3.5.2 presents the results for each individual subcategory (cattle, dairy, hog, and poultry
subcategories).
3.5.1 Market Analysis Results Across All Subcategories
This section presents the results of EPA's market model analysis across all subcategories. The
results presented in this section are based on the aggregate compliance costs that EPA estimated for both
CAFOs with more than 1,000 AU to comply with the effluent guideline revisions and for CAFOs with
between 300 and 1,000 AU, if defined as a CAFO, to comply with the NPDES permitting requirements.
Results are shown both for Option 1 and Option 2. These market effects are estimated based on
estimated regulatory costs presented hi Table 3-3.
3.5.1.1 Commodity Prices and Quantities
EPA's market model predicts that the final regulations will not result in significant industry-level
changes in production and prices. Predicted changes hi animal production might raise producer prices, as
the market adjusts to the final regulatory requirements. For all sectors, EPA estimates that farm level
prices will rise by less than one percent of pre-regulation baseline prices (Table 3-15). At the retail level,
EPA expects that the final regulations will not have a substantial impact on overall production or
consumer prices for value-added meat, eggs, and fluid milk and dairy products. EPA estimates that retail
price increases resulting from these regulations will also be less than one percent of baseline prices in all
sectors (Table 3-16). At the retail level, EPA expects that the final rule will not have a substantial impact
on overall production or consumer prices for value-added meat, eggs, and fluid milk and dairy products.
EPA estimates that retail price increases resulting from this rule will be less than one percent of baseline
prices in all sectors, averaging below the rate of general price inflation for all foods. In terms of retail
level price changes, EPA estimates that poultry and red meat prices will rise about one cent per pound.
EPA also estimates that egg prices will rise by about one cent per dozen and that milk prices will rise by
about one cent per gallon.
Tables 3-15 and 3-16 show predicted farm and retail price changes, as both absolute value and as
a percentage of pre-regulation baseline price levels. These economic effects reflect changes to both the
effluent guideline regulation and the NPDES permit regulation. For comparison purposes, the average
annual percentage change in price from 1990 to 1998 is provided. In all cases, the percent change in
price attributable to the regulation is well within the normal year-to-year variability of prices for these
products.
Table 3-17 summarizes the forecast reductions in farm level production, following a shift hi the
supply curve caused by compliance. As shown, predicted quantity reductions are less than two-tenths of
one percent of pre-regulation production levels for all sectors. Other than export and import changes,
quantity changes at the retail level (not shown) are expected to be directly proportional to changes at the
farm level because the model assumes a fixed-proportions production process.
3-27
-------
Table 3-15. Post-Compliance Farm Level Price Changes
Beef
Dairy
Hogs
($/hundredweight)
Broilers
(cents/Ib.)
Layers
(cents/doz.)
Turkeys
(cents/lb.)
Option 1
1997 Price
Change in Price
Percent Change in Price
Avg. Annual Change (%)
(1990-1998)
66.09
0.03
0.05
4.56
13.38
0.05
0.34
7.95
54.30
0.02
0.04
15.24
37.00
0.04
0.11
5.74
69.80
0.17
0.24
11.45
40.10
0.05
0.13
4.37
Option 2
1997 Price
Change in Price
Percent Change in Price
Avg. Annual Change (%)
(1990-1998)
66.09
0.13
0.19
4.56
13.38
0.08
0.61
7.95
54.30
0.09
0.17
15.24
37.00
0.04
0.12
5.74
69.80
0.22
0.31
11.45
40.10
0.07
0.18
4.37
Source: USEPA, except historical data (pre-regulatory average price and average annual change data) that are from
USDA/ERS, 1999c, 1998b; USDA/WAOB, 1999,2001; andNCBA, 2000.
Table 3-16. Post-Comoliance Retail Level Price Changes
Beef
($/lb.)
Dairy
(index)
Hogs
($/lb.)
Broilers
(cents/lb.)
Layers
(cents/doz.)
Turkeys
(cents/lb.)
Option 1
1997 Price
Change in Price
Percent Change in Price
Avg. Annual Change (%)
(1990-1998)
2.80
0.001
0.02
2.30
145.50
0.45
0.31
2.43
2.45
0.000
0.01
5.07
151.00
0.04
0.03
2.99
106.00
0.17
0.16
7.17
105.10
0.05
0.05
2.39
Option 2
1997 Price
Change in Price
Percent Change in Price
Avg. Annual Change (%)
(1990-1998)
2.80
0.002
0.09
2.30
145.50
0.81
0.56
2.43
2.45
0.001
0.05
5.07
151.00
0.04
0.03
2.99
106.00
0.22
0.20
7.17
105.10
0.07
0.07
2.39
Source: USEPA, except historical data (pre-regulatory average price and average annual change data) that are from
USDA/ERS, 1999c, 1998b; USDA/WAOB, 1999,2001; andNCBA, 2000.
3-28
-------
EPA uses the estimated production changes, multiplied by the appropriate per-unit market price,
to compute the overall change in market value associated with complying with the final regulations. The
overall change in market value is an input to EPA's input-output analysis framework, which allows EPA
to compute changes in employment and economic output after compliance.
As demonstrated by the results in these tables, there are only very minor differences in the
estimated results between the two regulatory options presented here (Optionl and Option 2).
Table 3-17. Post-Compliance Farm Production Changes
Beef
Dairy
Hogs
Broilers
(million pounds)
Layers
(mil. doz.)
Turkeys
(mil. Ibs.)
Option 1
1997 Quantity
Change in Quantity •
Percent Change in Quantity
47,967
9
0.0
156,100
145
0.1
23,542
3
0.0
27,551
3
0.0
6,473
1
0.0
5,412
1
0.0
Option 2
1997 Quantity
Change in Quantity
Percent Change in Quantity
47,967
39
0.1
156,100
259
0.2
23,542
11
0.0
27,551
3
0.0
6,473
1
0.0
5,412
2
0.0
Source: USEPA, except historical data (pre-regulatory quantity data) that are from USDA/ERS, 1998a, and 1998b;
USDA/WAOB, 1999; and Putnam and Allshouse, 1999.
3.5.1.2 Aggregate Employment and National Economic Output
EPA does not expect the final regulations to cause significant changes hi aggregate employment
or national economic output as measured by Gross Domestic Product (GDP). EPA expects, however,
that there will be losses in employment and economic output associated with decreases in animal
production due to rising compliance costs. These losses are estimated throughout the entire economy,
using available modeling approaches, and are not attributable to the regulated community only. This '
analysis also does not adjust for offsetting activity in other parts of the economy that may be stimulated
as a result of the final regulations, such as the construction and farm services sectors.
Employment losses are measured in full-tune equivalents (FTEs)28 per year nationwide. These
losses are associated with decreases in commodity production in response to higher compliance costs
(Table 3-18). Predicted changes in aggregate employment are measured in terms of both direct and
indirect/induced employment.29.
28
One FTE is equivalent to 2,080 hours of labor.
29 Direct employment measures the number of jobs related to production and processing, including
workers engaged in the manufacture of agricultural inputs and their suppliers. Other indirect or induced
employment provides a broader measure of industry-related employment and includes workers throughout the
3-29
-------
Table 3-18. Post-Compliance Changes in Total National Employment (FTEs)
Option
Beef
Dairy
Hogs
Poultry
Option 1
Total Baseline Direct "
Farm Employment
Direct Employment
Direct "Wholesale/
Processing Employment
Consumer/Indirect/
Induced Employment
Total Change
336,700
113
16
528
657
483,800
370
15
2,020
2,404
195,900
37
10
207
254
71,800
131
20
666
817
Total "
1,088,200
651
60
3,421
4,133
Option 2
Total Baseline Direct *
Farm Employment
Direct Employment
Direct Wholesale/
Processing Employment
Consumer/Indirect/
Induced Employment
Total Chance
336,700
476
66
2,218
2,759
483,800
660
26
3,603
4,289
195,900
149
40
832
1,021
71,800
159
24
806
990
1,088,200
1,444
156
7,460
9,059
Source: USEPA's market model results, in conjunction with RIMS II multipliers (USDC, 1997b). Totals may not
add due to rounding and may include double counting because each sector is modeled separately.
" Total farm employment is updated by EPA from 1990 estimates by Abel, Daft & Barley (1993) to account for
changes between 1990 and 1997 (Council of Economic Advisors, 2000). Estimates are allocated by sector based on
its share of annual farm revenue (USDA/NASS, 1999a) and exclude employment at cattle grazing operations.
Processing sector employment is from the 1997 Census of Manufactures (USDC, 1999a) and is, in some cases,
allocated to individual sectors based on farm sector employment proportions. See Section 2.5.3 of the Proposal EA
USEPA, 2001a). Total employment in 1997 was 129.6 million (Council of Economic Advisors, 2000).
EPA estimates of the reduction in total employment across all sectors to range from about 4,100
jobs lost (Option 1) to about 9,100 jobs lost (Option 2). Table 3-18. This projected change is modest
when compared to total national employment, estimated at about 129.6 million jobs in 1997. EPA
estimates of the aggregate reduction in national economic output range from about $400 million (Option
1) to about S900 million (Option 2). Table 3-19. This projected change is also modest when compared
to total GDP, estimated at $8.5 trillion in 1997 (Council of Economic Advisors, 2000).
economy. More information is provided in Section 4.4 of the Proposal EA.
3-30
-------
Table 3-19. Post-Compliance Changes in Total National Economic Output (GDP)
Option
Beef
Dairy
Hogs
Poultry
Total"'
(millions in 1997 dollars)
Option 1
Baseline Total
Post-Regulation
_
65
—
222
._
26
—
80
8,318,400
394
Option 2
Baseline Total
Post-Regulation
—
275
-
397
._
105
—
97
8,318,400
873
Source: USEPA's market model results, in conjunction with RIMS II multipliers (USDC, 1997b). Totals may not
add due to rounding and may include double counting since each sector is modeled separately.
a Council of Economic Advisors (2002).
3.5.1.3 Regional and Community Impacts
To evaluate the potential for differential impacts among farm production regions, EPA examined
employment impacts by region. EPA also evaluated whether the final requirements could result in
substantial changes in volume of production, given predicted facility closures, within a particular
production region. EPA concludes from these analyses that regional and community level effects are
estimated to be modest, but do tend to be concentrated within the more traditional agricultural regions.
EPA does not expect that this rule will have a significant impact on where animals are raised.
On one hand, on-site improvements in waste management and disposal, as required by the final rule,
could accelerate recent shifts in production to more nontraditional regions as higher-cost producers in
some regions exit the market to avoid the relatively high retrofitting costs associated with bringing
existing facilities into compliance. On the other hand, the final regulations might favor more traditional
production systems where operators grow both livestock and crops, since these operations tend to have
available cropland for land application of manure nutrients^ These types of operations tend to be more
diverse and less specialized and, generally, smaller in size. Long-standing farm services and input supply
industries in these areas could likewise benefit from the final rule, given the need to support on-site
improvements in manure management and disposal. Local and regional governments, as well as other
nonagricultural enterprises, would also benefit.
Table 3-20 breaks out the estimated regional employment impacts between direct (farm and
processing level) and indirect/induced (other economy-wide) job losses.30 As shown, EPA estimates
direct employment losses to be greatest in the Midwest region given the sheer volume of animal
production in the region, which includes the Dakotas, Nebraska, and Kansas as well as the Corn Belt and.
Lake states. Li the Midwest region, EPA estimated 300 to 700 direct job losses (depending on the
Indirect effects are a result of changes in consumer spending and thus occur in areas with higher
population densities regardless of the animal sectors affected.
3-31
-------
option). These estimated job losses include CAFO owner-operator job losses due to business closure.
Total estimated job losses, including indirect and induced employment impacts, are more evenly
distributed among regions and are greatest in the Mid-Atlantic, which covers areas with both high
consumer populations and concentrated hog and poultry operations hi North Carolina, Virginia, and the
Delmarva Peninsula.
Table 3-20. Regional Distribution of Predicted National Employment Reductions
Region ^
Agricultural
Sectors Direct
Indirect/
Induced
Total
Percent of
Labor Force
(FTEs)
Option 1
Pacific
Central
Midwest
South
Mid-Atlantic
Total
102
123
268
78
140
712
547
501
800
510
1,063
3,421
649
624
1,068
588
1,203
4,133
0.003
0.003
0.003
0.003
0.003
0.003
Option 2
Pacific
Central
Midwest
South
Mid-Atlantic
Total
192
347
700
108
253
1,599
1,194
1,092
1,745
1,111
2,318
7,460
1,386
1,439
2,444
1,219
2,571
9,059
0.006
0.007
0.007
0.006
0.006
0.007
employment data are from the U.S. Census Bureau (1999).
Totals may not add due to rounding and may include double counting since each sector is modeled separately.
""Regions are based on the USDA Farm Production Regions (see Figure 4-lin the Proposal EA): Pacific=Pacific,
Central=Mountain and Southern Plains, Midwest=Corn Belt, Lake States, and Northern Plains, South=Delta and
Southeast, Mid-Atlantic=Northeast and Appalachia.
To further evaluate regional impacts, EPA conducted the following additional assessment. The
geography of impacts may be more clearly seen if the information is disaggregated further to the farm
production region or state level. Table 3-21 shows the impact of the regulations at the farm production
region level. The regions are ranked by the severity of agricultural impacts. The Northern Plains, Corn
Belt, and Lake States dominate because of the regulation's focus on hog and cattle operations.
EPA believes that concerns about the potential regional and community effects are, in part,
mitigated by changes to the final regulations, as compared to the 2001 Proposal. For the final rule,
3-32
-------
Table 3-21. Farm Production Region Distribution of Predicted Changes in (Direct) National Employment
Farm
Production
Region *
Option 1
Northern Plains
Com Belt
Lake
Pacific
Southern Plains
Mountain
Northeast
Appalachia
Southeast
Delta
Total
Agricultural
Sectors Direct
Indirect/
Induced
Total
Percent of
Labor Force
(FTEs)
69
87
112
102
63
60
85
56
45
33
712
72
477
251
547
290
211
740
323
387
123
3,421
141
564
363
649
353
271
825
378
432
156
4,133
0.005%
0.003%
0.003%
0.003%
0.003%
0.003%
0.003%
0.003%
0.003%
0.003%
Q.003%
Option 2
Northern Plains
Corn Belt
Lake
Pacific
Southern Plains
Mountain
Northeast
Appalachia
Southeast
Delta
Total
257
225
218
192
191
156
148
104
63
45
1,599
157
1,040
548
1,194
633
459
1,614
704
844
268
7,460
414
1,264
766
1,386
824
615
1,763
808
906
313
9,059
0.014%
0.006%
0.007%
0.006%
0.007%
0.007%
0.006%
0.006%
0.006%
0.007%
0.007%
Source: USEPA's market model results, in conjunction with RIMS II multipliers (USDC, 1997b). State level
employment data are from the U.S. Census Bureau (1999). Totals may not add due to rounding and may include
double counting since each sector is modeled separately.
"'USDA Farm Production Regions (see Figure 4-1 in the Proposal EA): Pacific=CA,OR,WA; Mountain=
AZ,CO,ID,MT,NV,NM,UT,WY; Southern Plairis= OK,TX; Northern Plains= KS,NE,ND,SD; Lake= MI,MN,WI;
Corn Belt= IL,IA,IN,MO,OH; Delta= AR,LA,MS; Southeast^ AL,FL,GA,SC; Appalachia= KY,NC,TN,VA,WV;
Northeast CT,DE,DC,ME,MD,MA,NH,NJ,NY,PA)RI,VT.
3-33
-------
estimated market effects by region are considerably lower than those estimated for the proposal. For
example, compared to the proposed rule where EPA estimated direct farm employment losses of more
than 3,000 jobs, EPA estimates that the final rule could result in between 700 and 1,600 jobs lost. The
Midwest, where EPA predicts the highest predicted job losses, is reduced from nearly 1,300 jobs lost
estimated for proposal to between 300 and 700 jobs lost estimated for the final rule. Given these modest
estimated effects on national and regional employment, employment effects are not expected to reach
levels of concern in more finely drawn geographic regions.
3.5.1.4
Foreign Trade Impacts
Foreign trade impacts are difficult to predict because agricultural exports are determined by
economic conditions in foreign markets and changes in the international exchange rate for the U.S.
dollar. EPA predicts, however, that foreign trade impacts as a result of the final regulations will be
minor given the relatively small projected changes in overall supply and demand for these products and
the slight increase in market prices, as described Section 3.5.1.1. Measured as the percentage change in
traded volumes, the increases in imports and decreases in exports estimated by EPA will each total less
than 1 percent compared to baseline (pre-regulation) levels in each of the commodity sectors. Based on
these results, EPA believes that any quantity and price changes resulting from the final regulations will
not significantly alter the competitiveness of U.S. export markets for meat, dairy foods, and poultry.
Table 3-22 summarizes the impacts on retail level trade forecast by EPA's market model. By
sector, the projected changes in imports compared to baseline trade levels range from a 0.01 percent
increase in broiler imports to a 0.85 percent increase in dairy product imports. The predicted drops in
U.S. exports range from a 0.01 percent reduction in broiler exports to a 0.14 percent reduction in dairy
exports. Baseline information on U.S. imports and exports of livestock and poultry products is available
in Section 2.5 of the Proposal EA. As shown in the table, there is little difference in the estimated results
between the two regulatory options presented here (Option 1 and Option 2).
Option
Beef
Dairy
Hogs
Broilers
Layers
Turkeys
(percent)
Option 1
Increase in Imports
Decrease in Exports
0.02
0.01
0.48
0.08
0.01
0.01
0.01
0.01
Option 2
Increase in Imports
0.09
0.05
0.85
0.14
0.03
0.04
0.01
0.01
0.15
6.02
0.19
0.02
NA
0.03
NA
0.04
Source: USEPA, except historical data that are from Putnam and Allshouse, 1999. NA = Not applicable
3.5.2 Market Analysis Results across Individual Subcategories
This section presents the results of EPA's market model analysis for each individual subcategory
(cattle, dairy, hog, and poultry subcategories). The results presented in this section are based on the
3-34
-------
aggregate compliance costs that EPA estimated for both CAFOs with more than 1,000 AU to comply
with the effluent guideline revisions and for CAFOs with between 300 and 1,000 AU, if defined as a
CAFO, to comply with the NPDES permitting requirements. Results are shown both for Option 1 and
Option 2. These market effects are estimated based on estimated regulatory costs presented in Table 3-3.
The tables summarizing the results discussed in this section are provided at the end of the section.
Changes in employment and earnings can affect the vitality of local communities. Community
impacts are usually determined by employment changes at individual facilities. As facility-specific
information and analysis were not within the scope of this study, EPA is not able to speculate on
community impacts. However, EPA does disaggregate the national employment results to examine the
potential regional employment impacts of the final regulations. EPA allocates estimated national level
impacts by production shares across states and does not take into account existing environmental
practices or other production factors (see Section 4.4 of the Proposal EA).
5.5.2.1 Beef Sector
Compared to a baseline producer price of $66.09 per hundredweight, EPA's market model
predicts that the final CAFO regulations would raise producer cattle prices by $0.03 per hundredweight
(Option 1) to $0.13 per hundredweight (Option 2), or little more than 0.20 percent of the baseline
producer price (Table 3-23). (All prices are in 1997 dollars.) At the retail level, consumer prices for
beef products would rise less than half a cent per pound. At the retail commodity level, EPA's market
model predicts that U.S. beef imports would rise by less than 0.1 percent, and U.S. beef exports would
decrease by about 0.06 percent compared to baseline quantities.
Table 3-23 also presents EPA's estimates of both the direct (farm and processor level) and total
(i.e., national level) reductions in employment for the beef sector. Overall, the decrease in national
aggregate employment attributable to regulatory impacts on the beef sector range from about 700 FTE
(Option 1) to about 2,800 FTE (Option 2). Projected job losses are estimated throughout the entire
economy and are not attributable to the regulated community only. This analysis does not adjust for
offsetting increases in other sectors of the economy that might be stimulated as a result of the final
regulations. Estimated direct job losses include CAFO owner-operators, employed family members, and
hired farm labor. Total farm level employment in the cattle sector was 336,700 FTEs in 1997 (Abel,
Daft, and Earley, 1993, as updated by EPA; see Table 2-17 of the Proposal EA). More than 145,000
persons were employed in that sector's processing industries in 1997 (USDC, 1999a).
Table 3-23 shows that the traditional cattle production regions of the Midwest would be the most
affected, followed closely by the Central region. None of the impacts represent a significant share of
total employment in these regions. Compared to the baseline, EPA estimates the loss in beef agricultural
employment at less than 0.02 percent of total regional employment; about half of the estimated
agricultural job losses in the beef sector are expected in the Midwest region. Economy-wide employment
losses are estimated at less than 0.02 percent of baseline employment.
3.5.2.2 Dairy Sector
Compared to a baseline producer price of $13.38 per hundredweight, EPA's market model
predicts that as a result of the final regulations raw milk prices would rise compared to the baseline price
3-35
-------
by S0.05 per hundredweight (Option 1) to $0.08 per hundredweight (Option 2). (All prices are in 1997
dollars.) The retail dairy product price index rises by up to 0.8, less than 0.6 percent of the baseline
value (Option 2). These price increases are driven by slight changes in the amount produced at the farm
level and thus available for consumption (Table 3-24). At the retail commodity level, EPA's market
model predicts that U.S. dairy product imports would rise up to 0.9 percent, and U.S. dairy product
exports would decrease by about 0.14 percent compared to baseline quantities (Option 2).
Table 3-24 also presents EPA's estimates of both the direct (farm and processor level) and total
(national level) changes in employment for the dairy sector. EPA estimates total employment losses
attributable to the impact of the regulations on the dairy sector range from about 2,400 FTE (Option 1) to
about 4,400 FTE (Option 2). Projected job losses are estimated throughout the entire economy and are
not attributable to the regulated community only. This analysis does not adjust for offsetting increases in
other sectors of the economy that might be stimulated as a result of the final regulations. Estimated
direct job losses include CAFO owner-operators, employed family members, and hired farm labor. Total
farm level employment hi the dairy sector was 483,800 FTEs in 1997 (Abel, Daft, and Barley, 1993., as
updated by EPA). There were more than 141,000 FTE jobs in dairy processing in 1997 (USDC, 1999a).
Table 3-24 shows that the results of EPA's analysis indicate that dairy operations in the Midwest
region would be most affected, followed by operations in the Mid-Atlantic and Pacific regions. The loss
in dairy agricultural employment is estimated at less than 0.01 percent of total regional employment;
about 35 percent of the estimated agricultural job losses in the dairy sector are expected in the Midwest
region. Economy-wide employment losses are estimated at less than 0.02 percent of baseline
employment for the sector.
3.5.2.3 Hog Sector
Compared to a baseline producer price of $54.30 per hundredweight (hundredweight), EPA's
market model predicts that the final CAFO regulations would raise producer prices by by $0.02 per
hundredweight (Option 1) to $0.10 per hundredweight (Option 2), or less than 0.2 percent of baseline
producer price (Table 3-25). At the retail level, consumer prices for pork products would rise about one-
tenth of one cent per pound. These price increases are driven by slight changes in the amount of pork
products produced at the farm level and thus available for consumption. At the commodity level, EPA's
market model predicts that U.S. pork imports would rise by about 0.03 percent and U.S. pork exports
would decrease by about 0.04 percent compared to baseline quantities.
Table 3-25 also presents EPA's estimates of both the direct (i.e., farm and processor level) and
total (i.e., national level) reductions in employment for the hog sector. Overall, EPA decreases in
national aggregate employment in the hog sector by 300 FTE (Option 1) to about 1,000 FTE (Option 2).
Projected job losses are estimated throughout the entire economy and are not attributable to the regulated
community only. This analysis does not adjust for offsetting increases in other sectors of the economy
that might be stimulated as a result of the final regulations. Estimated direct job losses include CAFO
owner-operators, employed family members, and hired farm labor. Total farm level employment of
195,900 FTEs in the hog sector nationwide in 1997 (Abel, Daft, and Barley, 1993, as updated by EPA).
Employment in the hog processing sector accounted for over 84,000 FTE jobs in 1997 (USDC, 1999a).
Table 3-25 shows that the traditional hog growing regions of the Midwest would be the most
affected, followed by the Mid-Atlantic. None of the impacts represent a significant share of total
employment in these regions. Compared to the baseline, EPA estimates the loss in hog agricultural
3-36
-------
employment at under 0.01 percent; almost 70 percent of the estimated agricultural job losses in the hog
sector are expected in the more traditional Midwest region. Economy-wide employment losses are
estimated at under 0.01 percent compared to the baseline.
3.5.2.4 Poultry Sector
A summary of the key results of the market model for the broiler, layer, and turkey sectors is
shown hi Tables 3-26, 3-27, and 3-28. These tables indicate the predicted changes in farm and retail
prices, quantities, national and regional employment, and national economic output.
Compared to a baseline producer price of 37 cents perpound (in 1997 dollars), EPA's market
model predicts that the final CAFO regulations would raise broiler producer prices by about 0.05 cents
per pound, or about 0.10 percent of the baseline producer price (Table 3-26). At the retail level,
consumer prices for broiler products would also rise by about 0.05 cents per pound. Egg prices are
projected to increase by under 0.2 cent per dozen under the final regulations, or less than 0.4 percent of
the baseline producer price of 69.8 cents per dozen (Table 3-27). Consumer prices for eggs are also
projected to rise by about 0.3 cents per dozen. For turkey, EPA's market model predicts that the final
CAFO regulations would raise producer prices by under 0.1 cent per pound, less than 0.2 percent of the
40.1 cents per pound baseline producer price (Table 3-28). At the retail level, consumer prices for turkey
products would also rise by about 0.2 cent per pound. In most cases, there is little differences between
the estimated results for both Option 1 and Option 2.
These price increases are driven by slight changes in the amount of poultry products produced at
the farm level and thus available for consumption. At the commodity level, EPA's market model predicts
that U.S. egg imports would increase by about 0.20 percent and broiler imports would increase by 0.01
percent compared to baseline imports, but turkey imports would not change. U.S. broiler, turkey, and egg
exports would all decrease by less than 0.04 percent relative to baseline exports.
Tables 3-26 through 3-28 also present EPA's estimates of both the direct (farm and processor
level) and total (national level) reductions in employment for the poultry sector. Overall, national
aggregate employment reductions attributable to the impact of the regulations on the broiler sector are
estimated at 400 jobs to 500 jobs lost. National aggregate employment losses in the egg-laying sector
would be 300 jobs to 400 jobs lost. In the turkey sector, the analysis shows that about 200 jobs would be
lost. Projected job losses are estimated throughout the entire economy and are not attributable to the
regulated community only. This analysis does not adjust for offsetting increases in other sectors of the
economy that might be stimulated as a result of the final regulations. Estimated direct job losses include
CAFO owner-operators, employed family members, and hired farm labor. Total farm level employment
hi the poultry sector was 71,800 FTEs nationwide 1997 (Abel, Daft, and Barley, 1993, as updated by
EPA). More than 204,000 persons were employed hi poultry processing hi 1997 (USDC, 1999a).
Table 3-26 shows that the dominant broiler producing regions of the South would be the most
affected, followed by the Mid-Atlantic. The largest impacts on turkey and egg production would be in
the Midwest. None of the impacts represent a significant share of total employment hi these regions.
Compared to the baseline, EPA estimates the loss hi broiler agricultural employment would be less than
0.04 percent; almost 60 percent of the estimated agricultural job losses hi the broiler sector are expected
in the South (Table 3-26). About 40 percent of egg and turkey industry job losses are expected hi the
Midwest (Tables 3-27 and 3-28). Again, economy-wide employment losses are estimated at under 0.01
percent compared to baseline employment.
3-37
-------
Table 3-23. Summary of Market Model Results for the Beef Sector
Variable
Pre-Regulatory
Value/Units
Post-Regulatory Value/Units
Option 1
Option 2
Farm Products
Price
Quantity * Produced
Quantity Exported
Quantity Imported
$66.09/cwt
47,967 mil. Ibs.
331 mil. Ibs.
2,400 mil. Ibs.
$66.12/cwt
47,958 mil. Ibs.
331 mil. Ibs.
2,401 mil. Ibs.
$66.22/cwt
47,927 mil. Ibs.
330 mil. Ibs.
2,405 mil. Ibs.
Retail Products
Price
Quantity Demanded
Quantity Exported
Quantity Imported
$2.80/lb.
26,031 mil. Ibs.
2,136 mil. Ibs.
2,343 mil. Ibs.
$2.80 Mb.
26,028 mil. Ibs.
2,136 mil. Ibs.
2,344 mil. Ibs.
$2.803/lb.
26,016 mil. Ibs.
2,135 mil. Ibs.
2,345 mil. Ibs.
Employment Reduction b/
Direct Farm
Direct Processor
Total Economy
336,700 FTEs
145,6 17 FTEs
129.6 mil. FTEs
113 FTEs
15 FTEs
657 FTEs
487 FTEs
67 FTEs
2,827 FTEs
Output Reduction
National
$8,478,600 million
$65 million
$282 million
Regional Farm and Processing Employment Reduction
Pacific
Central
Midwest
South
Mid-Atlantic
Total
23,869 FTEs
195,434 FTEs
254,929 FTEs
1,430 FTEs
6,656 FTEs
482,3 17 FTEs
6 FTEs
52 FTEs
68 FTEs
OFTEs
2 FTEs
129 FTEs
27 FTEs
225 FTEs
293 FTEs
2 FTEs
8 FTEs
554 FTEs
Source: Post-regulatory changes are estimated by USEPA. Pre-regulatory prices, quantities, and trade volumes, see
Table 4-16 (Section 4 of the Proposal EA). Pre-regulatory employment, see Table 2-17 (Section 2 of the Proposal
EA) allocated to regions based on production as are the post-regulatory values.
•* Includes veal and heifer.
wl FTE - 2,080 hours of labor.
3-38
-------
Table 3-24. Summary of Market Model Results for the Dairy Sector
Variable
Pre-Regulatory
Value/Units
Post-Regulatory Value/Units
Option 1
Option 2
Farm Products
Price
Quantity Produced
$13.38/cwt
156,100 mil. Ibs.
$13.43/cwt
155,955 mil. Ibs.
$13.46/cwt
155,835 mil. Ibs.
Retail Products
Price
Quantity Demanded
Quantity Exported
Quantity Imported
145.50 Index
155,239 mil. Ibs.
5,244 mil. Ibs.
4,383 mil. Ibs.
145.95 Index •
155,1 19 mil. Ibs.
5,240 mil. Ibs.
4,404 mil. Ibs.
146.33 Index
155,020 mil. Ibs.
5,237 mil. Ibs.
4,421 mil. Ibs.
Employment Reduction ^
Direct Farm
Direct Processor
Total Economy
483,800 FTEs
141,400 FTEs
129.6 mil. FTEs
370 FTEs
15 FTEs
2,404 FTEs
675 FTEs
26 FTEs
4,387 FTEs
Output Reduction
National
$8,478,600 million
$222 million
$406 million
Regional Farm and Processing Employment Reduction
Pacific
Central
Midwest
South
Mid-Atlantic
Total
138,725 FTEs
91,963 FTEs
225,389 FTEs
27,405 FTEs
141,718 FTEs
625,200 FTEs
85 FTEs
57 FTEs
. 139 FTEs
17 FTEs
87 FTEs
384 FTEs
156 FTEs
103 FTEs
253 FTEs
31 FTEs
159 FTEs
701 FTEs
Source: Post-regulatory changes are estimated by USEPA. Pre-regulatory prices, quantities, and trade volumes, see
Table 4-1.6 (Section 4 of the Proposal EA). Pre-regulatory employment, see Table 2-17 (Section 2 of the Proposal
EA) allocated to regions based on production as are the post-regulatory values.
•"I FTE = 2,080 hours of labor. .
3-39
-------
Table 3-25. Summary of Market Model Results for the Hog Sector
Variable
Pre-Regulatory
Value/Units
Post-Regulatory Value/Units
Option 1
Option 2
Farm Products
Price
Quantity Produced
Quantity Exported
Quantity Imported
$54.30/cwt
23,542 mil. Ibs.
14 mil. Ibs.
8 14 mil. Ibs.
$54.32/cwt
23,539 mil. Ibs.
14.1 mil. Ibs.
813.8 mil. Ibs.
$54.40/cwt
23,530 mil. Ibs.
14.1 mil. Ibs.
8 14.5 mil. Ibs.
Retail Products
Price
Quantity Demanded
Quantity Exported
Quantity Imported
$2.45/lb.
16,863 mil. Ibs.
1,044 mil. Ibs.
633 mil. Ibs.
$2.45/lb.
16,862 mil. Ibs.
1,043.5 mil. Ibs.
633.1 mil. Ibs.
• $2.45/lb.
16,857 mil. Ibs.
1,043.2 mil. Ibs.
633. 2 mil. Ibs.
Employment Reduction
Direct Farm
Direct Processor
Total Economy
195,900 FTEs "
84,723 FTEs
129.6 mil. FTEs
37 FTEs
10 FTEs
254 FTEs
153 FTEs
40 FTEs
1,047 FTEs
Output Reduction
National
$8,478,600 million
$26 million
$108 million
Regional Farm and Processing Employment Reduction
Pacific
Central
Midwest
South
Mid-Atlantic
Total
1,507 FTEs
20,128 FTEs
189,391 FTEs
12,129 FTEs
57,468FTEs
280,623 FTEs
0 FTEs
3 FTEs
32 FTEs
2 FTEs
10 FTEs
47 FTEs
IFTEs
14FTEs
13 IFTEs
8 FTEs
40 FTEs
194 FTEs
Source: Post-regulatory changes are estimated by USEPA. Pre-regulatory prices, quantities, and trade volumes, see
Table 4-16 (Section 4 of the Proposal EA). Pre-regulatory employment, see Table 2-17 (Section 2 of the Proposal
EA) allocated to regions based on production as are the post-regulatory values.
"1 FTE = 2,080 hours of labor.
3-40
-------
fable 3-26. Summary of Market Model Results for the Broiler Sector
Variable
Pre-Regulatory
Value/Units
Post-Regulatory Value/Units
Option 1
Option 2
Farm Products
Price
Quantity Produced
37.000/Ib.
27,551 mil. Ibs.
37.04c71b.
27,548 mil. Ibs.
37.050/lb.
27,548 mil. Ibs.
Retail Products
Price .
Quantity Demanded
Quantity Exported
Quantity Imported
ISl.OOeTlb.
22,508 mil. Ibs.
5,048 mil. Ibs.
5 mil. Ibs.
151.04ji/lb.
22,506 mil. Ibs.
5,047.5 mil. Ibs.
5 mil. Ibs.
151.05c71b.
22,505 mil. Ibs.
5,047.4 mil. Ibs.
5 mil. Ibs.
Employment Reduction * b/
Direct Farm
Direct Processor
Total Economy
71,800 FTEs
204,200 FTEs
129.6 mil. FTEs
73 FTEs
13 FTEs
401 FTEs
88 FTEs
15 FTEs
487 FTEs
Output Reduction
National
$8,478,600 million
$40 million
$48 million
Regional Farm and Processing Employment Reduction
Pacific
Central
Midwest
South
Mid-Atlantic
Total
11,764 FTEs
22,826 FTEs
13,077 FTEs
156,986 FTEs
7 1,347 FTEs
276,000 FTEs
4 FTEs
7 FTEs
4 FTEs
48 FTEs
22 FTEs
85 FTEs
4 FTEs
9 FTEs
5 FTEs
59 FTEs
27 FTEs
103 FTEs
Source: Post-regulatory changes are estimated by USEPA. Pre-regulatory prices, quantities, and trade volumes, see
Table 4-16 (Section 4 of the Proposal EA). Pre-regulatory employment, see Table 2-17 (Section 2 of the Proposal
EA) allocated to regions based on production as are the post-regulatory values.
"'I FTE = 2,080 hours of labor.
b/ Estimated employment across all poultry sectors (Table 2-17 of the Proposal EA).
3-41
-------
Table 3-27. Summary of Market Model Results for the Egg-Laying Sector
Variable
Pre-Regulatory
Value/Units
Post-Regulatory Value/Units
Option 1
Option 2
Farm Products
*rice
Quantity Produced
69.800/doz.
6,473 mil. doz.
69.970/doz.
6,472 mil. doz.
70.070/doz.
6,471 mil. doz.
Retail Products
Price
Quantity Demanded
Quantity Exported
Quantity Imported
106.00|iS/doz
5,357 mil. doz.
227.8 mil. doz.
7 mil. doz.
106.170/doz.
5,356 mil. doz.
227.8 mil. doz.
7 mil. doz.
106.270/doz.
5,356 mil. doz.
227.7 mil. doz.
7 mil. doz.
Employment Reduction °yb/
Direct Farm
Direct Processor
Total Economy
71,800 FTEs
204,200 FTEs
129.6 mil. FTEs
17 FTEs
5 FTEs
259 FTEs
27 FTEs
7 FTEs
408 FTEs
Output Reduction
National
$8,478,600 million
$24 million
$38 million
Regional Farm and Processing Employment Reduction
Pacific
Central
Midwest
South
Mid-Atlantic
Total
11,764 FTEs
22,826 FTEs
13,077 FTEs
156,986 FTEs
71,347 FTEs
276 000 FTEs
3 FTEs
2 FTEs
8 FTEs
5 FTEs
4 FTEs
22 FTEs
4 FTEs
3 FTEs
13 FTEs
7 FTEs
7 FTEs
34 FTEs
Source: Post-regulatory changes are estimated by USEPA. Pre-regulatory prices, quantities, and trade volumes, see
Table 4-16 (Section 4 of the Proposal EA). Pre-regulatory employment, see Table 2-17 (Section 2 of the Proposal
EA) allocated to regions based on production as are the post-regulatory values.
"'I FTE = 2,080 hours of labor.
w Estimated employment across all poultry sectors (Table 2-17 of the Proposal EA).
3-42
-------
Table 3-28. Summary of Market Model Results for the Turkey Sector
Variable
Pre-Regulatory
Value/Units
Post-Regulatory Value/Units
Option 1
Option 2
Farm Products
Price
Quantity Produced
40.lQt/lb.
5,412 mil. Ibs.
40.15^.
5,410.6 mil. Ibs.
40.170/lb.
5,410.0 mil. Ibs.
Retail Products
Price
Quantity Demanded
Quantity Exported
105.100/lb
4,8 14 mil. Ibs.
598 mil. Ibs.
105.15(4/lb.
- 4,813 mil. Ibs.
597.8 mil. Ibs.
105.17|£/lb.
4,8 12 mil. Ibs.
597.8 mil. Ibs.
Employment Reduction ""*'
Direct Farm
Direct Processor
Total Economy
71,800 FTEs
204,200 FTEs
129.6 mil. FTEs
41 FTEs
3 FTEs
157 FTEs
59 FTEs
5 FTEs
227 FTEs
Output Reduction
National
$8,478,600 million
$16 million
$23 million
Regional Farm and Processing Employment Reduction
Pacific
Central
Midwest
South
Mid-Atlantic
Total
11,764 FTEs
22,826 FTEs
13,077 FTEs
156,986 FTEs
71,347 FTEs
276,000 FTEs
4 FTEs
2 FTEs
17 FTEs
6 FTEs
15 FTEs
45 FTEs
5 FTEs
3 FTEs
25 FTEs
9 FTEs
22 FTEs
65 FTEs
Source: Post-regulatory changes are estimated by USEPA. Pre-regulatory prices, quantities, and trade volumes, see
Table 4-16 (Section 4 of the Proposal EA). Pre-regulatory employment, see Table 2-17 (Section 2 of the Proposal
EA) allocated to regions based on production as are the post-regulatory values.
"I FTE = 2,080 hours of labor.
w Estimated employment across all poultry sectors (Table 2-17 of the Proposal EA).
3-43
-------
-------
SECTION FOUR
FINAL REGULATORY FLEXIBILITY ANALYSIS
This section considers the effects of the CAFO regulations on small businesses in the livestock
and poultry industries. Section 4.1 discusses EPA's requirements under the Regulatory Flexibility Act.
Section 4.2 outlines EPA's initial assessment of small businesses in the sectors affected by the
regulations. Section 4.3 presents EPA's final regulatory flexibility analysis and summarizes other steps
taken by the Agency to comply with the RFA. Section 4.4 presents the data, methodology, and results of
EPA's analysis of impacts on small businesses for this rulemaking.
4.1 THE REGULATORY FLEXIBILITY ACT AS AMENDED BY THE SMALL BUSINESS
REGULATORY ENFORCEMENT FAIRNESS ACT
The Regulatory Flexibility Act (RFA, 5 U.S.C etseq., Public Law 96-354), as amended by the
Small Business Regulatory Enforcement Fairness Act of 1996 (SBREFA) generally requires an agency to
prepare a regulatory flexibility analysis describing the impact of the regulatory action on small entities as
part of the rulemaking. .This analysis is required for any rule subject to notice-and-comment rulemaking
requirements under the Administrative Procedure Act or any other statute unless the agency certifies that
the rule will not have a "significant impact on a substantial number of small entities." Small entities
include small businesses, small organizations, and governmental jurisdictions. Because the CAFO
regulations could have a significant economic impact on a substantial number of small entities, EPA has
prepared this final regulatory flexibility analysis (FRFA).
In addition to the preparation of an analysis, the RFA, as amended by SBREFA, imposes certain
responsibilities on EPA when the Agency proposes rules that might have a significant impact on a
substantial number of small entities. These include requirements to consult with representatives of small
entities about the proposed rule. The statute requires that, where EPA has prepared an initial regulatory
flexibility analysis (IRFA), the Agency must convene a Small Business Advocacy Review (SBAR) Panel
for the proposed rule to seek the advice and recommendations of small entities concerning the rule. The
panel is composed of employees from EPA, the Office of Information and Regulatory Affairs within the
Office of Management and Budget, and the Office of Advocacy of the Small Business Administration
(SBA).
4.2
INITIAL ASSESSMENT
Prior to the 2001 Proposal, EPA conducted an initial assessment according to Agency guidance
on implementing RFA requirements (USEPA, 1999i). First, EPA must indicate whether the proposal is a
rule subject to notice-and-comment rulemaking requirements. EPA determined that the proposed CAFO
regulations were subject to notice-and-comment rulemaking requirements. Second, EPA should develop
a profile of the affected small entities. EPA has developed such a profile of the livestock and poultry
sectors, which includes all affected operations as well as small businesses. This information is provided
in Section 2 and other sections of the Proposal EA (USEPA, 2001a). Third, EPA's assessment needs to
4-1
-------
determine whether the rule would affect small entities and whether the rule would have an adverse
economic impact on small entities.
For the proposed rulemaking, EPA could not conclude that costs are sufficiently low to justify
"certification" that the regulations would not impose a significant economic impact on a substantial
number of entities. Instead, EPA complied with all RFA provisions and conducted outreach to small
businesses, convened an SBAR Panel, and prepared an IRFA. That analysis described EPA's assessment
of the impacts of the proposed CAFO regulations on small businesses in the livestock and poultry
sectors. A summary of this analysis was published in the Federal Register at the time of publication of
the 2001 Proposal (66 FR 3099-3103, see: USGPO, 2001a). More detailed information on EPA's IRFA
is provided in Section 9 of the Proposal EA. EPA's Proposal EA also describes other requirements of
EPA's initial assessment of small businesses and summarizes the steps taken by EPA to comply with the
RFA.
Since proposal, EPA has received new information and data related to small business in the
livestock and poultry industries, including revisions to the SBA's definition of "small business" in these
sectors and updates to EPA's estimate of the number of affected operations to reflect USDA estimates.
This information was presented in the 2001 Notice (66 FR 58556; USGPO, 2001b). Section 4.2.1 of this
report reviews SBA's revised definitions of small entities in the livestock and poultry industry and
discusses a rationale for using an alternative definition of small business in one sector. Section 4.2.2
then uses the definitions of small entities laid out in Section 4.2.1 to estimate the number of operations
that meet this small business definition. Section 4.2.3 presents the results of the initial assessment EPA
conducted for the 2001 Proposal, which provides a first level screen of potential impacts on small
business CAFOs and serves as a signal for additional analysis.
4.2.1 Definition of Small CAFO Businesses
The RFA defines a "small entity" as a small not-for-profit organization, small governmental
jurisdiction, or small business. No small governmental operations operate CAFOs. A few not-for-profit
organizations might operate CAFOs, but complete information is not available to warrant including not-
for-profit organizations in this analysis. The analysis therefore focuses only on small businesses that are
defined or designated as CAFOs. (Section 1 of this report describes the circumstances under which an
AFO is defined or designated as a CAFO and is subject to the final regulations.)
The RFA requires, with some exceptions, that EPA define small businesses according to SBA's
size standards. SBA sets size standards for defining small businesses by number of employees or amount
of revenues for specific industries. These size standards vary by North American Industry Classification
System (NAICS) code. CAFOs are listed under NAICS 112, Animal Production.31
Table 4-1 shows SBA size standards by SIC code for each of the six livestock and poultry
sectors, which are expressed in terms of average "annual receipts" (revenue). With one exception,
31 In September 2000, SBA updated the basis for its size standard from Standard Industrial Classification
(SIC) codes to NAICS codes (USGPO, 2000; U.S. Census Bureau, 2000). By SIC code, these industries are listed
under SIC 02, Livestock and Animal Specialties. The actual size standards for each sector, specified as an annual
revenue threshold, did not change as a result of this update.
4-2
-------
current SBA standards define a "small business" within each of the main livestock and poultry sectors as
an operation that generates average revenues ranging from less than $0.75 million per year (hog, dairy,
broiler, and turkey sectors) to less than $1.5 million per year (beef feedlot sector), averaged over the
three most recent fiscal years (USGPO, 2000; SBA, 1998). The exception is the revenue threshold for a
small chicken egg operation, which SBA has defined as a business that generates up to $9 million
annually. For reasons outlined in Section 9.2.1 of the Proposal EA, EPA believes that SBA's definition
of small business for the egg laying sector (revenues of $9 million per year) does not truly characterize a
small business in this sector. As discussed extensively in documentation supporting the 2001 Proposal,
EPA is using an alternative definition of $1.5 million annually for this analysis. Refer to the Proposal
EA (USEPA, 200la) and docket materials cited in that document, and the proposal itself (USGPO,
2001a).
SBA's size standards differ from the revenue cutoff generally recognized by USD A, which has
set $250,000 in gross sales as its cutoff between small and large family farms (USDA, 1998).
As discussed in the 2001 Notice (66 FR 58570-58571; see USGPO, 2001b), recent revisions to
SBA's small business definitions for some sectors necessitate changes to EPA's estimate of the number
of AFOs that are potentially defined as CAFOs and subject to the final requirements. Prior to June
2001, SBA defined a "small business" for the dairy, hog, broiler, and turkey sectors as an operation with
annual sales of less than $0.5 million per year. On June 7, 2001, SBA raised the size standards for these
four sectors to $0.75 million per year. SBA's notice of this change is at 66 FR 30646 (USGPO, 2001c).
Although SBA did not revise its small business definition for the beef feedlot and egg laying sectors,
updates to USDA estimates of the number of AFOs that are potentially defined as CAFOs also require
changes to EPA's overall estimates of the number of small businesses affected by the rulemaking. EPA's
revised estimates of the number of affected small businesses are presented in Section 4.2.2. .
Table 4-1. SBA Revenue Size Standards for Small Livestock and Poultry Operations
NAICS Code
(SIC Code)
112112(0211)
112111(0241/0212)
11221(0213)
11212(0241)
11232(0251)
11231(0252)
112330253
NAICS
Industry Description
Beef Cattle Feedlots
Beef Cattle Ranching and Fanning
Hog and pig farming
Dairy cattle and milk production
Broilers and other meat-type chickens
Chicken egg production
Turkey production
SBA Size
Standard*7
$1.5 million
$0.75 million
$0.75 million
$0.75 million
$0.75 million
$9.0 million
$0.75 million
EPA-Assumed
Revenue Cutoff
same as SBA
same as SBA
same as SBA
same as SBA
same as SBA
$1.5 million
same as SBA
Source: SBA, 1998; USGPO, 1991a, 1991b, 1996, 2000, 2001c; U.S. Census Bureau, 2000.
Size Standards by NAICS code (13 CFR Part 121) correspond to classifications under SIC classification.
4-3
-------
4.2.2 Number of Affected Small Businesses
EPA uses three steps to determine the number of small businesses that might be affected by the
CAFO regulations. First, EPA identifies small businesses in the relevant livestock and poultry sectors by
equating SBA's annual revenue definition with the number of animals at an operation. Second, EPA
estimates the total number of small businesses in these sectors using farm size distribution data from
USDA. Third, based on the regulatory thresholds being promulgated, EPA estimates the number of small
businesses that would be subject to the final requirements. These steps are summarized below. More
detailed information on this approach is presented in Section 9.2.2 of the Proposal EA.
In the absence of entity level revenue data, EPA identifies small businesses in the livestock and
poultry sectors by equating SBA's annual revenue definitions of "small business" to the number of
animals at these operations (step 1). This step produces a threshold based on the number of animals that
EPA uses to define small livestock and poultry operations and reflects the average farm inventory
(number of animals) that would be expected at an operation with annual revenues that define a small
business. This initial conversion is necessary because USDA data by farm size are not available by
business revenue. With the exception of egg laying operations, EPA uses SBA's small business
definition to equate the revenue threshold with the number of animals raised onsite at an equivalent small
business in each sector (shown in Table 4-1). For egg laying operations^ EPA uses an alternative revenue
definition of small business, discussed hi Section 4.2.1.
EPA estimates the number of animals at an operation to match SBA's small business definitions
based on annual revenue size standard (expressed as annual revenue per entity) and USDA-reported farm
revenue data that are scaled on a per-animal basis (expressed as annual revenue per inventory animal for
an average facility). Financial data used for this calculation are from USDA's 1997 ARMS database
(USDA/ERS, 1999a). USDA's data report average national revenue for each sector, combining both
livestock and nonlivestock farm revenue (income from crop sales and other farm-related income,
including government payments). EPA uses the derived per-animal revenues shown in Table 4-2 to
equate SBA's size standard (in revenues) with farm size based on the number of animals, as follows:
Average Number of Animals
Farm
SB A's small business definition ($ per year per farm)
average total revenue per head ($/animal)
The resultant number of animals represents the average animal inventory threshold for a small business.
Estimated "small business" thresholds for each sector are shown in Table 4-2. Additional information on
this approach and the data used for this calculation are outlined in Section 4.2.2 of the Proposal EA. The
resultant size threshold represents an average animal inventory for a small business.
For the purpose of conducting its FRFA for this rulemaking, EPA is defining "small business"
for these sectors as an operation that houses or confines less than the following: 1,400 fed beef cattle
(includes fed beef, veal, and heifers); 300 mature dairy cattle; 2,100 market hogs; 37,500 turkeys; 61,000
layers; or 375,000 broilers (Table 4-2). As shown in Table 4-2, with the exception of dairy and some
poultry operations, SBA's small business definition for these sectors more or less corresponds to
operations with fewer than 1,000 AU being considered small businesses.
EPA then estimates the total number of small businesses in these sectors using facility size
distribution data from USDA (step 2). Using the threshold sizes identified for small businesses in the
4-4
-------
livestock and poultry sectors (Table 4-2), EPA matches these thresholds with the number of operations
associated with the size thresholds, based on available USDA data, to estimate the total number of small
animal confinement operations in these sectors. EPA's estimates of the number of potential CAFOs,
derived from these USDA data (Kellogg, 2002), are presented in Section 3.1 of this report. This
constitutes the primary data source that EPA uses to match the small business thresholds corresponding
to SBA's definitions.
Because the USDA data are organized by broad AU groupings—operations with more than 1,000
AU, 750 AU, 500 AU and 300 AU—EPA has matched the animal thresholds above to the closest
available AU grouping as follows. For hogs, EPA assumes that data reported for the 1,000 AU threshold
(about 2,500 hogs) provide a close approximation of the 2,100 hog threshold to 'determine the number of
small businesses in this sector. For dairies, EPA assumes that the 500 AU threshold (about 350 dairy
cows) approximates the 300 dairy cow threshold. For turkey and egglaying operations with dry manure
systems, EPA assumes that the 750 AU threshold (about 61,500 layers and 38,500 turkeys) approximates
the 61,000 layers and 37,500 turkeys threshold. Because egg-laying operations with wet manure systems
are regulated based on a different AU threshold (1,000 AU is equivalent to 30,000 birds), EPA assumes
that all estimated operations for this category are small businesses. The resultant estimates of the number
of small businesses in these sectors derived under these assumptions, in conjunction with available
USDA data (Kellogg, 2002), are presented in Table 4-2.
For both cattle and broilers, EPA also relies on data on operations with more than 1,000 AU
(corresponding to operations with 1,000 beef, veal, and heifers, and about 125,000 broilers), but uses
these data as a starting point to assess the total number of small businesses in these sectors. To further •
determine the number of small businesses with more than 1,000 AU (corresponding to operations with
less than 1,400 cattle and 375,000 broilers, as shown in Table 4-1), EPA assumes that, for cattle, about
40 percent of operations with more than 1,000 AU are potentially small businesses. This assumption is
based on available USDA data on the share of feedlots with between 1,000 and 2,000 head, calculated as
a share of all operations with more than 1,000 AU (Krause, 1991). For broilers, EPA assumes that nearly
all operations are small businesses, with the exception of the largest 330 operations, which EPA assumes
have more than 375,000 birds. This assumption is consistent with that assumed for the 2001 Proposal
and is consistent with USDA broiler sales data and information (USDA/NASS, 2000a). The resultant
estimates of the number of small businesses in these sectors using this approach, in conjunction with
USDA data (Kellogg, 2002) are presented in Table 4-2.
USDA estimates that there were approximately 238,000 animal confinement facilities in 1997
(see Section 3). Table 4-2 presents EPA's estimates of the total number of small livestock and poultry
operations that are potentially small businesses. Using the approach outlined in this section, EPA
estimates that about 227,000 operations (95 percent of all operations)are small businesses. However, not
all of these operations would be affected by the CAFO regulations.
EPA recognizes that this approach might not accurately portray actual small businesses in all
cases across all sectors. On the one hand, the resulting small business estimate would suggest that a 15-
to 20-house broiler operation with 375,000 birds would be a small business. Information from industry
sources, however, suggests that a two-house broiler operation with roughly 50,000 birds is small
(Madison, 1999; USEPA, 2000d). Therefore, it is likely that some medium- and large-size broiler
operations are being considered small businesses (USEPA, 2000e).
On the other hand, it is possible that the resulting small business estimate might have failed to
identify some small businesses in the other sectors as "small." For example, EPA's approach identifies
4-5
-------
as a "small business" hog operations with fewer than 2,500 pigs and turkey operations with fewer than
41,250 turkeys, which account for less than 93 percent and 80 percent of all operations, respectively, and
less than 40 percent of sales in these sectors (Kellogg, 2002). These proportions are below SBA's
presumed coverage rates, which define as small about 99 percent of all operations and account for
approximately 62 percent of sales (Perez, 2000). Therefore, it is likely that there are additional small hog
and turkey businesses that are not captured under the revised methodology (USEPA, 2000e).
Table 4-2. Number of Small CAFOs That Might Be Affected by the CAFO Regulations
Sector
Cattle*
Dairy
Hogs
Broilers
Egg Layers
Turkeys
AH AFOs
Total
Annual
(Smillion)
Revenue"
00
$1.5
$0.75
$0.75
$0.75
$9.0
$1.5
$0.75
NA
Revenue
per
Head b/
(Avg. U.S.)
(y)
$1,060
$2,573
$363
$2
$25
$20
NA
Number
of Animals at
Small CAFO
Businesses
(z = x/y)
1,400
300
2,100
375,000
365,000
61,000
37,500
NA
Estimated
Number of
AFOs
21,800
94,800
51,800
17,800
ND
6,400
3,300
237,800 "
Total
"Small"
AFOs
20,430
91,360
47,850
17,450
ND
5,460
2,660
227,120 "
Small
Business
CAPOs
1,200
1,294
1,485
1,822
ND
486
27
6,314
NA=Not Applicable. ND = Not Determined. "AFOs" have confined animals on-site.
•'SBA size standards are at 13 CFR Part 121. EPA assumes an alternative definition of $1.5 million in annual
revenues for egg laying operations.
v Average revenue per head across all operations for each sector derived from data obtained from USDA's 1997
ARMS data (USDA/ERS, 1999a). For more information, see Section 4 of EPA's Proposal EA (USEPA, 2001a).
rfTotal small business CAFOs do not include estimates of designated CAFOs.
* Includes fed cattle, veal and heifers.
"'USDA total include estimates of the number of operations with "cattle other than fattened cattle or milk cows" and
also adjusts for double counting, accounting for roughly 42,000 operations (Kellogg, 2002). See Section 3. EPA's
total for broilers and egg layers also differs because of differing 1,000 AU definitions (see Section 3).
The final step (step 3) in EPA's approach is to estimate the number of small businesses subject to
the CAFO regulations based on the regulatory thresholds being promulgated, as discussed in Section 3 of
this report. Not all small confinement operations would be subject to the CAFO regulations. The final
regulations apply only to those operations that meet the regulatory definition of a CAFO or those that
have been designated as CAFOs by the NPDES permitting authority because of risks posed to water
quality and public health, as discussed in Section 1. The regulations define as a CAFO those operations
that confine more than 1,000 AU, as well as a subset of operations with between 300 and 1,000 AU. The
final regulations may also apply to an operation that is designated as a CAFO by the NPDES permitting
authority on a case-by-case basis, based on an on-site inspection. As described in this section, EPA's
estimates of the number of operations is based on USDA information for 1997 (Kellogg, 2002), which
4-6
-------
constitutes the primary data source that EPA uses to determine the number of potential small businesses
that might be subj ect to the regulations.
Table 4-3 presents the estimated number of livestock and poultry operations that might be subject
to the CAFO regulations and are also small businesses ("small business CAFOs") by facility size
category. EPA estimates that of the approximately 238,000 animal confinement facilities in 1997
roughly 95 percent are small businesses. Not all of these operations would be affected by the final rule.
Table 4-3 shows EPA's estimates of the number of small business CAFOs that are expected to be
affected by this rule. For this analysis, EPA estimates that about 6,200 affected CAFOs across all size
categories are small businesses, accounting for more than 40 percent of the estimated 14,515 affected
facilities. EPA estimates that among CAFOs with more than 1,000 AU about 2,330 operations are small
businesses (accounting for about one-fourth of all CAFOs in this size category). Most affected small
businesses are in the broiler sector. Among CAFOs with between 300 and 1,000 AU, EPA estimates
about 3,830 operations are small businesses, with most of the affected small businesses are in the hog,
dairy, and broiler sectors.
These estimates are based on USDA data for 1997. Because of continued consolidation and
facility closure since 1997, EPA's estimates might overstate the actual number of small businesses hi
these sectors. Ongoing trends are causing some existing small and medium operations to expand their
inventories to achieve economies of scale. Some of the CAFOs considered here as small businesses
might no longer be counted as small businesses because they now have higher revenues. Furthermore,
some CAFOs might now be owned by a larger, vertically integrated firm and might no longer be small
businesses. EPA expects that there are few such operations, but it does not have data or information to
reliably estimate the number of CAFOs that meet this description. In addition, for reasons noted in the
record, EPA believes that the number of small broiler operations is overestimated and might actually
include a number of medium and large broiler operations that should not be considered small businesses.
Table 4-3 also shows the expected number of small businesses that may be designated as CAFOs
and subject to the rule. EPA estimates that about 172 operations will be designated as CAFOs. This
estimate is expressed over the 5-year permit period (that is, assumes that roughly 35 operations will be
designated annually). Among these, an estimated 160 operations are in the 300 to 1,000 AU size
category; about 12 operations have fewer than 300 AU. (See Table 3-1.) EPA assumes that all of these
operations are small businesses.32 For analysis purposes, EPA also assumes that these operations are
located hi more traditional production regions and are characterized by operations with available land for
land application of manure but also high technology needs (see discussion in Section 4.4).
32EPA expects that USDA will continue to provide voluntary assistance to those additional operations that
are now defined as CAFCJs under the current permitting requirements and are not covered by the final regulations.
4-7
-------
Table 4-3. Total Number of Small Business CAFOs Subject to Regulation
Sector
Fed Cattle
Veal
Heifers
Dairy
Hogs
Broilers
Layers
Turkeys
Total
All AFOs
Total Small
Business AFOs
Small Business
CAFOs
>1,000 AU
(Defined)
Small Business
CAFOs
300-1000 AU
(Defined)
Small Business
CAFOs
(Designated)
(Number of operations)
17,800
3,840
170
94,790
51,770
17,780
6,450
3,310
237,820 "
16,570
. 160
3,700
91,360
47,850
17,450
5,460
2,660
227,120 w
538
5
97
0
0
1,303
383
0
2,326
174
7
230
1,330
1,485
520
48
31
3,825
15
0
'.
30
52
52
10
10
172 b/
numbers are rounded to the nearest ten.
•'USDA total include estimates of the number of operations with "cattle other than fattened cattle or milk cows" and
also adjusts for double counting, accounting for roughly 42,000 operations (Kellogg, 2002). See Section 3. EPA's
total for broilers and egg layers also differs because of differing 1,000 AU definitions (see Section 3).
"^Number of designated facilities shown over 5-year permit period. EPA assumes all estimated designated facilities
are small businesses.
4.2.3 Results of the Initial Assessment for the 2001 Proposal
For past regulations, EPA has often analyzed the potential impacts to small businesses by
evaluating the results of a costs-to-sales test, measuring the number of operations that will incur
compliance costs at varying threshold levels (including ratios where costs are less than 1 percent,
between 1 and 3 percent, and greater than 3 percent of gross income),33 EPA conducted such an analysis
at the time of the 2001 proposal, indicating that about 80 percent of the estimated number of small
businesses directly subject to the rule as CAFOs might incur costs in excess of three percent of sales.
These results were based on an assessment of the potential impacts on small CAFO businesses based on
the results of a sales test for all operations with more than 500 AU. This screening test indicated the
33 EPA believes that its more refined analysis used for its general analysis (presented in Section 3 of this
EA) better reflects the potential impacts to regulated small businesses.
4-8
-------
need for additional analysis to characterize the nature and extent of impacts on small entities. This
assessment is conducted for those CAFOs that are small businesses, as determined by EPA.
The results of this screening test for the 2001 Proposal indicate that, measured against all
confinement operations with more man 500 AU, about 80 percent of the estimated number of small
businesses could incur costs in excess of 3 percent of sales. Compared to the total number of all small
animal confinement facilities estimated by EPA, operations that are estimated to incur costs in excess of
three percent of sales constitute less than two percent of all small businesses in these sectors. The results
of this analysis are presented in Section 9.2.3 of the Proposal EA.
Based on the results of this initial assessment, EPA projected that it would likely not certify that
the regulations would not impose a significant impact on a substantial number of entities. This is
because EPA's initial assessment indicates that the regulations could impose a significant economic
impact on a substantial number of entities. Therefore, prior to the 2001 Proposal, EPA convened a
SB AR Panel and prepared an initial regulatory flexibility analysis (TRFA) pursuant to Sections 609(b)
and 603 of the RFA, respectively, and prepared an economic analysis. Sections 4.3 and 4.4 of this report
present the results of EPA's final regulatory flexibility analysis (FRFA).
4.3 EPA COMPLIANCE WITH RFA REQUIREMENTS
4.3.1 Outreach and Small Business Advocacy Review
As required by Section 609(b) of the RFA, as amended by SBREFA, EPA convened a SBAR
Panel for the proposed rule. See 66 FR 3121-3124; 3126-3128 (January 12, 2001). The Panel was
convened in December 1999. Panel participants included representatives from EPA, the Office of
Information and Regulatory Affairs within the Office of Management and Budget (OMB), and the Office
of Advocacy of the Small Business Administration (SB A). "Small Entity Representatives" (SERs), who
advised the Panel, included small livestock and poultry producers as well as representatives of the major
commodity and agricultural trade associations. Throughout the development of these regulations, EPA
conducted outreach to small businesses in the livestock and poultry sectors. EPA also consulted with
SBA on the use of an alternative definition of small business for the egg laying sector.
Consistent with the RFA/SBREFA requirements, the Panel evaluated the assembled materials
and small entity comments on issues related to the elements of the IRFA. The Panel's activities and
recommendations are summarized in the Final Report of the Small Business Advocacy Review Panel on
EPA's Planned Proposed Rule on National Pollutant Discharge Elimination System (NPDES) and
Effluent Limitations Guideline (ELG) Regulations for Concentrated Animal Feeding Operations (April 7,
2000), or "Panel Report" (USEPA, 2000e). This document is included in the public record (DCN
93001). Section 12 of the preamble to the 2001 Proposal provides a summary of the Panel's activities
and recommendations and describes the subsequent action taken by the Agency (see 66 FR 3121-3124).
Section 12 of the preamble to the 2001 Proposal also details various outreach activities conducted by
EPA, which include outreach to small businesses in these sectors.
For the 2001 Proposal, EPA prepared an economic analysis of the impacts on small businesses,
which is provided in Section 9.4 of the Proposal EA. EPA's economic analysis supporting the final
regulations is provided in Section 4.4 of this report.
4-9
-------
For all final regulations for which an FRFA is prepared, Section 212 of the UFA requires that the
Agency also issue a small entity compliance guide providing a plain language explanation of how to
comply with the final regulations. EPA's small entity compliance guide for the CAFO regulations will
be issued following promulgation.
4.3.2 EPA's Final Regulatory Flexibility Analysis
For the proposed regulations, EPA has conducted an IRFA, as required by Section 603 of the
RFA, as amended by SBREFA. The IRFA must contain the following: (1) a description of the reasons
why action by the agency is being considered; (2) a succinct statement of the objectives of, and legal
basis for, the proposed rule; (3) a description of and, where feasible, an estimate of the number of small
entities to which the proposed rule will apply; (4) a description of the projected reporting, recordkeeping,
and other compliance requirements of the proposed rule, including an estimate of the classes of small
entities that will be subject to the requirement and the type of professional skills necessary for
preparation of the report or record; and (5) identification, to the extent practicable, of all relevant Federal
rules that might duplicate, overlap or conflict with the proposed rule. The IRFA shall also contain a
description of any significant alternatives to the proposed rule that accomplish the stated objectives of
applicable statutes and that minimize any significant economic impact of the proposed rule on small
entities. Sections 9.3.2.1 through 9.3.2.6 of the Proposal EA show how EPA addressed each of these
requirements in the IRFA it prepared to support the 2001 Proposal. EPA also prepared an economic
analysis of the impacts on small CAFO businesses, which is provided in Section 9.4 of the Proposal EA
(USEPA, 2001a).
For the final regulations, EPA has conducted an FRFA, as required by Section 604 of the RFA,
as amended by SBREFA. The FRFA addresses the issues raised by public comments on the IRFA, which
was part of the proposal of this rule. The FRFA must contain: (1) a succinct statement of the need for,
and objectives of, the rule; (2) a summary of the significant issues raised by the public comments in
response to the initial regulatory flexibility analysis, a summary of the assessment of the agency of such
issues, and a statement of any changes made in the proposed rule as a result of such comments; (3) a
description of and an estimate of the number of small entities to which the rule will apply or an
explanation of why no such estimate is available; (4) a description of the projected reporting,
recordkeeping, and other compliance requirements of the rule, including an estimate of the classes of
small entities that will be subject to the requirement and the type of professional skills necessary for
preparation of the report or record; and (5) a description of the steps the agency has taken to minimize the
significant economic impact on small entities consistent with the stated objectives of applicable statutes,
including a statement of the factual, policy, and legal reasons for selecting the alternative adopted in the
final rule and why each one of the other significant alternatives to the rule considered by the agency that
affect the impact on small entities was rejected. Sections 4.3.2.1 through 4.3.2.5 of this report address
each of these FRFA requirements.
4.3.2.1 Need for and Objectives of the CAFO Regulations
A detailed discussion of the need for the regulation is presented in Section 4 of the 2001
Proposal (66 FR 2293-2972-2976). A summary is also provided in Sections 1 and 10 of the Proposal EA.
In summary, EPA's rationale for revising the existing regulations include the following: address reports
of continued discharge and runoff from livestock and poultry operations in spite of the existing
4-10
-------
requkements; update the existing regulations to reflect structural changes in these industries over the past
few decades; and improve the effectiveness of the existing regulations.
Despite nearly 30 years of regulation, there are persistent reports of discharge and runoff of
manure and manure nutrients from livestock and poultry operations. Revisions to the existing ELG and
NPDES regulations for CAFOs are expected to mitigate future water quality impairment and the
associated human health and ecological risks by reducing pollutant discharges from the animal
production industries.
EPA's revisions also address the changes that have occurred in the animal production industries
in the United States since the development of the existing regulations. The continued trend toward fewer
but larger operations, coupled with greater emphasis on more intensive production methods and
specialization, is concentrating more manure nutrients and other animal waste constituents within some
geographic areas. This trend has coincided with increased reports of large-scale discharges from these
facilities and continued runoff that is contributing to the significant increase in nutrients and resulting
impairment of many U.S. waterways.
EPA's revisions to the existing regulations will make the regulations more effective in protecting
or restoring water quality. The revisions will also make the regulations easier to understand and will
clarify the conditions under which an AFO is a CAFO and, therefore, subject to the regulatory
requirements.
A detailed discussion of the objectives and legal basis for these regulations is presented in
Sections 1 and 3 of the preamble to the final rule and also the 2001 Proposal (see: 66 FR 2959 or
USGPO, 2001a).
4.3.2.2 Significant Comments in Response to the IRFA
The significant issues raised by public comments on the IRFA address exemptions for small
businesses, disagreement with SBA definitions and guidance on how to define small businesses for these
sectors, and general concerns about EPA's financial analysis and whether the analysis adequately
captures potential financial effects on small businesses.
Commenters generally recommend that EPA exempt all small businesses from regulation,
arguing in some cases that regulating small businesses could affect competition in the marketplace,
discourage innovation, restrict improvements in productivity, create entry barriers, and discourage
potential entrepreneurs from introducing beneficial products and processes. Several commenters claimed
that EPA had misrepresented the number of small businesses. In particular, several commenters obj ected
to SBA's small business definition for dairy operations, claiming it understates the number of small
businesses in this sector (see, for example, NMPF, 2001). One commenter claimed that EPA's estimate
of the total number of operations is understated and therefore must understate the number of small
businesses (Department of Agriculture, 2001). Some commenters objected to the consideration of total
farm-level revenue to determine the number of small businesses because this approach understates the
number of small businesses, despite SBA guidance that bases its' definitions on total entity revenue for
purposes of defining a small business (NCBA, 2001). Other commenters, however, claimed that EPA's
approach does not truly capture operations that are, in fact, small businesses but reflect larger corporate
operations (see, for example, Citizens Against Poultry Pollution, 2001). Another commenter
, 4-11
-------
recommended that EPA simply consider any operation with fewer than 1,000 AU as small businesses
(Wyoming Office of Federal Land Policy, 2001). EPA also received comments requesting that EPA
consider use of regional-specific definitions of small business because of concerns that the revenue-based
SBA definition might not be applicable to operations in Hawaii since producers in that State generally
face higher cost of production and also higher producer prices relative to revenue and cost conditions at
farms in the contiguous 48 States. Comments from SBA recommended that EPA adopt the Panel's
recommendation not to consider changing the designation criteria for operations with fewer than 300
animal units as a means to provide relief to small businesses (SBA, 2001). SBA also recommends that
EPA adopt the SBAR Panel's approach and allow permitting authorities to focus resources where there is
greatest need (SBA, 2001). Finally, some commenters generally questioned the results of EPA's
financial analysis, giving similarly stated concerns about EPA's financial data and models used for its
main analysis (see, for example, NCBA, 2001).
In resp'onse, EPA notes that the projected impacts of today's final regulations on small
businesses are lower than the projected impacts of the proposed rule. For example, the final rule does
not extend the effluent guideline regulations to CAFOs with between 300 and 1,000 AU, as was proposed
in the 2001 proposal. Instead, EPA is retaining the existing regulatory threshold, applying the effluent
guideline to CAFOs with more than 1,000 AU only. Requirements for CAFOs with between 300 and
1,000 AU will continue to be subject to the BPJ requirements as determined by the permitting authority,
thus requiring that fewer small businesses adopt the effluent guideline standards. More information on
this topic is available hi section IV of this preamble. Section 4 of the final rule preamble discusses other
regulatory changes since the 2001 proposal, indicating greater alignment with SBAR Panel
recommendations. Refer to Section 4'of the preamble for more information on the comments and EPA's
responses to those comments, as well as EPA's justification for final decisions on these options.
EPA received two comments form one commenter requesting that EPA not use the alternative
definition for egg-laying operations but instead consider regional-specific conditions for determining the
number of small businesses. The commenter expressed concern that SBA's revenue-based definition
might not be applicable to operations in Hawaii since producers in that State generally face higher cost of
production and also higher producer prices relative to revenue and cost conditions at farms in the
contiguous 48 States. There are a number of reasons why EPA did not use a regional-specific definition
of small business for egg operations. First, as instructed under the Regulatory Flexibility Act (RFA),
EPA uses small business definitions as defined by the Small Business Administration (SBA) for all
sectors (except for the egg-laying sector). Since size standards set by the Small Business Administration
(SBA) do not vary by region, EPA follows SBA's lead. Second, the regulations set requirements by the
number of animal units at a farm, not the revenues associated with those animal units. A 1,000 AU egg-
laying operation hi the Midwest will be subject to the same effluent limitations guidelines as a 1,000 AU
egg-laying operation in Hawaii and the territories. Third, the economic analysis, uses a representative
farm approach. Only the broadest regional information could be obtained through USDA and other
sources. Although some small subregions or localities might face unique issues, without performing a
Section 308 survey of all regulated entities EPA must rely on the representative farm approach. (See also
response to comment DCN CAFO201246C-6 regarding EPA's u,se of a representative farm approach,
which is consistent with lonstanding practices at USDA and the land grant universities.) Fourth, very
few impacts are seen hi the egg-laying sector, regardless of size. Even if EPA had classified the maj ority
of egg-laying operations with less than 1,000 AU as small businesses, this would not have changed the
outcome of the Agency's small business analysis hi any material way. Finally, even if EPA were to
classify all operations as small businesses in areas outside the contiguous 48 States (including Hawaii
and Alaska), this would only raise the total number of small business by less than 10 operations. See
4-12
-------
response to comment DCN CAFO NODA600053-5 regarding EPA's consideration of regional-specific
definition of small business for the regulated sectors.
Regarding EPA's estimate of the number of small businesses, the Agency continues to follow
SBA guidance and SBA definitions on how to define small businesses for these sectors. However, EPA
has made substantial changes to the financial data and models used for its main analysis, which is also
used to evaluate financial effects on small businesses. Both the 2001 Notice (66 FR 58556) and the
2002 Notice (67 FR 48099) describe the public comments received by EPA on the baseline financial data
and the methodological approach developed by the Agency to evaluate financial effects. These
comments and how EPA has addressed them are discussed more fully throughout this report. EPA's
detailed responses to comments, and the comments themselves, are contained in the Agency's comment
response document (see, for example, DCN CAFO200179D-3).
4.3.2.3 Description and Estimate of Number of Small Entities Affected
The small entities subject to this rule are small businesses. No nonprofit organizations or small
governmental operations operate CAFOs. As discussed in section 7 of the preamble to the final rule, to
estimate the number of small businesses affected by this final rule, EPA relied on the SBA size standards
for these sectors, with the exception of size definitions for the egg sector. SBA defines a "small
business" in these sectors as an operation with average annual revenues of less than $0.75 million for
dairy, hog, broiler, and turkey operations; $1.5 million in revenue for beef feedlots; and $9.0 million for
egg operations. The definitions of small business for the livestock and poultry industries are in SBA's
regulations at 13 CFR 121.201. For this rule, EPA proposed and solicited public comment on and is
using an alternative defintion fo small business for the egg-laying operations. EPA defines a "small" egg
laying operation for purposes of its regulatory flexibility assessments as an operation that generates less
than $1.5 million in annual revenue. EPA consulted with SBA on the use of this alternative definition, as
documented in the rulemaking record for the 2001 proposal. Given these considerations^ EPA evaluates
"small business" for this rule as an operation that houses or confines fewer than 1,400 fed beef cattle
(includes fed beef, veal, and heifers); 300 mature dairy cattle; 2,100 market hogs; 37,500 turkeys; 61,000
layers; or 375,000 broilers. The approach used to derive these estimates is described in Section 4.2.
Using these definitions and available data from USDA and industry, EPA estimates that about
6,200 affected CAFOs across all size categories are small businesses. Among CAFOs with more than
1,000 AU, EPA estimates that about 2,330 operations are small businesses. Among CAFOs with
between 300 and 1,000 AU, EPA estimates that about 3,870 operations are small businesses. Table 4.3
shows EPA's estimates of the number of regulated small businesses across all industry sectors. Table 4.4
provides this information by sector and by representative CAFO model.
4-13
-------
Table 4-4. Numbers of Small CAFO Businesses by Sector, Size Grouping, and Region
Source: USEPA. Preliminary based on estimates associated with the August 4,2002, cost estimates. Size and
region breakouts are based on an analysis of the 1997 Census data by USDA (Kellogg, 2002). Facility size and
region definitions for model CAFOs are provided in Section 2, Table 2-1. Shaded cells indicate that there are no
small CAFO businesses that will be affected by the regulations and that meet the SB A definition of a small
business. Estimates do not include number of designated CAFOs.
4-14
-------
4.3.2.4 Description of the Reporting, Recordkeepingfdnd Other Requirements
The final regulations would require all AFOs that meet the CAFO definition to apply for a
permit, develop and implement a nutrient management plan, collect and maintain records required by
applicable technology-based effluent discharge standards, and submit an annual report to the responsible
NPDES permitting authority. (No nonprofit organizations or small governmental operations operate
CAFOs.) All CAFOs would also be required to maintain records of off-site transfers of manure. Record-
keeping and reporting burdens include the time to record and report animal inventories, manure
generation, field application of manure (amount, method, date, weather conditions), manure and soil
analysis results, crop yield goals, findings from visual inspections of feedlot areas, and corrective
measures. Records may include manure spreader calibration worksheets, manure application worksheets,
maintenance logs, and soil and manure test results. EPA believes the owner/operator has the skills
necessary to keep these records and make reports to the permitting authority.
State permitting authorities will incur reporting burdens when they update their NPDES
programs to incorporate the regulatory changes in the final rule. They will incur record keeping burdens
as they implement the final rule. Data collection and record keeping activities include reviewing CAFO
permit applications and periodic reports, and tracking compliance through on-site inspections.
EPA has estimated the burden and costs associated with information collection imposed on
CAFOs, including small businesses, and also States as a result of the CAFO regulations. This analysis is
provided in the Information Collection Request for the Final NPDES and ELG Regulatory Revisions for
Concentrated Animal Feeding Operations (EPA ICR NO. 1989.02) prepared by EPA (USEPA, 2002J),
which updates an analysis conducted for the 2001 Proposal (USEPA, 2000f).
For the purpose of this analysis, "burden" means the total time, effort, or financial resources
expended by persons to 'generate, maintain, retain, or disclose or provide information to or for a federal
agency. This includes the time needed to review instructions; develop, acquire, install, and utilize
technology and systems for the purposes of collecting, validating, and verifying information, processing
and maintaining information, and disclosing and providing information; adjust existing procedures to
comply with any previously applicable instructions and requirements; train personnel to be able to
respond to a collection of information request; search data sources; complete and review the collection of
information; and transmit or otherwise disclose the information.
EPA's labor burden estimates for CAFO and State respondents are the hours of activity required
to comply with changes to the NPDES CAFO program. For each activity, EPA estimates the burden in
terms of the expected effort necessary to carry out these activities under normal conditions and
reasonable labor efficiency. These activities and estimated burden and cost levels are described in more
detail in the Supporting Statement for the ICR (USEPA, 2002J). The ICR also contains a summary of
wage rate information from USD A and the Bureau of Labor Statistics, compiled by EPA for the purpose
of this analysis. Additional information on the ICR is provided in the preamble supporting the final
regulations. A summary of the analysis of impacts to CAFO operators is provided below. Additional
information on the estimated burden and costs is provided in the ICR (USEPA, 2002J).
EPA identifies four burden categories to CAFO operators, including start-up activities, permit
application, best available technology requirements, and NPDES record keeping and reporting
requirements.
4-15
-------
Start-up activities are steps that a CAFO owner or operator must take in preparation to comply
with the information collection requirements of the final rule. Owners or operators that are potentially
affected by the rule will need to familiarize themselves with the changes to the NPDES CAFO program
to determine that they will need to apply for a permit.
Permit application activities include completing and submitting either an NOI to obtain coverage
under a general permit or an application for an individual permit. These activities will be conducted once
every five years. The final rule requires that the following information be provided on the application
forms: the name of the owner or operator; facility address and mailing address; latitude and longitude of
the production area; a topographic map; the type and number of animals in open confinement and housed
under a roof; the type of containment and total capacity for manure, litter, and wastewater storage; the
number of acres for land application; the estimated amount of manure generated per year; and estimated
amount of manure transferred off site each year. As part of their record keeping responsibilities, CAFO
operators will be required to keep the plan on site for inspections and make it available to the permitting
authority on request. Nutrient management plans must be reviewed and rewritten at least every five
years.
CAFO owners or operators will perform and record various activities to meet the BAT
requirements such as visual inspections of the feedlot facilities, inspections of manure application
equipment, collection of soil samples, and recording of volume of manure and process wastewater
produced. CAFOs with more than 1,000 AU will also be required to record information for transfers of
manure, litter, and process wastewater to other people.
In addition to the labor costs associated with these activities, EPA estimates the capital and
operation and maintenance (O&M) costs incurred to collect data and keep records. A CAFO will incur
capital costs when it purchases equipment or builds structures that are needed for compliance with the
rule's reporting and record keeping requirements that the facility would not use otherwise. Consistent
with the overall cost analysis for the final rule, capital costs are annualized assuming a 10-year
amortization period and a 7 percent interest rate. Capital costs for the final rule include such items as
purchasing a soil auger to collect soil samples and a manure sampler. Some facilities will also need to
install depth markers in their lagoons. A facility incurs O&M costs when it regularly uses services,
materials, or supplies needed to comply with the rule's reporting and record keeping requirements that the
facility will not use otherwise. Any cost for the operation and upkeep of capital equipment is considered
an O&M cost. O&M costs may also be incurred on a non-annual basis, such as every five years for a soil
analysis. O&M costs include laboratory analysis of soil and manure.
EPA estimates that the public burden for this information collection request will require 1.6
million labor hours for all CAFO respondents to comply with the final regulations and 0.3 million labor
hours for State permitting authority respondents (USEPA, 2002J). Information collection and reporting
at a CAFO is associated with applying for permits, developing nutrient management plans, conducting
site inspections, tracking land application and off-site manure transfers. These estimates include the time
required to review instructions, search existing data sources, gather and maintain all necessary data, and
complete and review the information collection. EPA estimates costs to regulated CAFOs at $29 million
annually, which includes $25 million hi labor costs and $4 million capital and O&M expenditures;
annual State costs of $10 million include $8.6 million in labor costs and $1.6 million in O&M
expenditures (USEPA, 2002J). This estimate excludes NPDES burden for CAFOs covered by other ICR
estimates.
4-16
-------
Under the final rule, EPA estimates that there will be an annual average of 11,712 CAFO
respondents and an annual average of 82,705 CAFO responses, which includes multiple responses per
CAFO. Thus, the annual average burden per CAFO respondent is 138 hours and the average burden per
CAFO response is 19 hours. For this analysis, EPA assumes that the administrative burden assumptions
are generally the same regardless of CAFO size. The annual average burden per State respondent is
10,152 and the average burden per response is 16 hours (USEPA, 2002J).
More detailed information on the burden and associated costs for each of the activities described
above is provided in the ICR (USEPA, 2002J). Section 10 of the final rule preamble further summarizes
the expected reporting and record-keeping requirements under the final regulations based on information
compiled as part of the Information Collection Request for the Final NPDES and ELG Regulatory
Revisions for Concentrated Animal Feeding Operations (OMB ICR NO. 2040-0250) prepared by EPA.
4.3.2.5 Steps Taken to Minimize Significant Economic Impacts on Small Entities
For the final regulations, EPA has adopted an approach for a regulatory program that mitigates
impacts on small business, recognizes and promotes effective non-NPDES State programs, and works in
partnership with USDA to promote environmental stewardship through voluntary programs, and financial
and technical assistance. EPA's proposal included many options that were not finally adopted in
deference to these principles.
Because of the estimated impacts on small entities EPA is not certifying that this rule will not
impose a significant impact on a substantial number of small entities. EPA has complied with all RFA
provisions and conducted outreach to small businesses, convened a SBAR panel, prepared an Initial
Regulatory Flexibility Analysis (IRFA) and a Final Regulatory Flexibility Analysis (FRFA), and also
prepared an economic analysis. The Agency's actions include the following efforts to minimise, impacts
on small businesses:
• Retained structure of existing regulations, which allows EPA and states to focus on the
largest producers;
• Retained existing designation criteria and process;
• Retained existing definition of an AFO;
• Retained conditions for being defined as a Medium CAFO;
• Eliminated the "mixed" animal calculation for operations with more than a single animal
type for determining which AFOs are CAFOs;
• Raised the duck threshold for dry manure handling duck operations; and
• Adopted a dry-litter chicken threshold higher than proposed.
EPA went to some length to explore and analyze a variety of ELG regulatory alternatives to
minimize impacts on small businesses. The record for today's rule includes extensive discussions of the
alternatives, EPA's analysis of those alternatives, and the rationale for the Agency's decisions. In large
part, the Agency incorporated most of the alternative considerations to reduce the burden to small
businesses. By way of example, today's regulations will affect fewer small businesses at significantly
reduced costs, as compared to the estimates of the number of operations and expected costs to those
affected entities based on the requirements set forth in the 2001 proposal. For more information on
EPA's option selection rationale, see Section 4 of the preamble to the final rule.
4-17
-------
4.4 EPA'S ANALYSIS OF SMALL BUSINESS IMPACTS
This section discusses the data and methodology EPA uses to assess economic impacts on small
CAFO businesses (Section 4.4.1) and presents the results of this analysis (Section 4.4.2). This economic
analysis supports the FKFA (Section 4.3) by quantifying the effects of the CAFO regulations. Based on
the results of this analysis, EPA has determined that the CAFO regulations would result in financial
stress to some affected small businesses, but not a substantial number of operations relative to the total
number of affected small businesses in these sectors.
4.4.1 Data-and Methodology
To examine the economic impacts of the final regulations on small CAFO businesses, EPA uses
the same representative farm approach that is used to analyze impacts on all CAFOs (regardless of size),
as described in Section 2 of this EA.34 This approach evaluates impacts on select model CAFOs and
extrapolates these results to the number of operations identified by each representative model, thus
aggregating costs nationally across all sectors. Inputs for this analysis include the number of CAFOs
represented by each model (see Section 4.3.3) and, for each model CAFO, the costs of the final
regulations and selected financial characteristics (see Section 2).
EPA's analysis evaluates the economic achievability of the final regulatory options at small
CAFO businesses based on financial criteria established for this analysis. These criteria reflect a
combination of both farm level and enterprise level criteria. Three farm level criteria are assessed: (1) a
comparison of incremental costs to total revenue (sales test), (2) projected post-compliance cash flow
over a 10-year period, and (3) an assessment of an operation's debt-asset ratio under a post-compliance
scenario. Projected post-compliance cash flow over a 10-year period is also assessed at the enterprise
level in order to evaluate the potential effects at a facility's livestock or poultry enterprise, apart from the
effects assessed for the entire facility.
EPA used the results from these analyses to divide affected CAFOs into three financial impact
categories: Affordable, Moderate, and Stress. CAFOs experiencing affordable or moderate impacts are
considered to experience some financial impact on operations, but EPA does not expect the costs of
complying with this rule to make such operations vulnerable to closure. EPA considers that for CAFOs
in both the "Affordable" and "Moderate" impact categories the final requirements are economically
achievable. Operations experiencing financial stress, however, are considered to be vulnerable to' closure
because of the costs of this rule. EPA considers that for CAFOs in the "Stress" impact category, the final
requirements might not be economically achievable, subject to other considerations. For more
information on this decision framework, see Table 2-8 and Figure 2-1.
EPA conducted its analysis first at the farm level based on data reflecting financial conditions for
the entire farm operation (e.g., reflecting income and cost information spanning the entire operation, thus
34 For past regulations, EPA has often analyzed the potential impacts to small businesses by evaluating the
results of a costs-to-sales test, measuring the number of operations that will incur compliance costs at varying
threshold levels. EPA conducted such an analysis at the time of the 2001 proposal, but believes that its more
refined analysis used for its general analysis better reflects the potential impacts to regulated small businesses.
4-18
-------
considering the operation's primary livestock production, along with other income sources such as
secondary livestock and crop production, government payments, and other farm-related income). Based
on the farm level results, EPA also assessed the financial effects on CAFOs at the enterprise level (e.g.,
limiting the scope of the assessment to the operation's livestock or poultry enterprise, and excluding
other non CAFO-related sources of income from the analysis).
Starting with the farm level analysis, EPA considers the regulations to be economically
achievable for a representative model CAFO if the average operation has a post-compliance sales test
estimate within an acceptable range, a positive post-compliance cash flow over a 10-year period, and a
post-compliance debt-to-asset ratio not exceeding a benchmark value. Specifically, if the sales test
shows that compliance costs are less than 3 percent of sales, or if post-compliance cash flow is positive
and the post-compliance debt-to-asset ratio doss not exceed a benchmark (depending on the baseline
data) and compliance costs are less than 5 percent of sales, EPA considers the options to be "Affordable"
for the representative CAFO group. (Although a sales test result of less than 3 percent does indicate
"Affordable" in the farm level analysis, further analysis is conducted to determine the effects at the
operation's livestock or poultry enterprise.) The benchmark values assumed for the debt-asset test are
sector-specific. EPA assumes a 70 percent benchmark value for the debt-asset test to indicate financial
stress in the hog and dairy sectors, and an 80 percent benchmark for the debt-asset test to indicate
financial stress in the beef cattle sector. These benchmark values address public comment received and
alternative debt and asset data submitted for the livestock sectors. For the poultry sectors, however, EPA
did not obtain alternative debt and asset data and continues to evaluate data used for proposal against a
40 percent benchmark value.
A sales test of greater than 5 percent but less than 10 percent of sales with positive cash flow and
a debt-to-asset ratio of less than these sector-specific debt-asset benchmark values is considered
indicative of some impact at the CAFO level, but at a level not as severe as those indicative of financial
distress or vulnerability to closure. These impacts are labeled "Moderate" for the representative CAFO
group. EPA considers both the "Affordable" and "Moderate" impact categories to be economically
achievable by the CAFO, subject to the enterprise analysis (see below). If, with a sales test of greater
than 3 percent, post-compliance cash flow is negative or the post-compliance debt-to-asset ratio exceeds
these sector-specific debt-asset benchmarks, or if the sales test shows costs equal to or exceeding 10
percent of sales, EPA considers the final regulations to be associated with potential financial stress for
the entire representative CAFO group. In such cases, each of the operations represented by that group
might be vulnerable to closure. For operations that are determined to experience financial "Stress" at the
farm level, the final requirements are likely not economically achievable.
The enterprise level analysis builds on the farm level analysis, evaluating effects at a farm's
livestock or poultry enterprise. If the farm level analysis shows that the regulations impose "Affordable"
or "Moderate" effects on the operation, the enterprise level analysis is conducted to determine whether
the enterprise's cash flow is able to cover the cost of regulations. This analysis uses a discounted.cash
flow approach similar to that used to assess the farm level effects, in which the net present value of cash
flow is compared to the net present value of the total cost of the regulatory options over the 10-year time
frame of the analysis. Over, the analysis period, if an operation's livestock or poultry enterprise
maintains a cash flow stream that both exceeds the cash costs of the rule (operating and maintenance
costs plus interest) and covers the net present value of the principal payments on the capital, EPA
concludes that the enterprise will likely not close because of the CAFO rule. This analysis is conducted
on a pass/fail basis. If the net present value of cash flow minus the net present value of the rule's costs is
greater than zero, the enterprise passes the test and the enterprise is assumed to continue to operate. EPA
4-19
-------
considers these results to indicate that the final requirements are economically achievable. If the net
present value of cash flow is not sufficient to cover the net present value of the cost of the rule, EPA
assumes that the CAFO operator would consider shutting down the livestock or poultry enterprise. That
is, if an operation fails the enterprise level analysis, these operations are determined to experience
financial "Stress" and the final requirements are likely not economically achievable.
More detail on the classification scheme established for this analysis, along with a discussion of
the basis for EPA's use of these criteria, is provided in Section 2. Section 2.3. presents the baseline
(farm and enterprise level) financial data that EPA uses to analyze impacts on small CAFO businesses.
Appendix B shows EPA's estimated compliance costs for selected model CAFOs under the final
BAT Option. These costs reflect the range of facility level costs for model CAFOs based on estimated
per-unit costs aggregated by the average number of animals assumed for each model. All costs shown
are expressed on a per-animal basis and are differentiated by facility size, producing region, facility
types, and other factors. Costs are reported in ranges across three types of land availability for manure
application and also across three types of technology needs assumed for model CAFOs for the purpose of
this analysis. The land availability types include: Category 1 farms, which have sufficient cropland for
all on-farm nutrients generated; Category 2 farms, which have insufficient cropland; and Category 3
farms, which have no cropland. USDA data/information grouping facilities into the categories of
technology adoption and use are: "least needs" and "most needs" operations (assumed to account for 25
percent each of all facilities) and also "average needs" (assumed to account for 50 percent of all
operations). These groupings are based on available USDA data; detailed information is available in the
Development Document supporting the proposed regulations (USEPA, 2002). Section 2 provides a
summary on EPA's engineering cost models.
To estimate financial effects on operations with between 300 and 1,000 AU that may be defined
as CAFOs under the NPDES permit regulations, EPA assumes that the estimated costs for CAFOs with
between 300 and 1,000 AU to comply with the effluent guideline regulations are similar to the costs that
will be incurred by sized operations of that size to comply with BPJ requirements under the revised
NPDES regulations. Because the costs to comply with the effluent guideline represent the likely high
end of the possible cost range, estimated impacts on operations in this size range might be overstated.
To estimate financial effects on expected designated facilities, EPA uses the same general
approach described in Section 2 of this report to assess impacts on an estimated 344 designated facilities
over a 10-year period.35 For this analysis EPA uses estimated costs for the smallest size model CAFO
among operations with between 300 and 1,000 AU ("Medium" operations)36 for model CAFOs
developed for operations located in the more traditional production regions (Midwest for the livestock
and turkey operations and South for the broiler and egg-laying operations; Table 2-1 shows these
definitions). For example, EPA assumes that operations characterized as having available land for land
application of manure (Category 1 model facilities) and high technology needs ("most needs" or
Category H) may be characterized as Category 1H models for purposes of costing across the range of
35 As shown in Table 3-3, EPA estimates 172 designated facilities over a 5-year permit period. For the
purpose of this analysis, EPA assumes that half are expected to be designated during the first 5 years, and the other
half, in the second 5 years.
3TMedium 3 for wet layer operations.
4-20
-------
land base and technology needs cost models. These cost estimates are shown in Appendix B. More
detailed cost information is provided in the Development Document (USEPA, 2002).
For CAFOs with between 300 to 1,000 AU, operations are distributed in the key regions
(Midwest or South) in the key category group (Category 1H) across the Medium 1, 2, and 3 model sizes.
For all sectors excluding hog, the farm counts are distributed evenly across these three size groups. The
hog models are more complex, because the engineering costs are divided by size, region, operation type
(farrow finish and grow finish) and manure process (liquid and pit for Medium models), and the financial
models are divided by size, region, and contract versus independent, and so forth, leading to a much
larger matrix of models than those for other sectors. The designated counts were distributed in a ratio of
NPDES farm counts over the Medium 1,2, and 3 models for liquid and pit manure processes, by contract
vs. independent and by farrow finish and grow finish in the Midwest 1H categories. For designated
CAFOs with fewer than 300 AU, operations are placed in one model for each sector, with the exception
of hog facilities. Hog operations are distributed evenly among the model types (manure process by grow
finish or farrow finish and by contract versus independent). Costs for these "Small" models are
developed using the Medium 1, Category 1H costs for each sector (or in the case of hog, each process
and operation type). The cost per head for the Medium 1, 1H operation was applied to an assumed 300
AU number of head to estimate an annualized compliance cost per "small" facility. Because there was
no Medium 1 size for wet layer, the Medium 3 size group per head cost was applied to the number of
head associated with 300 AU.
4.4.2 Economic Analysis Results
Using the economic achievability criteria established for this analysis, discussed in Section 4.4.1,
EPA's economic analysis indicates that the CAFO regulations will not impose financial stress on a
substantial number of operations, relative to the total number of affected confinement operations in these
sectors. The results of this analysis are presented in Table 4-5.
EPA estimates that about 6,200 small business CAFOs would be affected by this rule. For this
analysis, EPA estimates that about 6,200 affected CAFOs are small businesses, consisting of about 2,330
operations with more than-1,000 AU and about 3,830 operations with between 300 and 1,000 AU. Most
of these affected small businesses are hi the hog, dairy, and broiler sectors.37
In examining the effects on small businesses for the final rule, EPA followed the same approach
used to evaluate the impacts on existing CAFOs, as described in Section ES.2. For the purposes of this
analysis, EPA assumes that small business CAFOs with between 300 and 1,000 AU would incur costs
similar to those estimated for CAFOs with more than 1,000 AU (although these smaller-sized operations
will be subject to BPJ and not the ELG requirements under the revised NPDES requirements). These
upper end cost estimates could, therefore, overstate the financial effects for small businesses in this size
category. For past regulations, EPA has often analyzed the potential impacts to small businesses by
evaluating the results of a costs-to-sales test, measuring the number of operations that will incur
compliance costs at varying threshold levels (including ratios where costs are less than 1 percent,
37 For reasons noted in the record, EPA believes that the number of small broiler operations is
overestimated and might actually include a number of medium and large broiler operations that should not be
considered small businesses.
4-21
-------
between 1 and 3 percent, and greater than 3 percent of gross income). EPA conducted such an analysis at
the time of the 2001 proposal, indicating that about 80 percent of the estimated number of small
businesses directly subject to the rule as CAFOs might incur costs in excess of three percent of sales.
EPA believes that its more refined analysis used for its general analysis (presented here) better reflects
the potential impacts to regulated small businesses.
Using this approach, EPA's analysis indicates that the final rule could cause financial stress to
some small businesses, making these businesses vulnerable to closure. These results are presented in
Table 4-5a (Option 1) and Table 4-5b (Option 2).
For Option 1, the analysis indicates that, among all small business CAFOs in the veal, dairy, hog,
turkey, and egg-laying sectors, the impacts due to this rule can be characterized as "Affordable" or
"Moderate." EPA estimates that a total of 172 small businesses (3 percent of all small business CAFOs
with more than 300 AU) would experience financial stress and might be vulnerable to closure. By sector,
these closures are comprised of about 131 small businesses in the beef sector, 38 businesses in the heifer
sector, and 3 businesses in the broiler sector. Most of these (nearly 90 percent) are operations with fewer
than 1,000 AU. For Option 2, the analysis indicates that, among all small business CAFOs in the veal,
dairy, hog, turkey, and egg-laying sectors, the impacts due to this rule can be characterized as
"Affordable" or "Moderate." EPA estimates that a total of 262 small businesses (4 percent of all small
business CAFOs with more than 300 AU) would experience financial stress and might be vulnerable to
closure. By sector, these closures are comprised of about 183 small businesses in the beef sector, 50
businesses in the heifer sector, and 19 businesses in the broiler sector. Nearly 90 percent of these
potential closures are operations with fewer than 1,000 AU.
These estimates of the number of potential CAFO closures are cumulative and reflect the results
of both the farm level analysis and the enterprise level analysis. These results are based on an analysis
that does not consider the longer term effects on market adjustment and also available cost-share
assistance from Federal and State farm conservation programs. EPA believes that such adjustments
could lessen the economic impacts of the final regulations over time.
Table 4-5 shows the results of this analysis aggregated across all estimated designated operations
with less than 1,000 AU, indicating that nearly one-half of all designated operations may go out of
business. Closures among designated operations are all in the broiler, beef, and heifer sectors.
4-22
-------
Table 4-5a. Results of EPA's SmaU Business Analysis (Option 1)
Sector
Number of
Small
CAFOs
Affordable
Moderate
Stress
(Number)
Affordable
Moderate
Stress
(Percent of Total Operations)
CAFOs >1000 AU (excl. designated operations)
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
712
12
327
1,330
1,485
1,823
24
407
31
6,151
581
12
289
1,330
1,485
1,395
24
407
31
5,554
0
0
0
0
0
424
0
0
0
424
131
0
38
0
0
3
0
0
0
172
82%
100%
88%
. 100%
100%
77%
100%
100%
100%
90%
0%
0%
0%
0%
0%
23%
0%
0%
0%
7%
18%
0%
12%
0%
0%
0%
0%
0%
0%
3%
CAFOs >1,OOOAU
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
538
5
97
0
0
1,303
0
383
0
2,326
533
5
97
-
-
1,065
-
383
-
2,083
0
0
0
-
•
234
~
0
--
234
5
0
0
~
-
3
-
0
-
8
99%
100%
100%
-
.
82%
-
100%
-
90%
0%
0%
0%
-
-
18%
.
0%
~
10%
1%
0%
0%
—
~
0%
r-
0%
0%
4-23
-------
Table 4-Sa. Results of EPA's Small Business Analysis (Option 1)
Sector
Number of
Small
CAFOs
Affordable
Moderate
Stress
(Number)
Affordable
Moderate
Stress
(Percent of Total Operations)
Operations 300 - 1,000 AU (Defined as CAFOs)
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
174
7
230
1,330
1,485
520
24
, 24
31
3,825
48
7
192
1,330
1,485
330
24
24
31
3,471
0
0
0
0
0
190
0
0
0
190
126
0
38
0
' 0
0
0
0
0
164
27%
100%
83%
100%
100%
63%
100%
100%
100%
91%
0%
0%
0%
0%
0%
37%
0%
0%
0%
5%
73%*
0%
17%
0%
0%
0%
0%
0%
0%
4%
Operations <1,000 AU (Designated as CAFOs)
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
30
0
6
60
104
104
4
16
20
344
4
0
0
60
104
0
4
16
20
208
0
0
0
0
0
0
0
0
0
0
26
0
6
0
0
104
0
0
0
136
13%
NA
0%
100%
100%
0%
100%
100%
100%
61%
0%
NA
0%
0%
0%
0%
0%
0%
0%
0%
87%
NA
100%
0%
0%
100%
0%
0%
0%
40%
Source: USEPA. May not add due to rounding. Does not includes the number of CAFOs includes designated
facilities. Assumes that the costs that will be incurred by those sized operations to comply with BPJ-based
limitations under the revised NPDES regulations are similar to the estimated costs that would be incurred if Medium
CAFOs had to comply with the ELG.
"Layers: dry" are operations with dry manure systems. "Layers: wet" are operations with liquid manure systems.
4-24
-------
Table 4-5b. Results of EPA's Small Business Analysis (Option 2)
Sector
Number of
Small
CAFOs
Affordable
Moderate
Stress
. (Number)
Affordable
Moderate
Stress
(Percent of Total Operations)
CAFOs >1000 AU (excl. designated operations)
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
712
12
327
1,330
1,485
1,823
24
407
31
6,151
529
12
277
1,306
1,483
1,026
24
407
31
5,129
0
0
0
24
.2
780
0
0
0
806
183
0
50
0
0
19
0
0
0
262
74%
100%
85%
98%
100%
56%
100%
100%
100%
83%
0%
0%
0%
2%
0%
43%
0%
0%
0%
13%
26%
0%
15%
0%
0%
1%
0%
0%
0%
4%
CAFOs >1,000 AU
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
538
5
97
0
0
1,303
0
383
0
2,326
522
5
88
-
_
763
-
383
-
1,795
0
0
0
.
-
532
-
0
-
532
16
0
9
-
-
9
-
0
"--
34
97%
100%
91%
-
-
58%
-
100%
-
76%
0%
0%
0%
-
_
41%
-
0%
-
23%
3%
0%
9%
-
-
1%
-
0%
•
1%
4-25
-------
Table 4-5b. Results of EPA's Small Business Analysis (Option 2)
Sector
Number of
Small
CAFOs
Affordable
Moderate
Stress
(Number)
Affordable
Moderate
Stress
(Percent of Total Operations)
Operations 300 - 1,000 AU (Defined as CAFOs)
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
174
7
230
1,330
1,485
520
24
24
31
3,825
7
7
189
1,306
1,483
263
24
24
31
3,334
0
0
0
24
2
248
0
0
.0
274
167
0
41
0
0
10
0
0
0
228
4%
100%
82%
98%
100%
51%
100%
100%
100%
87%
0%
0%
0%
2%
0%
48%
0%
0%
0%
7%^
96%
0%
18%
0%
0%
1%
0%
0%
0%
6%
Operations <1,000 AU (Designated as CAFOs)
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers: Dry
Layers: Wet
Turkeys
Total
30
0
6
60
104
104
4
16
20
344
4
0
0
60
104
0
4
16
20
208
0
0
0
0
0
0
0
0
0
0
26
0
6
0
0
104
0
0
0
136
13%
NA
o%-
100%
100%
0%
100%
100%
100%
61%
0%
NA
0%
0%
0%
0%
0%
0%
0%
0%
87%
NA
100%
0%
0%
100%
0%
0%
0%
40%
Source: USEPA. May not add due to rounding. Does not includes the number of CAFOs includes designated
facilities. Assumes that the costs that will be incurred by those sized operations to comply with BPJ-based
limitations under the revised NPDES regulations are similar to the estimated costs that would be incurred if Medium
CAFOs had to comply with the ELG.
"Layers: dry" are operations with dry manure systems. "Layers: wet" are operations with liquid manure systems.
4-26
-------
EPA believes that the estimated financial impacts shown in Tables 4-5(a) and 4.5(b) represent
the worst case. The reasons are summarized below.
First, all results are estimated assuming no costs can be passed through between CAFOs and the
processing sectors. As discussed hi Section 3 of this report, if modest levels of cost passthrough are
assumed in the broiler sectors, the BAT requirements are affordable to all small broiler operations. EPA
did not evaluate economic impacts on cattle operations under a cost passthrough scenario; however, it is
expected that long-run market and structural adjustment by producers in this sector will diminish the
estimated impacts. Even without an assumption of cost passthrough, EPA's analysis shows that adverse
impacts will not be experienced by a substantial number of operations, as compared to the number of
affected operations in these sectors. EPA has conducted an extensive literature review of issues
concerning cost passthrough. Based on the results of the available empirical research on market power
and price transmission in these industries, EPA believes that there is little evidence to support the
position that increased production costs may not be passed through the market levels. A summary of this
literature review is provided in the rulemaking record (ERG, 2000c — DCN 70640).
Second, as noted in the SBAR Panel Report, EPA believes that the number of small broiler
operations is overestimated. In the absence of business level revenue data, EPA estimates the number of
"small businesses" using the approach described in Section 4.2. Using this approach, virtually all (>99.9
percent) broiler operations are considered "small" businesses. This categorization may not accurately
portray actual small operations in this sector because it classifies a 15- to 20-house broiler operation with
375,000 birds as a small.business. Information from industry sources suggests that a two-house broiler
operation with roughly 50,000 birds is more appropriately characterized as a small business in this sector
(Madison, 1999; Staples, 1998). Therefore, it is likely that the number of small broiler operations might
include a number of medium and large size broiler operations being considered small entities. As
discussed in Section 9.2.1 of the Proposal EA, EPA consulted with SB A on the use of an alternative
definition for small businesses in all affected sectors based on animal inventory at an operation during
the development of the rulemaking.
Third, EPA believes that a costs-to-sales comparison is a crude measure of impacts on small
business in sectors where production contracting is commonly used, such as in the broiler sector (and
also hi the turkey, egg, and hog sectors, though to a lesser extent). As discussed in Section 4.2.4.5 of the
Proposal EA, lower reported operating revenues in the broiler sector reflect the predominance of contract
growers in this sector. Contract growers receive a prenegotiated contract price that is lower than the
USDA-reported producer price, thus resulting in lower gross revenues at these operations (USDA/ERS,
1996b; Perry et al., 1999; Farm Journal, 1998). Lower producer prices among contract growers are often
offset by lower overall production costs at these operations, because the affiliated processor firm pays for
a substantial portion of the grower's annual variable cash expenses. Inputs supplied by the integrator
may include feeder pigs or chicks, feed, veterinary services and medicines, technical support, and
transportation of animals (USDA, 1996a). These variable cash costs compose a large component of
annual operating costs, averaging more than 70 percent of total variable and fixed costs at livestock and
poultry operations (USDA/ERS, 1999a). The contract grower also faces reduced risk because the
integrator guarantees the grower a fixed output price (see Section 2 of the Proposal EA for more
information on contracting in animal agriculture). Because production costs at a contract grower
operation are lower than that at an independently owned operation, a profit test (costs-to-profit
comparison) is a more accurate measure of impacts at grower operations. However, financial data are not
available that differentiate between contract grower and independent operations.
4-27
-------
Fourth, EPA's initial regulatory flexibility analysis also does not consider a range of potential
cost offsets available to most farms. As discussed in Section 2.4 of this report, one source of potential
cost offset is cost share and technical assistance available to farmers for on-farm improvements from
various State and Federal programs, such as the Environmental Quality Incentives Program (EQIP)
administered by USDA. Cost sharing for eligible producers under EQIP may cover up to 75 percent of
the costs of certain conservation practices, such as grassed waterways, filter strips, manure management
facilities, capping of abandoned wells, and other practices important to improving and maintaining the
health of natural resources in the area. Technical assistance is also available for formulating
conservation plans. In. the Spring of 2002, new Farm Bill legislation passed by Congress might
significantly raise government expenditures for this program. Total EQIP authorization for FY 2002 to
FY 2007 is $5.8 billion, ranging from $400 million to $1.3 billion per year over the period. This
compares to current authorized levels of about $200 million per year. The new legislation targets 60
percent of available EQIP funds to livestock and poultry producers, including confinement and grass-
based systems. The new legislation also removed the previous EQIP eligibility requirements that
restricted funding for certain structural practices to operations with fewer than 1,000 AU (as measured by
USDA), replacing this restriction with an overall payment limitation of $450,000 per producer over the
authorized life of the 2002 Farm Bill. Many other State and Federal cost share programs base eligibility
not on size thresholds but on priority watersheds (e.g., USDA's Small Watershed Program; the New
York City Watershed Program), priority contaminants (e.g., Kansas Non-Point Source Pollution Control
Fund), or proposed waste management practices (e.g., Maryland, Minnesota, Missouri, Nebraska, and
North Carolina state programs). However, technical assistance under most programs is available to all
operations, regardless of watershed, contaminants, proposed practices, or size (ERG, 2000a). A review
of cost-share and technical assistance programs available to AFOs is provided in the rulemaking record
(ERG, 2000a—DCN 70130).
Section 2.4 also describes another source of potential cost offset, which is manure sales,
particularly of relatively higher value dry poultry litter. EPA estimates that sales of dry poultry litter
could offset the costs of meeting the regulatory requirements on the order of more than 50 percent. As
illustrated in the Proposal EA, this reduction alone exceeds the level of cost passthrough (42 percent)
assumed at proposal for the cost impact analysis of the broiler sector. Details on how EPA calculated
these manure sale offsets and how they would reduce the economic impacts at poultry operations are
presented in Section 6 of the Proposal EA.
Finally, this analysis does not take into account certain noneconomic factors that might influence
an operation's decision to weather the boom and bust cycles that are commonplace in agricultural
markets. Farm typology data from USDA indicate that a large share of farming operations (more than 90
percent) have annual sales of less than $250,000 and are considered "small family farms" by USDA
(USDA/ERS, 2000d, 2000e). Of these, about 60 percent are "limited-resource," "retirement," or
"residential" operations where farming is not the primary source of income (USDA/ERS, 2000e, 1999a).
In many cases, these operations have negative annual income supplemented by sources of off-farm
income that subsidize the farming operation (USDA/ERS, 2000d and 1996a).
USDA's ERS (1996a) reports that about 60 percent of farm operators reporting negative net
income hadnonfarm occupations. About 75 to 80 percent of farms rely on some nonfarm income, and
even in the largest operations nonfarm income can be a significant portion of total household income
(USDA/ERS, 1996a). More than 90 percent of farm operators with negative net income had nonfarm
income averaging more than $35,700 per year; even farms with positive net income rely somewhat on
nonfarm income (Heimlich and Barnard, 1995; USDA/ERS, 1996a).
4-28
-------
When farm income is negative over a period of time, sales tests can be very difficult to interpret
(Heimlich and Barnard, 1995). One reason that incomes can remain negative over several years is that
operators can supplement farm income with nonfarm income, and these losses can be used to reduce total
income tax liabilities while the real estate value of the farm property appreciates. Additional
noneconomic factors might also include the satisfaction of working for oneself, the ability to employ
family members, a sense of tradition and the ability to pass on that tradition to future generations, and the
fact that the operation is both a home and a livelihood. These and other noneconomic factors might
influence the decision to close a livestock or poultry operation cannot be adequately addressed in an
economic model. To the extent that these factors play a role in that decision, EPA's economic model
might overstate the possibility of closure among small businesses.
USDA's farm financial data include operations where farming is part-time and not the primary
occupation, but exclude sources of nonfarm income at these operations. As noted in Section 4.2 of the
Proposal EA, the inclusion of these operations may result in lower average data values than would be the
case if these operations were excluded from the analysis. EPA believes that including of these operations
might tend to overstate impacts. Previous analyses by USDA and EPA have also noted the potential
effect on average farm data of including these operations and have regarded these part-time business
more as "hobbies or recreational activities" (Heimlich and Barnard, 1995; DPRA, 1995). Heimlich and
Barnard (1995) further indicate that considering non-farm income in addition to farm income may
provide a more appropriate comparison to the costs of required measures where the motivation for
staying in business is not necessarily purely economic.
Overall, EPA expects that the CAFO regulations will benefit the smallest businesses in these
sectors, because the regulations might create a comparative advantage for small operations that are not
subject to the regulations. Except for the few AFOs that are designated as CAFOs, these small
operations will not incur costs associated with the final requirements and may benefit from eventual
higher producer prices as these markets adjust to higher production costs in the long term.
4-29
-------
-------
SECTION FIVE
OTHER REGULATORY ANALYSIS REQUIREMENTS
This section addresses the requirements to comply with Executive Order (EO) 12866 and the
Unfunded Mandates Reform Act (UMRA), both which require Federal agencies to assess the costs and
benefits of each significant rule they propose or promulgate.
This section is organized as follows. Section 5.1 describes the administrative requirements of
both EO 12866 and UMRA. Section 5.2 identifies the reasons why EPA has determined that the existing
regulations need to be revised. Section 5.3 provides a summary of the total social costs of the final
CAFO regulations. Section 5.4 briefly summarizes the expected pollutant reductions. Section 5.5
summarizes the estimated monetized benefits for regulatory Options 1 and 2.
Much of the information provided in this section is summarized from, and extensively references,
other documents that support this rulemaking, as well as other sections of this report that present more
detailed accounts of EPA's supporting analyses.
5.1 ADDITIONAL ADMINISTRATIVE AND REGULATORY ANALYSES
5.1.1 Requirements of Executive Order 12866 ,
Under Executive Order 12866 (58 FR 51735, October 4,1993), the Agency must determine
whether a regulatory action is "significant" and therefore subject to Off cie of management and Budget
(OMB) review and the requirements of the Executive Order. The Order defines a "significant regulatory
action" as one that is likely to result in a rule that may:
• have an annual effect on the economy of $ 100 million or more or adversely affect
in a material way the economy, a sector of the economy, productivity, competition,
jobs, the environment, public health or safety, or state, local, or tribal governments
or communities;
« create a serious inconsistency or otherwise interfere with an action taken or
planned by another agency;
• materially alter the budgetary impact of entitlements, grants, user fees, or loan
programs or the rights and obligations of recipients thereof; or
• raise novel legal or policy issues arising out of legal mandates, the President's
priorities, or the principles set forth in the Executive Order.
EPA has determined that the final CAFO rulemaking is a "significant regulatory action" under
the terms of Executive Order 12866. As such, this action was submitted to OMB for review. Changes
made in response to OMB's suggestions or recommendations will be documented in the public record.
In addition to submission of the action to OMB, the principal requirements of the Executive
Order are that the Agency perform an analysis comparing the benefits of the regulation to the costs that
5-1
-------
the regulation imposes, that the Agency analyze alternative approaches to the rule, and that the need for
the rule be identified. Wherever possible, the costs and benefits of the rule are to be expressed in
monetary terms. To address the analytical requirements, as specified by the Executive Order, Section 5.2
describes the reasons why EPA is revising the existing regulations, and Sections 5.3 through 5.6 present
the estimated social costs, pollutant reductions, and monetary benefits of the proposed CAFO
regulations. An in-depth profile of these industry sectors is presented hi Section 2 of the Proposal EA
and additional information for each affected industry subcategory is provided in Sections 6, 7, and 8 of
the Proposal EA. The preamble to the final CAFO regulations describes revisions to the existing
regulations, which are briefly summarized hi Section 1 of this report).
5.1.2 Requirements of the Unfunded Mandates Reform Act (UMRA)
Title n of the UMRA Pubh'cXaw 104-4, establishes requirements for Federal agencies to assess
the effects of their regulatory actions on State, Tribal, local, governments and the private sector. Under
Section 202 of the UMRA, EPA generally must prepare a written statement, including a cost-benefit
analysis, for proposed and final rules with 'Tederal mandates" that may result hi expenditures to State,
Tribal, and local governments, hi the aggregate, or to the private sector, of $ 100 million or more hi any
one year.
This final rule is anticipated to cost the private sector more than $100 million per year for the
time period analyzed. In particular, this section addresses the following:
» Section 202(a)(l): authorizing language (also see Section 10 of the preamble to the
final rule)
• Section 202(a)(2): a qualitative and quantitative assessment of the anticipated costs
and benefits of the regulation
• Section 202(a)(3)(A): accurate estimates of future compliance costs (as reasonably
feasible)
• Section 202(a)(3)(B): disproportionate effects on particular segments of the private
sector
• Section 202(a)(3)(B): disproportionate effects on local communities (this rule is
not expected to have disproportionate effects on local communities.)
» Section 205(a): least burdensome option or explanation required (also see Section
4 of the preamble to the final rule)
EPA has determined that the final CAFO regulations contain a Federal mandate that may result
in expenditures of $100 million or more for the private sector in any one year (see Section 3.3).
Accordingly, EPA has prepared the written statement required by section 202 of the UMRA. This and
previous sections of the EA constitute this statement: Sections 5 through 8 of the EA identify costs and
impacts (burdens) on CAFOs that are subject to the final regulations, as well as impacts on processors in
these industries and other market affects. Appendix E of the Proposal EA (USEPA, 200 la) presents
5-2
-------
information comparing the cost-effectiveness of the proposed regulatory alternatives; Appendix E of this
report presents EPA's cost-effectiveness for the final regulations. Additionally, EPA's Benefits Analysis
(USEPA, 2002k) presents estimated monetary benefits that might accrue under the proposed regulations,
as required under UMRA when costs of a federal mandate exceed $ 100 million in any one year.
Before promulgating an EPA rule for which a written statement is needed, Section 205 of the
UMRA generally requires EPA to identify and consider a reasonable number of regulatory alternatives
and adopt the least costly, most cost-effective or least burdensome alternative that achieves the objectives
of the rule. The provisions of section 205 do not apply when they are inconsistent with applicable law.
In this rule, the Clean Water Act requires EPA to establish effluent limitations for point sources based on
the "best available technology economically achievable" (Sections 301(b)(2)(A) and 304(b)(2)). Factors
that EPA shall consider in an assessment of best available technology include the cost of achieving
effluent reductions, among other factors (Section 304(b)(2)(B)). Pursuant to section 205(a)(l)-(2), EPA
selected the least expensive option that also meets the requirement that EPA select the "best available
technology economically achievable." More information is provided in Section 4 of the preamble
supporting the final regulations.
EPA has also determined that the final CAFO regulations do not include a Federal mandate that
may result in estimated costs of $100 million or more to State, Tribal, or local governments in the
aggregate. Accordingly, the regulations contain no regulatory requirements that might significantly or
uniquely affect small governments and therefore are not subject to the. requirement of Section 203 of the
UMRA. Costs incurred by Federal or State governments under the final regulations are presented in
Section 5.3. Tnbal governments may also incur compliance costs; however, these costs are expected to
be modest and have not been estimated. EPA has determined that the regulations do not include
requirements that might significantly or uniquely affect local governments; therefore, this rule does not.
affect small governments as outlined in Section 203. Therefore a small governments agency plan has not
been developed. (If EPA establishes any regulatory requirements that may significantly or uniquely
affect small governments, including Tribal governments, it must have developed under Section 203 of the
UMRA a small government agency plan. The plan must provide for notifying potentially affected small
governments, thus enabling officials of affected small governments to have meaningful and timely input
in the development of EPA regulatory proposals with significant Federal intergovernmental mandates,
and informing, educating, and advising small governments on compliance with the regulatory
requirements.)
5.2 NEED FOR THE REGULATIONS
Executive Order 12866 requires that the Agency identify the need for the regulation or
regulations being proposed. A detailed discussion of the need for the regulations is presented in Section
4 of the 2001 Proposal (66 FR 2293-2972-2976). A summary may also be found in Sections 1 and 10 of
the Proposal EA. These reasons are summarized briefly below:
• In spite of existing regulatory controls, there is continued discharge and runoff of
manure and nutrients from livestock and poultry operations. The proposed
regulations are expected to address the impairment of many U.S. waterways and
the associated human health and ecological risks by reducing nutrient contributions
from animal agriculture.
5-3
-------
» Periodic review and revision of existing regulations is envisioned in the CWA. The
existing regulations need to be updated to reflect structural changes in these
industries over the past few decades. The continued trend toward fewer but larger
operations, coupled with greater emphasis on more intensive production methods
and specialization, is concentrating more manure nutrients and other animal waste
constituents within some geographic areas. This trend has coincided with
increased reports of large-scale discharges from these facilities.
• The existing regulation needs to be more effective at protecting or restoring water
quality. The revisions will make the regulations easier to understand and better
clarify the conditions under which an AFO is a CAFO and, therefore, subject to the
regulatory requirements. Currently, few livestock and poultry operations have
NPDES permits.
Both UMRA and EO 12866 require the statutory authority for the rule to be cited. A detailed
discussion of the objectives and legal basis for these regulations is presented in Sections 1 and 3 of the
preamble to the final rule and also the 2001 Proposal (see: 66 FR 2959 or USGPO, 2001a).
53 TOTAL SOCIAL COSTS
EPA estimates the total social costs of Option 2 at $335 million annually in 2001 dollars. These
costs include compliance costs borne by CAFOs and administrative costs to States and the Federal
government. Costs to regulated CAFOs constitute the bulk of this total cost, estimated by EPA at $326
million annually. EPA estimates that the administrative cost to Federal and State governments to
implement this rule is $9 million per year. (For purposes of discussing EPA's analysis supporting
UMRA, this section discusses results for Option 2 only; see Table 5-1).
5.3.1 Costs to Regulated CAFOs
The largest component of social cost is the cost to industry of complying with the regulation.
Costs to industry include annualized capital costs, operating and maintenance costs, start-up and
recurring costs, and also record-keeping costs. Estimated costs cover four broad categories, including
nutrient management planning, facility upgrades, land application, and technologies for balancing
on-farm nutrients. All capital costs are depreciated over a 10-year recovery period, based on the Internal
Revenue Code's guidance for single-purpose agricultural or horticultural structures. More detail on how
EPA estimates compliance costs for mis rulemaking is in the Development Document (USEPA, 2002).
Table 5-1 shows the total annualized compliance costs to CAFOs. EPA estimates that of the
total estimated social cost of Option 2 ($335 million annually), compliance costs borne by CAFOs
constitute the bulk of this total cost and are estimated by EPA at $326 million annually. Of this total,
compliance cost to operations with more than 1,000 AU are estimated at$283 million per year. Costs to
operations with between 300 and 1,000 AU are estimated at $39 million per year. Cost to operations that
may be designated as CAFOs is estimated at $4 million annually under Option 2. Information on these
costs, along with a comparison of cost estimates for other regulatory options considered by EPA, is
provided in Section 3.
5-4
-------
These costs are pre-tax and do not reflect tax savings of incurred compliance costs.38 For the
purpose of this analysis, estimated pre-tax compliance costs can be viewed as an estimate of the net
output loss to the economy, plus consumer and producer surplus losses. EPA does not use an estimate of
net output loss because the Agency would then need to compute output gains and consumer and producer
surplus losses associated with the proposed regulations. Because the pre-tax costs include no cost
passthrough assumptions, no consumer surplus is lost. Additionally, the pre-tax cost will incorporate the
loss in producers' surplus. The pre-tax costs of compliance thus serve as an estimate for the net output
loss to the economy plus losses in consumer and producer surplus.
.EPA assumes that all confinement operations that are defined or designated as CAFOs will incur
these costs. Cost estimates include costs to facilities that are projected to experience financial stress that
could lead to facility closure. In some cases, it is possible that a CAFO might be liquidated instead of
incurring these costs. EPA considers the compliance costs assigned to these model CAFO to be a
reasonable upper estimate of the costs to liquidate such operations.39 An operation will choose to
liquidate (to the extent that the choice is theirs to make) only when the costs of liquidating are less than
the costs of installing and implementing pollution control.
5.3.2 Costs to the Permitting Authority (Federal and State Governments)
As discussed in Section 5.3.1, the overwhelming majority (more than 95 percent) of the
estimated total regulatory costs will accrue to industry and to Federal and State governments in the form
of foregone tax revenues. However, additional costs will be incurred by the NPDES perrmtting authority
to alter existing state programs and obtain EPA approval to develop new permits, review new permit
applications and issue revised permits that meet the final regulatory requirements.
Under the final rule, Federal and State National Pollutant Discharge Elimination System
(NPDES) permitting authorities will incur administration costs related to the development, issuance, and
tracking of general and individual permits. State NPDES permitting authorities would also incur costs to
modify existing State NPDES programs for CAFOs and obtain EPA approval of the modifications. EPA
estimates that under the final regulations an estimated 15,400 CAFOs would be permitted. This estimate
consists of about 14,920 CAFOs covered by State permits and about 480 CAFOs covered by Federal
permits. Administrative costs incurred by State permitting authorities are expected to be $8.5 million.
EPA permitting authorities would incur the remaining $0.3 million (Table 5-1). These costs are
expressed hi 2001 dollars and are annualized over the 5-year permit life using a 7 percent discount rate.
This analysis is available in the record and in the Development Document (USEPA, 2002). This analysis
was conducted to evaluate the costs of the proposed rule to governments, as required under the Unfunded
Mandates Reform Act (UMRA), as discussed in the preamble to the final regulations.
There are several ways that issuance of general permits will result in administrative costs to State
and federal permitting authorities. First, State permitting authorities will need to revise their programs to
incorporate changes in the final rule. Second, States will need to revise existing general permits; those
38The tax shield is the cost to the Federal and State governments of subsidizing, in effect, the cost of the
final regulations. Tax shields are also a cost to society and must be included in the estimate of social costs.
39These liquidation costs include legal fees, broker fees, and so forth.
5-5
-------
that do not currently use them may choose to develop a general permit. The permitting authority is
required to give public notice announcing the development of a draft permit and allow an opportunity for
public comments. Often permitting authorities issue a response to the public comments received and,
occasionally, hold public hearings on the draft general permit. Following the issuance of the final
general permit, States and EPA may begin to incur administrative costs per facility. For example, each
time a facility operator files a Notice of Intent (NOI) to obtain coverage under a general permit, the
permitting authority will incur costs to review the application, file the NOI, or enter permittee
information into a permit tracking system. Per-facility administrative costs might also include facility
inspections to ensure compliance with permit conditions or to ensure a facility qualifies for coverage
under the general permit. Finally, State and federal NPDES permitting authorities will need to review
the annual reports submitted by each facility covered by a general permit.
When a facility submits an application for an individual permit, the permitting authority incurs
administrative costs for review of the individual permit application and development of the individual
permit by a permit writer. Additionally, public notice must be given about the development of the draft
permit, and the authority may respond to any comments received and conduct public hearings as needed.
Facility inspections might also be necessary prior to issuing a permit or to ensure compliance with permit
conditions. As with general permits, permitting authorities will incur expenses for record-keeping,
associated filing and tracking of individual permit applications and review of annual reports submitted by
each facility covered by an individual permit.
EPA assumes that under the final regulations an estimated 15,400 CAFOs would be permitted.
This estimate consists of 14,920 State permits (10,440 general and 4,480 individual permits) and 480
Federal permits (340 general and 140 individual permits). Table 5-2 shows EPA's estimate of the
number of CAFO permits by State and EPA Region. More information on EPA's estimates is provided
in the Development Document (USEPA, 2002) and rulemaking record.
The unit permit costs EPA assumed for this analysis are based on information obtained from
State and EPA Regional permitting personnel. The cost assumptions used to develop, review, and
approve permits and inspect facilities, as well as the estimate of annual administrative costs is presented
in the Development Document (USEPA, 2002). These documents also provide detailed discussions on
EPA's assumptions for the state and federal wage rates used to estimate costs.
5.3.3 Other Social Costs
An estimate of total social costs of the proposed regulations comprises costs that go beyond the
compliance costs of constructing and implementing pollution control procedures. Some of these
additional costs are monetary, but many are nonmonetary or not easily monetized (i.e., a dollar value
cannot be attributed or is difficult to attribute to the items).
Additional monetary costs include the cost of Federal and State subsidies in the form of a tax
shield (or lost tax revenue) and costs of administering a regulation (permitting costs). These costs are
presented in Sections 5.3.1 and 5.3.2. Other costs, however, might also be incurred under the proposed
regulations and constitute the full range of total social costs. For example, costs might be incurred as a
result of worker dislocations. These costs comprise the value to workers of avoiding unemployment and
the costs of administering unemployment, including the costs of relocating workers, and the
inconvenience, discomfort, and time loss associated with unemployment (the unemployment benefits
5-6
-------
themselves are generally considered transfer payments, not costs). Other potential social costs include
the cost associated with a slowdown in the rate of innovation. In theory, there might be some impact on
the rate of innovation to the extent that farms might invest in newer technologies if they did not have to
allocate resources to meeting the requirements of the proposed regulations. Generally, however, unless
an industry is highly technical, with major investments in research and development, impacts on the rate
of innovation are likely to be minimal.
Monetizing such social costs is difficult. EPA does not evaluate these other potential social costs
but expects that such costs that are not specifically addressed by the analyses presented in this report will
be modest.
Table 5-1 Annual Pre-tax Cost of the Rule, $2001 (Option 2)
Sector
^Operations/Permittees
>1,000 AU
300-1,000 AU
(number)
Aggregate Incremental Costs
Total
>1,000
AU
300-1,000
AU
Designated
CAFOs
($2001, millions, pre-tax)
Regulated CAFOs •"
Fed Cattle
Veal
Heifer
Dairy
Hogs
Broilers
Layers - Dry
Layers - Wet
Turkeys
Total
1,766
12
242
1,450
3,924
1,632
729
,383
388
10,526
174
230
7
1,949
1,485
520
26
24
37
4,452
$88.2
$0.0
$6.3
$151.1
$34.8
$20.5
$7.5
$8.9
$8.7
$326.0
$85.8
<$0.1
$3.8
$128.2
$24.9
$16.8
$7.2
$8.4
$8.1
$283.2
$1.9
<$0.1
$2.4
$22.0
$9.5
$2.4
$0.1
$0.5
$0.3
$39.1
$0.5
$0.0
$0.1
$0.9
$0.4
$1.3
$0.2
<$0.1
$0.3
$3.8
Permitting Authority w
States
Federal
Subtotal
NA
NA
10,526
NA
NA
4,452
$8.7
$0.3
$9.0
NA
NA
$6.0
NA
NA
$3.0
ND
ND
ND
Total Social Costs
TOTAL
10,526
4,452
$335.0
$289.2
$42.1
$3.8
Source: USEPA. May not add due to rounding. Number of operations and total costs shown do not include
designated facilities. "Layers: dry" are operations with dry manure systems. "Layers: wet" use liquid systems.
"'See Section 3 of this report for more information on the number and cost to affected CAFOs.
''Number of permits includes permits for designated facilities on an annualized basis. Table 5-2 provides additional
information on estimated number of permits.
5-7
-------
Table 5-2. Medium and Large CAFOs by Region, State, and Sector
Region and State
Region 1
Connecticut
Maine
Massachusetts
>lew Hampshire
Ihode Island
Vermont
Region 2
^lew Jersey
^lew York
Region 3
Jelaware
Maryland
'ennsylvania
/irginia
iVest Virginia
Region 4
\labama
Florida
jeorgia
Centucky
Mississippi
^lorth Carolina
South Carolina
Tennessee
Region 5
llinois
ndiana
Michigan
Minnesota
Dhio
Visconsin
Region 6
Arkansas
,ouisiana
•Jew Mexico
Oklahoma
Texas
Region 7
owa
Cansas
Missouri
Nebraska
Beef
0
0
0
0
0
0
0
2
0
2
10
2
0
6
2
0
4
0
0
0
1
0
2
1
0
105
31
5
20
39
7
3
330
0
0
21
45
264
1072
166
294
21-
591
Veal
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
16
0
2
1
3
3
7
0
0
0
0
0
0
0
0
0
0
0
Dairy
137
18
18
13
8
1
79
352
6
346
245
6
31
135
65
8
354
17
99
61
31
17
56
17
56
622
27
31
127
112
58
267
337
8
22
103
15
189
117
43
22
31
21
Heifer
0
0
0
0
0
0
0
0
•o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
121
9
7
2
46
8
49
69
0
0
27
13
29
46
17
8
11
10
Swine
1
0
0
1
0
0
0
10
1
9
170
4
11
135
19
1
1292
16
4
54
61
17
1076
27
37
1742
442
403
84
595
142
76
171
106
1
0
48
16
1809
1236
130
195
248
Broiler
0
0
0
0
0
0
0
0
0
0
284
58
67
50
89
20
1226
290
37
372
30
214
197
39
47
34
0
1
0
19
4
10
542
277
66
0
75
124
42
3
0
39
0
Turkey ,
14
1
5
3
2
0
3
9
2
7
37
0
. 2
14
18
3
78
3
7
3
1
1
39
22
2
102
8
18
17
26
20
13
59
40
2
1
4
12
53
15
4
30
4
E»yer--
17
7
5
3
0
0
2
20
3
17
147
0
15
122
10
0
318
45
45
137
6
10
27
46
2
214
11
63
20
27
82
11
192
55
5
2
• 18
112
99
65
5
16
13
5-8
-------
Table 5-2. Medium and Large CAFOs by Region, State, and Sector
Region and State
Region 8
Colorado
Vtontana
forth Dakota
South Dakota
Jtah
Wyoming
Region 9
\rizona
California
Jawaii
Nevada
Region 10
Alaska
daho
Dregon
iVashington
Beef
273
153
15
6
72
12
15
64
16
43
2
3
80
0
46
13
21
Veal
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Dairy
121
42
3
6
28
40
2
851
70
763
6
12
263
0
132
28
103
Heifer
65
23
0
1
10
27
4
72
13
59
0
0
99
0
48
19
32
Swine
188
16
13
20
133
5
1
16
3
11
2
0
10
0
3
3
4
Broiler
0
0
d
0
0
0
0
9
0
9
0
0
15
0
0
7
8
Turkey
22
5
3
2
3
7
2
28
1
26
0
1
23
0
2
13
8
Layer-,
20
7
0
0
6
7
0
102
1
98
3
0
33
0
4
7
22
Source: USEPA, 2002, 2002n. May not add due to rounding.
5.4 POLLUTANT REDUCTIONS
EPA's analysis of pollutant discharges under the final rule addresses changes in pollutant
discharges occurring at the production area, and also changes in the quantity of pollutants in runoff from
land on which manure has been applied. Estimates of pollutant discharges from these manure application
sites, or "edge-of-field" loadings, include nutrients, metals, pathogens, and sediment for both pre-rule
conditions (baseline) and post-rule conditions.
Table 5.2 provides estimates for combined total (all animal sectors) baseline and post-regulation
edge of field loading reductions for CAFOs with more than 1,000 AU only for Option 2.
Table 5.3 Edge of Field Loading Reductions for CAFOs (Option 2, >1,OOOAU), AH Sectors
Parameter/Units
Nutrients (million Ib.)
Metals (million Ib.)
Pathogens (10I9cfti)
Sediment (million Ib.)
Baseline
Pollutant Loading
(Pre-regulation)
658
20
5,784
35,493
Post-regulation
Pollutant
Loading
503
19
3,129
33,434
Pollutant Reduction
Units
155
1
2,655
2,059
Percent
24
5
46
6
Source: USEPA; see Development Document (2002).
5-9
-------
EPA estimates edge-of-field loadings using a simulation modeling approach based on
representative model CAFOs used to estimate compliance'costs of the final regulations, as described in
Development Document (USEPA, 2000a, 2002). This model uses estimates of manure generation and
information on cropping systems specific to animal operations under various pre- and post-regulation
model simulation conditions. Model CAFOs take into account differing conditions at representative
operations. These conditions include animal type, production region, facility size, current management
systems and practices, and regionally based physiographic conditions regarding soil, rainfall, hydrology,
crop rotation, and other factors. Reductions in pollutant discharges using the Groundwater Loading
Effects of Agricultural Management Systems (GLEAMS) model, which uses information on soil
characteristics and climate, along with characteristics of the applied manure and commercial fertilizers,
to estimate losses of nutrients, metals, pathogens, and sediment in surface runoff, sediment, and ground
water leachate. EPA used GLEAMS to quantify the reduction of nitrogen and phosphorus loads, and
reductions of discharges of zinc, copper, cadmium, nickel, lead, and arsenic. Fecal coliform and Fecal
streptococcus were used as surrogates to estimate pathogen reductions that would likely be achieved by
this rule.
Edge-of-field loadings are differentiated by broad animal sector categories (cattle, dairy, hog, and
poultry). More details on these models and a summary of the estimated loadings and post-compliance
reductions are provided in the Development Document (USEPA, 2000a, 2002).
Edge-of-field loading estimates are used as inputs to EPA's water quality modeling framework
that simulates the potential amount of pollutant loadings that reach U.S. waterways (measured as rivers
and streams). The resultant loading estimates are referred to in EPA's analysis as "at-stream" loadings.
Information on EPA's fate and transport model and a comparison of edge-of-field loadings and pollutants
that reach U.S. waters is provided in the Benefits Analysis (USEPA, 2000d, 2002k). This analysis
indicates that roughly 80 percent of all land applied manure runoff of nitrogen, phosphorous, and
sediments (edge-of-field) reach U.S. waters (at-stream) (USEPA, 2000d, 2002k). The level of nutrients
reaching U.S. waters can be explained by differing assumptions on a variety of levels, including manure
generation by animal species, the share of animals in confinement, and losses due to volatization and
management practice, as well as other factors, including rounding and truncation error and assumptions
regarding background levels.
Tables 5.4 through 5.6 provide a more in-depth presentation of edge of field loading reductions
for all contributors by pollutant, option, sector size, and sector.
5.5 COMPARISON OF COST AND BENEFITS ESTIMATES
This section compares the estimated costs and benefits attributable to the final rule for both
Option 1 and Option 2 for CAFOs with more than 1,000 AU only. Tables 5-7 and 5-8 present the
annualized estimated costs and benefits in 2001 dollars (pre-tax) assuming both a 7-percent and a 3-
percent discount rate, respectively. This section provides only a summary of EPA's analysis of the
estimated monetized benefits of the final regulations, which is based on the more detailed assessment
available in the Agency's Benefits Analysis (USEPA, 2002k).
These tables show that the economic value of the environmental benefits EPA is able to monetize
(i.e., evaluate in dollar terms) is comparable to the estimated costs of the rule. EPA has estimated the
monetized benefits of the final rule for all operations with more than 1,000 AU. Assuming a 7-percent
5-10
-------
Table 5-4 Edge-of-Field Loading Reductions (All Contributions) Nitrogen
Sector
Option 1
Option 2
Option 3
Option 5
million Ibs./year
All Operations CAFOs >1000 AU
Cattle
Dairy
Hogs
Poultry
Total
45.2
14.1
0.3
29.9
89.6
47.9
14.7
4.0
36.4
103.0
54.3
17.9
13.6
38.1
123.8
47.9
14.7
(21.3)
41.6
82.9
Operations Defined as CAFOs 300- 1,000 AU
Cattle
Dairy
Hogs
Poultry
Total
0.17
4.59
0.03
0.81
5.60
0.22
5.03
0.98
0.88
7.10
0.22
7.34
3.11
0.90
11.56
0.22
5.03
(0.59)
0.95
5.60
Source: USEPA (USEPA, 2002)
Table 5-5 Edge-of-Field Loading Reductions (AH Contributions) Phosphorous
Sector
Option 1
Option 2
Option 3
Option 5
million Ibs./year
All Operations CAFOs >1000 AU
Cattle
Dairy
Hogs
Poultry
Total
15.6
3.2
0.1
8.5
27.4
23.1
5.0
. 4.7
19.2
52.1
,23.1
5.0
4.7
19.2
52.1
23.1
5.1
8.1
20.4
56.5
Operations Defined as CAFOs 300-1,000 AU
Cattle
Dairy
Hogs
Poultry
Total
0.05
1.33
0.01
0.26
1.66
0.27
2.55
0.70
0.72
4.24
0.27
2.55
0.70
0.72
4.24
0.27
2.55
1.50
0.73
5.05
Source: USEPA (USEPA, 2002)
5-11
-------
Table 5-6 Edee-of-Field Loading Reductions (All Contributions) Sediment
Sector
Option 1
Option 2
Option 3
Option 5
million Ibs./year
All Operations CAFOs >1000 AU
Cattle
Dairy
Hogs
Poultry
Total
1,523.5
126.0
0.0
31.2
1,680.8
1,523.5
126.1
143.5
265.9
2,059.0
1,523.5
126.1
143.5
265.9
2,059.0
1,523.5
126.1
(584.7)
310.7
1,375.6
Operations Defined as CAFOs 300-1,000 AU
Cattle
Dairy
Hogs
Poultry
Total
1.4
2.6
0.0
2.2
63
20.1
57.5
20.0
6.0
103.6
20.1
57.5
20.0
6.0
103.6
20.1
57.5
12.1
6.6
96.3
Source: USEPA (USEPA, 2002)
discount rate, under Option 1, total monetized benefits for CAFOs with more than 1,000 AU range from
S141 million to $224 million. For Option 2 (assuming a 7-percent rate), total monetized benefits for
CAFOs with more than 1,000 AU range from $204 million to $340 million annually. Assuming a 3-
percent discount rate, under Option 1, total monetized benefits for CAFOs with more than 1,000 AU
range from $157 million to $240 million. For Option 2 (assuming a 3-percent rate), total monetized
benefits for CAFOs with more than 1,000 AU range from $219 million to $255 million annually. See
Table 5-7 and Table 5-8.
Monetized benefit categories are primarily in the areas of improved surface water quality
(measured in terms of enhanced recreational value), reduced nitrates in private wells, reduced shellfish
bed closures from pathogen contamination, and reduced fish kills from episodic events. EPA also
identified a number of benefits categories mat could not be monetized, including reduced euthrophication
of estuaries, reduced pathogen contamination in private wells, reduced health and environmental risks
associated with episodic pollutant discharge events, drinking water treatment cost savings, reduced odor
and air emissions, and avoided loss in property value near CAFOs, among other benefits. These benefits
are listed in Tables 5-7 and 5-8, and are described in more detail the Benefits Analysis and other
supporting documentation provided in the record.
These estimated benefits compare to EPA's estimate of the total social costs covering both
industry and permit authority costs for operations with more than 1,000 AU only. Assuming a 7-percent
discount rate, these costs range from $125 million (Option 1) to $289 million (Option 2) annually for all
CAFOs with more than 1,000 AU, as was estimated hi the Agency's Benefit Analysis. Assuming a 3-
percent discount rate, these costs range from $132 million (Option 1) to $285 million (Option 2) annually
for all CAFOs with more than 1,000 AU. See Table 5-7 and Table 5-8. These costs include compliance
costs to all CAFOs, as well as administrative costs to Federal and State governments. EPA estimates of
the administrative cost to Federal and State governments to implement this rule is $9 million per year.
5-12
-------
There may be additional social costs that have not been monetized. However, these costs are
estimated based on the cost of land application based on nitrogen-based application rates, except in those
instances where EPA believes that phosphorus-based rates are likely to be appropriate. As discussed
previously, the final rule includes provisions for appropriate flexibilities in the use of phosphorus-based
rates, such as multi-year phosphorus application, but the potential costs savings resulting from these
flexibilities are not reflected in the analysis. Therefore, the costs of this rule may have been
overestimated.
Table 5-7 Total Annual Monetized Social Costs and Benefits (7% Rate); CAFOs >1,OOOAU
Category
Option 1
Option 2
millions $2001
Total Monetized Social Costs
industry Compliance Costs (pre-tax):
State/Federal Administrative Costs:
Total Social Costs
$119
$6
$125
$283
$6
$289
Total Monetized Benefits
Improved Surface Water Quality$166.2 to $298.6
Reduced Incidence of Fish KillsSO.l
Improved Commercial Shell FishingSO.3 to $3.4
Reduced Contamination of Private Wells$30.9
Reduced Contamination of Animal Water Supplies
Reduced Eutrophication of Estuaries$l.l to $1.7
Reduced Water Treatment Costs
Reduced eutrophication & pathogen contamination
of coastal & estuarine waters
Reduced pathogen contamination of private & public
underground sources of drinking water
Reduced human & ecological risks from antibiotics,
hormones, metals, salts
Improved soil properties
Reduced cost of commercial fertilizers for non-
CAFO operations
Total Benefits
$102.4 -$182.6
$0.0-80.1
$0.1 -$2.0
$33.3
$4.7
$0.1
$0.7 - $1,0
not monetized
not monetized
not monetized
not monetized
not monetized
$141.3 + [B]
- $223.8 + [B1
$166.2 -$298.6
$0.1
$0.3 -$3.4
$30.9
$5.3
$0.2
$1.1 -$1.7
not monetized
not monetized
not monetized
not monetized
not monetized
$204.1 + [B]
- $340.2 +[B]
Source: USEPA. May not add due to rounding. [B] represents the non-monetized benefits of the rale.
5-13
-------
I Category
Option 1
Option 2 1
millions $2001
| Total Monetized Social Costs
| Industry Compliance Costs (pre-tax):
I State/Federal Administrative Costs:
|j Total Social Costs
$279
$6
$285
| Total Monetized Benefits
1 Improved Surface Water Quality
| Reduced Incidence of Fish Kills
IJ Improved Commercial Shell Fishing
U Reduced Contamination of Private Wells
Reduced Contamination of Animal Water
1 Supplies
| Reduced Eutrophication of Estuaries
1 Reduced Water Treatment Costs
|{ Reduced eutrophication & pathogen
contamination of coastal & estuarine waters
II Reduced pathogen contamination of private &
| public underground sources of drinking water
1 Reduced human & ecological risks from
1 antibiotics, hormones, metals, salts
|| Improved soil properties
I] Reduced cost of commercial fertilizers for non-
11 CAFO operations
ViTotal Benefits
$102.4 -$182.6
$0.0 - $0.1
$0.1 -$2.0
$49.3
$4.7
$0.1
$0.7 -$1.0
not monetized
not monetized
not monetized
not monetized
not monetized
$157.3 + [B]
- $239.8 + [B]
$122
$6
5/32
$166.2 - $298.6 ||
— 1]
$0.1 1
$0.3 - $3.4
$45.7
$5.3
$0.2
$1.1 -$1.7
not monetized
not monetized
not monetized
not monetized
not monetized
Source: USEPA. May not add due to rounding.
5-14
-------
SECTION SIX
REFERENCES
AAEA (American Agricultural Economics Association). 2002. AAEA Distinguished Policy
Contribution Award Nomination, Food and Agricultural Policy Research Institute. Draft,
January 24. Attached letter from U.S. House of Representatives, Committee on Agriculture
members, Larry Combest and Charles Stenholm, supporting the nomination.
AAEA (American Agricultural Economics Association). 2001. Commodity Costs and Returns
Estimation Handbook. Updated October, 2001. .
Abel, Daft & Barley. 1993. Meat, Poultry and Dairy Product Exports: A Silent Revolution. Study
commissioned by several agricultural trade associations. Alexandria, VA: Abel, Daft & Barley.
ASAE (American Society of Agricultural Engineers). 1993. Manure Production and Characteristics.
ASAE D384-1. St. Joseph, Michigan: American Society of Agricultural Engineers.
Brigham, E.F., and L.C. Gapenski. 1997. Financial Management Theory and Practice. Fort Worth, TX:
The Dryden Press.
CCH (Commerce Clearing House, Inc.). 1999a. 2000 State Tax Handbook. Chicago, JJL: Commerce
Clearing House, Inc.
CCH (Commerce Clearing House, Inc). 1999b. 2000 U.S. Master Tax Guide. Chicago, IL: Commerce
Clearing House, Inc.
CCH (Commerce Clearing House, Inc.). 1995. Personal communication between Eastern Research
Group, Inc., and CCH, Inc., to resolve discrepancies on tax rates for Missouri and Rhode Island.
March 30. Chicago., IL: Commerce Clearing House, Inc..
Citizens Against Poultry Pollution. 2001. Public comments submitted to EPA on the Proposed National
Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Submitted by Jean Hagerbaumer. DCN 202603.
Council of Economic Advisors. 2000. Economic Report of the President. Washington, DC: U.S.
Government Printing Office. February.
Cryan, R. 2001. Personal communication between EPA and Roger Cryan concerning Farm Financial
Ratios. Attachments include information on financial performance and benchmark measures
from Gary Snider of Farm Credit of Western New York and David Kohl of Virginia Polytechnic
Institute and State University, Blacksburg, VA. September.
Cunningham, D. 2002. 2001-2002 Broiler Production Systems in Georgia: Costs and Returns Analysis.
University of Georgia. College of Agricultural and Environmental Sciences.
6-1
-------
Department of Agriculture (Illinois). 2001. Public comments submitted to EPA on the Proposed National
Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs (Illinois Department of Agriculture). Submitted by Joseph
Kernan.DCN 200280.
DPRA (DPRA Incorporated). 2001. Literature Review of Financial Impact Analyses of Agriculture
Facilities. Memorandum to A. Jones, Eastern Research Group, Inc., and R. Johnson, EPA.
November 23,2001.
DPRA (DPRA Incorporated). 1995. Economic Impact of National Nonpoint Source Management
Measures Affecting Confined Animal Facilities. Analysis on Agricultural Management
Measures under Section (g) of the Coastal Zone Act Reauthorization Amendments of 1990.
Prepared for U.S. EPA's Nonpoint Source Control Branch. Unpublished. Manhattan, Kansas.
May.
DPRA (DPRA Incorporated). 1993. Regulatory Impact Analysis: Proposed Standards for Pesticide
Containment Structures Under the Federal Insecticide, Fungicide, and Rodenticide Act as
Amended, 1998 (Final Report). September.
El-Osta, H.S., and J.D. Johnson. 1998. Determinants of Financial Performance of Commercial Dairy
Farms. Technical Bulletin No. 1859. Washington, DC: U.S. Department of Agriculture,
Economic Research Service, .
ENR (Engineering News Record). 2002. Construction Cost Index History (1908-2002).
.
Environmental Defense. 2001. Public comments submitted to EPA on the Proposed National Pollutant
Discharge Elimination System Permit Regulation and the Effluent Limitations Guidelines and
Standards for CAFOs. Submitted by Joe Rudek. DCN 202392.
ERG (Eastern Research Group, Inc.) 2002a. Hog Prices for 1998 and Future Years. Memorandum to R.
Johnson, EPA. June 4. (Memo submitted to USDA ERS for formal review; see USEPA, 2002f.)
ERG (Eastern Research Group, Inc.) 2002b. Option Selection Output Tables. Memorandum to R.
Johnson,' EPA. August 22.
ERG (Eastern Research Group, Inc.) 2002c. Sensitivity analyses using alternative financial data or
economic impact thresholds for the dairy, hog, and contract egg laying sectors. Memorandum to
R. Johnson, EPA. December 10.
ERG (Eastern Research Group, Inc.) 2001a. Review and Assessment of NCBA, FAPRI, and Iowa State
University Data Submittals. Memorandum to R. Johnson, EPA. October 3.
ERG (Eastern Research Group, hie.) 200 Ib. Discussion of Potential Changes or Additions to
Methodologies for the Farm Level Analysis. October 26.
ERG (Eastern Research Group). 2001c. Assessment of Need for Loan Feasibility Analysis Based on 40
Percent Down Payment on Environmental Improvements to Meet Proposed CAFO Regulations.
Memorandum to R. Johnson, EPA. November 20.
6-2
-------
ERG (Eastern Research Group, Inc.) 2001d. Compilation of Enterprise Budgets. Memorandum to R.
Johnson, EPA, June 29.
ERG (Eastern Research Group Inc.) 2001e. Lessons Learned from Sensitivity Analysis and Enterprise
Budgets. Memorandum to EPA's Aquatic Animal Production Industry Project File. December
31.
ERG (Eastern Research Group, Inc.). 2000a. Cost-Share and Technical Assistance Programs and the
CAFO Analysis. Memorandum to R. Johnson, EPA. August 16.
ERG (Eastern Research Group, Inc.). 2000c. Review of Cost Passthrough and Market Power
Literature-Revised. Memorandum to R. Johnson, EPA. August 24.
ERG (Eastern Research Group, Inc.). 2000d. Review of Productivity Literature—Revised.
Memorandum to R. Johnson, EPA. August 30.
ERG (Eastern Research Group, Inc.). 1999a. Beef and dairy market model development. Memorandum
to R. Johnson, EPA. July 30. (Revised January 29,2002, in order to include additional literature
source submitted by NCBA during the comment period.)
ERG (Eastern Research Group, Inc.). 1999b. Review of pork and poultry market studies. Memorandum
to R. Johnson, EPA. September 17.
ERG & DPRA (Eastern Research Group, Inc., and DPRA Incorporated). 2001. Review and Assessment
of USD A and FAPRI Data Submittals for the Hog Sector. Memorandum to R. Johnson, EPA.
November 13.
FAPRI (Food and Agricultural Policy Research Institute). 2001a. FAPRI's Analysis of EPA's Proposed
CAFO Regulations. Attachments include spreadsheets with modeling output and other input
data. University of Missouri-Columbia (see DCN 175051). FAPRI-UMC Report No. 06-01.
Juty- . (Submitted by Scott Brown as
public comments to EPA on the Proposed CAFO Regulations. DCN 235619.)
FAPRI (Food and Agricultural Policy Research Institute). 200 Ib. Financial Impact of Proposed CAFO
Regulations on Representative Broiler Farms. University of Missouri-Columbia. FAPRI-UMC
Report No. 07-01. July. . Submitted
by Brent Carpenter as public comments to EPA on the Proposed CAFO Regulations DCN
235695.
FAPRI (Food and Agricultural Policy Research Institute). 2001c. 2001 U.S. Baseline Briefing Book.
University of Missouri-Columbia. .
FAPRI (Food and Agricultural Policy Research Institute). 2001d. FAPRI U.S. Livestock and Dairy
Tables. December 2001. Preliminary estimates presented to USDA and industry analysts in
Washington, DC, in December 2001.
Faeth, P. 2000. Fertile Ground: Nutrient Trading's Potential to Cost-Effectively Improve Water
Quality. Chapter 5: .Economic Results, pp. 31-37. Washington, DC: World Resources Institute.
6-3
-------
Farm Journal. 1998. Find market niche online. Hogs Today. July/August.
Heimlich, R., and C.H. Barnard. 1995. Economics of Agricultural Management Measures in the Coastal
Zone. AER 698. Washington, DC: U.S. Department of Agriculture, Economic Research
Service.
House Committee on Agriculture. 2002. Joint Explanatory Statement of the Committee of Conference.
Conference Rep., H.R. 107-424, Cong. Rec. at H1923. Conference Committee report on the
2002 Farm Bill, . May 1.
flcerd, J. 2002. FAPRI's Analysis of EPA's Proposed CAFO Regulations. University of Missouri,
Department of Agricultural Economics. Attachment A of public comments submitted to EPA on
the 2001 Notice for Proposed National Pollutant Discharge Elimination System Permit
6-4
-------
Regulation and the Effluent Limitations Guidelines and Standards for CAFOs. Comments
submitted by the Sierra Club (Alex Sagady). DCN 400132. January 30.
Iowa State University. 2001. Public comments submitted to EPA on the Proposed National Pollutant
Discharge Elimination System Permit Regulation and the Effluent Limitations Guidelines and
Standards for CAFOs. Comments submitted by Richard F. Ross. DCN 201602. July 27.
Iowa State University. 1999. Planning the Farm Business. Commercial Egg Production Budget.
.
Iowa State University. 1999b. Financial Troubleshooting. Iowa State University Extension.
.
Iowa State University. 1998. Iowa's Pork Industry: Dollars and Scents. Pm-1746. Iowa State University
of Science and Technology, University Extension. January.
IRS (Internal Revenue Service). 1999a. The Complete Internal Revenue Code. New York, NY: The
Research Institute of America, Lie. July.
IRS (Internal Revenue Service). 1999b. How to Depreciate Property. Publication 946. Washington,
DC: Internal Revenue Service.
IRS (Internal Revenue Service). 1999c. Fanner's Tax Guide. Publication 225. Washington, DC:
Internal Revenue Service.
Jarnagin, B.D. 1996. Financial Accounting Standards: Explanation and Analysis. 18th edition. Chicago,
IL: Commerce Clearing House, Inc.
Kellogg, R. 2002. Profile of Farms with Livestock in the United States: A Statistical Summary.
Washington, DC: U.S. Department of Agriculture, Economic Research Service. January 4.
http://www.nhq.nrcs.usda.gov/land/pubs/livestockfarni.html
Kellogg, R.L., C. Lander, D. Moffitt, andN. Gollehon. 2000. Manure Nutrients Relative to the Capacity
of Cropland and Pastureland to Assimilate Nutrients: Spatial and Temporal Trends for the U.S.
Washington, DC: U.S. Department of Agriculture, Natural Resources Conservation Service.
Koonts, S., D. Hoag, L. Walker, and J. Brethour. 2000. Returns to Sorting and Market Timing of
Animals Within Pens of Fed Cattle. Paper presented at the Western Agricultural Economics
Association Annual Meetings, Vancouver, British Columbia, June 29-July 1.
Lander, C.H., D. Moffitt, and K. Alt. 1998. Nutrient Available from Livestock Manure Relative to Crop
Growth Requirements. Washington, DC: U.S. Department of Agriculture, Natural Resources
Conservation Service, .
LCBP (Lake Champlain Basin Program). 2000. Preliminary Evaluation of Progress Toward Lake
Champlain Basin Program Phosphorus Reduction Goals. Prepared by the Lake Champlain
Steering Committee. June.
6-5
-------
Madison, M. 1999. Personal communication between EPA and Milton Madison, poultry specialist, of
U.S. Department of Agriculture, Economic Research Service. January.
Martinez, S.W. 1999. Vertical Coordination in the Pork and Broiler Industries: Implications for Pork
and Chicken Products. AER777. Washington, DC: U.S. Department of Agriculture, Economic
Research Service. April, .
Massey^ R., Zulovich, J., Lory, J., and A. Milmier. 2002. Agronomic and Economic Impacts of Lagoon
Based Swine Operations Complying with the Proposed EPA Zero Discharge Rule (draft paper
and Power Point presentation).
McBride, W.D. 1997. Changes in U.S. Livestock Production, 1969-92. 'AER 754. Washington, DC:
U.S. Department of Agriculture, Economic Research Service. July.
Midwest Envrionmental Advocates. 2002. Public comments submitted to EPA on the Notice of Data
Availability for the Proposed National Pollutant Discharge Elimination System Permit
Regulation and the Effluent Limitations Guidelines and Standards for CAFOs. Comments
submitted by A. Hansen. DCN 400123.
National Center (National Center for Manure and Animal and Waste Management). 2002. Public
comments submitted to EPA on the Notice of Data Availability for the Proposed National
Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Comments submitted by Frank Humenik. DCN 400159.
NCBA (National Cattlemen's Beef Association). 2002. NCBA response to additional EPA request for
financial iriformation. April 8.
NCBA (National Cattlemen's Beef Association). 2002a." Public comments submitted to EPA on the
Notice of Data Availability for the Proposed National Pollutant Discharge Elimination System
Permit Regulation and the Effluent Limitations Guidelines and Standards for CAFOs. DCN
400192.
NCBA (National Cattlemen's Beef Association). 2001. Public comments submitted to EPA on the
Proposed National Pollutant Discharge Elimination System Permit Regulation and the Effluent
Limitations Guidelines and Standards for CAFOs. Includes attachment with alternate financial
data submitted to EPA. DCN 201165.
NCBA etal. (National Cattlemen's Beef Association etal.). 2001. Letter from National Cattlemen's
Beef Association, National Chicken Council, National Milk Producers Federation, National Pork
Producers Council, National Turkey Federation, The Alliance of Western Milk Producers, and
United Egg Producers to U.S. Senators. December 13.
NCBA (National Cattlemen's Beef Association et al.). 2001a. Testimony of Eric Davis, National
Cattlemen's Beef Association, Committee on Agriculture, Nutrition and Forestry, United States
Senate. July 24.
NCBA (National Cattlemen's Beef Association). 2000. Cattle and Beef Industry Statistics. March.
.
6-6
-------
NCSU (North Carolina State University). 1999. Alternative Animal Waste Management Technologies:
A Status Report. North Carolina State University, Animal and Poultry Waste Management
Center (APWMC). June 8.
NCSU (North Carolina State University). 1997a. Off-site Tom Finishing Operation: Enterprise Budget
for a Contract Grower. Prepared by Tom Vukina, extension economist, and James Parsons, areas
specialized agent. January.
.
NCSU (North Carolina State University). 1997b. Turkey Hens: Enterprise Budget for a Contract
Grower. Prepared by Tom Vukina, extension economist, and James Parsons, areas specialized
agent. January.
.
NCSU (North Carolina State University). 1994. Livestock Manure Production and Characterization in
North Carolina. Raleigh, NC: North Carolina Cooperative Extension Service.
NCSU (North Carolina State University). 1993. Broilers: Enterprise Budget for a Contract Grower.
October. .
NEWWT (Northeast Wisconsin Waters for Tomorrow, Inc.). 1994. Toward a Cost-Effectiveness
Approach to Water Resource Management in the Fox-Wolf River Basin: A First Cut Analysis.
Executive Summary. Green Bay, WI: Northeast Wisconsin Waters for Tomorrow, Inc.
NRDC, et al. (Natural Resources Defense Council). 2002. Letter to EPA Administrator, Christine Todd
Whitman, from NRDC, American Rivers, Defenders of Wildlife, Earthjustice, Environmental
Defense, Environmental Working Group , Friends of the Earth, Izaak Walton League of America,
National Audubon Society, National Environmental Trust, Oceana, Sierra Club, the Ocean
Conservancy, Union of Concerned Scientists, and US Public Interest Research Group on issues
pertaining to the Final CAFO Regulations. August 6.
NRDC (Natural Resources Defense Council). 2002. Public comments submitted to EPA on the Second
Notice of Data Availability for the National Pollutant Discharge Elimination System Permit
Regulation and the Effluent Limitations Guidelines and Standards for CAFOs. Comments
submitted by Melanie Shepherdson. DCN 400166.
NRDC (Natural Resources Defense Council). 2002a. Correspondence from Melanie Shepherdson, NRDC
to R.S. Johnson, EPA, Office of Water. Includes information from Ken Midkiff, member of the
. Missouri Technical Advisory Committee, obtained from Roger Hanson, Director of the Missouri
USDA, NRCS, during a Technical Advisory Committee meeting on August 9,2002. August 23.
NRDC (Natural Resources Defense Council). 1999. Settlement Agreement between EPA and NRDC
and Public Citizen, Inc. under NRDC et al. v. Reillv. Civ. No. 89-2980 (D.D.C.). December 7.
NMPF (National Milk Producers Federation). 2002. Public comments submitted to EPA on the Notice
of Data Availability for the Proposed National Pollutant Discharge Elimination System Permit
Regulation and the Effluent Limitations Guidelines and Standards for CAFOs. Comments
submitted by Jerome Kozak. DCN 400158.
6-7
-------
NMPF (National Milk Producers Federation). 2001. Public comments submitted to EPA on the
Proposed National Pollutant Discharge Elimination System Permit Regulation and the Effluent
Limitations Guidelines and Standards for CAFOs. Comments submitted by Jerome Kozak.
DCN 201352.
NPPC (National Pork Producers Council). 2002. Public comments submitted to EPA on the Notice of
Data Availability on the National Pollutant Discharge Elimination System Permit Regulation and
the Effluent Limitations Guidelines and Standards for CAFOs. Comments submitted by Kirk
Ferrell. DCN 400155.
NPPC (National Pork Producers Council). 2001. Public comments submitted to EPA on the Proposed
National Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Comments submitted by Barbara Determan. DCN
201438.
NPPC (National Pork Producers Council). 2001 a. Testimony of Jon Gaspers, National Pork Producers
Council, Committee on Agriculture, Nutrition and Forestry, United States Senate. July 24.
NPPC (National Pork Producers Council). 1998. Pork facts 1998/1999. Des Moines, IA: National Pork
Producers Council.
Ohio State University. 1999. Transferring Your Farm Business to the Next Generation. Ohio State
University Extension. Bulletin 862. .
Oklahoma State University. 1997. Contract Broiler Production Unit- New Grower; 20,000 Sq Ft Steel
Truss Poultry Building, 25,000 chicks. September 15.
.
OMB (Office of Management and Budget). 1996. Economic Analysis of Federal Regulations Under
Executive Order 12866. Washington, DC: Office of Management and Budget. January 11.
.
OMB (Office of Management and Budget). 1992. Guidelines and Discount Rates for Benefit-Cost
Analysis of Federal Programs. Appendix A. Revised circular no. A-94. Washington, DC:
Office of Management and Budget. October 29.
OSHA (Occupational Safety and Health Administration). 1999. Federal Register. 29 CFR Parts 1910,
1915, etc. Employer Payment for Personal Protective Equipment. Proposed Rule. March 31.
Perry, J., D. Banker, and R. Green. 1999. Broiler Farms' Organization, Management, and Performance.
ATJB 748. Washington, DC: U.S. Department of Agriculture, Economic Research Service.
March
Perez, A. 2000. Personal communication between EPA and Austin Perez of the Small Business
Administration. March.
Putnam, J.J., and J.E. Allshouse. 1999. Food Consumption, Prices, and Expenditures, 1970-97. SB 965.
Washington, DC: U.S. Department of Agriculture, Economic Research Service.
.
6-8
-------
Randall, C.W. 2000. Personal communication between EPA and Dr. Clifford Randall of Virginia
Polytechnic Institute and State University, Blacksburg, VA. August 6.
Randall, C.W., Z. Kisoglu, D. Sen, P. Mitta, and U. Erdal. 1999. Evaluation of Wastewater Treatment
Plants for BNR Retrofits using Advances in Technology. Final Report. Virginia Polytechnic
Institute and State University, Blacksburg, VA. Submitted to the Point Source Workgroup,
Nutrient Removal Subcommittee, Implementation Committee, Chesapeake Bay Program. May.
SBA (Small Business Administration). 2001. Public comments submitted to EPA on the Proposed
National Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Comments submitted by A. Perez and S. Walthall. DCN
202490.
SBA (Small Business Administration). 1998. Size Standards Used to Define Small Business Concerns.
ISCFRPart 121. Washington, DC: Small Business Administration.
http://www.sba.gov/regulations/121b.html#l21.201.
Sierra Club. 2001. Public comments submitted to EPA on the Notice of Data Availability for the
Proposed National Pollutant Discharge Elimination System Permit Regulation and the Effluent
Limitations Guidelines and Standards for CAFOs. Attachment 1: FAPRI's Analysis of EPA's
Proposed CAFO Regulations (John Dcerd, University of Missouri). Comments submitted by A.
Sagady. DCN 400132.
Sims, TJ. 1995. Characteristics of Animal Wastes and Waste-Amended Soils: An Overview of the
Agricultural and Environmental Issues. La: Animal Waste and the Land-Water Interface.
Kenneth Steele, ed., CRC Press/Lewis Publishers, Boca Raton.
Snyder, B. 2000. Personal communication between Eastern Research Group, Inc., and Brett Snyder of
the Office of Policy, USEPA. February 1.
Sommer, J., R. Hoppe, R. Green, and P. Korb. 1998. Structural and financial characteristics of U.S.
farms, 1995: 20* annual family farm report to Congress. Affi 746. Washington, DC: U.S.
Department of Agriculture, Economic Research Service. July.
Stam, J.M., D.L. Milkove, and G.B. Wallace. 2000. Indicators of Financial Stress in Agriculture
Reported by Agricultural Banks, 1982-99. Agricultural Income and Finance. AIS-74.
Washington, DC: U.S. Department of Agriculture, Economic Research Service. February.
.
Stam, J.M., S.R. Koenig, S.E. Bently, and H.F. Gale, Jr. 1991. Farm Financial Stress, Farm Exits, and
Public Sector Assistance to the Farm Sector in the 1980's. AER 645. Washington, DC: U.S.
Department of Agriculture, Economic Research Service.
Staples, D. 1998. Personal communication between EPA and David Staples of the United Egg
Producers. February.
6-9
-------
Tippett, J.P., and R.C. Dodd. 1995. Cost-Effectiveness of Agricultural BMPs for Nutrient Reduction in
the Tar-Pamlico Basin. Prepared by Research Triangle Institute for the North Carolina
Department of the Environment, Health, and Natural Resources. January.
<^ttp://www.epa.gov/owowwtrl/watershed/Proceed/mccarthy.html>.
University of Arkansas. 2000. Development of the Interactive Broiler Income Spreadsheet.
.
University of Idaho Cooperative Extension System. 1998. Idaho Livestock Cost and Returns Estimate.
Authors: Fiez, E.A., D.E. Falk, C.W. Gray, andKR. Rimbey. December. Holstein Replacement
Enterprise Budget: . Jersey
Replacement Budget: .
U.S. Census Bureau. 2000. 1997 NAICS Matched to 1997 SIC Sectors and Subsectors.
http://www.census.gov/epcd/naics/naics3dx.htnrifNll
U.S. Census Bureau. 1999. Statistical Abstract of the United States: 1999.
.
USDA (U.S. Department of Agriculture). 2001. World Agricultural Supply and Demand Estimates
(WASDE-BB). Office of the Chief Economist. Various dates. Downloaded 3/12/2002.
.
USDA (U.S. Department of Agriculture). 1998. Report of the USDA National Commission on Small
Farms: A Time to Act. MP-1545. January, http://www.reeusda.gov/agsys/smallfarm/report.htm
USDA and USEPA (U.S. Department of Agriculture and U.S. Environmental Protection Agency). 1999.
Unified National Strategy for Animal Feeding Operations. March 9.
.
USDA/APHIS (U.S. Department of Agriculture, Animal and Plant Health Inspection Service). 1995b.
Swine '95. Reference of 1995 Swine Management Practices: Parts I and n. October.
.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2002a. 1998 ARMS, Hog
data for EPA. (Second follow-up run for EPA based on EPA request.) Attachment includes
data. Memo to J. Agapoff and M. Ribaudo from M. Padgitt, USDA, Economic Research Service.
January 31.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2002b. Data: Commodity
Cost and returns. Data for farrow-finish, grow-finish, and dairy operations.
.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2002c. 2000 ARMS, Dairy
data for EPA. Attachment includes data. Memo to R. Johnson, EPA, from N. Gollehon, USDA
Economic Research Service. July 1.
6-10
-------
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2002d. Staff Analysis 02-
229. E-mail and attachment to R. Johnson, EPA, from M. Ribaudo, USDA Economic Research
Service. August 2.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2001. 1998 ARMS, Hog
data for EPA. (First EPA run.) Attachment in e-mail from M. Ribaudo, USDA, Economic
Research Service, to R. Johnson, EPA. August 21.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2001a. Costs and Returns:
Methods. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2001b. Farm Income and
Costs: Glossary. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2001c. Farm Business
Income Statements, 1996-99. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2001d. Farm Business
Balance Sheets, 1996-99. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2000a. ERS' New ARMS
Survey. January. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2000b. Farm Typology.
July. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2000d. Off-Farm Income
Supports Many Farm Households. Agricultural Income and Finance. AIS-74. February.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 2000e. USDA's Glossary
of Farm Structure Terms.
.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1999a. Data from the Farm
Costs and Returns Survey database (11,724 observations). February 17. Revised March 25.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1999c. Livestock, Dairy
and Poultry Outlook. January 26.
.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1998a, Livestock, Dairy
and Poultry Outlook. May 21.
.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1998b. Livestock, Dairy
and Poultry Outlook. December 29.
.
6-11
-------
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1997a. Classification of
Overall Financial Performance. .
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1997e. Staff Briefing
Paper. Financial Performance of U.S: Farm Businesses, 1996.
.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1996a. The Economic
Well-being of Farmer Operator Households, 1991-92. AER-666. Updated May, 1996.
USDA/ERS (U.S. Department of Agriculture, Economic Research Service). 1996b. Farmers' Use of
Marketing and Production Contracts. AER747. December.
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 2000a.
Census of Agriculture General Information and Frequently Asked Questions. January.
.
1997
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1999a. 1997
Census of Agriculture, Volume 1, Part 51, Chapter 1, United States summary and state data.
.
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1999c. Milk
Cows and Production: Final Estimates 1993-97. SB 952.
.
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1999d. Poultry
Production and Value. Final Estimates: 1994-1997. SB 958. May.
.
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1998a.
Agricultural Prices 1997 Summary. July.
.
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1998b.
Chicken and Eggs. Final Estimates: 1994-1997. SB 944. December.
.
USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1998f. Poultry
Production and Value: 1997 Summary. April, .
USDA/WAOB (U.S. Department of Agriculture, World Agricultural Outlook Board). 2002. USDA
Agricultural Baseline Projections to 2011. Staff Report WAOB-2002-1. A product of the
Interagency Agricultural Projections Committee. Office of the Chief Economist.
USDA/WAOB (U.S. Department of Agriculture, World Agricultural Outlook Board). 2000. USDA
Agricultural Baseline Projections to 2009. Staff Report WAOB-00-1. February.
.
6-12
-------
USDA/WAOB (U.S. Department of Agriculture, World Agricultural Outlook Board). 1999. USDA
Agricultural Baseline Projections to 2008. Staff Report WAOB-99-1.
.
USDC (U.S. Department of Commerce). 1999a. 1997 Census of Manufactures. Includes industry series
reports: Animal (Except Poultry) Slaughtering (EC97M-3116A), Meat Processed From Carcasses
(EC97M-3116B), Poultry Processing (EC97M-3116D), All Other Miscellaneous Food
Manufacturing (EC97M-3119H), Fluid Milk Manufacturing (EC97M-31 ISA), Creamery Butter
Manufacturing (EC97M-3115B), Cheese Manufacturing (EC97M-3115C), Dry, Condensed and '
Evaporated Dairy Product Manufacturing (EC97M-3115D), and Ice Cream and Frozen Dessert
Manufacturing (EC97M-3115E). .
USDC (US Department of Commerce, Bureau of Economic Analysis). 1997. Regional Multipliers, A
User Handbook for the Regional Input-Output Modeling System (RIMS n).
USDC (US Department of Commerce, Bureau of Economic Analysis). 1997b. Regional Multipliers, A
User Handbook for the Regional Input-Output Modeling System (RIMS II).
USDC (U.S. Department of Commerce, Bureau of Economic Analysis). 1996. Regional Input-Output
Modeling System (RIMS n) Data Files. June 19.
USEPA (U.S. Environmental Protection Agency). 2002. Development Document for the Final
Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent
Guidelines for Concentrated Animal Feeding Operations.
USEPA (U.S. Environmental Protection Agency). 2002a. Summary of USDA-EPA Meeting on
Financial Data (December 4,2001). Memorandum to the Rulemaking Record. Includes follow-
up e-mail. R.S. Johnson, U.S. Environmental Protection Agency, Office of Water. January 4.
USEPA (U.S. Environmental Protection Agency). 2002b. Summary of USDA-EPA Meeting on
Financial Data (February 27). Memorandum to the Rulemaking Record. R.S. Johnson, U.S.
Environmental Protection Agency, Office of Water. February 28.
USEPA (U.S. Environmental Protection Agency). 2002c. Summary of USDA-EPA Meeting on
Financial Data (May 9). Memorandum to the Rulemaking Record. R.S. Johnson, U.S.
Environmental Protection Agency, Office of Water. May 14.
USEPA (U.S. Environmental Protection Agency). 2002d. EPA Request for Additional Data and
Information from USDA. Memorandum to the Rulemaking Record. R.S. Johnson, U.S.
Environmental Protection Agency, Office of Water. February 28.
USEPA (U.S. Environmental Protection Agency). 2002e. EPA's Consideration of an Approach that
Would Involve a Comprehensive Overhaul of EPA's Model to Assess Financial Impacts.
Memorandum to the Rulemaking Record. R. Johnson, U.S. Environmental Protection Agency,
Office of Water. January 30.
USEPA (U.S. Environmental Protection Agency). 2002f. EPA Request for USDA Review.
Memorandum to R. Heimlich, USDA ERS, from R.S. Johnson, U.S. Environmental Protection
6-13
-------
Agency, Office of Water. June 20. (Memo with attachment—ERG, 2002a—submitted to USDA
for review.)
USEPA (U.S. Environmental Protection Agency). 2002g. Economic Analysis for the Proposed Effluent
Guidelines and Standards for the Meat and Poultry Products Industry. EPA-821-B-01-006.
February.
USEPA (U.S. Environmental Protection Agency). 2002h. Economic Analysis of the Proposed Effluent
Limitations Guidelines and Standards for the Iron and Steel Manufacturing Point Source
Category. EPA 821-B-00-009. February.
USEPA (U.S. Environmental Protection Agency). 2002i. Economic and Environmental Impact Analysis
of the Proposed Effluent Limitations Guidelines and Standards for Concentrated Aquatic Animal
Production Industry Point Source Category. Forthcoming.
USEPA (U.S. Environmental Protection Agency). 2002J. Supporting Statement for the Information
Collection Request for the Final Regulatory Revisions to the National Pollutant Discharge
Elimination System Regulations for Concentrated Animal Feeding Operations and Feedlot
Effluent Limitations Guidelines.
USEPA (U.S. Environmental Protection Agency). 2002k. Environmental and Economic Benefit
Analysis of the Final Revisions to the National Pollutant Discharge Elimination System
Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations.
USEPA (U.S. Environmental Protection Agency). 20021. Summary of Option Selection Cost Analysis
Results. Memo to record from R.S. Johnson, EPA. Includes attachment of cost and regulatory
impact simulations conducted by Eastern Research Group (using EPA compliance cost estimates
from April, 2002). August 22.
USEPA (U.S. Environmental Protection Agency). 2002m. Summary of compiled data and information
comparing waste generation estimates from USDA for CAFO/AFOs and EPA estimates of
human waste. Memorandum to the Rulemaking Record by R.S. Johnson, EPA, Office of Water.
Includes follow-up e-mail and other supporting information. August 26.
USEPA (U.S. Environmental Protection Agency). 2002n. NPDES Support Document for the Final
Concentrated Animal Feeding Operations Rule. Office of Wastewater Management, Water
Permits Division, Rural Branch. December.
USEPA (U.S. Environmental Protection Agency). 2002o. Correspondence from Joseph Piotrowski,
USEPA, Region 3, to R.S. Johnson, EPA, Office of Water. August 29.
USEPA (U.S. Environmental Protection Agency). 2001a. Economic Analysis for the Proposed
Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent
Guidelines for Concentrated Animal Feeding Operations. EPA-821 -R-01-001. January.
USEPA (U.S. Environmental Protection Agency). 2001b. Development Document for the Proposed
Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent
Guidelines for Concentrated Animal Feeding Operations.
6-14
-------
USEPA (U.S. Environmental Protection Agency). 2001c. Summary of Correspondence to Obtain
Additional Follow-up Information. Memorandum to the Rulemaking Record by R.S. Johnson,
EPA, Office of Water. Includes follow-up e-mail. October 19.
USEPA (U.S. Environmental Protection Agency). 2001d. Summary of USDA-EPA Workgroup on
EPA's Cost and Economic Analysis. Memorandum to the Rulemaking Record by R.S. Johnson,
EPA, Office of Water. Includes agenda and meeting notes. October 19.
USEPA (U.S. Environmental Protection Agency). 2001e. Economic, Environmental, and Benefits
Analysis for the Proposed Metal Products & Machinery Rule. EPA-821-B-00-008. January.
USEPA (U.S. Environmental Protection Agency). 200 If. Summary of EPA Meeting with Natural
Resources Defense Council, Environmental Defense, and the Sustainable Agriculture Coalition.
September 19.
USEPA (U.S. Environmental Protection Agency). 2000a. Guidelines for Preparing Economic Analyses.
Washington, DC: U.S. Environmental Protection Agency. September.
.
USEPA (U.S. Environmental Protection Agency). 2000b. Economic Analysis of Final Effluent
Limitations Guidelines and Standards for the Landfills Point Source Category. EPA-821-B-99-
005.
USEPA (U.S. Environmental Protection Agency). 2000c. Economic Assessment for the Final Action
Regarding Pretreatment Standards for the Industrial Laundries Point Source Category (Revised
March 2000). 821-R-00-004. March.
USEPA (U.S. Environmental Protection Agency). 2000d. EPA Alternative Small Business Definition
for Animal Feeding Operations. Memorandum to the Rulemaking Record and unpublished
analysis. R.S. Johnson, U.S. Environmental Protection Agency, Office of Water. July 7.
USEPA(U.S. Environmental Protection Agency). 2000e. Final Report of the SBREFA Small Business
Advocacy Review Panel on National Pollutant Discharge Elimination System (NPDES) and
Effluent Limitations Guidelines for Concentrated Animal Feeding Operations (CAFOs). March.
.
USEPA (U.S. Environmental Protection Agency). 2000f. Supporting Statement for the Information
Collection Request for the Proposed Regulatory Revisions to the National Pollutant Discharge
Elimination System Regulations for Concentrated Animal Feeding Operations and Feedlot
Effluent Limitations Guidelines. July 31.
USEPA (U.S. Environmental Protection Agency). 2000g. Environmental Assessment of the Proposed
Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent
Guidelines for Concentrated Animal Feeding Operations.
USEPA (U.S. Environmental Protection Agency). 2000h. National Water Quality Inventory: 1998
Report to Congress. EPA-841-F-00-006. June.
.
6-15
-------
USEPA (U.S. Environmental Protection Agency). 2000J. Toxic and Pollutant Weighting Factors of the
Effluent Limitations Guidelines for Concentrated Animal Feeding Operations.
USEPA (U.S. Environmental Protection Agency). 1999a. Economic Analysis of Proposed Effluent
Limitations Guidelines and Standards for the Transportation Equipment Cleaning Industry Point
Source Category. May. .
USEPA (U.S. Environmental Protection Agency). 1999b. Economic Analysis of Final Effluent
Limitations Guidelines and Standards for the Commercial Hazardous Waste Combustors. EPA-
821-B-99-008.
USEPA (U.S. Environmental Protection Agency). 1999c. Revised Interim Guidance for EPA
Rulewriters: Regulatory Flexibility Act as amended by the Small Business Regulatory
Enforcement Fairness Act. March 29. .
USEPA (U.S. Environmental Protection Agency). 1999i. Revised Interim Guidance for EPA
Rulewriters: Regulatory Flexibility Act as amended by the Small Business Regulatory
Enforcement Fairness Act. March 29. .
USEPA (U.S. Environmental Protection Agency). 1999J. Memorandum documenting meetings between
EPA personnel and National Turkey Federation. December 1998 and February 1999.
USEPA (U.S. Environmental Protection Agency). 1998a. Economic Analysis of Effluent Limitations
Guidelines and Standards for the Centralized Waste Treatment Industry. EPA 821/R-98-019.
USEPA (U.S. Environmental Protection Agency). 1998b. Economic Analysis of Final Effluent
Limitations Guidelines and Standards for the Pharmaceutical Manufacturing Industry. .July.
USEPA (U.S. Environmental Protection Agency). 1997. Economic Analysis for the National Emission
Standards for Hazardous Air Pollutants for Source Category: Pulp and Paper Production;
Effluent Limitations Guidelines, Pretreatment Standards, and New Source Performance
Standards: Pulp, Paper, and Paperboard Category-Phase I. EPA 68-C3-0302. October 27.
USEPA (U.S. Environmental Protection Agency). 1996. Economic Analysis of Final Effluent
Limitations Guidelines and Standards for the Pesticide Formulating, Packaging, and Repackaging
Industry. EPA 821-R-96-017. September.
USEPA (U.S. Environmental Protection Agency). 1995. Economic Impact Analysis of Proposed
Effluent Guidelines and Standards for the Metal Products and Machinery Industry (Phase 1).
EPA 821-R-95-022. April.
USEPA (U.S. Environmental Protection Agency). 1994. Medical Waste Incinerators - Background
Information for Proposed Standards and Guidelines: Analysis of Economic Impacts for New
Sources. EPA 453/R-94-047a. July.
6-16
-------
USEPA (U.S. Environmental Protection Agency). 1987. Economic Impact Analysis of Effluent
Limitations Guidelines and Standards for the Organic Chemicals, Plastics and Synthetic Fibers
Industry. EPA 440/2/87-007. September.
USGPO (U.S. Government Printing Office). 2002. Notice of Data Availability; National Pollutant
Discharge Elimination System Regulation and the Effluent Guidelines for Concentrated Animal
Feeding Operations. Washington, DC: Environmental Protection Agency. Federal Register
67(141): 48099-48110. July 23.
USGPO (U.S. Government Printing Office). 2001a. National Pollutant Discharge Elimination System
Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations; Proposed
Revisions. Washington, DC: Environmental Protection Agency. Federal Register 66(9): 2960-
3145. January 12.
USGPO (U.S. Government Printing Office). 2001b. Notice of Data Availability; National Pollutant
Discharge Elimination System Regulation and the Effluent Guidelines for Concentrated Animal
Feeding Operations. Washington, DC: Environmental Protection Agency. Federal Register
66(225): 58556-58607. November 21.
USGPO (U.S. Government Printing Office). 2001c. Size Eligibility Requirements for SBA Financial
Assistance and Size Standards for Agriculture. 13 CFR Parts 107 and 121. Washington, DC:
Small Business Administration. Federal Register 66(110): 30646-30649. June 7.
.
USGPO (U.S. Government Printing Office). 2000. Small Business Size Regulations; Size Standards and
the North American Industry Classification System; Correction. 13 CFR Part 121. Washington,
DC: Small Business Administration. Federal Register 65(172): 53533-53558. September 5.
.
USGPO (U.S. Government Printing Office). 1999. Standard for Pesticide Containers and Containment.
Federal Register. 64(203): 56917-56944. October 21. Additional supporting information of
EPA's economic analysis for the proposed rulemaking is in "Regulatory Impact Analysis:
Standards for Pesticide Containment Structures Under the Federal Insecticide, Fungicide, and
Rodenticide Act as Amended, 1988" (1993).
USGPO (U.S. Government Printing Office). 1996. Several minor corrections were published on
February 23, 1996 (61 FR 6421). Federal Register 61(3175). January 31.
.
USGPO (U.S. Government Printing Office). 1991a. Small Business Size Standards; Egg Chicken
Industry. Federal Register 56(83): 19821-19825. April.
USGPO (U.S. Government Printing Office). 1991b. Small Business Size Standards; Egg Chicken
Industry. Federal Register 56(209): 55617. October.
USGPO (U.S. Government Printing Office). 1986. Best Conventional Pollutant Control Technology.
Effluent Limitations Guidelines. Final Rule. Federal Register 51'(103):24974-25002. July 9.
6-17
-------
Vukina, T. 2000. Personal communication between Eastern Research Group, Inc., and Tomislav Vukina
of North Carolina State University. March 3.
Waterkeepers Alliance et al. 2001. Public comments submitted to EPA on the Proposed National
Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Attachment B: Economic Analysis of FAPRI Report (Bill
Weida, Department of Economics at The Colorado College. Comments submitted by Nicolette
Hahn. DCN 400250.
Weida, B. 2002. Economic Analysis of FAPRI Report. Colorado College, Department of Economics.
Attachment B of public comments submitted to EPA on the 2001 Notice for the Proposed
National Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Comments submitted by the Waterkeepers Alliance et al.
(Nicolette Hahn). DCN 400250. February 4.
Westat. 2000. Methodology for Imputing Missing or Omitted USDA Census Data (with accompanying
data). Memorandum from Westat to M. Smith, U.S. Environmental Protection Agency, Office of
Water.
Wiedeman, A. 1998. Correspondence from Allison Wiedeman, Point Source Coordinator, Chesapeake
Bay Program, U.S. Environmental Protection Agency, to Mr. John Adsit, Stewards of Jackson
River. May 3.
Wisconsin Department of Natural Resources, 2002. Public comments submitted to EPA on the Proposed
National Pollutant Discharge Elimination System Permit Regulation and the Effluent Limitations
Guidelines and Standards for CAFOs. Comments submitted by Darrell Bazzell. DCN 201450
Wyoming Office of Federal Land Policty. 2002. Public Comments Submitted to EPA on the 2001
Notice of Data Availability (November, 2001). Submitted by Julie Hamilton. DCN 400172.
6-18
-------
APPENDIX A
COST ANNUALIZATION MODEL
This appendix provides an overview of the cost annualization model used by EPA. This model
calculates four types of compliance costs for a model CAFO:
• Present value of expenditures—before-tax basis
• Present value of expenditures—-after-tax basis
• Annualized cost—before-tax basis
• Annualized cost—after-tax basis '
The following sections present the input data and assumptions (Section A.1) and provide details about
the workings of the model (Section A.2). All supporting tables are provided at the end of this section.
A.1 INPUT DATA SOURCES
The cost annualization model requires four key data inputs:
• Capital and O&M costs (including startup, recurring, and annual O&M costs)
• Depreciable life of the asset
• Discount rate
• Marginal tax rate
The capital and O&M costs that EPA uses in the cost annualization model are developed by the
Agency. The capital cost is the initial investment needed to purchase and install the structure; it is a one-
time cost. The O&M cost is the annual cost of operating and maintaining the structure. O&M costs can
be incurred in the first year (start-up O&M costs), at periodic intervals (recurring O&M costs), or every
year of the structure's operation (annual O&M costs).
The depreciable life of the asset refers to EPA's assumption of the time period used to depreciate
capital improvements that are made because of the proposed CAFO regulations.
EPA's annualization model uses a real discount rate of 7 percent, as recommended by the Office
of Management and Budget (OMB) (OMB, 1992). EPA assumes this input to be a real interest rate, and
therefore it is not adjusted for inflation.
A-l
-------
The marginal tax rate (used to compute the tax shield) depends on the amount of taxable earnings
(estimated as net cash income minus depreciation plus value of inventory) at the model CAFO. Inputs to
the cost annualization model to calculate an average operation's tax shield include both federal and state
tax rates.
Additional information about compliance cost estimates and development of the model CAFOs is
provided in Section 2.2 of this report. Detailed information about the costs used as inputs to the
annualization model is provided in the Development Document (USEPA, 2002). Section A. 1.1 presents
the tax rates EPA assumes; Section A. 1.2 discusses the depreciation method in more detail.
A.1.1 Marginal Tax Rate
i
EPA conducts its financial analysis at the CAFO level using representative average models. The
cost annualization model uses both federal and state tax rates as inputs to calculate an average
operation's tax shield (see Table A-3 for sample worksheet). For this analysis, EPA uses federal and
state corporate income tax rates because it is not possible to definitively identify whether CAFOs
represented by each model pay taxes at the corporate or the individual rate.
Table A-l lists the range of federal tax rates that EPA assumes for this analysis and attributes to
model CAFOs based on estimated taxable earnings. As shown, federal tax rates range from 15 percent to
34 percent, depending on the amount of taxable income at a facility (CCH, 1999b). As an example, using
these rates, model CAFOs with earnings gi eater than or equal to $335,000 would be assigned the federal
tax rate of 34 percent; model CAFOs with earnings greater than or equal to $100,000 but less than
$335,000 would be assigned a tax rate of 28.3 percent.
Table A-l (provided at the end of this section) lists each state's top corporate tax rates and rates on
individual income (CCH, 1999a, 1995). The cost annualization model refers to reported average state tax
rates; however, because of the uncertainty over which state tax rate to apply to a given model CAFO, EPA
uses the national average across all states. Table A-l lists the national average values EPA assumes for this
analysis (CCH, 1999a, 1995). As shown, the average national rates are 6.6 percent (corporate income) and
5.8 percent (personal income). EPA uses the higher corporate income tax rate for this analysis.
The cost annualization model can incorporate variable tax rates according to the level of income
to address differences between small and large model CAFOs. For example, a large model CAFO might
have a combined tax rate of 40.6 percent (34 percent federal rate plus 6.6 percent state rate). After tax
shields, this model CAFO would pay 59.4 cents for every dollar of incremental animal waste
management costs. A small model CAFO might be in the 21.6 percent tax rate (15 percent federal rate
plus 6.6 percent state rate). After tax shields, the small model CAFO would pay 78.4 cents for every
dollar of incremental animal waste management costs. For the DCF analysis, EPA uses the net present
value of after-tax cost because it reflects the impact the business would actually see in its net income.'
'The cost annualization model does not consider tax shields on interest paid to finance animal waste
management investments. The cost annualization model assumes a cost to the operation to use the money (the
discount/interest rate), whether the money is paid as interest or is the opportunity cost of internal funding. Tax
shields on interest payments are not included in the cost annualization model because it is not known what mix of
debt and capital an operation will use to finance the cost of incremental animal waste management investments and
to maintain a conservative estimate of the after-tax annualized cost.
A-2
-------
A.1.2 Depreciation Method
After examining three alternatives to depreciate capital investments, including Modified
Accelerated Cost Recovery System (MACRS), straight-line depreciation, and section 179 of the Internal
Revenue Code, EPA chose to use the MACRS. MACRS allows businesses to depreciate a higher
percentage of an investment in the early years and a lower percentage in the later years. In contrast,
straight-line depreciation writes off a constant percentage of the investment each year. MACRS offers
companies a financial advantage over the straight-line method because a model CAFO's taxable income
may be reduced under MACRS by a greater amount in the early years when the time value of money is
greater. EPA also considered using the Internal Revenue Code section 179 provision to elect to expense
up to $ 17,500 in the year the investment is placed in service, assuming that the investment costs do not
exceed $200,000 (IRS, 1999a). EPA assumes, however, that this provision is already applied to other
investments at the CAFO.
To determine the recovery period of depreciable property, IRS identifies asset classes based on
the activity in which the property is being used. If no activity matches the use, IRS provides classes for
specific depreciable assets that are used across multiple business activities such as office furniture,
information systems, and automobiles. Under MACRS, the cost of property is recovered over a set
period. The recovery period is based on the property class to which your property is assigned. If the
property of interest is not identified by the IRS, it usually has a recovery period of 7 years (IRS, 1999b).
The capital costs required by this regulation fall across three IRS asset classes: land
improvements (15-year recovery period), agriculture (7-year recovery period), and single-purpose
agricultural or horticultural structures (10-year recovery period). Table A-2 (also provided at the end of
this section) presents these IRS asset classes as well as the capital costs associated with them. EPA has
identified the appropriate class for each type of cost and has judged that a 10-year time frame is
appropriate for this analysis for the following reasons:
• A 10-year depreciation time frame is consistent with the 10-year property classification of a
single-purpose livestock structure, which is defined under section(i)(13)(B) as any enclosure
or structure specifically designed, constructed and used for housing, raising, and feeding a
particular kind of livestock, including their produce, or for housing the equipment necessary
for the housing, rasing, and feeding of livestock (IRS, 1999a).
• A 10-year depreciation time frame is a fairly conservative assumption considering that some
assets, such as land improvements, have a longer 15-year time frame whereas others, such as
agricultural equipment, have a shorter 7-year time frame.
• This assumption provides a uniform time frame for use in the annualization model and
prevents the use of separate annualization calculations for individual capital costs.
• A 10-year time frame is consistent with the practice of cost-share programs, which typically
organize contracts over 5- to 10-year periods.
EPA conducted initial sensitivity analyses of the annualization model using initial cost estimates and
determined that the differences between using a 7-, 10-, or 15-year time frame for depreciation did not
result in large changes in annualized costs.
A-3
-------
A.2 SAMPLE COST ANNUALIZATION SPREADSHEET
Table A-3 shows a sample cost ammalization worksheet. The top of the spreadsheet shows the
data inputs described in Section A.l. The spreadsheet contains numbered columns that calculate the
before- and after-tax annualized cost of the investment to the CAFO. Column 1 of Table A-3 lists each
year of the investment's life span, from its installation through its 10-year depreciable lifetime (shown
over years 1 through 11, because a mid-year convention is used).
Column 2 of Table A-3 represents the percentage of the capital costs that can be written off or
depreciated each year. These rates are based on the MACRS and are taken from the 2000 U.S. Master
Tax Guide (CCH, 1999b). Multiplying these depreciation rates by the capital cost gives the annual
amount the model CAFO may depreciate, which is listed hi Column 3. EPA uses depreciation expense to
offset annual income for tax purposes; Column 4 shows the tax shield provided from the depreciation
expense—the overall tax rate times the depreciation amount for the year.
Column 5 of Table A-3 is the annual O&M expense. Because of the mid-year convention
assumption for depreciation, Year 1 and Year 11 show only 6 months of annual O&M costs. Year 1
O&M also includes the startup O&M cost. Years 2 through 10 include annual O&M plus recurring
O&M costs for every third and fifth year. Column 6 is the tax shield or benefit provided from expensing
the O&M costs.
Columns 7 and 8 represent any negative costs that should be evaluated when considering
compliance costs for model CAFOs. This example includes a scenario where EPA considers payments
from Federal, State, or local cost-share programs as well as other offsets measured in terms of cost
savings from use of manure as a fertilizer substitute. (These two examples are shown for illustrative
purposes only and do not necessarily reflect assumptions for EPA's final analysis.)
Column 9 lists a model CAFO's annual cash outflow, or total expenses, associated with the
additional animal waste management, under the analysis assumptions presented here. Total expenses
include capital costs, assumed to be incurred during the first year when the structure is installed, plus
each year's O&M expense.
Column 10 lists the annual cash outflow less the tax shields from the O&M expenses and
depreciation; a model CAFO will recover these costs in the form of reduced income taxes. The sum of
the 11 years of after-tax expenses is $106,546 (1997 dollars). The equation EPA uses to calculate the
present value of cash flow is :
NPV =
n
I
where:
v,...vn = series of cash flows
r = interest rate
n = number of cash flow periods
/ = current iteration
A-4
-------
EPA uses the present value of the after-tax cash outflow in the CAFO level impact analysis to calculate
the post-regulatory present value of future earnings for a model CAFO.
EPA transforms the present value of the cash outflow into a constant annual payment for use as
the annualized model CAFO's compliance cost. Column 9 calculates the annualized cost as a 10-year
annuity that has the same present value as the total cash outflow. The annualized cost represents the
annual payment required to finance the cash outflow after tax shields. In essence, paying the annualized
cost each year and paying the amounts listed in Column 8 for each year are equivalent. EPA calculates
the annualized cost as follows (where «is the number of payment periods):
Annualized Cost = present value of cash outflows * real discount rate
1 - (real discount rate + l)"n
In the example used in Table A-3 (provided at the end of this section), based on the capital
investment of $100,000, start-up O&M costs of $1,000, 3-year recurring O&M costs of $500, 5-year
recurring O&M costs of $1,500, annual O&M costs of $10,000 per year, a tax rate of 40.6 percent, and a
real discount rate of 7 percent, the model CAFO's annualized cost is $20,591 on apre-tax basis and
$ 12,729 on a post-tax basis.2
EPA uses the pre-tax annualized cost to calculate the total social cost of the regulation (presented
in Section 10). This approach incorporates the cost to industry for the purchase, installation, and
operation of additional animal waste management structures, as well as the cost to Federal and State
government from lost tax revenues. (Every tax dollar that a business does not pay due to a tax shield is a
tax dollar lost to the government.)
EPA uses the post-tax annualized cost to reflect what a business actually pays to comply with
incremental animal waste management requirements. The post-tax present value of incremental animal
waste management expenditures is used in the CAFO level impact analysis.
Appendix B of this report shows post-tax annualized costs to regulated CAFOs to comply with the
proposed revisions to the CAFO regulations. Annualized costs are shown in 1997 dollars and are
expressed on a per-facility and a per-animal (inventory) basis. Costs are shown for the BAT option only.
There are two ways to calculate post-tax annualized cost. One is to calculate the annualized cost as the
difference between the annuity value of the cash flows (Column 9) and the tax shields (Columns 4 and 6). The
second is to calculate the annuity value of the cash flows after tax shields (Column 10). Both methods yield the
same result.
A-5
-------
Table A-l. State Income Tax Rates
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
Corporate
Income Tax Rate
5.00%
9.40
9.00%
6.50%
9.30%
5.00%
11.50%
8.70%
5.50% '
6.00%
6.40%
" 8.00%
4.80%
3.40%
12.00%
4.00%
8.25%
8.00%
8.93%
7.00%
9.50%
2.30%
9.80%
5.00%
6.25%
6.75%
7.81%
0.00%
Basis for States
With Graduated
Tax Tables
$90,000+
$100,000+
$100,000+
$250,000+
$50,000+
$250,000+
$200,000+
$250,000+
$10,000+
$50,000+
Personal
Income Tax
Upper Rate
5.00%
0.00%
6.90%
7.00%
11.00%
5.00%
4.50%
7.70%
0.00%
6.00%
10.00%
8.20%
3.00%
3.40%
9.98%
7.75%
6.00%
6.00%
8.50%
6.00%
5.95%
4.40%
8.50%
5.00%
6.00%
11.00%
6.99%
0.00%
Basis for States
With Graduated
Tax Tables
$3,000+
$150,000+
$25,000+
$215,000+
$40,000+
$7,000+
$21,000+
$20,000+
$47,000+
$30,000+
$8,000+
$50,000+
$33,000+
$100,000+
$50,000+
$10,000+
$9,000+
$63,000+
$27,000+
A-6
-------
Table A-l. State Income Tax Rates
State
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Average:
Corporate
Income Tax Rate
7.00%
7.25%
7.60%
9.00%
7.75%
10.50%
8.90%
6.00%
6.60%
9.90%
9.00%
5.00%
0.00%
6.00%
0.00%
5.00%
8.25%
6.00%
0.00%
9.00%
7.90%
0.00%
6.61%
Basis for States
With Graduated
Tax Tables
$1 Million+
$50,000+
Based on stock
value
1997 and thereafter
$250,000+
Personal
Income Tax
Upper Rate
0.00%
6.65%
8:50%
7.88%
7.75%
12.00%
7.50%
7.00%
9.00%
2.80%
10.40%
7.00%
0.00%
0.00%
0.00%
7.20%
9.45%
5.75%
0.00%
6.50%
6.93%
0.00%
5.84%
Basis for States
With Graduated
Tax Tables
$75,000+
$42,000+
$13,000+
$60,000+
$50,000+
$200,000+
$10,000+
$5,000+
$250,000+
$11,000+
$4,000+
$250,000+
$17,000+
$60,000+
$20,000+
Source: CCH, 1999a, 1995.
Basis for rates is reported to nearest $1,000. Personal income tax rates for Rhode Island and Vermont
based on federal tax (not taxable income). Tax rates given here are equivalents for highest personal
federal tax rate.
A-7
-------
S
o
eo a .S S
a s — « s
11!
S §P 8 —
1 _l O "g
a f>.
CO ^=5 W *e3 H-3 W Q^t^r^^
i i i G i l <5 i i i i
to or
245
J5
el
l
I •§ 111 i
-------
&>.>;•«
I I JS
.52 t t t t t
S^Is
v v v v
a a a
ro CQ CO
o o o o o
ff* O O O
u W ^3 ^3 tJ
A O" "X" O" V?
A wi r- o m
, if *"*f®
•i fa
PH
O
O
•n.
& §§§§=>§ oSjvq
I—c o"o"-<''a~'^~*' — i« ^>
—• O t-ri 6
-------
-------
APPENDIX B
SUMMARY TABLES:
ANNUALIZED COSTS PER FACILITY AND PER ANIMAL
This appendix shows EPA's annualized compliance cost estimates for two technology options
evaluated for this rulemaking. The first option (Option 1) will require land application at the CAFO to be
consistent with proper agricultural practices, including limiting manure application to the nitrogen needs of
the crops grown. The second option (Option 2) will require land application at the CAFO to be consistent
with proper agricultural practices, including limiting manure application to the nitrogen needs of the crops
grown or where necessary, to the phosphorus needs of the crops.
Costs presented in this section are annualized using the methods described in Appendix A.
Annualized costs presented in this appendix include representative model CAFO costs by fecility (Table
B-l) and by per-animal inventory (Table B-2). Costs are expressed in 1997 dollars.
Compliance costs are estimated for each representative model CAFO and are broken out by
animal sector, production region, and facility size, as well as groupings based on land availability and the
technology needs of the facility:
Production region: Midwest (MW); Central (CE); Pacific (PA); Mid-Atlantic (MA);
and South (SO). For more information, see Table 2-1 in Section 2 of this report.
• Facility size: Varies by sector. See Table 2-1 in Section 2 of this report.
Land availability: Category 1 CAFOs (sufficient cropland for all manure nutrients
generated), Category 2 CAFOs (insufficient cropland), and Category 3 CAFOs (no
available cropland for land application).
Technology needs: Medium (average needs); Low (least needs); High (most needs).
More detailed cost information is available in the Development Document (USEPA, 2002).
B-l
-------
Table B-I(a)
Total Estimated Annuallzed Compliance Costs, Option 1
Sector Model
Bctf
MW Region
Medium 1
Medium 2
Medium 3
Lugel
LirgeZ
CE Region
Medium 1
Medium 2
Mediums
Luiel
Large 2
PA Region
Medium 1
Medium 2
Mediums
large I
Large 2
SO Region
Medium 1
Medium 2
Mediums
Ltrge 1
Large 2
MA Region
Medium 1
Medium 2
MediumS
Large 1
Large 2
Veal
MW Region
Medium I
Medium 2
Medium 3
Large I
CE Region
Medium 1
Medium 2
Mediums
Large 1
PA Region
Medium 1
Medium 2
Medium 3
Lugel
SO Region
Medium 1
Medium 2
MediumS
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Head Cat. 1L
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897.
370
552
766
1,839
25,897
370
552
766
1,839
25,897
-100
540
1,080
1,080
400
540
1,080
NA
400
540
1,080
NA
400
540
1,080
NA
400
540
1,080
NA
54,298
$4,630
$4,915
53,848
$19.994
53,980
$4,269
$4,139
$4,025
$23,423
S4.984
S5.479
$6,021
$5,324
$21,149
$4,415
$5,287
$6,337
$5,403
$30,374
$4,131
$4,919
$5,993
$5,208
$27,815
$1,813
$1,813
$1,813
$1,813
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
$1,813
$1,813
51,813
NA
Cat2L CatSL Cat 1M
$4,383
$4,715
$5,002
$5,114
$14,775
$4,101
•$4,388 '
$4,642
$3,411
$16,366
$6,943
$5,773
$6,316
$81,099
$40,082
$16,355
$5,045
$6,420
$89,641
$257,633
$9,679
$4,615
$5,086
$27,085
$54,186
$1,535
$1,535
$1,535
$1,535
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$2,388
$2,604
$2,885
$1,363
$3,621
$2,230
$2,381
$2,573
$1,415
$2,000
$2,956
$3,405
$3,892
$1,317
$2,972
$3,055
$3,529
$4,040
$1,796
$6,436
, $2,742
$3,120
$3,535
$1,513
$4,357
$1,400
$1,400
$1,400
$1,400
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$6,114
$6,442
$6,828
$5,902
$30,765
$5,980
$6,264
$5,741
$6,173
$32,826
$6,673
$7,213
$7,805
$8,526
$33,372
$6,720
$8,225
$10,145
$11,044
$59,834
$5,854
$7,105
$8,925
$9,457
$51,354
$1,813
$1,813
$1,813
$1,813
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
Cat. 2M Cat.3M Cat. 1H
$6,189
$6,518
$6,907
$7,121
$25,003
$6,087
$6,370
$6,695
$5,485
$24,920
$8,626
$7,501
$8,093
$83,064
$51,885
$18,643
$7,388
$10,212
$92,266
$280,277
$11,390
$6,358
$6,868
$29,011
$66,159
$1,535
$1,535
$1,535
$1,535
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$2,676
$2,944
$3,260
$1,984
$7,314
$2,460
$2,642
$2,850
$1,838
$4,074
$3,254
$3,745
$4,275
$1,892
$6,018
$3,361
$3,878
$4,439
$2,436
$11,277
$3,037
$3,442
$3,885
$2,020
$7,491
$1,400
$1,400
$1,400
$1,400
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$7,698
$8,045
$8,460
$7,639
$39,479
$7,577
$7,881
$7,024
$7,930
$40,983
$8,241
$8,799
$9,410
$11,434
$43,861
$8,297
$10,242
$12,764
$14,912
$79,486
$7,245
$8,889
$11,324
$12,963
$69,907
$1,813
$1,813
$1,813
$1,813
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
$1,813
$1,813
$1,813
NA
Cat.2H Cat.SH
$7,765
$8,111
$8,531
$8,812
$33,175
$7,671
$7,974
$8,328
$7,168
$32,229
$10,187
$9,081
$9,691
$84,734
$61,955
$20,212
$8,990
$12,823
$94,044
$295,331
$12,776
$7,800
$8,367
$30,724
$76,019
$1,535
$1,535
$1,535
$1,535
$1,535
.$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$2,867
$3,148
$3,489
$2,288
$8,951
$2,658
$2,852 '
$3,080
$2,126
$4,900
$3,430
$3,935
$4,481
$2,173
$7,332
$3,551
$4,096
$4,689
$2,831
$13,960
$3,322
$3,780
$4,277
$2,630
$10,532
$1,400
$1,400
$1,400
$1,400
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
-------
Table B-l(a)
Total Estimated Annuitized Compliance Costs, Option 1
Sector Model
Heifers
MW Region
Medium 1
Medium 2
Medium 3
Large!
CE Region
Medium 1
Medium 2
Medium 3
Large 1
PA Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Dairy- Flush
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium3
Large 1
CE Region
Medium i
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Dairy- Hose
PA Region
Medium 1
Medium 2
Medium 3
Large 1
Head
400
625
875 •
1,500
400
625
875
' 1,500
400
625
875
1,500
400
625
875
1,500
400
625
875
1,500
250
425
600
1,430-
250
425
600
1,430
250
.425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
Cat. 1L
$6,044
$4,579
$4,852
$3,440
$5,379
$4,111
$4,317'
$3,282
$6,988
$7,544
$6,006
$3,335
$5,672
$4,880
$6,315
$4,436
$5,487
$4,551
$6,062
$4,531
$1,772
$2,121
$2,460
$2,011
$1,912
$2,351
$2,781
$2,754
$1,924
$2,373
$2,815
$2,863
$1,841
$2,240
$2,627
$2,414
$1,416
$1,790
$2,160
$1,809
$3,267
$4,793
$5,207
$2,299
Cat2L
. $6,145
$4,683
$4,871
$3,545
$5,498
$4,230
$4,360
$3,401
$23,067
$15,577
$9,485
$4,028
$18,589
$17,877
$12,519
$17,576
$11,996
$9,321
$7,682
$4,490
$1,794
$60,242
$22,406
$121,703
$1,878
$32,791
$2,595
$24,811
$1,899
$60,175
$2,673
$32,251
$1,820
$57,886
$54,503
$66,531
$1,393
$42,235
$8,217
$61,026
$3,376
$5,387
$5,797
$4,343
Cat.3L
$2,507
$2,645
$2,947
$1,322
$2,301
$2,408
$2,625
$1,380
$3,202
$3,491
$4,007
$1,287
$3,325
$3,602
$4,161
$1,688
$2,967
$3,189
$3,629
$1,450
$1,537
$1,796
$2,045
$1,174
$1,556
$1,820
$2,074
$1,219
$1,537
$1,796
$2,045
$1,174
$1,537
$1,796
$2,045
$1,174
$1,181
$1,441
$1,693
$791
$2,743
$4,178
$4,504
$1,174
Cat. 1M
$9,358
$6,389
. $6,764
$5,382
$9,108
$6,094
$6,365
$5,324
$10,041
$10,832
$7,788
$5,236
$9,926
$7,227
$10,225
$9,426
$8,594
$6,301
$9,068
$8,317
$3,789
$5,185
$6,531
$11,083
$3,951
$5,446
$6,896
$11,915
$3,955
$5,459
$6,920
$12,013
$3,875
$5,328
$6,731
$11,548
$3,386
$4,809
$6,188
$10,841
$4,235
$5,805
$6,262
$3,495
Cat2M
$9,457
$6,492
$6,782
$5,485
$9,223
$6,210
$6,405
$5,441
$26,118
$17,309
$11,266
$5,927
$22,841
$20,221
$14,920
$22,321
$15,098
$11,068
$9,465
$7,884
$3,808
$63,290
$26,461
$130,723
$3,912
$35,859
$6,682
$33,876
$3,924
$63,231
' $6,745
$41,293
$3,849
$60,946
$58,578
$75,569
$3,361
$45,237
$12,228
$69,999
$4,342
$6,385 .
$6,835
$5,485
CaLSM
$2,795
$2,992
$3,332
$1,866
$2,533
$2,674
$2,908
$1,763
$3,501
$3,838
$4,401
$1,795
$3,632
$3,961
$4,573
$2,241
$3,264
$3,515
$3,987
$1,904
$3,529
$4,826
$6,075
$10,166
$3,558
$4,864
$6,120
$10,236
$3,529
$4,826
$6,075
$10,166
$3,540
$4,839
$6,091
$10,191
$3,129
$4,429
$5,681
$9,739
$3,108
$4,580
$4,939
$1,712
Cat 1H
$12,306
$7,986
$8,390
$7,056
$12,061
$7,697
$7,992
$6,994
$12,972
$13,966
$9,385
$6,886
$12,867
$8,833
$12,918
$12,859
$11,078
$7,752
$11,539
$11,447
$3,958
$5,368
$6,727
$13,031
$4,131
$5,648
$7,119
$13,927
$4,137
$5,665
$7,148
$14,039
$4,050
$5,522
$6,942
$13,532
•$3,499
$4,933
$6,325
$12,724
$4,982
$6,567
$7,037
$4,411
Cat 2H
. $12,402
$8,087
$8,405
$7,157
$12,175
$7,811
$8,031
$7,108
$29,049
$18,886
$12,863
$7,576
$25,779
$21,826
$16,561
$25,584
$17,581
$12,518
$10,974
$10,708
$3,975
$63,458
$26,642
$132,616
$4,087
$36,034
$6,878
$35,792
$4,101
$63,406
$6,943
$43,210
$4,018
$61,112
$58,762
$77,458
$3,470
$45,345
$12,349
$71,821
$5,087
$7,131
$7,595
$6,347
Cat.SH
$2,988
$3,200
$3,566
$2,140
$2,730
$2,886
$3,141
$2,030
$3,679
$4,031
$4,610
$2,053
$3,823
$4,184
$4,829
$2,583
$3,550
$3,862
$4,391
$2,436
$3,672
$4,976
$6,230
$12,034
$3,702
$5,014
$6,275
$12,104
$3,672
$4,976
$6,230
$12,034
$3,683
$4,990
$6,246
$12,059
$3,221
$4,525
$5,779
$11,539
$3,252
$4,730
$5,094
$1,969
-------
Table B-I(a)
Total Estimated Annuitized Compliance Costs, Option 1
Stctor Model Head Cat. 1L Cat2L
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Mediums
Largel
SO Region
Medium t
Medium 2
Medium 3
Large 1
MA. Region
Medium 1
Medium 2
Medium 3
Largel
Hogs Liquid
MW Region (GF)
Medium 1
Medium 2
Medium 3
Largel
Large 2
MA Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Largo 2
MW Region (FF)
Medium 1
Medium 2
Medium 3
Largel
Large 2
MA Region (FF)
Medium 1
Medium 2
Medium 3
Largel
Large 2
Hogs Fit
MW Region (GF)
Medium 1
Medium 2
Medium 3
Largel
Large 2
MA Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
863
1.311
1,884
2,500
5.094
883
1,345
1,887
2,500
6,390
863
Ull
1.884
2,500
5,094
883
1,345
1,887
2,500
6,390
$2,748
$3,817
S4.374
$3,149
$2,921
$3,716
$4,801
$3,152
$4,058
$5,551
59,316
$3,905
$2,606
$3,294
$4,033
$2,784
$1,223
SI, 26-1
$1,312
$902
S906
$1,173
$1,223
$1,277
$904
$915
$1,223
$1,264
$1,312
$902
$906
$1,173
$1,223
$1,277
$904
$915
$1,180
$1,227
$1,286
S904
$911
$1,141
$1,204
$1,274
$908
$926
$2,756
$3,467
$4,421
$2,512
$2,969
$3,974
$4,764
$2,919
$4,082
$5,679
$6,097
$7,203
$2,614
$3,347
$4,084
$2,542
$1,834
$2,036
$2,274
$1,947
$3,334
$1,717
$1,881
$2,078
$2,148
$3,548
$1,834
$2,036
$2,274
$1,947
$3,334
$1,717
$1,881
$2,078
$2,148
$3,548
$1,274
$1,331
$1,425
$1,527
$925
$1,138
SI, 155
$1,206
$904
$915
Cat3L Cat. 1M Cat.ZM Cat.SM
$2,021
$2,515
$3,297
$1,219
$2,246
$2,850
$3,449
$1,174
$2,685
$4,038
$4,315
$1,174
$1,807
$2,380
$2,999
$791
$1,002
$1,017
$1,030
$899
$899
$1,002
$1,016
$1,029
$899
$899
$1,002
$1,017
$1,030
$899
$899
' $1,002
$1,016
$1,029
$899
$899
$919
$919
$919
$899
$899
$919
$919
$919
$899
$899
$4,389
$6,841
$6,123
$5,103
$3,903
$4,751
$6,475
$4,426
$4,869
$6,415
$11,496
$5,149
$3,530
$4,265
$5,049
$4,221
$1,360
$1,405
$1,459
$1,282
$1,360
$1,401
$1,469
$1,543
$1,210
$1,279
$1,360
$1,405
$1,459
$1,282
$1,360
$1,401
$1,469
$1,543
$1,210
$1,279
$1,329
$1,384
$1,453
$1,255
$1,346
$1,398
$1,493
$1,598
$1,167
$1,228
$4,392
$5,137
$6,143
1 $4,370
$3,946
$4,979
$5,820
$4,085
$4,888
$6,514
$6,982
$8,191
$3,536
$4,301
$5,082
$3,598
$1,909
$2,094
$2,320
$2,185
$3,679
$1,879
$2,023
S2-.2I6
$2,243
$3,570
$1,909
$2,094
$2,320
$2,185
$3,679
$1,879
$2,023
$2,216
$2,243
$3,570
$1,439
$1,505
$1,614
$1,899
$1,510
$1,395
$1,421
$1,497
$1,154
$1,191
$2,399
$2,933
$3,751
$1,781
$2,611
$3,252
$3,883
$1,712
$3,061
$4,452
$4,766
$1,736
$2,132
$2,742
$3,396
$1,285
$1,084
$1,099
$1,112
$1,189
$1,246
$1,084
$1,098
$1,111
$1,188
$1,239
$1,084
$1,099
$1,112
$1,189
$1,246
$1,084
$1,098
$1,111
$1,188
$1,239
$1,008
$1,008
$1,008
$1,118
$1,118
$1,008
$1,008
$1,008
$1,118
$1,118
Cat. 1H Cat.ZH Cat.3H
$5,612
$9,215
$7,392
$6,511
$4,664
$5,536
$7,868
$5,419
$5,449
$7,014
$13,379
$6,087
$4,148
$4,895
$5,692
$5,215
$1,451
$1,496
$1,550
$1,586
$1,733
$1,494
$1,563
$1,637
$1,642
$1,953
$1,451
$1,496
$1,550'
$1,586
$1,733
$1,494
$1,563
$1,637
$1,642
$1,953
$1,420
$1,476
$1,545
$1,527
$1,694
$1,492
$1,587
$1,694
$1,619
$2,031
$5,610
$6,356
$7,384
$5,683
$4,701
$5,731
$6,596
$4,969
$5,463
$7,086
$7,571
$8,873
$4,150
$4,914
$5,707
$4,261
$2,001
$2,187
$2,413
$2,528.
$4,255
$1,972
$2,117
$2,310
$2,699
$4,317
$2,001
$2,187
$2,413 .
$2,528
$4,255
.$1,972
$2,117
$2,310
$2,699
$4,317
$1,531
$1,598
$1,707
$2,190
$1,995
$2,091
$3,571
$4,449
$2,006
$3,200
$2,545
$3,086
$3,910
$2,038
$2,755
$3,402
$4,039
$1,969
$3,204
$4,603
$4,921
$1,993
$2,227
$2,841
$3,498
$1,474
$1,173
$1,187
$1,200
$1,363
$1,480
$1,173
$1,186
$1,199
$1,361
$1,464
$1,173
$1,187
$1,200
$1,363
$1,480
$1,173
$1,186
$1,199
$1,361
$1,464
$1,096
$1,096
$1,096
' $1,223
$1,223
$1,096
$1,096
$1,096
$1,223
$1,223
B-4
-------
Table B-l(a)
Total Estimated Annualizcd Compliance Costs, Option 1
Sector Model
MW Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MA Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Hogs Evaporate
CE Region (GF)
Large 1
Large 2
CE Region (FF)
Large!
Large 2
Broilers
SO Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Layers
Wet SO Region
Medium 2
Medium 3
Large 1
Dry SO Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Dry MW Region
Medium 1
Medium 2
Medium 3
Large]
Large 2
Turkeys
MA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
Head
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
2,500
6,038
2,500
6,038
38,802
53,942
82,907
125,000
219,247
39,642
55,618
85,355
125,000
219,247
NA
19,500
146,426
36,068
61,734
78,546
291,153
856,368
36,068
61,734
78,546
291,153
856,368
22,246
34,640
47,534
127,396
22,246
34,640
47,534
127,396
Cat. 1L
$1,180
$1,227
$1,286
$904
$911
$1,141
$1,204
$1,274
$908
$926
$902
. $907
$902
$907
$1,456
$1,704
$2,112
$2,760
$4,509
$1,495
'$1,724
$2,096
$2,886
$4,874
NA
$808
$955
$1,378
$1,808
$2,112
$3,723
$9,307
$1,126
$1,377
$1,563
$2,710
$6,328
$2,552
$3,346
$4,167
$9,311
$2,305
$3,018
$3,754
$8,515
Cat2L
$1,274
$1,331
$1,425
$1,527
$925
$1,138
$1,155
$1,206
. $904
$915
$906
$920
$906
$920
$1,193
$1,283
$1,434
$1,683
$2,349
$1,295
$1,425
$1,597
$1,947
$2,834
NA
$809
$918
$1,373
$1,801
$2,119
$3,623
$9,004
$1,120
$1,369
$1,568
$2,602
$6,002
$2,128
$2,535
$3,047
$5,427
$2,030
$2,438
$2,950
$5,416
CaL3L
$919
$919
$919
$899
$899
$919
$919
$919
$899
$899
$899
$899
$899
$899
$883
$946
$1,009
$1,226
$1,726
$1,021
$1,088
$1,160
$1,470
$2,106
NA
$801
$902
$1,365
$1,786
$2,084
$3,618
$8,999
$1,112
$1,353
$1,533
$2,597
$5,996
$1,463
$1,770
$2,085
$4,174
$1,459
$1,767
$2,081
$4,172
Cat. 1M
$1,329
$1,384
$1,453
$1,255
$1,346
$1,398
$1,493
$1,598
$1,167
$1,228
$1,290
$1,391
$1,290
. $1,391
$3,915
$5,039
$7,068
$8,696
$16,089
$1,853
$2,138
$2,607
$3,374
$5,701
NA
$1,096
$1,425
$2,705
$3,898
$4,703
$8,556
$23,008
$2,175
$3,001
$3,565
$6,41!
$16,724
$3,94!
$5,461
$7,037
$16,957
$3,766
$5,203
$6,693
$16,102
Cat. 2M
$1,439
$1,505
$1,614
$1,899
$1,510
$1,396
$1,422
$1,500
$1,154
$1,191
$1,350
$1,577
$1,350
$1,577
$3,558
$4,576
$6,313
$7,509
$15,352
$1,593
$1,748
$1,958
$2,262
$3,269
NA
$1,100
$16,116
$2,722
$3,923
$4,737
$8,241
$21,794
$2,202
. $3,042
$3,583
$6,176
$15,749
$3,660
$4,924
$6,294
$14,342
$3,623
$4,902
$6,276
$14,500
Cat. 3M
$1,008
$1,008
$1,008
$1,118
$1,118
$1,008
$1,008
$1,008
$1,118
$1,118
$1,200
$1,328
$1,200
$1,328
$3,066
$4,039
$5,651
$6,671
$14,825
$1,119
$1,195
$1,275
$1,619
$2,325
NA
$1,015
$1,129
$2,595
$3,745
$4,521 •
$8,017
$21,518
$2,086
$2,875
$3,416
$5,965
$15,487
$2,846
$3,877
$4,944
$11,711
$2,845
$3,876
$4,943
$11,711
Cat. 1H
$1,420
$1,476
$1,545
$1,527
$1,694
$1,492
$1,587
$1,694
$1,619
$2,031
$1,602
$1,792
$1,602
$1,792
$5,540
$7,288
$10,476
$15,035
$28,719
$3,359
$4,224
$5,758
$7,947
$15,589
NA
$1,786
$4,503
$4,189
$6,238
$7,605
$16,507
$45,824
$3,607
$5,246
$6,345
$13,897
$38,162
$5,646
$8,068
$10,582
$26,327
$5,496
$7,835
$10,262
$25,468
Cat2H
$1,531
$1,598
$1,707
$2,190
$1,995
$2,113
$3,646
$4,553
$2,006
$3,200
$1,714
$2,138
$1,714
$2,138
$5,192
$6,929
$9,878
$14,328
$31,090
$3,100
$3,918
$5,238
$7,123
$15,123
NA
$1,827
$18,965
$3,973
$5,918
$8,025
$11,040
$28,962
$3,397
$4,927
$6,594
$8,932
$22,839
$5,548
$7,881
$10,324
$25,417
$5,523
$7,892
$10,341
$25,773
CatSH
$1,096
$1,096
$1,096
$1,221
$1,223
$1,096
$1,096
$1,096
$1,223
$1,223
$1,389
$1,642
$1,389
$1,642
$4,697
$6,383
$9,204
$13,342
$31,145
$2,615
$3,283
$4,436
$7,108
$16,033
NA
$1,173
$1,300
$3,235
$4,759
$5,784
$10,347
$28,132
$2,720
$3,882
$4,670
$8,278
$22,059
$4,548
$6,479
$8,483
' $21,068
$4,548
$6,479
$8,483
$21,068
-------
Table B-l(b)
Total Estimated Ar Dualized Compliance Costs, Option 2
Sector Model Head Cut 1L
Beef
MW Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
CE Region
Medium 1
Medium 2
Mcdium3
Large 1
Urge 2
PA Region
Medium I
Medium 2
Mediums
Largel
Large 2
SO Region
Medium 1
Medium 2
Medium3
Largel
Large 2 ,
MA Region
Medium 1
Medium 2
Mediums
Largel
LargeZ
Veal
MW Region
Medium 1
Medium 2
Medium 3
Largel
CE Region
Medium 1
Medium 2
Medium 3
Largel
FA Region
Medium 1
Medium 2
Mediums
Largel
SO Region
Medium 1
Medium 2
Mediums
Largel
MA Region
Mediuml
Medium 2
Mediums
Largel
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
400
540
1,080
1,080
400
540
1,080
NA
400
540
1/180
NA
400
540
1,080
NA
400
540
1,080
NA
57,020
S8.692
511,019
S12.630
568,683
56,647
59,979
510,725
514^80
592.196
59,706
513,459
517,015
520,910
5132,527
55,645
56,604
58,582
58,926
S57.942
57,711
510,690
513,300
515,415
575,667
51,813
51,813
51,813
51,813
51,813
51,813
51,813
NA
51,813
51,813
. 51,813
NA
51,813
51,813
51,813
NA
51,813
51,813
51,813
NA
Cat2L
57,369
511,621
517,502
515,819
5106,164
57,023
510,689
515,550
516,888
5138^03
510,130
517,123
524,307
540,951
5237,752
58,107
•57,843
510,567
532,852
5203,623
59,520
513,252
519,256
522,740
5145,294
51,535
51,535
51,535
51,535
51,535
51,535
51,535
NA
51,535
51,535
51,535
NA
51,535
51,535
51,535
NA
51,535
51,535
51,535
NA
CatSL CatlM Cat2M Cat.3M
53,723
54,594
, 55,649
57,830
594,689
53,703
54,532
55,947
59,983
5120,467
513,585
519,262
525,897
554,147
5548,859
512,443
515,886
523,093
547,539
5485351
525,069
536,431
551,645
590,161
5735328
51,400
51,400
51,400
51,400
51,400
51,400
51,400
NA
51,400
51,400
51,400
NA
51,400
51,400
51,400
NA
51,400
51,400
51,400
NA
58,861
510,541
513,400
515,912
580,830
58,683
514,090
512,873
517,255
5103,292
511,429
515,948
519,783
524,802
5150,331
58,294
59,492
512,642
514,763
588,935
59,860
514,016
516,621
520,011
5101,528
51,813
51,813
51,813
51,813
51,813
51,813
51,813
NA
51,813
51,813
51,813
NA
51,813
51,813
$1,813
NA
51,813
51,813
51,813
NA
59,196
513,472
520,366
519,407
5122,510
59,041
512,735
517,712
520,763
5151,823
511,837
520,026
527,625
545,477
5269,815
510,410
511,211
514,806
538,219
5235,605
511,969
516,144
$22,576
527,150
5172,361
51,535
51,535
51,535
51,535
51,535
51,535
, $1,535
NA
51,535
51,535
51,535
NA
51,535
51,535
51,535
NA
51,535
51,535
51,535
NA
54,010
54,935
56,023
58,451
598,383
53,933
$4,793
56,224 .
510,406
$122,540
513,883
519,603
526,280
$54,722
5551,905
512,749
516,236
$23,492
548,180
$490,191
$25,364
$36,752
$51,996
590,669
5738,462
$1,400.
$1,400
51,400
$1,400
$1,400
$1,400
51,400
NA
51,400
51,400
51,400
NA
$1,400
$1,400
51,400
NA
51,400
51,400
$1,400
NA
Cat. 1H
$10,469
512,180
515,464
$18,877
$90,920
510,316
$17,428
514,605
$19,644
$113,140
$13,032
$18,289
$22,375
528,400
$166,401
510,111
511,471
515,433
518,758
5109,609
$11,563
$16,663
$19,275
$23,721
$121,613
51,813
$1,813
51,813
51,813
$1,813
$1,813
$1,813
NA
51,813
$1,813
51,813
NA
51,813
$1,813
51,813
NA
$1,813
51,813
$1,813
NA
Cat2H
$10,793
515,113
522,870
522,678
5136,798
510,655
514,403
$19,456
523,980
$164,098
$13,425
$22,779
$30,766
$49,710
5300,145
511,987
513,527
517,721
541,901
5257,120
513,920
$18,451
$25,222
$30,762
5193,714
51,535
$1,535
51,535
$1,535
$1,535
51,535
51,535
NA
51,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
$1,535
$1,535
$1,535
NA
CatSH
$4,201
55,140
$6,252
58,755
5100,020
54,131
55,003
56,454
$10,694
5123,368
514,059
$19,793
526,486
$55,003
5553,217
512,939
516,454
523,742
$48,575
5492,875 ,
$25,649
$37,090
$52,388
591,278
5741,503
$1,400
$1,400
51,400
51,400
$1,400
51,400
51,400
NA
51,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
$1,400
$1,400
$1,400
NA
B-6
-------
Table B-l(b)
Total Estimated Annualized Compliance Costs, Option 2
Sector
Heifers
Model
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
PA Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Head
400
625
875
1,500
'400
625
'875
1,500
400
625
875
1,500
400
625
875
1,500
400
625
.875
1,500
CatlL
$6,849
$6,337
$7,261
S5.593
$6,158
$5,299
$6,232
$5,906
$8,376
$8,626
$10,587
$7,733
$5,970
S5.804
'$7,076
$5,165
$7,523'
$6,845
$8,846
$7,221
CatZL
$7,116
$8,044
$10,086
$12,798
$6,477
$6,391
$8,106
$11,928
$11,294
$12,242
$14,228
S16.883
$10,043
$9,777
$9,418
$10,607
$10,273
$9,951
$12,080
$14,592
CatSL
$3,857
$4,753
$5,899
86,257
$3,789
$4,683
$6,225
$7,909"
$13,963
$20,306
$27,548
$41,643
$12,830
$16,707
$24,546
$36,634
$25,570
$38,506
$55,092
.• $74,445
CatlM
$10,173
$8,575
$9,771
$7,947
$9,897
$7,297
$8,305
$8,464
$11,439
$11,116
$13,552
$10,495
$10,229
$9,084
$11,216
$10,303
$11,855
$9,466
$12,452
$11,431
Cat2M
510,437
$10,742
$13,245
$16,338
$10,212
$8,390
$10,185
515,403
$14,353
$15,172
. 517,567
$20,955
$14,297
$13,201
$13,401
$15,993
$15,622
$13,287
$15,873
$19,555
Cat3M
$4,145
$5,101
$6,284
$6,800
54,020
$4,949
$6,508
$8,291
$14,263
$20,653
527,942
$42,151
•$13,137
$17,065
524,957
537,186.
$25,867
$38,832
$55,450
$74,899
CatlH
$13,130
$10,577
$11,942
$10,032
$12,861
$8,916
$9,958
$10,572
$14,380 •
$13,453 .
$16,332
$13,006
$13,172
$11,342
$14,069
$13,838
$15,294
$11,587
$15,372
$14,871
Cat2H
$13,391
$13,181
$16,009
519,610
513,172
$10,010
$11,845
$18,289
$17,291
$17,949
$20,720
$24,776
$17,237
$15,560
$16,144
$19,699
$19,867
$15,971
$18,934
$23,553
CafcSH
$4,338
$5,309
, 56,518
57,074
$4,218
$5,161
$6,742
$8,558
$14,440
$20,846
$28,151
$42,408
$13,328
$17,289
$25,215
$37,529
$26,153
$39,179
$55,854
$75,431
Dairy- Flush
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
$4,652
$7,017
59,372
$15,821
$4,627
$6,967
$8,971
$14,550
$3,888
$5,633
$7,185
$9,848
$2,202
$2,835
$3,701
$4,583
$3,804
$5,955
$8,336
$14,071
$7,269
551,023
$15,689
$180,078
$7,424
$16,283
$10,607
$25,080
$5,836
$24,501
$8,159
$50,375
$2,616
$57,356
$24,271
$135,167
$6,294
$35,356
$11,129
$133,548
$28,483
$47,017
$65,543
$103,001
$10,238
$16,378
$21,737
$40,084
$15,089
$24,093
$32,155
$53,300
$20,425
$32,779
554,658
$89,191
$49,255
$75,112
$103,754
$195,095
$6,690
$10,116
$13,494
$24,993
• $6,699
$10,118
' $13,161
$23,853
$5,945
$8,763
$11,347
$19,090
$4,239
$5,929
57,817
513,743
$5,793
59,007
$12,413
$23,200
$9,313
$54,087
$19,784
$189,121
$9,508
$19,383
$14,766
$34,208
$7,902
$27,581
$12,288
559,457
$4,653
$60,419
$28,356
5144,201
$8,289
$38,374
$15,180
$142,545
$30,475
$50,048
$69,573
$111,994
$12>10
$19,422
$25,783
$49,102
$17,082
$27,123
$36,186
$62,292
$22,427
$35,822
$58,703
$98,209
$51,205
$78,100
$107,742
$204,044
$6,879
$10,335
$13,741
$27,041
56,912
$10,377
$13,459
$26,005
$6,154
$9,014
$11,635
521,209
54,419
56,132
58,042
$15,755
$5,924
$9,165
$12,600
$25,178
$9,508
$54,271
$20,005
$191,041
$9,733
$19,591
$15,035
$36,187
$8,119
$27,782
$12,542
$61,412
' $4,831
$60,588
$28,551
$146,086
$8,428
$38,497
$15,341
$144,392
$30,619
$50,198
$69,728
$113,861
$12,384
$19,572
$25,938
$50,968
$17,225
$27,272
$36,341
$64,159
$22,571
$35,971
$58,858
$100,076
$51,295
578,195
$107,840
$205,843
Dairy- Hose
PA Region
Medium 1
Medium 2
Medium 3
Large 1
250
425
600
1,430
$6,146
$9,688
$12,119
$16,238'
$9,077
$8,418
$13,740
$10,185
$7,326
$11,350
$14,264
$22,383
$7,136
$10,737
$13,224
$17,791
$10,072
$9,431
$14,820
$11,832
$7,691
$11,751
$14,698
$22,920
$7,903
$11,534
$14,049
$19,063
$10,845
510,192
$15,618
$13,198
$7,835
$11,901
$14,853
$23,177
B-7
-------
Table B-l(b)
Total Estimated Annuallzed Compliance Costs, Option 2
Sector Model
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
* Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Hog] Liquid
MW Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Large2
MA Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MW Region (FF)
Medium I
Medium 2
Medium 3
Large 1
Large 2
MA Region (FF)
Medium I
Medium 2
Medium 3
Large 1
Large 2
Hogs Pit
MW Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Luge 2
MA Region (GF)
Medium I
Medium 2
Medium 3
Large 1
Large 2
Head
250
425
600
1,430
250
425
£00
1,430
250
425
600
1,430
250
425
600
1,430
863
1,311
1,884
2,500
5.094
883
1,345
1,887
2,500
6,390
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6390
CatlL
55,463
58,033
S10.564
515,067
54,885
56,976
58,798
510,167
54,419
56,145
57,040
S6.199
54,997
57,560
$10,404
515,300
$2,841
53,550
54,599
S3.781
56,771
52,737
53,255
54,128
52,611
55,277
52,841
53,550
54,599
53,781
56,771
52,737
53,255
54,128
52,611
55,277
52,777
53,484
54,531
53,782
56,774
52,681
S3.205
54,083
. 52,614
55,285
Cat2L
58383
57,138
512,592
510,689
57,047
56,459
510,509
57,921
55,017
56,033
57,444
517,097
57,841
56,836
512,448
510,353
53,942
55,055
56,467
55,594
514,614
53,181
53,162
53,861
54,033
59,223
53,942
55,055
56,467
55,594
514,614
53,181
53,162
53,861
54,033
59,223
53,792
54,919
56,409
57,448
522,233
53301
57,958
510,656
524,292
570,928
Cat3L
53,020
54,002
55,196
54,991
53,499
54,607
55,645 ,
54,771
56,084
59,266
512,941
520,417
512,464
519,288
526,808
552,214
51,184
51,300
51,424
51,736
54,022
51,181
51,287
51,406
51,729
53,702
51,184
51,300
51,424
51,736
54,022
51,181
51,287
51,406
51,729
53,702
53,050
54,246
55,545
510,724
537,555
56,528
59,445
512,769
526,971
588,925
Cat. 1M
57,137
59,785
512,388
517,547
55,895
58,056
59,783
511,592
55,235
57,016
57,966
57,516
55,941
58,662
511,661
517,057
53,022
53,754
54,836
54,298
57,498
53,108
53,688
54,656
52,940
55,700 '
53,022
$3,754
54,836
54,298
57,498
53,108
53,688
54,656
$2,940
55,700
52,968
53,699
$4,781
54,260
$7,459
$3,071
53,666
54,648
52,895
55,642
Cat2M
510,070
58,841
514,387
513,423
58,065
57,489
511,622
59,259
55,832
56,871 -
58,340
518,081
58,792
57,980
513,824
$12,074
54,059
$5,174
$6,599
55,958
$15,306
53,449
$3,379
$4,103
$4,144
59,284
54,059
$5,174
56,599
55,958
$15,306
$3,449
$3,379
54,103
54,144
59,284
53,998
$5,153
56,681
$7,936
523,142
53,661
58,294
511,046
$24,553
$71,235
Cat3M
53,399
54,419
55,650
55,554
53,865
$5,008
56,080
55,309
56,460
59,681
513,393
520,980
512,790
$19,651
$27,205
$52,708
$1,266
$1,382
$1,506
$2,025
$4,369
51,263
$1,369
$1,488
$2,018
$4,042
$1,266
51,382
51,506
52,025
54369
51,263
51,369
$1,488
52,018
54,042
53,139
$4,335
$5,633
510,944
$37,775
$6,617
59,534
512,858
527,190
589,144
CatlH
58,394
511,087
$13,732
$19,408
56,681
58,885
510,490
512,737
55,819
57,623
$8,596
$8,529
$6,577
59,411
$12,520
518,333
53,115
53,848
54,932
54,727
$8,118
53,205
$3,787
$4,758
53,569
$6,865
53,115
53,848
$4,932
$4,727
58,118
53,205
53,787
54,758
53,569
$6,865
53,061
53,794
$4,877
$4,648
$8,035
53,168
$3,765
54,751
53,527
56,888
Cat2H
511,339
$10,093
515,701
$15,457
58,859
58,267
$12,453
510,318
56,415
$7,445
$8,939
518,761
$9,435
58,762
$14,784
513,300
$4,153
$5,269
$6,696
$6,403
516,168
53,546
$3,475
$4,200
$4,670
$10,243
$4,153
$5,269
$6,696
56,403
516,168
53,546
$3,475
$4,200
54,670
510,243
54,092
55,248
56,778
58,332
523,922
53,897
$9,016
$12,012
525,175
572,557
CatSH
53,544
54,573
$5,809
$5,811
$4,009
$5,159
$6,236
$5,566
56,604
59,830
$13,548
$21,237
512,883
$19,749
527,306
$52,896
51,355
$1,471
51,595
$2,200
$4,601
$1,352
$1,458
$1,577
$2,192
54,267
$1,355
$1,471
$1,595
$2,200
54,601
51,352
51,458
$1,577
52,192
54,267
53,228
54,423
$5,722
$11,049
$37,880
$6,706
$9,623
$12,946
$27,295
$89,249
B-8
-------
Table B-l(b)
Total Estimated Annuitized Compliance Costs, Option 2
Sector Model
MW Region (FF)
Medium I
Medium 2
Mediums
Large 1
Large 2
MA Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Hogs Evaporate
CE Region (GF)
Large 1
Large 2
CE Region (FF)
Large 1
Large 2
Broilers
SO Region
Medium 1
Medium 2
Medium 3
Large 1
' Large2
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Layers
Wet SO Region
Medium 2
Medium 3
Large 1
Dry SO Region
Medium 1
Medium 2
Medium 3
Large I
Large 2
Dry MW Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Turkeys
MA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
Head
'863
1,311
1,884
2,500
5,094
883
1,345
1,887
' 2,500
6,390
2,500
6,038
2,500
6,038
38,802
53,942
82,907
125,000
219,247
39,642
55,618
85,355
125,000
219,247
NA
19,500
146,426
36,068
61,734
78,546
291;153
856,368
36,068
61,734
78,546
291;153
856,368
22,246
34J640
47,534 .
127,396
. 22^46
34,640
47,534
127,396
CatlL
$2,777
S3.484
$4,531
$3,782
$6,774
52,681
$3,205
$4,083
$2,614
$5,285
$2,604
$5,018
$2,604
55,018
$3,906
$4,546
$6,610
$8,501
$14,447
$3,013
$3,535
$4,813
$5,166
$8,733
NA
. $1,268
$4,413
$2,820
$4,668
$5,751
$17,211
$48,980
$1,903
$2,949
$3,563
$10,121
.$28,127
$7,169
$10,536
$14,033
$9,311
$7,496
$11,101
' $14,846
$8,515
Cat2L
$3,671
$4,736
$6,154
$7,085
$21,076
$3,186
$7,794
$10,428
$23,854
S69.614
$2,941
$7,013
$2,941
$7,013
$1,521
$1,671
$1,966 '
$2,267
$3,322
$2,155
$2,435
$3,016
$3,577
$5,596
NA
$2,057
$2,393
$2,174
$3,253
$7,451
54,035
$9,537
$1,697
$2,401
$5,309
$2,888
$6,370
$4,094
$4,375
$6,221
$10,557
$3,701
$3,992
$5,648
$9,798
Cat3L
$3,050
$4,246
$5,545
$10,724
$37,555
$6,528
$9,445
$12,769
$26,971
$88,925
$899
$899
5899
$899
$883
$946
$1,009
$1,226
$1,690
$1,021
$1,088
$1,160
$1,432
$2,107
NA
S801
$902
$1,365
$1,786
$2,084
$3,618
$8,999
$1,112
$1,353
$1,533
$2,597
$5,996
$1,463
$1,770
$2,085
$4,174
$1,459
$1,767
$2,081
$4,172
Cat 1M
$2,968
$3,699
$4,781
$4,260
$7,459
$3,071
$3,666
$4,648
$2,895
$5,642
$3,079
$5,708
$3,079
$5,708
$6,536
$8,068
$11,861
$14,874
$26,411
$3,430
$4,019
$5,430
$5,713
$9,641
NA
$1,566
$4,949
$4,175
$6,812
$8,412
$22,302
$63,438
$2,962
$4,593
$5,591
$13,923
$38,818
$8,563
$12,657
$16,912
$16,957
$8,959
$13,290
$17,790
$16,102
Cat2M
$3,876
$4,969
$6,426
$7,573
$21,986
$3,546
$8,131
$10,818
$24,114
$69,921
$3,452
$7,870
$3,452
$7,870
$3,890
$4,968
$6,849
$8,100
$16,304
$2,477
$2,784
$3,415
$3,922
$6,080
NA
$2,367
$16,811
$3,626
$5,547
$10,174
$8,829
$22,551
$2,822
$4,146
$7,386
$6,514
$16,185
$6,432
$8,022
$11,185
.$24,155
$5,515
$6,764
$9,389
$19,776
CatSM
$3,139
$4,335 .
$5,633
$10,944
$37,775
$6,617
$9,534
$12,858
$27,190
$89,144
$1,200
$1,328
$1,200
$1,328
$3,066
$4,039
$5,650
$6,671
$14,785
$1,119
$1,195
$1,275
$1,577
$2,325
NA
$2,270
$6,366
$2,685
$3,900
$4,719
$8,751
$23,677
$2,110
$2,917
$3,470
$6,167
$16,080
$3,660
$5,144
$6,683
$16,372
$2,959
$4,054
$5,187
$12,363
CatlH
$3,061
$3,794
. $4,877
$4,648
$8,035
$3,168
$3,765
$4,751
$3,527
$6,888
• $3,470
$6,296
$3,470
$6,296
$8,161
$10,311
$15,259
$21,222
$38,630
$4,935
$6,103
$8,577
$10,289
$19,167
NA
$2,379
$8,961
$6,049
$9,925
$12,296
$33,895
$96,968
$4,573
57,199
$8,831
$23,110
$65,259
$10,270
$15,270
$20,464
$26,327
$10,692
$15,927
$21,365
$25,468
Cat2H
$3,971
$5,064
$6,523
$7,969
$22,765
$3,787
$8,875
$11,816
$24,736
$71,244
$3,875
$8,612
$3,875
$8,612
$5,525
$7,320
$10,413
$14,923
$32,006
$3,985
$4,948
$6,686
$8,769
$17,864
NA
$3,358
$19,516
$4,919
$7,613
$14,202
511,699
529,813
$4,034
. $6,060
$10,840
$9,292
523,303
$9,253
$12,580
$17,336
$41,174
$7,695
$10,142
$13,982
532,189
Cat. 3H
$3,228
$4,423
$5,722
511,049
$37,880
$6,706
$9,623
512,946
$27,295
$89,249
$1,389
$1,642
$1,389
$1,642
$4,697
$6,383
$9,204
$13,342
$31,100
52,615
$3,283
$4,436
57,021
516,102
NA
$2,481
56,934
$3,364
$4,980
$6,065
$11,387
$31,191
$2,755
$3,943
$4,747
$8,563
$22,899
$6,396
$9,359
$12,435
$31,662
$4,806
$6,882
$9,037
$22,551
B-9
-------
Table B-2(a)
Per-Animal Pre-tax Annuallzed Compliance Costs, Option 1
Sector Model
Beef
MW Region
Medium 1
Medium 2
Medium3
Large 1
Large 2
CE Region
Medium 1
Medium 2
Mediums
Large 1
Large 2
PA Region
Medium 1
Medium 2
Mediums
Large 1
Large 2
SO Region
Medium I
Medium 2
Mediums
Large 1
Large 2
MA Region
Medium I
Medium 2
Mediums
Large 1
Large 2
Veal
MW Region
Medium 1
Medium 2
Mediums
Large 1
CE Region
Medium 1
Medium 2
Mediums
Large!
PA Region
Medium 1
Medium 2
Mediums
Large 1
SO Region
Medium 1
Medium 2
Mediums
Large 1
MA Region
Medium 1
Medium 2
Mediums
Large 1
Head Cat 1L Cat2L CatSL Cat 1M Cat 2M CatSM Cat 1H Cat2H CatSH
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
400
540
1,080
1,080
400
540
1,080
NA
400
540'
1,080
NA
400
540
1,080
NA
400
540
1,080
NA
$11.62
$839
$6.42
S2.09
S0.77
$10.76
$7.73
$5.40
S2.19
$0.90
$13.47
$9.92
$7.86
$2.89
$0.82
$11.93
$9.58
$8.27
$2.94
SI. 17
$11.16
$8.91
$7.82
$2.83
$1.07
$4.53
$336
$1.68
$1.68
$4.53
$336
$1.68
NA
$4.53
S3.36
$1.68
NA
$4.53
$3.36
$1.68
NA
$4.53
$336
$1.68
NA
$11.85
$8.54
$6.53
$2.78
$0.57
$11.08
$7.95
S6.06
$1.85
$0.63
$18.76
$10.46
$8.24
$44.10
$1.55
$44.20
$9.14
$838
$48.74
$9.95
$26.16
$8.36
$6.64
$14.73
S2.09
$3.84
$2.84
$1.42
$1.42
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
S6.45
$4.72
$3.77
S0.74
$0.14
$6.03
$4.31
$3.36
$0.77
$0.08
$7.99
$6.17
$5.08
$0.72
$0.11
$8.26
$6.39
$5.27
$0.98
$0.25
$7.41
$5.65
$4.61
$0.82
$0.17
$3.50
$2.59
SI.30
$1.30
$3.50
$2.59
$130
NA
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$1.30
NA
$16.52
$11.67
$8.91
$3.21
$1.19
$16.16
$11.35
$7.49
$3.36
$1.27
$18.04
$13.07
$10.19
$4.64
$1.29
$18.16
$14.90
$13.24
$6.01
$2.31
$15.82
$12.87
$11.65
$5.14
$1.98
$4.53
$3.36
. $1.68
$1.68
$4.53
$3.36
$1.68
NA
$4.53
' $3.36
$1.68
NA
$4.53
$3.36
$1.68
NA
$4.53
$336
$1.68
NA
$16.73
$11.81
$9.02
$3.87
$0.97
$16.45
$11.54
$8.74
$2.98
$0.96
$23.31
$13.59
$10.56
$45.17
$2.00
$50.39'
$13.38
$13.33
$50.17
$10.82
$30.79
$11.52
$8.97
$15.78
$2.55
$3.84
$2.84
$1.42
$1.42
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$7.23
$5.33
$4.26
$1.08
$0.28
$6.65
$4.79
' $3.72
$1.00
$0.16
$8.79
$6.78
$5.58
$1.03
$0.23
$9.08
$7.03
$5.80
$1.32
$0.44
$8.21
$6.24
$5.07
$1.10
$0.29
$3.50
$2.59
$130
$1.30
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$130
NA
$3.50
$2.59
$130
NA
$3.50
$2.59
$1.30
NA
$20.81
$14.57
$11.04
$4.15
$1.52
$20.48
$14.28
$9.17
$4.31
$1.58
$22.27
$15.94
$12.28
$6.22
$1.69
$22.43
$18.56
$16.66
$8.11
$3.07
$19.58
$16.10
$14.78
$7.05
$2.70
$4.53
$3.36
$1.68
$1.68
$4.53
$336
$1.68
NA
$4.53
$3.36
$1.68
NA
$4.53
$336
$1.68
NA
$4.53
$3.36
$1.68
NA
$20.99
$14.69
$11.14
$4.79
$1.28
$20.73
$14.44
$10.87
$3.90
$1.24
$27.53
$16.45
$12.65
$46.08
$2.39
$54.63
$16.29
$16.74
$51.14
$11.40
$34.53
$14.13
$10.92
$16.71
$2.94
$3.84
$2.84
$1.42
$1.42
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$7.75
$5.70
$4.56
$1.24
$0.35
$7.18
$5.17 •
$4.02
$1.16
$0.19
$9.27
$7.13
$5.85
$1.18
$0.28
$9.60
$7.42
$6.12
$1.54
$0.54
$8.98
$6.85
$5.58
$1.43
$0.41
$3.50
$2.59
$130
$1.30
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$130
NA
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$1.30
NA
B-10
-------
Table B-2(a)
Per-Animal Pre-tax Annualizcd Compliance Costs, Option 1
Sector Model
Heifers
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
PA Region
Medium 1
Medium 2
Medium 3
Large!
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Dairy- Flush
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large]
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Dairy- Hose
PA Region
Medium 1
Medium 2
Medium 3
Large 1
Head
400
625
875
1,500
400
625
875
1,500
400
625
875
1,500
400
625
875
1,500
400
625
875
1,500
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
425
600
• 1,430
250
425
600
1,430
250
425
600
1,430
CatIL
$15.11
$7.33
$5.55
$2.29
$13.45
$6.58
$4.93
$2.!9
$17.47
$12.07
$6.86
$2.22
$14.18
$7.81
$7.22
$2.96
$13.72
$7.28
$6.93
$3.02
$8.53
$6.31
$5.36
$1.41
$9.15
$6.89
$5.93
$1.95
$9.13
$6.90
$5.95
$2.00
$8.80
$6.59
$5.63
$1.69
$7.13
$5.55
$4.87
$1.28
$15.89
$16.99
$13.04
$1.73
CatIL
$15.36
$7.49
$5.57
$2.36
$13.75
$6.77
$4.98
$2.27
$57.67
$24.92
$10.84
$2.69
$46.47
$28.60
$14.31
$11.72
$29.99
$14.91
$8.78
$2.99
$8.61
$197.80
$38.60
$101.38
$9.01
$78.52
$5.62
$17.38
$9.04
$142.91
$5.71
$30.04
$8.72
$192.26
$92.09
$55.31
$7.04
$100.72
$14.97
$55.21
$16.33
$18.39
$14.03
$3.15
CatSL
$6.27
$4.23
$3.37
$0.88
$5.75
$3.85
$3.00
$0.92
$8.01
$5.59
$4.58
$0.86
$8.31
$5.76
$4.76
$1.13
$7.42
$5.10
$4.15
$0.97
$7.59
$5.54
$4.66
$0.82
$7.72
$5.65
$4.75
$0.88
$7.59
$5.54
$4.66
$0.82
•$7.59
$5.54
$4.66
$0.82
$6.19
$4.73
$4.09
$0.56
$13.12
$15.15
$11.59
$0.82
CatlM
$23.40
$10.22
$7.73
$3.59
$22.77
$9.75
$7.27
$3.55
$25.10
$17.33
$8.90
$3.49
$24.82
$11.56
$11.69
$6.28
$21.48
$10.08
$10.36
$5.54
$22.39
$18.82
$17.18
$12.55.
$23.13
$19.50
$17.85
$13.17
$23.05
$19.46
$17.83
$13.20
$22.76
$19.18
$17.5*
$12.89
$20.81
$17.96
$16.63
$12.39
$21.85
$20.67
$15.76
$3.01
Cat2M
$23.64
$10.39
$7.75
$3.66
$23.06
$9.94
$7.32
$3.63
$65.30
$27.69
$12.88
$3.95
$57.10
$32.35
$17.05
$14.88
$37.75
$17.71
$10.82
$5.26
$22.46
$210.27
$50.40
$112.48
$22.97
$91.06
$17.49
$28.53
$22.93
$155.40
$17.54
$41.16
$22.66
$204.78
$103.95
$66.44
$20.71
$113.08
$26.70
$66.29
$22.28
$22.04
$16.72
$4.40
CatSM
$6.99
$4.79
$3.81
$1.24
$6.33
$4.28
$3.32
$1.18
$8.75
$6.14
$5.03
$1.20
$9.08
$6.34
$5.23
$1.49
$8.16
$5.62
$4.56
$1.27
$21.35
$17.97
$16.42
$11.91
S21-.55
$18.13
$16.56
$11.99
$21.35
$17.97
$16.42
$11.91
$21.42
$18.03
$16.47
$11,94
$19.78
$17.06
$15.79
$11.62
$15.33
$16.61
$12.72
$1.41
CatlH
$30.77
$12.78
$9.59
$4.70
$30.15
$12.32
$9.13
$4.66
$32.43
$22.35
$10.73
$4.59
$32.17
$14.13
$14.76
$8.57
$27.70
$12.40
$13.19
$7.63
$23.13
$19.30
$17.55
$14.85
$23.91
$20.03
$18.26
$15.51
$23.84
$20.00
$18.25
$15.55
$23.53
$19.68
$17.93
$15.21
$21.30
$18.28
$16.89
$14.64
$26.24
$23.30
$17.65
$3.95
Cat2H
$31.01
$12.94
$9.61
$4.77
$30.44
• $12.50
$9.18
$4.74
$72.62
$30.22
$14.70
$5.05
$64.45
$34.92
$18.93
$17.06
$43.95
$20.03
$12.54
$7.14
$23.19
$210.72
$50.74
$114.74
$23.73
$91.52
$17.86
$30.80
' $23.70
$155.86
$17.91
$43.44
$23.40
$205.22
$10430
$68.70
$21.18
$113.37
$26.93
$68.49
$26.66
$24.63
$18.58
$5.31
Cat. 3H
$7.47
$5.12
$4.08
$1.43
$6.82
$4.62
$3.59
$1.35
$9.20
$6.45
$5.27
$1.37
$9.56
$6.69
$5.52
$1.72
$8.87
$6.18
$5.02
$1.62
$21.98
$18.37
$16.72
$14.15
$22.19
$18.53
$16.86
$14.24
$21.98
$1837
$16.72
$14.15
$22.06
$18.43
$16.77
$14.18
$20.19
$17.32
$15.98
$13.81
$15.98
$17.01
$13.02
$1.66
B-ll
-------
Table B-2(a)
Per-Animal Pre-tax Annualized Compliance Costs, Option 1
SKtor Moid Head Cat 1L Cat2L CatSL Cat 1M CatZM Cat3M Cat 1H CatZH Cat3H
MW Region
Medium I
Medium 2
Medium 3
Large 1
CE Region
Medium I
Medium 2
Mediums
Large 1
SO Region
Medium!
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium3
Large!
Hogs Liquid
MW Region (GF)
Medium!
Medium 2
Mediums
Large!
Large2
MA Region (GF)
Medium !
Medium 2
Mediums
Large!
Luge 2
MW Region (FF)
Medium 1
Medium 2
Mediums
Large!
Large 2
MA Region (FF)
Medium 1
Medium 2
Mediums
Large!
Large 2
Hogs Pit
MW Region (GF)
Medium!
Medium 2
Mediums
Large!
Large 2
MA Region (GF)
Medium 1
Medium 2
McdiumS
Large!
Large 2
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
363
1,311
1,884
2^00
5,094
883
1,345
1,887
2,500
6,390
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6390
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
$13.20
S10.58
S10.33
$239
$13.90
$10.37
$9.38
$232
$20.65
$19.65
$20.46
$3.64
$13.15
$9.67
$9.99
$2.48
$1.40
$0.95
$0.69
$036
$0.15
$1.32
$0.89
$0.67
$034
$0.12
$1.40
$0.95
$0.69
$0.36
$0.15
$132
$0.89
$0.67
$034
S0.12
$135
$0.92
$0.68
$036
$0.15
$1.28
$0.88
$0.67
$0.34 .
$0.12
$13.23
$9.76
$10.40
$1.94
$14.09
$10.98
$9.32
$2.16
$20.75
$19.95
$15.10
$5.47
$13.19
$9.80
$10.07
$2.04
$1.93
$139
$1.12
$0.56
$0.27
$1.67
$1.21
$0.96
$0.47
$0.26
$1.93
$139
$1.12
$0.56
$0.27
$1.67
$1.21
$0.96
$0.47
$0.26
$1.34
$0.91
$0.70
$0.44
$0.08
$1.10
$0.74
$0.56
$0.20
$0.07
$9.43
$7.01
$8.17
$0.88
$10.53
$7.94
$6.85
$0.82
$12.68
$14.63
$11.10
$0.82
$8.66
$6.76
$7.72
$0.56
$1.03
$0.67
$0.49
$0.20
$0.05
$1.03
$0.69
$0.50
$0.20
$0.06
$1.03
$0.67
$0.49
$0.20
$0.05
$1.03
$0.69
$0.50
$0.20
$0.06
$0.94
$0.60
$0.43
$0.20
$0.05
$0.94
$0.62
$0.45
$0.20
$0.06
$23.39
$19.91
$14.85
$4.49
$19.92
$14.10
$13.13
$3.66
$25.62
$22.76
$24.91
$5.09
$18.95
$13.26
$12.65
$4.17
$1.56
$1.05
$0.77
$0.51
$023
$1.58
$1.07
$0.81
$0.45
$0.16
$1.56
$1.05
$0.77
$0.51
$0.23
$1.58
$1.07
$0.81
$0.45
$0.16
$1.53
$1.04
$0.77
$0.50
$0.23
$1.57
$1.09
$0.84
$0.44
$0.16
$23.40
$15.90
$14.89
$3.98.
$20.09
$14.64
$12.04
' $3.43
$25.69
$23.00
$17.39
$6.56
$18.97
$13.35
$12.70
$3.21
$2.01
$1.43
$1.14
$0.63
$0.30
$1.82
$1.30
$1.03
$0.49
$026
$2.01
$1.43
$1.14
$0.63
$0.30
$1.82
$1.30
$1.03
$0.49
$0.26
$1.51
$1.03
$0.79
$0.55
$0.12
$1.35
$0.91
$0.69
$0.25
$0.09
$11.73
$8.53
$9.36
$1.50
$12.74
$9.39
$7.98
$1.41
$14.97
$16.14
$12.27
SI. 45
$10.72
$8.13
$8.80
$1.13
$1.11
$0.72
$0.53
$0.26 .
$0.07
$1.11
$0.74
$0.54
$0.27
$0.08
$1.11
$0.72
$0.53
$0.26
$0.07
$1.11
$0.74
$0.54
$0.27
$0.08
$1.03
$0.66
$0.48
$0.25
$0.07
$1.03
$0.68
$0.49
$0.25
$0.07
$30.77
$26.97
$18.02
$5.95
$24.36
$16.79
$16.05
$4.66
$28.94
$24.77
$28.48
$6.16
$22.63
$15.46
$14.23
$5.31
$1.67
$1.12
$0.82
$0.63
$0.29
$1.68
$1.14
$0.86
$0.62
$0.25
$1.67
$1.12
$0.82
$0.63
$0.29 •
$1.68
$1.14
$0.86
$0.62
$0.25
$1.63
$1.11
$0.81
$0.61
$0.29
$1.68
$1.16
$0.89
$0.61
$0.26
$30.76
$20.24
$18.01
$537
$24.51
$17.25
$13.93
$4.34
$28.99
. $24.94
$18.80
$7.26
$22.63'
$15.51
$14.26
$3.91
$2.11
$1.49
$1.19
$0.73
$0.35
$1.91
$1.36
$1.07
' $0.59
$031
$2.11
$1.49
$1.19
$0.73
$0.35
$1.91
$1.36
$1.07
$0.59
$0.31
$1.61
$1.09
$0.84
$0.63
$0.16
$2.03
$2.30
' $2.06
$0.44
$0.23
$1239
$8.95
$9.67
$1.75
$1338
$9.80
$8.28
$1.66
$15.61
$16.54
$12.57
$1.69
$11.15
$8.40
$9.00
$132
$1.20
$0.78
$0.57
$0.30
$0.09
$1.20
$0.80
$0.58
$0.31
$0.10
$1.20
$0.78
$0.57
$030
$0.09
$1.20
$0.80
$0.58
$031
$0.10
$1.12
$0.72
$0.52
$0.27
$0.07
$1.12
$0.74
$0.53
$0.28
$0.08
B-12
-------
Table B-2(a)
Per-Animal Pre-tax Annualized Compliance Costs, Option 1
Sector Model
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MA. Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Hogs Evaporate
CE Region (GF)
Large 1
Large 2
CE Region (FF)
Large 1
Large 2
Broilers
SO Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Layers
Wet Layers
SO Region
Medium 2
Medium 3
Large 1
Dry Layers
SO Region '
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Dry MW Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Turkeys
MA Region
• Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
Head
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
2,500
6,038
• 2,500
6,038
' 38,802
' 53,942
82,907
125,000
219,247
39,642
55,618
85,355
125,000
219,247
NA
19,500
146,426
36,068
61,734
78,546
291,153
.856,368
36,068
61,734
78,546
291,153
856,368
22,246
34,640
47,534
127,396
22,246
34,640
47,534
127,396
CatlL
$1.35
$0.92
$0.68
$0.36
$0.15
$1.28
$0.88
$0.67
$0.34
$0.12
$0.36
$0.14
$0.36
$0.14
$0.04
$0.03
$0.03
$0.02
$0.02
$0.04
$0.03
$0.02
$0.02
$0.02
NA
$0.04
$0.01
$0.04
$0.03
$0.03
$0.01
$0.01
$0.03
$0.02
$0.02
$0.01
$0.01
$0.11
$0.10
$0.09
$0.07
$0.10
$0.09
$0.08
$0.07
Cat2L
$1.34
$0.91
$0.70
$0.44
$0.08
$1.10
$0.74
$0.56
$0.20
$0.07
$0.25
$0.08
$0.25
$0.08
$0.03
$0.02
$0.02
$0.01
$0.01
$0.03
$0.02
$0.02
$0.01
$0.01
NA
$0.04
$0.01
$0.04
$0.03
$0.03
$0.01
$0.01
. $0.03
$0.02
$0.02
$0.01
$0.01
$0.10
$0.07
$0.06
$0.04
$0.09
$0.07
$0.06
$0.04
CatSL
S0.94
$0.60
$0.43
$0.20
$0.05
$0.94
' $0.62
$0.45
$0.20
$0.06
$0.18
$0.03
$0.18
$0.03
$0.02
$0.02
$0.01
$0.01
$0.01
$0.03
$0.02
$0.01
$0.01
$0.01
NA
$0.04
$0.01
$0.04
$0.03
$0.03
$0.01
$0.01
$0.03
$0.02
$0.02
$0.01
$0.01
$0.07
$0.05
$0.04
$0.03
$0.07
$0.05
$0.04
$0.03
CatlM
$1.53
$1.04
$0.77
$0.50
$0.23
$1.57
$1.09
$0,84
$0.44
$0.16
$0.52
$0.21
$0.52
$0.21
$0.10
$0.09
$0.08
$0.07
$0.06
$0.05
$0.04
$0.03-
$0.03
$0.02
NA
$0.06
$0.01
$0.07
$0.06
$0.06
$0.03
$0.03
$0.06
$0.05
$0.05
$0.02
$0.02
$0.18
$0.16
$0.15
$0.13
' $0.17
$0.15
$0.14
$0.13
Cat2M
$1.51
$1.03
$0.79
$0.55
$0.12
$1.35
$0.92
$0.70
$0.25
$0.09
$0.37
$0.14
$0.37
$0.14
$0.09
$0.08
$0.07
$0.06
$0.05
$0.04
$0.03
$0.02
$0.02
$0.01
NA
$0.06
$0.11
$0.08
$0.06
$0.06
$0.03
$0.03
$0.06
$0.05
$0.05
$0.02
$0.02
$0.16
$0.14
$0.13
$0.11
$0.16
$0.14
$0.13
$0.11
CatSM
$1.03
$0.66
$0.48
$0.25
$0.07
$1.03
$0.68
$0.49
$0.25
$0.07
$0.24
$0.04
$0.24
$0.04
$0.08
$0.07
$0.06
$0.05
$0.05
$0.03
$0.02
$0.01
$0.01
$0.01
NA
$0.05
$0.01
$0.07
$0.06
$0.06
$0.03
$0.03
$0.06
$0.05
$0.04
$0.02
$0.02
$0.13
$0.11
$0.10
$0.09
$0.13
$0.11
$0.10
$0.09
CatlH
$1.63
$1.11
$0.81
$0.61
$0.29
$1.68
$1.16
$0.89
$0.61
$0.26
$0.64
$0.27
$0.64
$0.27
$0.14
$0.13
$0.12
$0.12
$0.11
$0.08
$0.08
$0.07
$0.06
$0.06
NA
$0.09
$0.03
$0.12
$0.10
$0.10
$0.06
$0.05
$0.10
$0.08
$0.08
$0.05
$0.04
$0.25
$0.23
$0.22
$0.21
$0.25
$0.23
$0.22
$0.20
Cat2H
$1.61
$1.09
$0.84
$0.63
$0.16
$2.05
$2.35
$2.11
$0.44
$0.23
$0.46
$0.19
$0.46
$0.19
$0.13
$0.12
$0.11
$0.11
$0.10
$0.08
$0.07
$0.06
$0.05
$0.05
NA
$0.09
$0.13
$0.11
$0.10
$0.10
$0.04
$0.03
$0.09
$0.08
$0.08
$0.03
$0.03
$0.25
$0.23
$0.22
$0.20
$0.25
$0.23
$0.22
$0.20
Cat3H
$1.12
$0.72
$0.52
$0.27
$0.07
$1.12
$0.74
$0.53
$0.28
$0.08
$0.28
$0.05
$0.28
$0.05
$0.12
$0.11
$0.10
$0.10
$0.10
$0.07
$0.06
$0.05
$0.05
$0.04
NA
$0.06
$0.01
$0.09
$0.08
$0.07
$0.04
$0.03
$0.08
$0.06
$0.06
$0.03
$0.03
$0.20
$0.19
$0.18
$0.17
$0.20
$0.19
$0.18
$0.17
B-13
-------
Table B-2(b)
Pcr-Anlmal Pre-tax AnnuaSlzcd Compliance Costs, Option 2
Sector Model
Beef
MW Region
Medium 1
Medium 2
Medium 3
Large 1
Luge 2
CE Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
PA Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
SO Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
X'e»l
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
PA Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large!
Head CatlL CatZL Cat3L Cat 1M Cat. 2M CatSM Cat. 1H Cat. 2H CatSH
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
370
552
766
1,839
25,897
400
540
1,080
1,080
400
540
1,080
NA
400
540
1,080
NA
400
540
1,080
NA
400
540
1,080
NA
S18.97
S15.75
S14.38
S6.87
$2.65
S17.97
S18.0S
S 14.00
S7.82
S3 .56
S26.23
S24.38
S22.21
S11.37
S5.12
S15.26
S11.96
SI 1.20
S4.85
S2.24
S20.84
S19.37
S17.36
S8.38
S2.92
S4.53
S3 .36
S1.68
SI. 68
S4.53
S3.36
SI. 68
NA
S4.53
S3.36
S1.68
NA
S4.53
S3 .36
S1.68
NA
S4.53
S3.36
S1.68
NA
S19.92
S21.05
S22.85
S8.60
S4.10
$18.98
S19.36
S20.30
S9.18
S5.34
S27.38
S31.02
S3 1.73
S22.27
S9.18
S21.91
S14.21
S13.80
S17.86
S7.86
S25.73
S24.01
S25.14
S12.37
S5.61
S3.84
S2.84
S1.42
S1.42
S3.84
S2.84
SI. 42
NA
S3.84
S2.84
S1.42
NA
S3.84
S2.84
S1.42
NA
S3.84
S2.84
S1.42
NA
S10.06
S8.32
S7.37
S4.26
S3.66
S10.01
S8.21
S7.76
S5.43
S4.65
S36.72
$34.90
S33.81
S29.44
S21.19
S33.63
S28.78
S30.15
S25.85
S18.74
S67.75
S66.00
S67.42
$49.03
$28.39
S3.50
$2.59
$1.30
SUO
$3.50
$2.59
SUO
NA
S3.50
S2.59
$1.30
NA
S3.50
S2.59
$1.30
NA
S3.50
S2.59
S1.30
NA
$23.95
$19.10
S17.49
$8.65
$3.12
$23.47
$25.53
$16.81
S9.38
$3.99
$30.89
$28.89
$25.83
$13.49
$5.80
$22.42
$17.20
S16.50
$8.03
$3.43
$26.65
$25.39
$21.70
$10.88
$3.92
$4.53
$3.36
$1.68
$1.68
$4.53
$336
$1.68
NA
$4.53
S3.36
SI. 68
NA
S4.53
$3.36
$1.68
NA
$4,53
$3.36
$1.68
NA
$24.86
$24.41
$26.59
$10.55
$4.73
$24.44
$23.07
$23.12
$11.29
$5.86
$31.99
$36.28
$36.06
$24.73
$10.42
$28.14
$20.31
$19.33
$20.78
$9.10
$32.35
$29.25
$29.47
$14.76
$6.66
. $3.84
$2.84
$1.42
$1.42
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
S3.84
$2.84
S1.42
NA
$3.84
$2.84
$1.42
NA
$10.84
$8.94
$7.86
$4.60
$3.80
' SI 0.63
$8.68
$8.13
$5.66
$4.73
.$37.52
S35.51
$34.31
S29.76
S21.31
$34.46
$29.41
$30.67
$26.20
$18.93
$68.55
$66.58
$67.88
$49.30
$28.52
$3.50
$2.59
$1.30
$1.30
$3.50
$2.59
SI. 30
NA
$3.50
$2.59
SI. 30
NA
$3.50
$2.59
_$1.30
NA
$3.50
$2.59
$1.30
NA
$28.30
$22.07
$20.19
$10.26
S3.S1
$27.88
$31.57
S19.07
$10.68
$4.37
$35.22
$33.13
$29.21
SI 5.44
$6.43
$27.33
$20.78
$20.15
$10.20
$4.23
S31.25
$30.19
$25.16
$12.90
$4.70
$4.53
$3.36
$1.68
$1.68
S4.53
$3.36
$1.68
NA
$4.53
$3.36
$1.68
NA
$4.53
$3.36
$1.68
NA
$4.53
S3.36
$1.68
NA
$29.17
$27.38
S29.86
$12.33
$5.28
$28.80
$26.09
$25.40
$13.04
$6.34
$36.28
$41.27
$40.16
$27.03
$11.59
$32.40
$24.51
$23.13
$22.78
$9.93
$37.62
$33.43
$32.93
$16.73
$7.48
$3.84
S2.84
$1.42
SI. 42
S3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$3.84
$2.84
$1.42
NA
$11.36
$9.31
S8.16
$4.76
$3.86
$11.16
$9.06
$8.43
$5.82
$4.76
$38.00
$35.86
S34.58
$29.91
$21.36
$34.97
$29.81
$30.99
$26.41
$19.03
$69.32
$67.19
$68.39
$49.63
$28.63
$3.50
$2.59
$1.30
$1.30
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$1.30
NA
$3.50
$2.59
$1.30
NA
$3.50
, $2.59
$1.30
NA
B-14
-------
Table B-2(b)
Per-Animal Pre-tax Annualizcd Compliance Costs, Option 2
Sector
Heifers
Model
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
FA Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large!
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Head
400
625
875
1,500
400
625
875
1,500
400
625'
875
1,500
400
625
875
1,500
400
625
875
1,500
CatIL
$17.12
S10.14
S8.30
S3.73
$15.40
$8.48
$7.12
$3.94
$20.94
S13.80
$12.10
$5.16
$14.93
$9.29
$8.09
$3.44
$18.81
$10.95
$10.11
$4.81
Cat2L
$17.79
$12.87
$11.53
$8.53
$16.19
$10.22
$9.26
$7.95
$28.24
$19.59
$16.26
$11.26
$25.11
$15.64
$10.76
$7.07
$25.68
$15.92
$13.81
S9.73
CatSL
$9.64
$7.61
$6.74
$4.17
S9.47
$7.49
$7.11
$5.27
$34.91
$32.49
$31.48
$27.76
$32.08
$26.73
$28.05
$24.42
$63.93
$61.61
$62.96
$49.63
CatlM
$25.43
$13.72
$11.17
$5.30
$24.74
$11.67
$9.49
$5.64
$28.60
$17.79
$15.49
$7.00
$25.57
$14.54
$12.82
$6.87
$29.64
$15.15
$14.23
$7.62
Cat2M
$26.09
S17.19
$15.14
$10.89
$25.53
$13.42
$11.64
$10.27
$35.88
$24.28
$20.08
$13.97
$35.74
$21.12
$15.32
$10.66
$39.06
$21.26
$18.14
$13.04
Cat3M
$10.36
$8.16
$7.18
$4.53
$10.05
$7.92
$7.44
$5.53
$35.66
$33.04
$31.93
$28.10
$32.84
$27.30
$28.52
$24.79
$64.67
$62.13
$63.37
$49.93
CatlH
$32.83
$16.92
$13.65
$6.69
$32.15
$14.27
$11.38
$7.05
$35.95
$21.52.
$18.66
$8.67
$32.93
$18.15
$16.08
$9.23
$38.23
$18.54
$17.57
$9.91
Cat2H
$33.48
$21.09
$18.30
$13.07
$32.93
$16.02
$13.54
$12.19
' $43.23
$28.72
$23.68
$16.52
$43.09
$24.90
$18.45
$13.13
$49.67
$25.55
$21.64
$15.70
CatSH
$10.84
$8.49
$7.45
$4.72
$10.54
$8.26
$7.71
$5.71
$36.10
$33.35
$32.17
$28.27
$33.32
$27.66
$28.82
$25.02
$65.38
$62.69
$63.83
$50.29
Dairy- Flush
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1 ,
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
250
425
600
1,430
250
425
600
1,430
250
425
600
1,430
250
. 425
600
1,430
250
425
600
1,430
S20.05
$17.83
$16.88
$11.06
$20.01
$17.76
$16.25
$10.20
$16.99
$14.57
$13.23
$6.89
$10.25
$7.99
$7.42
$3.20
$16.68
S15.35
$15.17
$9.85
$30.52
$121.37
$27.40
$125.93
$31.20
$39.68
$18.97
$17.56
$24.78
$58.97
$14.85
$35.23
$11.91
$136.27
$41.71
$94.52
$26.64
$84.53
$19.82
$93.40
$,115.37
$111.95
SU0.49
$81.79
$42.45
$39.90
$37.52
$28.06
$61.80
$58.01
S54.85
$37.27
$83.14
$78.44
$92.35
$70.99
$247.80
$207.63
$195.91
$145.55
$33.99
$30.42
$28.79
$22.28
$34.12
$30.49
$28.29
$21.52
$31.01
$27.24
$25.21
$18.15
$24.22
$20.59
$19.35
$14.42
$30.44
$27.84
$27.01
$21.04
$44.48 •
$133.88
$39.27
$137.05
$45.35
$52.29
$30.97
$28.76
$38.84
$71.51
$26.78
$46.38
$25.87
$148.80
$53.58
$105.65
$40.42
$96.93
$31.62
$104.49
$129.13
$124.38
$122.25
$92.88
$56.28
$52.38
$49.33
$39.17
$75.56
$70.44
$66.61
$48.36
$96.97
$90.93
$104.16
$82.11
$261.40
$219.97
$207.60
$156.61
$34.81
$30.98
$29.24
$24.65
$35.03
$31.15
$28.83
$23.96
$31.91
$27.88
$25.73
$20.57
$25.00
$21.12
$19.77
S16.77
$31.00
$28.24
$27.35
$23.35
$45.33
$134.36
$39.68
$139.33
$46.32
$52.83
$31.46
$31.08
$39.77
$72.04
$27.25
$48.68
$26.65
$149.25
$53.95
$107.91
$41.01
$97.25
$31.92
$106.71
$129.77
$124.78
$122.55
$95.12
$56.92
$52.79
$49.63
$41.42
$76.20
$70.84
$66.91
$50.60
$97.61
$91.33
$104.46
$84.35
$261.80
$220.22
$207.79
$158.80
Dairy- Hose
PA Region
Medium 1
Medium 2
Medium 3
Large 1
250
425
600
1,430
$27.41
$28.51
S24.56
$11.52
$39.13
$25.52
$27.27
$7.33
$31.46
$32.03
$27.86
$15.65
$33.45
$32.27
$27.37
S13.16
S45.20
$29.20
$30.03
$9.12
$33.67
$33:48
$28.99
$16.25
$37.93
$34.98
$29.34
$14.45
$49.69
$31.83
$31.96
$10.56
$34.31
$33.88
$29.29
$16.49
B-15
-------
Table B-2(b)
Pcr-Anlmal Pre-tax Annualized Compliance Costs, Option 2
Sector Model
MW Region
Medium t
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Utgcl
SO Region
Medium I
Medium 2
Medium 3
Large 1
MA Region
Medium I
Medium 2
Medium 3
Large 1
H»|J Liquid
MA Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MW Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MA Region (FF)
Medium t
Medium 2
Medium 3
Large 1
Large 2
MW Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Hogs Pit
MA Region (GF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MW Region (GF)
Medium 1
Medium 2
Medium3
Large 1
Large 2
Head CatlL CatZL Cat3L Cat 1M Cat2M Cat.3M Cat. 1H Cat2H Cat3H
250
425
600
1,430
250
425
' 600
1,430
250
425
600
1,430
250
425
600
1,430
863
1,311
1.884
2,500
5,094
883
1,345
1,887
2,500
6^90
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
863
1,311
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
S24.06
S20.50
S20.64
SI0.77 .
S21.76
S18.04
S16.04
S7.26
S22.09
S21.05
S16.67
$5.25
S22.72
S20.03
S20.85
SI 1.25
S3.28
S2.69
S2.43
S1.51
S1.21
S3.09
S2.39
S2.18
S0.99
S0.70
S3.28
S2.69
$2.43
S1.51
S1.21
S3.09
S2.39
S2.18
S0.99
S0.70
S3.21
S2.64
S2.40
S1.51
S1.21
S3.02
S2.36
S2.15
S0.99
S0.70
S35.74
$18.40
S24.02
S7.77
S30.41
$16.83
$18.90
S5.72
$24.49
$20.78
$17.34
$12.39
$34.09
$18.57
• S24.43
$7.70
$4.24
$3.55
$3.27
$1.86
$1.49
$3.24
$2.09
$1.84
$0.94
$0.72
$4.24
$3.55
S3.27
$1.86
$1.49
$3.24
$2.09
$1.84
$0.94
$0.72
$4.08
$3.45
$3.24
$2.48
$2.27
S3 .36
S5.26
$5.07
S5.67
S5.53
$13.43
S10.5I
$11.34
S3.51
$15.54
$12.08
$10.51
$3.34
$26.28
$26.93
S25.47
S14.28
S51.29
S46.54
S47.41
S36.52
$1.21
S0.85
S0.67
S0.39
• S0.24
$1.21
$0.87
S0.69
$0.39
$0.25
$1.21
$0.85
$0.67
S0.39
$0.24
$1.21
$0.87
$0.69
$0.39
$0.25
S3.13
$2.79
$2.62
S2.38
$2.24
S6.69
S6.40
$6.23
S6.10
SS.96
$34.38
$26.83
$25.29
S13.40
S27.89
$21.88
S18.65
S8.76
$27.08
$24.18
$19.03
S6.75
S28.59
S24.24
S24.16
S13.17
$3.49
S2.84
S2.56
$1.72
$1.34
, S3.51
S2.71
S2.46
S1.12
S0.76
S3.49
' S2.84
$2.56
S1.72
$1.34
S3.51
S2.71
. S2.46
S1.12
$0.76
$3.42
S2.80
S2.53
S1.70
SI. 34
S3.46
$2.70
S2.45
S1.10
S0.75
$46.12
$24.61
$28.63
$10.75
$36.56
$20.55
$21.71
S7.24
$29.47
$23.84
$19.65
$13.47
$40.00
S23.15
S28.13
S9.52
$4.36
$3.63
$3.34
$1.99
S1.56
$3.52
$2.23
$1.95
$0.97
$0.72
$4.36
$3.63
$3.34
S1.99
S1.56
$3.52
$2.23
$1.95
$0.97
$0.72
S4.30
S3.62
$3.38
$2.65
$2.36
$3.73
S5.48
$5.25
$5.73
S5.55
$15.73
$12.03
S12.52
$4.14
S17.76
$13.53
SI 1.64
S3.93
S28.57
$28.44
$26.65
$14.90 '
$53.35
$47.92
$48.48
S37.09
S1.30
S0.91
$0.71
$0.45
$0.26
$1.29
$0.93
S0.73
S0.46
S0.27
$1.30
$0.91
$0.71
$0.45
$0.26
SI. 29
S0.93
$0.73
$0.46
$0.27
$3.22
$2.85
$2.67
$2.43
S2.25
$6.78
$6.46
$6.27
S6.15
S5.97
S41.89
S31.37
$28.58
$15.31
$32.43
S24.67
S20.42
$9.92
$30.41
$26.21
$20.51
$7.87
S32.34
$27.01
$26.32
S14.52
$3.59
$2.91
$2.61
$1.89
$1.45
$3.62
$2.79
$2.51
$1.36
S0.91
$3.59
$2.91
$2.61
$1.89
$1.45
S3.62
$2.79
$2.51
$1.36
S0.9I
$3.53
$2.87
$2.58
$1.86
S1.44
S3.57
$2.77
$2.51
$1.34
$0.92
S53.67
$29.03
$31.87
$12.92
$41.15
$23.21
$23.70
$8.42
$32.80
$25.79
$21.08
$14.18
S43.78
$26.21
$30.62
$10.76
$4.46
$3.70
$3.39
$2.13
SI. 65
$3.61
S2.30
$2.00
$1.09
$0.80
$4.46
S3.70
$3.39
S2.13
S1.65
$3.61
$2.30
$2.00
$1.09
$0.80
$4.40
$3.69
$3.43
$2.78
$2.44
$3.97
S5.96
S5.71
$5.88
$5.66
S16.38
$12.45
$12.83
$4.38
$18.40
$13.93
$11.94
S4.18
S29.20
$28.84
$26.95
$15.15
$53.77
$48.18
$48.68
$37.28
$1.39
$0.97
$0.75
$0.49
$0.27
$1.38
$0.99
S0.77
$0.50
$0.29
S1.39
$0.97
$0.75
S0.49
S0.27
S1.38
S0.99
$0.77
$0.50
$0.29
$3.31
$2.91
$2.71
$2.45
$2.26
$6.87
$6.52
$6.31
$6.17
$5.98
B-16
-------
Table B-2(b)
Per-Animal Pre-tax Annualized Compliance Costs, Option 2
Sector Model
MA Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MW Region (FF)
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Hogs Evaporate
CE Region (GF)
Large 1
Large 2
CE Region (FF)
Large 1
Large 2
Broilers
SO Region ;
Medium 1 .
Medium 2
Medium 3
Largel .
Large 2
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
Layers
Wet Layers
SO Region
Medium 2
Medium 3
Large 1
Dry Layers
SO Region
Medium I
Medium 2
Medium 3
Large 1
Large 2
Dry MW Region
Mediurh 1
Medium 2
Medium 3
Large 1
Large 2
Turkeys
MA Region
Medium 1
Medium 2
Medium 3
Largel
MW Region
Medium 1
Medium 2
Medium 3
Large 1
Head Cat 1L CatZL Cat3L
863
Ull
1,884
2,500
5,094
883
1,345
1,887
2,500
6,390
2,500
6,038
2,500
6,038-
38,802
53,942
82,907
125,000
219,247
39,642
55,618
85,355
125,000
219,247
NA
19,500
146,426
36,068
61,734
78,546
291,153
856,368
36,068
61,734
78,546
291,153
856,368
22,246
34,640
47,534
127,396
22,246
34,640
47,534
127,396
S3.21
S2.64
$2.40
S1.51
S1.21
S3.02
$2.36 '
$2.15
S0.99
$0.70
$1.04
$0.79
$1.04
$0.79
$0.10
$0.08
$0.08
$0.07
$0.06 '
$0.08
$0.06
$0,06
$0.04
$0.03
NA
$0.07
$0.03
$0.08
$0.08
$0.07
$0.06
S0.06
$0.05
$0.05
$0.05
$0.03
$0.03
S0.32
$0.30
S0.30
$0.07
S0.34
$0.32
$0.31
$0.07
$3.95
$3.33
S3.ll
$2.36
$2.15
S3.25
$5.15
$4.96
$5.57
$5.43
$0.85
$0.68
$0.85 '
$0.68
$0.04
$0.03
$0.02
$0.02
$0.01
$0.05
$0.04
$0.03
$0.03
$0.02
NA
$0.11
$0.02
$0.06
$0.05
$0.09
$0.01.
$0.01
$0.05
$0.04
$0.07
$0.01
$0.01
$0.18
$0.13
$0.13
$0.08
$0.17
$0.12
$0.12
$0.08 .
$3.13
$2.79
$2.62
$2.38
$2.24
$6.69
$6.40
$6.23
$6.10
$5.96
$0.18
$0.03
$0.18
$0.03
$0.02
$0.02
$0.01
$0.01
$0.01
$0.03
$0.02
$0.01
$0.01
$0.01
NA
$0.04
$0.01
$0.04
$0.03
$0.03
$0.01
$0.01
$0.03
$0.02
$0.02
$0.01
$0.01
$0.07
$0.05
$0.04
$0.03
$0.07
$0.05
$0.04
$0.03
CatlM Cat2M CatSM Cat 1H Cat2H Cat3H
$3.42
.. $2.80
$2.53
$1.70
$1.34
$3.46
$2.70
$2.45
$1.10
$0.75
$1.23
$0.90
$1.23
$0.90
$0.17
$0.15
$0.14
$0.12
$0.11
$0.09
$0.07
$0.06
$0.05
$0.04
NA
$0.08
$0.03
$0.12
$0.11
$0.11
$0.08
$0.07
$0.08
$0.07
S0.07
$0.05
$0.05
$0.38
$0.37
$0.36
$0.13
$0.40
$0.38
,' $0.37
$0.13
$4.17
$3.49
$3.25
$2.52
$2.24
$3.61
$5.37
$5.15
S5.63
$5.45
$1.00
$0.76
$1.00
$0.76
$0.10
$0.09
$0.08
$0.06
$0.05
$0.06
$0.05
$0.04
$0.03
$0.02
NA
$0.12
$0.11
$0.10
$0.09
$0.13
$0.03
$0.03
$0.08
$0.07
$0.09
$0.02
$0.02
$0.29
$0.23
$0.24
$0.19
$0.25
$0.20
$0.20
$0.16
$3.22
$2.85
$2.67
$2.43
$2.25
$6.78
$6.46
$6.27
$6.15
$5.97
$0.24
$0.04
$0.24
$0.04
$0.08
$0.07
$0.06
$0.05
$0.05
$0.03
$0.02
$0.01
$0.01
$0.01
NA
$0.12
$0.04
$0.07
$0.06
$0.06
$0.03
$0.03
$0.06
$0.05
$0.04
$0.02
$0.02
$0.16
$0.15
$0.14
$0.13
$0.13
$0.12
$0.11
$0.10
. $3.53
$2.87
$2.58
$1.86
$1.44
$3.57
$2.77
$2.51
$1.34.
$0.92
$1.39
$0.99
$1.39
$0.99
$0.21
$0.19
$0.18
$0.17
$0.16
$0.12
$0.11
$0.10
$0.08
$0.07
NA
$0.12
$0.06
$0.17
$0.16
$0.16
$0.12
$0.11
$0.13
$0.12
$0.11
$0.08
$0.08
$0.46
$0.44
$0.43
$0.21
$0.48
$0.46
$0.45
$0.20
$4.27
$3.56
$3.30
$2.66
$2.32
S3.86
S5.86
$5.62
$5.77
$5.56
$1.12
$0.83
$1.12
$0.83
$0.14
$0.13
$0.12
$0.11
$0.10
$0.10
$0.09
$0.07
$0.07
$0.05
NA •
$0.17
$0.13
$0.14
$0.12
$0.18
$0.04
$0.03
$0.11
$0.10
SO. 14
$0.03
$0.03
$0.42
$0.36
$0.36
$0.32
$0.35
$0.29
$0.29
$0.25
$3.31
$2.91
$2.71
$2.45
$2.26
$6.87
S6.52
S6.31
$6.17
$5.98
$0.28.
$0.05
$0.28
$0.05
$0.12
$0.11
$0.10
$0.10
$0.10
$0.07
$0.06
$0.05
$0.05
$0.04
NA
$0.13
$0.05
$0.09
$0.08
$0.08
$0.04
$0.04
$0.08
$0.06
$0.06
$0.03
$0.03
$0.29
, $0.27
$0.26
$0.25
$0.22
$0.20
S0.19
$0.18
B-17
-------
-------
APPENDIX C
METHODOLOGY TO ASSESS MARKET EFFECTS OF CAFO REVENUE
This appendix describes EPA's methodology for estimating changes in farm revenue based on
predicted changes in market prices and quantities attributable to the final regulations. This analysis
modifies a similar analysis conducted for the 2001 Proposal, in which EPA assumed a portion of the costs
are passed up through the food marketing chain under assumptions of long-run market adjustment.
Section C.I presents the methodology and underlying concepts for estimating changes in farm revenues
using this approach. Section C.2 describes how EPA applies this information to its discounted cash flow
analysis. Section C.3 discusses how EPA uses information on alternative revenue scenarios at
representative model CAFOs.
C.I METHODOLOGY FOR ESTIMATING CHANGES IN FARM REVENUE
The impact of the ELG on farm revenues is directly derived from the market model as described
above. The market model for each type of livestock contains baseline equilibrium price (P° in Figure C-l)
and quantity, as well as equations representing estimated supply and demand responses to changes in
price. From the cost annualization model, EPA estimates compliance costs per unit of production (CC/Q
in Figure C-l). This measures the vertical shift in the supply curve. Given the vertical shift in the supply
curve, the model solves for the post-regulatory equilibrium price (P! in Figure C-l). Thus, all components
are baseline parameters, inputs, or outputs of the market model.
A key factor that determines how much compliance costs will increase market price is the
equations that represent the responsiveness of supply and demand to changes in price. Elasticities are
used to measure how responsive supply and demand quantities are to changes in price. To illustrate how
elasticities affect price change, Figure C-2 compares how post-regulatory market equilibrium will differ
according to the price elasticity of demand in response to a given shift in the supply curve. The steeper of
the two demand curves is relatively inelastic: consumers are relatively unresponsive to an increase in
price in the sense that they decrease purchases of meat by only a small amount. The flatter of the two
demand curves is relatively elastic: consumers are relatively responsive to a price increase in the sense
that the decrease in their meat purchases is much larger compared to the case of relatively inelastic
demand. Thus, holding all other things constant (e.g., price elasticity of supply, initial market equilibrium
price and quantity, and compliance costs per head), an ELG will cause a greater increase in market price
if demand is relatively inelastic than if demand is relatively elastic. This can be observed in Figure C-2 in
that the post-regulatory equilibrium price if demand is relatively inelastic (Py) is higher than the post-
regulatory equilibrium price if demand is relatively elastic (P2). In a similar manner, differences in the
price elasticity of supply also affect how the market price responds to a shift in supply.
For the purpose of its market analysis, EPA uses estimates of price elasticities of supply and
demand obtained through an extensive search of the agricultural economics literature and consultation
with leading experts in the field. The price elasticity of demand may be defined as the percentage change
in quantity demanded caused by a 1-percent change in price. If demand is inelastic, the price elasticity of
C-l
-------
demand lies between zero and minus one: a 1-percent increase in price causes a less than one percent
decrease in quantity demanded; consumers are unresponsive to the price change. If demand is elastic,
the price elasticity of demand lies between minus one and -°°: a 1-percent increase in price causes a
greater than 1-percent decrease in quantity demanded.
The price elasticity of supply may be defined as the percentage change in quantity supplied
caused by a 1-percent change in price. If supply is inelastic, the price elasticity of supply is greater than
zero but less than one: a 1-percent increase in price causes a less than one percent increase in quantity
supplied. If supply is elastic, the price elasticity of supply is greater than one: a 1-percent increase in
price causes a greater than one percent increase in quantity supplied.
The measured price elasticities used in the market model are based on econometric estimation of
data. That is, the equations that represent the responsiveness of consumers and producers to price
changes are based on observation and measurement of their responsiveness in the past.
Much of this research to estimate price elasticities of supply and demand for the livestock and
poultry sectors is conducted by the various land grant universities and is published in the leading academic
journals. Research by USDA also contributes to this body of work. For the 2001 Proposal, EPA
compiled a list of published supply and demand elasticities in each sector for use in its market model.
(See Appendix C of the Proposal EA; also, ERG, 1999a, 1999b.) Because the market model is designed
to measure long-term market adjustment, elasticities that are specified in the long run are the most
appropriate for this analysis. In particular, estimates of supply elasticities are highly dependent on time
frame. Generally, the longer the time frame, the more elastic is supply because farms have an' opportunity
to change production in the most efficient way while these expand or contract their operations. In the
short term, however, farms have less flexibility and cannot change production as efficiently. The supply
elasticities identified in the literature, however, include short-, intermediate-, and long-run estimates. The
demand elasticities identified usually do not specify a time period.
From its compiled studies, EPA selected elasticity values to reflect baseline market conditions.
These values represent a consensus of expert opinion on a reasonable estimate of supply and demand
elasticities for each sector (Vukina, 2000; Foster, 2000) and are considered to reflect long-run conditions.
Appendix C of the Proposal EA contains a complete listing of studies and values found. Section 4.2.6 of
the Proposal EA provides more detailed information on EPA's methodology for computing cost
passthrough for this analysis.
Table C-l presents the elasticity values EPA selected for use in its market model and also to
estimate regulatory price effects as a percentage of unit compliance costs for this analysis.
Table C-l also shows EPA's estimate of the relative impact compliance costs will have on price
given the specified price elasticities of supply and demand. EPA expresses the price impact as a percent
of unit compliance costs for two reasons. First, it simplifies comparing the responsiveness of price in
different markets—or different specifications of the same market (see Table C-2)—to regulatory costs.
In Table C-l, for example, it is readily apparent that the price of beef cattle is much more responsive to
increased regulatory costs than the price of turkeys. Second, because this measure of the responsiveness
of markets is essentially determined by the price elasticities of supply and demand (as well as the
elasticities of imports and exports), once this measure is estimated, the percentage will remain constant as
C-2
-------
long as the elasticities are unchanged. Therefore, the change in market price can be estimated knowing
this percentage and per unit compliance costs.1 EPA demonstrates how it uses this characteristic in its
analysis of discounted cash flow in Section C.2.
EPA employs a simple method for calculating the estimated price impact as a percentage of unit
compliance costs using supply and demand elasticities. This approach is consistent with that used by the
Agency in past regulatory analyses (see references in the Proposal EA, USEPA, 2001a). This approach
uses estimates of price elasticity of supply divided by the difference in estimated price elasticity of supply
and the price elasticity of demand for each sector, as shown below:
Percentage Price Impact =
price elasticity of supply
price elasticity of supply - price elasticity of demand
Table C-l. Selected Elasticity Estimates and Estimated Regulatory Price Impact
Animal Sector
Beef
Dairy
Hogs
Broiler1"'
Layer
Turkey
Selected
Price Elasticity of Supply ^
1.020
1.527
0.628
0.200
0.942
0.200
Selected
Price Elasticity of Demand"'
-0.621
-0.247
-0.728
-0.372
-0.110
-0.535
Price Increase as
Percent of per unit
Compliance Costs
70.7%
84.8%
69.7%
68.7%
93.7%
49.5%
[sources: Vanous (ERG, 1999a, 199b); also see summary in Appendix C in Proposal EA (USEPA, 2001a).
a/Elasticities representing a consensus of expert opinion (Vukina, 2000; Foster, 2000a).
b'Includes elasticity estimates for both broilers and chickens because studies vary between the two terms when
analyzing the markets for meat from chickens.
C.2 APPLICATION TO DISCOUNTED CASH FLOW ANALYSIS
Conceptually, applying the impact of the ELG on facility revenues to the DCF analysis is
straightforward. In essence, the DCF analysis compares the cash flow of a model CAFO with its
estimated compliance costs for each year of the project life. Although in some individual years cash flow
1 Because EPA's CAFO market model is not a constant elasticity model, the change in price as a
percentage of unit compliance costs varies as unit compliance costs change. In practice, because of the relatively
small magnitude of estimated unit compliance costs used in this analysis, the change in elasticities— and therefore
the variance in the measured change in price as a percentage of unit compliance costs—is so small that it can be
treated as constant.
C-3
-------
might exceed compliance costs and in other years compliance costs might exceed cash flow, over the
project life the stream of discounted cash flows must exceed the stream of discounted compliance costs
for the rule to be economically achievable.
In effect, EPA first calculates the post-regulatory cash flow for each year of the project life by
subtracting operating expenses and compliance costs from operating revenues, discounting the result, and
then summing the stream of post-regulatory discounted cash flows over the entire project life. For each
year of the project life, this calculation can be represented (in simplified form) as
where:
post-regulatory CFt = PtxQt - OEt - CCt
CF, = cash flow in year t '
PtxQt =- market price times units sold in year t (i.e., operating revenues)
OEt — operating expenses in year t
CC, = compliance costs hi year t
As a conservative estimate, EPA performs the analysis assuming that the rule will have no impact on
facility level revenues. That is, EPA assumes that the equilibrium market price is unchanged by the rule
(i.e., EPA essentially uses price P° in Figure C-l for the analysis).
To estimate post-regulatory cash flow assuming that market price is affected by the ELG, the
model CAFO's operating revenues should reflect the expected price after the effluent guideline is
promulgated (i.e., price P1 in Figure C-l). As a practical matter, however, applying this concept to the
analysis of the model CAFO's DCF is more complex than plugging the estimated post-regulatory market
price (P1) into the equation above. First, pre-regulatory model CAFO revenues and market model prices
are estimated from different (albeit consistent) data sources. Second, model CAFO cash flow is
estimated over a 10-year period based on USDA projections of industry conditions. Revenues in each of
these years are affected by the ELG. The market model, on the other hand, provides a "snapshot" of the
market in two periods: the initial pre-regulatory equilibrium and the long-run, post-regulatory equilibrium
after all market adjustments have occurred. The market model does not provide a time series of price
estimates over a 10-year period. For detailed discussion of how EPA developed these models, see the
Proposal EA. This report provides a summary overview of the DCF model assumptions (Section 2.4) and
the market model (Section 2.5).
EPA estimates the increase in model CAFO revenues over the 10-year period based on the
relationship between price and unit compliance costs. In Figure C-l, post-regulatory market price, P1, is
equal to the market price in the absence of the regulation, P°, plus the change in price (P1 - P°)
attributable to the effluent guideline (i.e., the vertical shift in the supply curve). This change in price is
expressed as a percentage of unit compliance costs. Because it is a function of the price elasticities of
demand and supply used in the market model, it will not change regardless of the size of the supply curve
shift (as long as the elasticities are unchanged).
C-4
-------
Therefore, for each time period EPA can estimate the change in market price (P1, - P0,)—and
thus the model CAFO's change in revenues—from initial revenues (P°, x Q0t) using the change in price
as a percent of unit compliance costs derived from the market model (APCC = (P1, - P0,)/(CC/Q)) and
estimated per unit compliance costs (CC/Q). Using these definitions and substitutions the cash flow
analysis for each year after adjusting for market-induced changes in revenues can be represented as:
post-regulatory CFt = P^xQj - OEt - CCt
= (P°t + (P't -P°t))xQt - QEt - CCt
= p(
cc
Qt
L xQ( - OEt - CCt
= P°txQt + APccxCCt - OEt - CCt
Discounting for the project year and summing over all years of the project life result conceptually in the
DCF formula EPA uses to project impacts after modifying facility revenues to account for market price
adjustments. For ease of calculation, EPA performs its DCF analysis using the equivalent calculation:
Post-regulatory
- OE - CC x (1 - APCC).
In addition, EPA first estimates the discounted stream of pre-regulatory model facility cash flow over the
entire 10-year period (i.e., the equivalent of estimating P° *Q° - OE for each period, discounting, then
summing over all periods) and the discounted stream of compliance costs per period, and then adjusts
these compliance costs by (1 - APCC) to account for revenue changes.
C.3 USE OF ALTERNATIVE REVENUE SCENARIO IN IMPACT ESTIMATION
Because of uncertainties over how market-induced price increases will affect farm income, EPA
presents its economic impact analysis under two different assumptions: (1) there will be no change in farm
revenues to offset compliance costs, and (2) farm prices will increase as projected by the market model to
partially offset compliance costs. Although EPA considers the results of both analyses in making its
determination of economic achievability, the Agency's overall conclusions do not rely on the assumption
that farm revenues will increase to offset compliance costs.
EPA uses these alternative assumptions to estimate a range of potential economic impacts. The
most conservative estimate of impacts occurs under the assumption that facilities receive no additional
revenues after promulgation of the rule to help offset increased costs of production. This analysis is too
pessimistic because the market model clearly demonstrates that price can be expected to increase, and
because the facility is assumed to make no changes to its operations to mitigate the impacts of increased
costs. Smaller impacts will occur under the alternative assumption that an increased market price
resulting from the ELG will increase facilities' revenues, thus partially offsetting the impacts of increased
C-5
-------
costs. However, this analysis might be too optimistic for a number of reasons. First, it assumes that the
full increase in price will affect revenues immediately; this is an unrealistic assumption in that market
adjustment to the final long-run price occurs over time, not instantaneously. Second, this assumption does
not account for potential decreases in facility production that may occur in response to increased
production costs. Third, the unknown effects of market power and vertical integration on the relationship
between processors and growers has the potential to modify these results. Therefore, performing the
DCF analysis under alternative assumptions, some of which are too pessimistic, and others of which are
too optimistic, provides EPA with upper and lower bounds to the impacts projected by its DCF analysis.
EPA also performs sensitivity analyses to examine how projected market level impacts vary with
alternative values for price elasticities of supply and demand. These sensitivity analyses have implications
for the DCF analysis because different specifications for the price elasticities affect the responsiveness of
market price to unit compliance costs. EPA selected the highest and lowest (acceptable) price elasticity
estimates that it found in its literature search as alternative parameter values in its market model.
Table C-2 shows the high and low elasticity estimates used in market model sensitivity analysis
and estimated regulatory price impact as a percent of unit compliance costs. As shown in Table C-2,
should the true market response be more consistent with the "high" values for price elasticities than with
the values EPA selected for its market model, the impact of compliance costs on market price will be
larger than those cited in Table C-2. The impact of the rule on facility level DCF will be further mitigated
by the increased revenues. Conversely, should the true market response be more consistent with the
"low" values for price elasticities than with the values EPA selected, the impact of compliance costs on
market price will be smaller and the rule's impact on facility level DCF will be more severe.
Table C-2. Selected Hieh and Low Elasticity Estimates and Estimated Regulatory Price Effect
Animal
Sector
Beef
Dairy
Hogs
Broiler1"
Layer
Turkey
High Value for Price Elasticities
Selected Price
Elasticity of
Supply1'
3.240
4.000
1.800
0.587
0.942
0.518
Selected Price
Elasticity of
Demand*7
-0.450
-0.050
-0.070
-0.104
-0.022
-0.372
Price Increase
as %per unit
Compliance
Costs
91%
96%
96%
96%
99%
78%
Low Value for Price Elasticities
Selected Price
Elasticity of
Supply"
0.060
0.070
0.007
0.064
0.031
0.210
Selected
Price
Elasticity of
Demand"7
-1.270
-0.650
-1.234
-1.250
-0.780
-0.680
Price Increase
as %per unit
Compliance
Costs
7%
10%
2%
17%
7%
45%
Sources: Various (ERG, 1999a, 199b); also see summary in Appendix C in Proposal EA (USEPA, 2001a).
''Estimated elasticities as identified in Tables C-l through C-12, Appendix C of the Proposal EA.
'''Includes elasticity estimates for both broilers and chickens because studies vary between the two terms when
analyzing the markets for meat from chickens.
C-6
-------
Decrease in Supply of Livestock/Poultry
Type i caused by ELG on that sector
(= Annualized Compliance Costs per Head)
S2,
D, S1 = pre-regulatory market supply and demand conditions
D, S2 = post-regulatory market supply and demand conditions
P°, Q° = pre-requlatory equilibrium price and quantity
P1, Q1 = post-requlatory equilibrium price and quantity
Figure C-l.
Impact of the Effluent Guideline on Market for Livestock/Poultry Type i
C-7
-------
Decrease in Supply of Livestock/Poultry
Type i caused by ELG on that sector g2
(= Annualized Compliance Costs per Head)
Relatively Elastic Demand
Relatively Inelastic Demand
Q2
Q1 Q°
S1 = pre-regulatory market supply
Sz = post-regulatory market supply
P°, Q> - pre-requlatory equilibrium price and quantity
P1, Q1 = post-requlatory equilibrium price and quantity if demand is relatively inelastic
PZ, Q2 = post-requlatory equilibrium price and quantity if demand is relatively elastic
Figure C-2.
Effect of Price Elasticity of Demand on Change in Market Price
Due to Impact of Effluent Guideline on Market for Livestock/Poultry
C-8
-------
APPENDIX D
SUMMARY TABLES:
ESTIMATED CAFO FINANCIAL EFFECTS
This appendix shows EPA's estimates of financial effects on operations with more than 300
AU for the two technology options evaluated for this rulemaking. The first option (Option 1) will require
land application at the CAFO to be consistent with proper agricultural practices, including limiting manure
application to the nitrogen needs of the crops grown. The second option (Option 2) will require land
application at the CAFO to be consistent with proper agricultural practices, including limiting manure
application to the nitrogen needs of the crops grown or where necessary, to the phosphorus needs of the
crops.
Using the approach described in Section 2.4 of this report, EPA conducts its analysis first at the
farm level based on data reflecting financial conditions for the entire farm operation (i.e., reflecting
income and cost information spanning the entire operations, and thus considering the operation's primary
livestock production, along with other income sources such as secondary livestock and crop production,
government payments, and other farm-related income). Based on the farm level results, EPA also
assesses the financial effects on CAFOs at the enterprise level (e.g., limiting the scope of the assessment
to the operation's livestock or poultry enterprise, and excluding other non-CAFO related sources of
income from the analysis).
This appendix presents estimated financial effects using the farm level data and model and
enterpise level data. Financial effects are estimated for each representative model CAFO and are broken
out by animal sector, production region, and facility size, as well as groupings based on land availability
and the technology needs of the facility. These groupings include the following:
Production region: Midwest (MW); Central (CE); Pacific (PA); Mid-Atlantic (MA); and
South (SO). For more information, see Table 2-1 in Section 2 of this report.
Facility size: Varies by sector. See Table 2-1 in Section 2 of this report.
Land availability: Category 1 CAFOs (sufficient cropland for all manure nutrients
generated), Category 2 CAFOs (insufficient cropland), and Category 3 CAFOs (no available
cropland for land application).
• Technology needs: Medium (average needs); Low (least needs); High (most needs).
Results are presented in terms of EPA impact categories to assess the financial effects of the final
regulations: Affordable, Moderate, and Stress. As discussed in Section 2.4, the first category is the
affordable category, which means that the regulations have little or no financial impact on CAFO
operations. The second category, the moderate impact category, means that the regulations will have
some financial impact on operations at the affected CAFOs, but EPA does not consider these operations
to be vulnerable to closure as a result of compliance. Table D-l presents these results. The third
category is the financial stress category, which means that EPA considers these operations to be
vulnerable to closure post-compliance, subject to other considerations. Table D-2 presents these results at
the farm level, then combined with the results at the enterprise level. Section 2.4 of this report describes
the decision framework that EPA assumes for this analysis.
D-l
-------
Table D-l(a)
Option 1
Estimating the Number of Farms
Under Each AchJcvabtllty Criteria
Affordable and Moderate
Farm Cowit by Category
S«t«>'M«M
Medium 1
Medium 3
LKS*!
CERqfei
MaXtxnl
MeAm3
Urtol
Ut«c2
rAR«rk«
Medina!
Ma&an3
Lirjcl
SORtchi
M«ifara2
Lafzel
U--JC2
^tlShral
Motel 2
,. ., -
laml
LlfJ«2
Veal
KWRcflo
Moluml
M«&Jra3
Urjsl
NMtial
Moiural
Mahm3
Medium 1
Mo!itira2
Mal-imS
MoAral
Me&raZ
MARttba
Moffura2
MaJtwnl
llriftn
M\VRttlcn
MoEunl
Motel
Mofcjral
M«&im3
Urpl
IL
15
8
4
146
5
4
2
72
3
0
0
0
10
0
0
0
0
0
0
t
0
o
1
0
0
0
1
3
0
0
0
0
0
a
0
0
0
0
0
0
31
4
2
0
2
5
2
24
2L 3L 1M 2M 3M 111 2H 3H
2 I 30
1 1 17
008
45 24 291
36 26 11
007
004
003
22 12 144
17 13 5
0 0 1
000
000
3 2 20
2 2 1
000
000
000
000
000
0 0 1
0 0 1
00 0
003
1 0 0
0 0 1
000
002
006
000
000
0 0 1
000
000
000
000
000
000
000
000
000
3 3 63
008
003
000
003
009
004
a 4 so
3 3 IS 21
21811
11400
90 47 146 45 24
71 52 5 36 26
11400
00200
001 00
45 23 72 22 12
36 26 3 17 13
000 00
000 00
000 00
6 3 10 32
54022
000 00
000 00
00000
000 00
000 00
001 00
000 00
000 00
101 00
100 10
300-IOOOAU
>1000AU
Total Beet
000 00
000 00
001 00
003 00
00000
000 00
000 00
000 00
000 00
000 00
000 00
000 00
000 00
000 00
000 00
000 00
300-IOOOAU
>1000AU
Total Veal
7 5 31 33
11400
00200
00000
002 00
1 1 5 0 0
002 00
15 8 24 84
All
73
40
20
856
268
17
9
6
424
133
2
1
1
57
17
0
0
0
0
0
2
1
0
8
3
173
1,766
1,939
2
1
4
12
0
0
1
0
0
0
0
0
0
0
0
0
12
20
150
20
8
0
8
22
9
145
Number of Affordable by Category
IL 2L 3L 1M 2M 3M 1H 2H 3H
15 2 1 30 3 3 IS 2 1
8 1 1 17 21 811
4 00 8 11 400
146 45 24 291 90 47 146 45 24
5 36 26 11 71 52 5 36 26
4 00 7 II 400
2 00 4 00 200
1 00 3 00 100
72 22 12 144 45 23 72 22 12
3 17 13 5 36 26 3 17 13
0 00 1 00 000
0 00 0 00 000
0 00 0 00 000
10 0 2 20 0 3 10 0 2
0 22 1 54 022
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
1 00 1 00 100
0 00 1 00 000
0 00 0 00 000
1 00 3 10 100
0 10 0 10 010
300-IOOOAU
>1000AU
Total Beef
0 00 1 00 000
0 00 0 00 000
1 00 2 00 100
3 00 6 00 300
0 00 0 00000
0 00 0 00 000
0 00 I 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
0 00 0 00 000
300-IOOOAU
>IOOO AU
Total Veal
31 3 3 63 75 003
4 00 8 II 400
2 00 3 00 200
0 00 0 00 000
2 00 3 0. 0 000
5 00 9 11 500
2 00 4 00 200
24 84501582484
Number of Moderate by Category
All
73
40
20
856
268
17
9
6
424
133
2
1
1
45
17
0
0
0
0
0
2
1
0
8
3
173
1,754
1,927
2
1
4
12
0
0
I
0
0
0
0
0
0
0
0
0
8
12
20
115
20
8
0
6
22
9
145
IL 2L 3L 1M 2M 3M 1H 2H 3H
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
000
000
000
000
0 9. 0
o o *• o
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
^
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
•o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
300-IOOOAU
>100DAU
Total Beef
000
000
000
000
000
0 0 ' 0
000
000
000
000
000
000
000
000
000
000
300-IOOOAU
>1090 AU
Total Veal
000
000
000
000
000
000
000
000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 .
0
0
All
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
D-2
-------
Table D-I(a)
Option 1
Estimating the Number of Farms
Under Each Achievability Criteria
Affordable and Moderate
Farm Count by Category
Sector/Model
PA Region
Medium 1
Medium 2
Mediums
Large I
SO Region
Medium I
Medium 2
Mediums
Large 1
MA Region
Medium 1
Medium 2
Mediums
Large 1
IL
. I
1
1
16
0
0
0
0
0
0
0
0
2L
0
0
0
5
0
0
0.
0
0
0
0
0
3L
0
0
0
3
0
0
. 0
0
0
0
0
0
1M
2
3
I
33
0
0
0
0
. 0
0
0
0
2M
0
0
0
10
0
0
0
0
0
0
0
0
3M IB
0 1
0 1
0 1
5 16
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
2H
0
0
0
5
0
0
0
0
0
0
0
0
3H
0
0
0
• 3
0
0
0
0
0
0
0
0
300-1000AU
>IOOOAU
Total Heifer
Dairy- Flush
PA Region
Medium 1
Medium 2
Mediums
Large 1
MW Region
Medium 1
Medium 2
Mediums
Large 1
CE Region
Medium 1
Medium 2
Medium3
Large 1
SO Region
Medium 1
Medium 2
Mediums
Large 1
MA Region
Medium!
Medium 2 -
Mediums
Large 1
Dairy- Hose
PA Region
Medium 1
Medium 2
Mediums
Large 1
MW Region
Medium 1
Medium 2
Mediums
Large 1
CE Region
Medium 1
Medium 2
Mediums
Large 1
SO Region
Medium 1
Medium 2
Mediums
Large 1
MA Region
Medium 1
Medium 2
Mediums
Large 1
5
2
2
38
15
5
1
3
8
3
2
20
6
2
1
5
17
6
1
4
5
2
2
13
45
16
2
3
8
3
2
7
6
2
1
2
51
18
4
4
4
I
1
72
11
4
I
6
6
2.
1
38
5
2
1
9
12
4
1
7
4
1
1
24
32
12
2
6
6
2
I
13
5
2
1
3
36
IS
3
7
1
I
1
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
1
1
1
10
13
5
1
3
2
1
0
6
2
I
0
1
14
5
1
3
10
:4
4
77
SO
11
2
6
17
6
.3
41
12
5
2
9
34
12
2
7
10
4
4
26
90
32
5
6
17
6
3
14
12
5
2
3
101
37
8
7
7
3
3
145
22
8
1
12
12
4
2
77
9
3
2
17
24
9
2
13
7
3
3
49
64
23
3
12
12
4
2
26
9
3
I
6
73
26
6
13
3 5
1 2
1 2
63 38
8 15
3 5
0 I
5 3
5 8
2 3
1 2
33 20
3 6
1 2
1 I.
7 5
9 17
3 6
1 1
6 4
3 5
1 2
1 2
21 13
25 45
9 16
1 2
5 3
5 8
2 3
1 2
11 7
3 6
1 2
1 1
2 2
28 51
, 10 18
2 4
6 4
4
1
1
72
11
4
1
6
6
2
1
38
5
2
1
9
12
4
1
7
4
1
1
24
32
12
2
6
6
2
1
13
5
2
1
3
36
IS
3
7
I
I
I
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
1
1
1
10
13
5
1
3
2
1
0
6
2
I
0
1
14
5
1
3
300-1000AU
. >1000AU
Total Dairy
All
4
7
3
97
0
0
0
0
0
0
0
0
IS
97
110
41
15
15
569
120
'43
7
47
67
24
13
301
50
18
8
68
134
48
10
52
41
15
15
190
358
129
19
48
67
24
12
100
50
18
7
23
404
146
31
52
1,948
1,450
3,536
IL
,
1
1
16
0
0
0
0
0
0
0
0
5
2
2
38
15
5
1
3
8
3
2
20
6
2
1
5
17
6
1
4
5
2
2
IS
45
16
2
3
8
3
2
7
6
2
1
2
51
18
4
4
2L
0
0
0
5
0
0
0
0
0
0
0
0
4
0
I
72
11
4
1
6
6
0
1
38
5
0
1
9
12
4
1
7
4
1
1
24
32
12
2
6
6
2
1
IS
5
2
1
3
36
13
3
7
Number of Affordable by Category
3L
0
0
0
3
0
0
0
0
0
0
0
0
1
1
1
31
4
2
0
3
2
,1
0
17
2
1
0
4
5
2
0
3
I
1
I
10
13
5
1
3
2
1
0
6
2
1
0
1
14
5
I
3
1M
2
3
1
33
0
0
0
0
0
0
0
0
10
4
4
77
30
11
2
6
17
6
3
41
12
5
2
9
34
12
2
7
10
4
4
26
90
32
5
6
17
6
3
14
12
5
2
3
101
37
8
7
2M 3M 1H 2H 3H
00 0" 0 0
00 100
00 100
10 5 16 5 3
00 000
00000
00 000
00 000
00 000
00 000
00000
00 000
300-1000AU
>IOOOAU
Total Heifer
73 541
01 201
31211
0 63 38 0 31
22 8 15 11 4
83 542
10110
12 5 363
12 5 862.
02 301
2 1 2 I ' 0
77 33 20 38 17
93 652
.01 201
01 100
17 7 594
24 9 17 12 5
93 642
21 110
13 6 473
73 541
31 211
31 211
49 21 13 24 10
64 25 45 32 13
23 9 16 12 5
31 221
12 5 3' 6 3
12 5 862
42321
21 210
26 II 7 13 6
93 652
31 221
11 110
62 231
73 28 51 36 14
26 10 18 13 5
62431
13 6 473
SOO-1000AU
>1000AU
Total Dairy
All
3
6
3
97
0
0
0
0
0
0
0
0
12
97
109
41
9
15
351
120
43
7
47
-- 67
15
13
301
50
12
6
68
134
48
10
52
41
15
15
190
358
129
19
48
67
24
12
100
50
18
7
23
404
146
31
52
1,925
IL 2L
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
Number of Moderate bv Category
3L 1M 2M 3M 1H
0
0
0
0
0
0
0
0
^
0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
2H
0
0
0
0
0
0
0
0
0
0
0
0
3H
0
0
0
0
0
0
0
0,
0
0
0
0
300-1000AU
MOOOAU
Total Heifer
0 0
0 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 2
0 0
0 0
0 0
0 2
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0
0
0
0
0
0
0
0
0
0
0
0'
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0 3
0 0
0 145
0 0
0 0
0 0
0 0
0 0
0 4
0 0
0 0
0 0
0 '3
0 2
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0'
0 0
0 0
0 0
0 0
o o
0 q
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
1
0
72
0
0
0
0
0
2
0
0
0
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0 .
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
9
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
300-1000AU
If 32 >10«OAU
3,158
Total Dairy
All
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
0
218
0
0
0
0
0
9
0
0
0
7
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
23
218
240
-------
Table D-l(a)
Option 1
Estimating Ike Number of Farms
Under Each Acblcyablllty Criteria
Affordable >nd Moderate
Farm f!MTOt by Category
SccUrModd
MWRcjiim
Mediizal
!^
Uipt
MeAml
MtdfaraS
1*1.2
MWXiffea
Meditml
U^r*!
UQC!
U.-J02
Medium 1
Median!
Utpl
Uriel
H.jiri(
-------
Table D-l(a)
Option 1
Estimating the Number of Farms
Under Each Achievability Criteria
Affordable and Moderate
Farm Count by Category
Sector/Model 1L
Hogs Evaporate
CE Region (GFCont)
Large 1
Large 2
Broilers
SO Region
Medium 1
Medium 2
Medium3
Large 1
Large 2
MA Region
Medium 1
Medium 2
Medium3
Large 1
Large 2
Layers (Wet)
SO Region
Medium3
Large 1
Layers (Dry)
SO Region
Medium 1
Medium 2
Mediums
Large 1
Large 2
MW Region
Medium 1
Medium 2
Mediums
Large 1
Large 2
Turkeys
MA Region
Medium 1
Medium 2
Mediums
Large 1
MW Region
Medium 1
Medium 2
Mediums
Large 1
4
3
2
I
1
3
2
2
2
2
7
4
I
10
1
0
0
6
1
1
0
0
11
2
0
0
0
3
0
0
0
4
2L
5
3
14
23
21
12S
72
5
8
8
50
29
2
40
1
0
0
24
3
I
0
0
42
6
1
1
0
22
1
1
0
30
3L
3
2
7
9
8
46
26
6
6
6
27
15
3
46
1
0
0
28
3
I
0
0
49
7
1
0
0
16
1
0
0
22
1M
7
'5
4
:3
.2
7
4
,3
3
3
15
8
2
21
I
0
0
13
1
' 1
0
0
22
3
1
0
0
6
1
0
0
8
2M
9
7
27
46
42
250
145
10
16
16
100
58
5
79
2
1
0
49
5
2
1
0
84
13
3
2
1
44
2
2
1
61
3M 1H 2H
645
533
300-1000AU
>1000AU
Total Hog
14 2 14
18 1 23
16 1 21
91 3 125
53 2 72
11 2 5
12 2 8
12 2 8
53 • 7 SO
31 4 29
300-1000AU
>1000AU
Total Broiler
5 1 2
91 10 40
300-1000AU
>1000AU
Total Wet Layer
1 1 1
1 0 0
00 0
56 6 24
6 1 3
1 1 1
1 0 0
000
97 11 42
15 2 6
300-1000AU
>1000AU
Total Dry Layer
2 0 1
1 0 1
1 0 0
32 3 22
1 0 1
1 0 1
1 0 0
43 4 SO
300-10DOAU
s-lOOOAU
Total Turkey
3H
3
2
7
9
8
46
26
6
6
6
27
15
3
46
1
0
0
28
3
1
0
0
49
7
I
0
0
16
I
0
0
22
All
45
32
1,485
3,924
5/109
90
133
120
698
404
48
64
64
336
194
520
1,632
2,152
24
383
24
383
407
8
4
0
235
25
8
4
1
407
62
26
729
755
11
6
3
163
9
5
3
225
37
388
425
1L 2L
4 5
3 3
2 14
1 23
I 21
3 125
2 72
2 5
2 8
2 8
7 50
4 29
1 2
10 40
1 1
0 0
0 0
,6 24
1 3
1 1
0 0
0 0
11 42
2 6
0 1
0 1
0 0
3 22
0 1
0 1
0 0
4 30
Number of Affordable by Cateeorv
3L
3
2
7
9
8
46
26
6
6
6
27
15
3
46
1
0
0
28
3
1
0
0
49
7
1
0
0
16
'l
0
0
22
1M
7
5
0
0
0
0
0
3
3
3
15
8
2
21
1
0
0
IS
1
1
0
0
22
3
1
0
0
6
1
0
0
8
2M
9
7
0
0
42
250
145
10
16
16
100
58
5
79
2
1
0
49
5
2
1
0
84
13
3
2
1
44
2
2
1
61
3M 1H 2H
645
533
300-1000AU
>1000 AU
Total Hog
000
18 0 0
16 0 0
91 0 0
53 0 0
11 0 0
12 0 8
12 2 8
53 0 50
31 0 29
300-1000AU
>1000AU
Total Broiler
5 1 2
91 10 40
300-1000AU
>1000AU
Total Wet Layer
1 1 1
1 0 0
0 00
56 6 24
6 I 3
1 1 1
1 0 0
0 00
97 11 42
15 2 6
300-1000AU
>1000AU
Total Dry Layer
2 0 1
1 0 I
1 0 0
32 3 22
1 0 1
I 0 1
1 0 0
43 4 30
300-1000AU
>1000 AU
Total Turkey
3H
3
2
0
0
0
0
0
6
6
6
27
15
3
46
1
0
0
28
3
I
0
0
49
7
1
0
0
16
I
0
0
22
All
45
32
1,485
3,924
5,409
23
51
88
516
299
42
63
64
329
190
330
1,334
1,664
24
383
24
383
407
8
4
0
235
25
8
4
1
407
62
26
729
755
11
6
3
163
9
5
• 3
225
37
388
425
1L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
. 0
0
0
0
0
0
0
0
0
0
0
2L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Number of Moderate bv Cateeorv
3L 1M
0 0
0 0
0 4
0 3
0 2
0 7
0 4
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
2M
0
0
27
46
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3M IH 2H 3H
00 00
00 00
300-1000AU
>1000AU
Total Hog
14 2 14 ' 7
0 1 23 9
0 1 21 8
0 0 125 46
02 72 26
0250
02 00
00 00
07 00
04 00
300-1000AU
>1000AU
Total Broiler
00 00
00 00
300-1000AU
>1000AU
Total Wet Layer
00 00
00 00
00 00
00 00
00 00
0000
00 00
0000
oo oo
00 00
300-1000AU
>IOOOAU
Total Dry Layer
00 00
00 00
00 00
00 00
00 00
00 00
0 0 00
00 00
300-1000AU
>1000AU
Total Turkey
AU
0
0
0
0
0
68
82
33
178
105
6
2
0
7
4
190
294
485
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
• 0
-------
Table D-l(b)
Option 2
Estimating tbe Number of Farms
Under Each Achlevability Criteria
Affordable and Moderate
Sa.utV.sttt
lot
MWRcflm
M«dM*a2
Xbditonl
Uffel
tap2
tcl
Motel
Mcdhajil
Medhm3
1L
15
8
4
139
S
3
2
1
49
2
0
0
0
0
0
0
0
Q
0
0
0
0
o
s
o
1
3
0
0
0
0
0
0
0
0
0
0
0
o
30
4
2
0
2
4
2
17
r
2L 3L
2 1
1 I
1 0
52 24
36 26
1 0
0 0
0 0
46 12
19 13
0 0
0 0
0 0
7 2
2 2
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 0
1 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
4 3
1 0
0 0
0 0
0 0
1 0
0 0
16 4
araCl
IM
29
16
8
277
10
6
4
2
97
3
I
0
0
12
0
0
0
0
0
0
1
I
0
2
0
0
2
6
0
0
1
0
0
0
0
0
0
0
0
0
61
8
3
3
8
3
34
2M 3M 1H 2H 3B
4. 3
2 1
1 1
104 47
72 52
1 1
I 0
1 0
91 23
38 26
0 0
0 0
0 0
14 3
5 4
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 0
1 0
15 2 I
8 I 1
4 1 0
139 52 24
5 36 26
3 1 0
200
1 0 0
49 46 12
2 19 13
0. 0 0
000
000
672
022
000
000
000
000
000
000
000
0 00
1 1 0
0 1 0
300-1MGAU
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
9 5
1 1
0 0
1 0
2 1
1 0
31 8
>1009AU
Total Beef
000
000
1 0 0
300
000
000
000
000.
000
000
000
000
000
000
000
000
3MMOOOAU
>1009AU
Total Veil
30 4 3
4 1 0
200
200
4 1 0
200
17 16 4
AH
73
40
20
856
268
17
9
6
424
133
2
1
57
17
0
0
0
0
0
2
1
0
8
3
173
1,766
1,939
2
1
4
12
0
0
1
0
0
0
0
II
0
0
0
0
8
12
20
150
20
8
Q
8
22
9
145
1L
15
8
4
139
5
3
2
1
49
2
0
0
0
6
0
0
0
0
0
0
0
0
0
1
0
0
0
1
3
0
0
0
0
0
0
0
0
0
0
0
0
30
4
2
Q
2
4
2
17
Number or Affordable by Category
2L 3L IM 2M 3M 1H 2H 3H
2 1 29 4 3 15 0 1
1 1 16 21 811
1-0 8 11 400
52 24 277 104 47 139 52 24
36 26 10 72 52 5 36 26
10 6 11 300
00 4 10 000
00 2 1 0 ' 1 0 0
46 12 97 91 23 49 46 12
19 13 3 38 26 2 19 13
00 0 00 000
00 0 • 0 0 000
00 0 00 000
00 12 00 000
20 0 50 020
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
0010 ""0 000
00 1 OO'OOO
00 0 00 000
10 2 10 100
10 0 10 010
300-1000AU
>1000AU
Total Beer
00 1 00 000
00 0 DO 000
00 2 00 100
00 6 00 300
00 0 00 000
DO 0 00 000
00 1 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
00 0 00 000
300-1000AU
>1000AU
Total Veal
43 61 95 003
10 8 11 410
00 3 00 200
00 0 00 000
00 3 10 000
10 8 21 410
00 3 10 200
16 4 34 31 8 17 16 4
Number orModer
All
70
4D
19
856
268
16
8
6
424
133
0
0
17
10
0
0
0
0
0
I
1
0
6
2
164
1,717
1,881
2
1
4
12
0
0
I
0
0
0
0
i
0
0
0
0
8
12
20
115
20
8
0
6
22
9
145
ate by Category
1L 2L 3L IM 2M 3M 1H 2H 3H
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0 •
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0.
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
000
000
000
000
000
000
000
000
000
ooo
OOP
000
000
000
000
000
000
000
000
000
000
000
000
000
300-10COAU
HOOOAU
Total Beer
000
000
00 0
000
000
0 ' 0 0
000
000
000
000
000
000
000
000
000
000
300-10DOAU
MOOOAU
Total Veal
000
000
000
000
000
000
000
000
0
0
0
0
p
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
All
0
0
0
0
t
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-l(b)
---. - Option2
Estimating the Number of Farms
Under Each Achicvsbllity Criteria
Aflbrdable and Moderate
Farm Count by Category
Sector/Model
PA Region
Medium !
Medium 2
Medium 3
Large 1
SO Region
Medium I
Medium 2
Medium3
Large 1
MA Region
Medium 1
Medium 2
. Medium 3
Large 1
Dairy- Flush
PA Region
, Medium 1
Medium 2
Medium 3
Large I
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large!
MA Region
Medium 1
Medium!
Medium 3
Large 1
Dairy- Hose
PA Region
Medium]
Medium 2
Medium 3
Large 1
MW Region
Medium!
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large!
SO Region
Medium!
Medium 2
Medium 3
Large!
MA Region
Medium 1
Medium!
Medium 3
Largel
1L
1
1
0
10
0
0
0
0
0
0
0
0
4
1
1
24
12
4
1
2
6
2
!
16
6
2
1
3
13
S
1
2
4
1
1
8
35
13
2
2
6
2
1
5
6
2
1
1
39
14
3
2
2L
0
0
0
12
0
0
0
0
0
0
0
0
5
2
2
87
14
5
1
7
8
3
2
42
5
2
1
10
16
6
1
8
5
2
2
29
42
IS
2
7
8
3
1
14
5
2
1
3
48
17
4
8
3L
0
0
0
3
0
0
0
0
0
0
0
0
1
1
1
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
1
1
1
10
13
5
1
3
2
1
0
6
2
1
0
1
14
5
1
3
1M
1
2
I
20
0
0
0
0
0
0
0
0
7
3
3
48
24
9
i
5
. 13
5
2
33
11
4
2
7
26
9
2
S
7
3
3
16
71
25
4
5
. 13
5
2
11
11
4
2
2
77
28
- 6
5
2M
0
1
0
24
0
0
0
0
0
0
0
0
10
4
4
174
28
10
1
13
16
6
3
85
10
4
2
20
32
12
2
16
10
4
4
59
83
30
4
14
16
6
3
28
10
4
2
6
96
35
7
16
3M 1H 2H
0 1 0
.0 1 0
,000
5 10 '12
000
000
000
000
000
000
000
000
300-1000AU
>!OOOAU
Tola! Heifer
345
1 1 2
1 1 2
63 24 87
8 12 14
345
• o i i
527
568
223
1 1 2
33 16 42
365
I 2 2
1 1 1
7 3 10
9 13 16
356
1 1 1
628
34-5
1 1 2
1 1 2
21 8 29
25 35 42
9 13 15
1 2 2
527
568
223
1 1 1
11 5 14
365
1 2 2
1 1 1
2 1 3
28 39 48
10 14 17
234
628
300-1000AU
>1000 AU
Total Dairy
3H
0
0
0
3
0
0
0
0
0
0
0
0
1
1
' 1
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
I
1
10
13
5
1
3
2
1
0
6
2
1
0
I
14
5
1
3
AU
4
7
3
97
0
0
0
0
0
0
0
0
230
142
472
41
15
15
569
120
43
7
47
67
24
13
301
50
18
8
68
134
48
10
52
15
15
190
358
129
19
48
K!
24
12
100
50
18
7
23
404
146
31
52
1,948
1,450
3,398
IL
1
1
0
10
0
0
0
0
'0
0
0
0
4
1
1
24
12-
4
1
2
6
2
1
16
6
2
1
3
13
5
1
2
I
1
S
35
13
2
2
6
2
1
5
6
2
1
1
39
14
3
2
Number of Aflbrdable bv Category
2L
0
0
0
12
0
0
0
0
0
0
0
0
5
0
2
0
14
5
1
rj
8
3
2
42
5
0
I
0
16
'6
1
0
2
2
29
42
15
2
,7
8
3
1
14
5
2
1
3
48
17
4
8
3L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
31
4
2
0
2
1
0
17
2
1
0
4
0
0
0
0
1
I
10
13
5
1
3
2
1
0
6
2
1
0
1
14
S
1
3
1M
0
2
1
20
0
0
0
0
0
0
0
0
7
3
3
48
24
9
I
13
5
2
33
11
4
2
•7
26
9
2
5
3
3
16
71
25
4
5
13
5
2
11
II
4
2
2
77
28
6
5
2M
0
1
0
24
0
0
0
0
0
0
0
0
10
0
4
0
28
10
• 1
16
6
3
85
10
0
2
0
32
12
2
0
4
4
59,
83
30
4
14
16
. 6
3
28
10
4
2
6
96
35
7
16
3M 1H 2H
000
0 i 0
000
0 10 0
0 00
000
000
000
000
000
0 00
000
300-1000AU
>1000 AU
Total Heifer
045
0 1 0
0 1 2
63 24 0
8 12 14
345
0 1 I
568
223
1 1 2
33 16 42
365
1 2 0
0 11
730
0 13 16
056
0 1 1
0 20.
1 1 2
1 1 2
21 8 29
25 35 42
9 13 15
,1 22
527
568
223
I 1 1
11 5 14
365
1 2 2
1 1 1
2 1 3
28 39 48
10 14 17
234
628
300-1000AU
>1000 AU
Total Dairy
3H
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
31
4
2
0
2
1
0
17
2
1
0
4
0
0
0
0
1
1
10
13
5
1
3
2
1
0
6
2
1
0
I
14
5
1
3
All
1
6
3
7S
0
0
189
220
409
35
5
13
221
120
43
7
67
24
13
301
50
11
7
28
115
42
9
9
15
15
190
358
129
19
48
67
24
12
100
50
18
7
23
404
146
31
52
1,895
1,019
2,915
IL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2L
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
87
0
0
0
0
0
0
0
0
0
2
0
10
0
0
0
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Number of Moderate bvCateeorv
3L 1M
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
1 0
1 0
1 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
5 0
2 0
0 0
3 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
. 0 0
2M
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
174
0
0
0
0
0
0
0
0
0
4
0
20
0
0
0
16
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3M 1H 2H 3H
00 00
00 00
0000
00 00
ft-'- 000
0~ 0 00
00 00
00 00
0000
0 00 0
0 0 00
00 00
300-1000AU
=•1000 AU
Total Heifer
30 01
1021
10 01
0 0 87 0
00 00
00 00
00 00
00 00
0 0 00
00 00
00 00
00 00
00 00
0020
1000
0 0 10 0
90 05
3002
10 00
60 83
00 00
00 00
00 00
0000
0000
00 00
00 00
0000
00 00
00 00
00 00
0 0 ,0 0
00 00
00 00
00 00
00 00
00 00
00 00
00 00
0000
300-1000AU
>1000 AU
Total Dairy
AH
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
10
2
348
0
0
0
0
0
0
0
0
0
8
1
40
19
7
1
43
0
0
0
0
0
0
0
0
0
0
0
0
D
Q
0
0
0
0
0
0
53
431
483
-------
Table D-l(b)
Option 2
Estimating the Number of Farms
Under Each Achievabllity Criteria
Affordable and Moderate
SrtMMiid
Mediml
Medium!
MaS»m3
Urjel
Medtwfll
M«*ra2
Medial]
Uriel
MWRtfka
MoSoal
Midiural
MediumS
Uriel
MARrdM
Mc*JiiXTtl
Mcdiuml
Median]
Urpl
Unel
ll.yfh(CFlad)
MWRrtlo
Medium 1
Mrfiun3
Urtel
Urp2
MA^j2^nl
Moiitnil
Uriel
Uriel
MWRetfe*
MoJinl
Mrfianl
Uriel
MARerj»
Median 1
Medt«n3
Uriel
Uriel
H*ca Evaporate
Uriel
Uriel
C£Rf«!o« (triad)
Urtel
Urcel
H.pUq»:.(GFC.»0
MWR«fl««
Mcdionl
M«ta2
M«fi«n3
Uriel
Urpl
SIWMr*ll
MtdhnZ
Motel)
Urtel
Ur»e3
1L
IS
5
3
8
6
1
1
7
'
41
15
7
17
19
5
2
1
S
6
22
10
S
20
14
1
0
0
4
3
50
18
9
35
25
1
0
0
2
2
2
1
4
3
5
3
2
10
7
II
I
3
25
I!
JL 3L
2 1
2 1
1 I
8 7
6 5
2 1
1 1
38 11
28 8
7 7
6 4
3 2
27 22
19 16
3 2
4 2
2 1
46 13
33 10
4 4
4 2
2 1
20 16
14 12
1 0
1 0
0 0
23 7
17 5
9 8
7 4
3 2
35 29
25 21
1 0
1 0
0 0
14 4
10 3
4 2
3 2
10 6
7 4
1 1
1 i
1 0
10 9
7 6
2 2
1 1
1 1
25 21
18 15
IM 2M 3M
21
10
6
16
12
3
1
13
9
82
30
IS
54
39
11
4
2
16
11
44
21
12
39
28
2
1
1
8
6
100
37
18
70
50
2
1
0
5
4
4
3
9
6
11
5
3
21
IS
23
11
6
50
36
4 3
4 2
2 1
16 14
12 10
5 2
3 1
77 22
55 16
IS 14
11 7
54 45
38 32
8 3
4 2
91 27
65 19
8 7
8 5
4 3
39 33
28 24
1 1
2 1
1 0
46 13
33 10
18 17
13 9
7 4
69 58
50 42
1 1
I 1
1 0
29 8
21 6
9 5
6 4
19 11
14 8
2 2
2 1
1 1
21 17
15 12
4 4
4 3
2 2
SO 42
36 30
1H
10
5
3
8
6
1
I
7
5
41
IS
27
19
2
1
8
6
22
10
6
20
14
1
0
0
4
3
50
18
9
35
25
1
0
0
2
2
2
1
4
3
5
3
2
10
7
11
5
3
25
18
2H 311
2
2
1
8
6
2
1
38
28
7
6
27
19
4
2
46
33
4
4
2
20
14
1
. 1
0
23
17
9
7
3
35
25
1
1
0
14
10
4
3
10
7
1
1
1
10
7
2
2
1
25
18
2
1
1
7
5
1
1
11
8
7
4
22
16
2
1
13
10
4
2
1
16
12
0
0
0
7
5
8
4
2
29
21
0
0
0
4
3
2
2
6
4
1
1
0
9
6
2
1
1
21
15
AH
56
32
19
92
66
20
19
11
225
161
221
97
305
219
31
15
267
192
118
66
39
223
160
7
7
4
135
97
2(9
119
58
394
283
7
5
. 1
84
60
35
25
78
56
29
16
10
118
84
61
"34
20
284
203
1L
10
5
3
8
6
1
1
7
5
41
15
27
19
2
1
8
6
22
10
6
20
14
1
0
0
4
3
50
18
9
35
25
1
0
0
2
2
2
1
4
3
5
3
2
10
7
11
5
3
25
18
Number of Affordable by Category
2L 3L
2
2
1
8
6
2
1
38
28
7
6
27
19
4
2
46
33
4
4
2
20
14
1
1
0
0
0
9
7
3
35
25
1
1
0
14
10
4
3
10
7
1
1
1
0
7
2
2
1
0
0
2
1
1
7
5
I
1
11
8
7
4
22
16
2
1
13
10
4
2
1
16
12
0
0
0
0
0
8
4
2
29
21
0
0
0
4
3
2
2
6
4
1
1
0
9
6
2
1
1
0
0
IM 2M 3M
21
10
6
16
12
3
2
13
9
82
30
54
39
4
2
16
11
44
21
12
39
28
2
1
1
8
6
100
37
18
70
50
2
1
0
5
4
4
3
9
6
11
5
3
0
15
23
li
6
0
36
4 3
4 2
2 1
16 14
12 10
5 2
3 1
77 22
55 16
IS 14
11 7
54 45
38 32
7 4
8 3
4 2
91 27
65 19
8 7
8 5
4 3
39 33
28 24
1 1
2 1
1 0
0 0
0 0
18 17
13 9
7 4.
69 58
SO 42
1 1
1 1
1 0
29 8
21 6
9 S
6 4
19 11
14 8
2 2
2 1
1 1
0 17
15 12
4 4
4 3
2 2
0 0
0 0
1H 2H 3H
10 2
5 2
3 1
8 8
6 6
1 2
1 1
7 38
5 28
41 7
15 6
27 27
19 19
5 3
2 4
1 2
8 46
6 33
22 4
10 4
6 2
20 20
14 14
1 1
0 1
0 0
4 0
3 0
50 9
18 7
9 3
35 35
25 25
1 1
0 1
0 0
2 H
2 10
2 4
1 3
4 10
' 3 7
5 1
3 1
2 1
0 0
7 0
11 2
5 2
3 1
0 0
18 0
2
1
1
7
5
j
I
1
11
8
7
4
2
22
16
2
2
1
13
10
4
2
1
16
12
0
0
0
0
0
8 -
4
2
29
21
0
0
0
4
3
2
2
6
4
1
1
0
9
6
2
1
1
0
0
All
56
32
19
92
66
20
19
11
225
161
221
97
47
305
219
44
31
15
267
192
118
66
39
223
160
7
7
4
16
11
269
119
58
394
283
7
S
1
84
60
35
25
78
56
29
16
10
45
77
61
34
20
25
72
Number of Moderate by Category
1L 2L 3L IM 2M 3M 1H 2H 3H
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
10 0
0 0
0 0
0 0
0 0
25 21
18 15
0
0
0
0
0
Q
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
21
0
0
0
0
50
0
0
0
0
0
0
Q
0
0
0
0
0
0
Q
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
21
0
0
0
0
50
36
0
0
0
0
0
o
0
0
0
0
0
0
o
0
0
Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
42
30
0
0
0
0
0
o
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
0
0
0
0
25
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
7
0
0
0
25
IS
0
0
0
0
0
o
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
21
IS
All
0
0
0
0
0
o
0
0
0
0
0
0
o
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
72
7
0
0
0
2:9
132
-------
Table D-l(b)
Option 2
Estimating the Number of Farms
Under Each Achievabillty Criteria
Affordable and Moderate
Farm Count by Category
Sector/Model 1L
Hogs Evaporate
CE Rf j»n (CFCont)
Urge! 2
Large 2 2
Broilers
SO Region
Medium 1 2
Medium 2 1
Medium 3 1.
Large 1 3
Urge 2 2
MA Region
Medium 1 1
Medium 2 1
Medium 3 1
Large 1 4
Large 2 2
Layers (Wet)
SO Region
Medium .1 1
Large 1 7
Layers (Dry)
SO Region
Medium t 0
Medium 2 0
Medium 3 0
Large 1 3
Large 2 0
MW Region
Medium 1 0
Medium 2 0
Medium] 0
Large 1 8
Large 2 1
Turkeys
MA Region
Medium 1 0
Medium 2 0
Medium] 0
Large ) 1
MW Region
Medium 1 0
Medium 2 0
Medium] 0
Large 1 2
2L
6
4
14
23
21
126
73
5
9
9
54
31
3
43
1
0
0
27
3
1
0
0
46
7
2
1
0
24
1
1
0
33
3L
3
2
7
9
8
46
26
6
6
6
27
15
3
46
1
0
0
28
3
I
0
0
49
7
I
0
0
16
1
0
D
22
1M
5
4
3
2
2
6
3
2
2
2
7
4
1
14
i
1
0
0
7
. 1
1
0
0
15
2
0
0
()
2
0
0
0
3
2M 3M 1H 2H
11 6 2 6
85 24
300-1000AU
>1000 AD
Total Hog
28 14 2 14
46 18 1 23
42 16 1 21
252 91 3 126
146 53 2 73
11 11 I 5
18 12 1 9
18 12 1 9
108 53 4 54
62 31 2 31
300-IOOOAU
>1000 AU
Total Broiler
5513
86 91 7 43
300-IOOOAU
>1000AU
Total Wet Layer
2101
1100
0000
55 56 3 27
6603
21 0 1
1100
0000
91 97 8 46
14 15 1 7
300-IOOOAU
>1000 AU
Total Dry Layer
3202
2101
1 1 0 0
48 32 1 24
3101
2101
1100
66 43 2 33
300-IOOOAU
>IOOOAU
Total Turkey
3H
3
2
7
9
8
46
26
6
6
6
27
15
3
46
1
0
0
28
3
1
0
0
49
7
1
0
0
16
1
0
0
22
AU
45
1,484
3,924
5,408
90
133
128
698
404
48
64
64
336
194
520
1,632
2,152
24
383
24
383
407
8
4
0
235
25
8
4
1
407
62
26
729
755
11
6
3
163
9
5
3
225
37
388
425
Number of Affordable by Category
1L 2L
2 6
0 14
0 23
0 21
0 126
0 73
0 5
1 9
1 9
4 54
2 31
1 3
7 43
0 1
0 0
0 0
3 27
0 3
0 1
0 0
0 0
8 46
1 7
0 2
0 1
0 0
1 24
0 1
0 1
0 0
2 33
3L
3
7
9
8
46
26
6
6
6
27
15
3
46
1
0
0
28
3
•I
0
0
49
7
1
0
0
16
I
0
0
22
1M
5
0
0
0
0
0
0
2
2
7
4
1
14
I
0
0
7
1
1
D
0
15
2
0
0
0
2
0
0
0 .
3
2M
11
11
0
0
0
146
11
18
18
108
62
5
86
2
1
0
55
6
2
1
0
91
14
3
2
1
48
3
2
1
66
3M 1H 2H
626
300-IOOOAU
>1000AU
Total Hog
000
18 0 0
16 0 0
91 0 0
53 00
11 0 0
12 0 0
12 0 0
53 0 0
31 11 31
300-IOOOAU
>1000AU
Total Broiler
5 1 3
91 7 43
300-IOOOAU
>1000 AU
Total Wet Layer
' ~
1 0 1
1 0 0
000
56 3 27
603
1 0 " 1
1 0 0
000
97 8 46
15 1 7
300-IOOOAU
>1000AU
Total Dry Layer
202
1 0 1
1 00
32 1 24
1 0 1
1 0 1
1 0 0
43 2 33
300-IOOOAU
>1000 AU
Total Turkey
3H
3
0
0
0
0
0
6
6
6
27
15
3
46
1
0
0
28
3
1
0
0
49
7
1
0
0
16
1
0
0
22
All
45
32
1,483
3449
4,733
21
50
45
263
298
38
54
54
279
192
263
1,032
1,295
24
383
24
383
407
8
4
0
235
25
8
4
1
407
62
26
729
755
11
6
3
163
9
5
3
225
37
388
425
1L
0
2
1
1
3
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Number of Moderate bvCatenorv
2L 3L 1M
000
000
000
000
002
000
003
002
000
000
000
000
000
000
000
000
000
000
000
000
0 0.0
000
000
000
000
000
000
000
000
000
000
000
2M
0
0
28
46
42
252
0
0
b
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3M 1H 2H
000
00 0
300-IOOOAU
>1000 AU
Total Hog
14 0 14
0 0 23
0 0 21
0 0 126
0 0 73
0 1 5
0 I 9
0 1 9
0 4 54
02 0
300-IOOOAU
>1000 AU
Total Broiler
00 0
000
300-IOOOAU
>1000 AU
Total Wet Layer
000
000
00.0
000
000
000
00 0
000
000
000
300-IOOOAU
>IOOOAU
Total Dry Layer
000
000
000
000
000
000
000
000
300-IOOOAU
>IOOOAU
Total Turkey
3H
0
0
7
9
8
46
26
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
All
0
0
0
470
470
64
79
74
426
104
10
10
10
57
2
248
590
838
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-2(a)
Option 1
Estimating tbc Number of Farms
Under Each AchievablUty Criteria
Farm and Enterprise Stress
Farm Covotbv Catceorv
StettrMxiel
Mcdkral
Medium 2
Medium]
Land
UTJC2
Medtuml
Medhxa)
Ufjcl
Medtaal
Medina 3
topi
Medium!
Medium}
Utpl
MAReshu
Medhxal
Medium}
7
tgt
Vtal
MWRctlni
Medium 1
M1000AU
Total Veal
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
All
73
40
20
856
268
17
9
6
424
133
2
1
I
57
17
0
0
0
0
0
2
j
0
'8
3
173
1,766
1,939
2
1
4
12
0
0
1
0
0
0
0
0
0
0
0
0
8
12
20
0
0
0
0
0
0
0
0
No. of Distress bv Category (Farm Level)
1L 2L 3L 1M 2M 3M IH 2H 3H All
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 3
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
000
000
000
000
000
000
000
000
000
000
000
000
000
006
000
000
000
000
00 0
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
003
000
000
000
000
000
0 0 0
000
000
000
000
000
300-1000AU
>1000AU
Total Beef
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
300-1000AU
>1000AU
Total Veal
0 31 3
000
000
000
020
000
000
000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
12
0
0
0
0
0
0
0
0
0
0
0
0
12
12
0
0
0
0
0
0
0
p
0
0
0
0
0
0
0
0
0
0
0
35
0
0
0
2
0
. 0
0
No. of Distress by Cat. (Farm plus Enterprise)
1L 2L 3L 1M 2M 3M IH 2H 3H All
15 2 0 30 3
0 0 0 17 2
OOOOO
OOOOO
OOOOO
40071
00040
OOOOO
OOOOO
ooooo
00010
ooooo
ooooo
03006
0 0 0 0 '0
ooooo
ooooo
ooooo
ooooo
ooooo
10010
00010
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
ooooo
0 15 2
0 8 1
000
000
000
040
020
0 1 0
000
000
000
000
000
003
000
000
000
000
000
000
0 1 0
000
000
000
000
300-1000AU
=•1000 At
Total Beef
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
300-1000AU
=•1000 AU
Total Veal
0 31 3
000
000
000
020
000
000
000
0 68
0 28
0 0
0 0
0 0
0 16
0 7
0 1
0 0
0 0
0 2
0 1
0 0
0 12
0 0
0 0
0 0
0 0
0 0
0 0
0 2
0 1
0 0
0 0
0 0
126
12
138
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0 0
0 0
0 0
o o
0 0
o o
0 0
0 0
0
0
0
0 35
0 0
0 0
0 0
0 2
0 0
0 0
0 0
-------
Table D-2(a)
Option 1
Estimating the Number of Farms
Under Each Achievabillty Criteria
Farm and Enterprise Stress
Farm Count by Category
Sector/Model
FA Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Mediums '
Large 1
Dairy- Flush
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large i
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Dairy- Hose
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
IL
1
1
1
16
0
0
0
0
0
0
0
0
5
2
2
38
15
5
1
3
8
3
2
20
6
2
1
5
17
6
I
4
S
2
2
13
45
16
2
3
S
3
'2
7
6
2
1
2
51
IS
4
4
2L
0
0
0
S
0
0
0
0
0
0
0
0
4
1
1
72
11
4
1
6
6
2
' 1
38
5
2
1
9
12
4
I
7
4
I
1
24
32
12
2
6
6
2
1
13
5
2
1
3
36
13
3
7
3L
0
0
0
3,
0
0
0
0
0
0
0
0
1
1
1
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
I
1
1
10
13
5
1
3
2
1
0
6
2
1
0
1
14
5
I
3
1M
2
. 3
1
33
0
0
0
0
0
0
0
0
10
4
4
77
30
11
2
6
17
6
3
41
12
5
2
9
34
12
2
7
10
4
4
26
90
32
5
6
17
6
3
14
12
5
2
3
101
37
8
7
2M
0
0
0
10
0
0
0
0
0
o'
0
0
7
3
3
145
22
8
1
12
12
4
2
77
9
3
2
17
24
9
• 2
13
7
3
3
49
64
23
3
12
12
4
2
26
9
3
I
6
73
26
6
13
3M 1H 2H
0 I 0
0 1 0
0 1 0
5 16 5
000
000
000
000
000
000
000
000
300-IOOOAU
>1000AU
Total Heifer
354
1 2 1
1 2 1
63 38 72
8 15 11
354
0 1 1
536
586
232
1 2 1
33 20 38
365
1 2 2
1 1 1
759
9 17 12
364
1 1 1
647
354
1 2.1
1 2 1
21 13 24
25 45 32
9 16 12
1 2 2
536
586
232
1 2 1
11 7 13
365
1 22
I I 1
223
28 51 36
10 18 13
243
647
300-IOOOAU
>1000AU
Total Dairy
3H
0
0
0
3
0
0
0
0
0
0
0
0
1
1
1
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
1
1
1
10
13
5
1
3
2
1
0
6
2
1
0
1
14
5
1
3
All
4
7
3
97
0
0
0
0
0
0
0
0
13
97
110
41
IS
IS
569
120
43 •
7
47
67
24
13
301
50
18
8
68
134
48
10
52
41
15
IS
190
358
129
19
48
67
24
12
100
50
18
7
23
404
146
31
52
1,948
1,450
3,398
IL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
No. of Distress by Category (Farm Level)
2L 3L 1M
000
0 00
000
000
000
000
o o o-
000
00 0
000
000
000
000
0 0 0
000
000
000
000
000
000
00 0
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
0 ' 0 0
0 0,0
000
000
000
000
000
000
000
000
000
000
000
000
000
2M
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3M 1H 2H 3H
0100
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
300-IOOOAU
>1000AU
Total Heifer
0000
0000
0000
00 0 0
0000
0000
0000
0000
0000
0000
0000
0000
0 0.0 0
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0 ' 0 0 0
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
300-IOOOAU
>1000AU
Total Dairy
All
1
0
0
0
0
0
0
0
0
0
0
0
38
0
38
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
No. of Distress by Cat (Farm plus Enterprise)
IL
0
0
0
• o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0_
0
0
0
0
0
0
0
0
0
0
0
0
0
2L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
IM 2M
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 -0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
3M 1H 2H 3H
0100
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
300-IOOOAU
>IOOOAU
Total Heifer
0000
0000
0000
0000"
0000
0000
•0000
0000
0000
0 0 00
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0 0 00
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
300-IOOOAU
>1000AU
Total Dairy
All
1
0
0
0
0
0
0
0
0
0
0
0
38
0
38
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-2(a)
Optltra 1
Estimating the Number of Firms
Under Emch Aehlevablllty Criteria
Ftrm and Enterprise Stress
Farm Count by Catemry
StcUr/MKkl 1L 2L 3L 1M 2M 3M IH 2H 3H
H.CI Liquid (CFl«
MW Hilton
Mttiixal
MediuraZ
Medium}
Larjel
Urge 2
MARirls.
Mednml
Medium}
KtKl
larf.2
MWRtflM
Maltnt
Mcdrara2
MofcimJ
Larjel
Large 2
Medium!
Mtdhm)
Uriel
Utj.2
MWRtjlca
MaStxal
Medfam}
Lattcl
MARcttea
Mcdhml
Mtdmm3
Laael
Ucic2
Hip fit (fTIad)
MWRtjica
MeoAxnl
Mcdnra2
M«Sin3
L«te 2
Medttml
Medium 3
targe 2
1!ȣJ Enpon'.c
12 1
6 1
3 0
12 4
9 3
3 1
2 2
1 I
13 32
9 23
45 3
18 3
9 1
40 14
28 10
3 3
2 1
IS 38
11 27
24 2
12 2
7 1
29 10
21 7
1 0
I 1
0 0
S 19
5 14
55 4
22 3
11 2
51 18
37 13
1 0
1 1
0 0
5 12
CEJUtlcuCCFlod)
Larjel 3 4
UrjcJ
Largo 1
Larje2
llttl Liquid (CFOnt)
MWRcflM
Medium 1
M«Sum2
Meiurn}
Intel
Lntc2
Medina 1
Medium}
Uric 2
2 3
6 8
4 6
6 0
3 0
2 0
15 5
11 4
12 1
6 1
4 1
37 13
26 9
2 23
1 12
I 7
7 24
5 17
1 6
I 4
I 2
11 25
8 18
7 90
4 36
2 18
22 79
16 57
2 6
1 3
13 30
10 22
4 48
2 25
I 15
16 58
12 42
0 2
0 1
0 1
7 IS
5 11
8 110
4 44
2 21
29 102
21 74
0 2
0 1
0 1
4 9
2 6
2 4
6 12
4 9
1 12
1 6
0 4
9 31
6 22
2 25
I 13
I 8
21 74
15 53
2 3
2 2
1 1
9 14
IS 10
2 2
4 2
2 1
64 22
46 16
6 14
5 7
2 4
28 45
20 32
6 3
3 2
77 27
55 19
3 7
3 5
2 3
21 33
15 24
1 1
1 1
1 0
39 13
23 10
8 17
6 9
3 4
37 58
26 42
1 1
1 1
0 0
24 8
7 5
5 4
16 11
II 8
1 2
1 1
1 1
11 17
8 12
2 4
2 3
1 2
26 42
19 30
12 I
6 1
3 0
12 4
9 3
3 1
2 2
1 1
13 32
9 23
45 3
18 3
9 1
40 14
28 10
3 3
2 1
15 38
II 27
24 2
12 2
7 1
29 10
21 7
1 0
1 1
0 0
8 19
5 14
55 4
22 3
II 2
51 18
37 13
1 0
1 1
0 0
5 12
3 4
2 3
6 8
4 6
6 0
3 0
2 0
15 5
11 4
12 1
6 1
4 1
37 13
26 9
2
1
1
7
5
1
1
1
11
8
7
4
2
22
16
2
2
1
13
10
4
2
1
16
12
0
0
0
7
S
8
4
2
29
21
0
0
0
4
2
2
6
4
1
1
0
9
6
2
1
1
21
15
All
56
32
19
92
66
20
19
11
225
161
221
97
47
305
219
44
31
IS
267
192
118
66
39
223
160
7
7
4
135
97
269
119
58
394
283
7
5
3
84
60
35
25
78
56
29
16
10
118
84
61
34
20
284
203
No. of Distress by Cateeory (Farm Leyel)
1L 2L 3L 1M 2M 3M IH 2H 3H All
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
•0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
o'
0
0
0
0
0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 . 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0.
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0"
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0-
0
0
0
0
0
0
0
0
0
0
0
0
0
No.
of Distress by Cat (Farm Dim Enterprise)
1L 2L 3L 1M 2M 3M IH 2H 311 All
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o-
0
0
0
0
0
0
0
0
0
0
• 0
0
0
0
0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
.0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 . 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 '
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-2(a)
Option 1
Estimating the Number of Farms
Under Each Acbievabllity Criteria
Farm and Enterprise Stress
Farm Count by Category
. Sector/Model
Hogs Evaporate
CE Region (GF)
Large 1
Large 2
Broilers
SO Region
Medium 1
Medium 2
Medium 3
Large I
Large 2
. MA Region
Medium 1
Medium 2
Medium?
Large 1
Large 2
Layers (Wet)
SO Region
Medium 3
Large 1
Layers (Dry)
SO Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MW Region
Medium 1
Medium 2
Medium 3
Large!
Large 2
Turkeys
MA Region
Medium 1
Medium 2
Medium3
Large 1
MW Region
Medium I
Medium 2
Mediums
Large 1
1L 2L
4 5
3 3
2 14
I 23
1 21
3 I2S
2 72
2 5
2 8
2 8
7 50
4 29
1 2
10 40
3L 1M
3 7
2 5
7 4
9 3
S 2
46 7
26 4
6 3
6 3
6 3
27 15
15 8
3 2
46 2i
2M
9
7
27
46
42
250
145
10
16
16
100
58
5
79
3M 1H 2H
645
533
300-IOOOAU
>1000AU
Total Hog
14 2 14
18 1 23
16 1 21
51 3 125
53 2 72
11 2,5
12 2 8
12 2 8
53 7 50
31 4 29
300-IOOOAU
>1000AU
Total Broiler
5 1 2
91 10 40
300-IOOOAU
>1000AU
3H
3
2
7
9
8
46
26
6
6
6
27
15
3
46
Total Wet Layer
1 1
0 0
0 0
6 24
1 3
1 1
0 0
0 0
11 42
2 6
1 1
0 0
0 0
28 13
3 1
1 1
0 0
0 0
49 22
7 3
2
I
0
49
5
2
1
0
84
13
1 1 1
1 0 0
000
56 6 24
6 1 3
1 1 1
1 00
000
97 11 42
15 2 6
300-IOOOAU
>1000AU
I
0
0
28
3
1
0
0
49
7
Total Dry Layer
0 1
0 1
0 0
3 22
0 1
0 1
0 0
4 30
1 1
0 0
0 0
16 6
I 1
0 0
0 0
22 8
3
2
1
44
2
2
1
61
2 0 I
1 0 1
1 0 0
32 3 22
1 0 1
1 0 1
100
43 4 30
300-IOOOAU
>1000AU
Total Turkey
1
0
0
16
1
0
0
22
All
45
32
1,485
3,924
5,409
90
133
120
698
404
48 '
64
64
336
194
520
1,632
2,152
24
383
24
383
407
8
4
0
235
25
8
4
1
407
62
26
729
755
11
6
3
163
9
5
3
225
37
388
425
1L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
No. orDistress by Category (Farm Level)
2L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3L 1M 2M
000
000
000
000
000
000
000
000
000
000
000
000
000
000
3M 1H 2H
000
000
300-IOOOAU
>1000AU
Total Hog
000
000
000
030
000
000
.000
000
000
000
300-IOOOAU
>1000AU
Total Broiler
000
000
300-IOOOAU
>1000AU
Total Wet Layer
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
000
000
000
000
000
000
000
000
000
.000
000
000
000
000
000
0 00
000
000
000
300-IOOOAU
>1000AU
Total Dry Layer
0
.0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
000
000
000
000
000
000
000
000
000
000
0 0 0
000
000
000
000
300-IOOOAU
>1000 AU
Total Turkey
3H All
0 0
0 0
0
0
0
0 0
0 0
0 0
0 3
0 0
0 0
0 0
0 0
0 0
0 0
0
3
3
0 0
0 0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0
0
0
0 0
0 0
0 0
0 0
0 0
0 0
6 o
0 0
0
0
0
No. of Distress by Cat (Farm plus Enterprise)
IL 2L 3L 1M 2M 3M IH 2H 3H All
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
000
000
000
000
000
0 0 0
000
000
'0 00
000
000
000
000
000
000
0 00
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
0000
0000
300-IOOOAU
>1000AU
Total Hog
0000
0000
0000
0 0 30
0000
oooo
0000
0 0 0 0
0000
0000
300-IOOOAU
>1000AU
Total Broiler
0000
0000
300-IOOOAU
>1000AU
Total Wet Layer
0000
0 0 ' 0 0
0000
00 0 0
00 0 0
0000
0000
0000
0000
0000
300-IOOOAU
>1000AU
Total Dry Layer
0000
0000
0000
0000
0000
0000
0000
0000
300-IOOOAU
>1000AU
Total Turkey
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
3
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-2(b)
Option 2
Estimating tfae Number of Farms
Under Each Acblevabllity Criteri*
Farm and Enterprise Stress
Steun'Miu'el
Medium I
Medium 2
Medium!
Uqtcl
CEReffe*
Median 1
Medium 2
Medium!
Uriel
Medium 1
Medium 2
Uriel
UrjtJ
SOReit»
Medium 1
Medium!
M«!rjm3
Uriel
Uriel
Medium 1
Medium!
Medium]
Uriel
Ut|C
MWRettt*
Medium]
CER>t>«
Medium 1
Medium!
Medium J
fAReika
Medium 1
Medium 2
Medium]
SORetta
Medium 1
Medium 2
Medium.]
Medium 1
Medium 2
Medium]
lleHera
MWRtfle*
Medium 1
Medfem!
Medium]
Uriel
CERtfl"
Median 1
Medium 2
Medium]
Urpl
pBnnCi
lust bv Cateterv
IL 2L 3L 1M 2M 3M IH ZH 3H
IS
S
4
139
S
3
2
49
2
0
0
0
6
0
0
0
0
0
0
0
0
0
1
g
a
0
i
3
0
0
0
0
0
0
0
Q
e
0
0
0
30
4
2
0
2
4
2
17
2
1
1 29
I 16
0 8
4
2
1
52 24 277 104
36 26 10 72
1
0
0
46"
19
0
0
0
7
2
0
0
0
0
0
0
0
0
1
1
0
0
s
0
0
0
0
0
0
0
0
0
0
0
0
0
•
4
1
0
0
0
1
0
16
0 6
0 4
0 2
12 97
1] 3
0 1
0 0
0 0
2 12
2 0
Q 0
0 0
0 0
0 0
0 0
0 1
0 1
0 0
0 2
0 0
0 1
0 0
0 2
0 £
a o
0 0
0 1
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
3 61
0 8
0 3
0 0
0 3
0 S
0 3
4 34
1
1
91
38
0
0
0
14
5
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
9
1
0
0
1
2
1
31
3 15 2
1 8 1
1 4 1
1
1
0
47 139 52 24
52 5 36 26
1 3 1
020
0 1 0
23 49 46
26 2 19
000
000
000
367
402
000
000
000
000
000
000
000
000
0 1 1
001
3WMBOQAU
>IOOOAU
TelalBeef
000
000
0 1 0
030
000
000
000
000
000
A 0 0
000
000
000
000
000
000
3CO-1000AU
Total Veal
5 30 4
1 4 1
020
000
020
1 4 '1
020
8 17 16
0
0
0
12
13
0
0
0
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
4
AH
73
40
20
856
268
17
9
6
424
133
2
1
1
57
17
0
0
0
0
0
2
1
0
8
3
173
1,766
1,939
2
1
4
12
0
0
1
0
0
0
0
0
0
t
0
0
8
12
20
150
20
8
0
8
22
9
145
No. of Distress by Catecory (Farm Level)
IL 2L 3L 1M 2M 3M IH 2H 3H An
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 7
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
000002
000000
000001
000000
000000
000001
000020
000000
000000
000000
0 1 0 0 0, 0
000000
000000
2 0 14 3 6 7
200400
000000
000000
000000
000000
000000
000000
000000
000000
000001
000000
300-1000AU
>1000AU
Total Beef
000000
000000
000000
000000
000000
000000
000000
oooooo
000000
oooooo
oooooo
oooooo
oooooo
oooooo
oooooo
oooooo
300-1000AU
>ICOOAU
Total Veal
0 0 0 0 30 4
OOOOOO
oooooo
000000
000020
oooooo
oooooo
oooooo
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
1
0
0
1
2
0
0
0
2
1
1
40
7
0
0
0
0
0
1
0
0
2
1
10
49'
59
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
35
0
0
0
2
0
0
0
No. of Distress bv Cat (Farm talus Eaterprlse)
IL 2L 3L 1M 2M 3M IH 2H 3H
15 2 0 29 4
8 1 0 16 2
41081
00000
00000
31061
2 0 04 1
10021
00000
00000
0 0 0 1 0
00000
00000
0 7 2 0 14
00200
00000
00000
00000
00000
00000
00010
00010
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
00000
3 15 2
0 8 1
0 4 1
000
000
1 3 1
020
0 1 0
000
000
000
000
000
367
400
000
000
000
000
000
000
000
000
0 0 1
000
300-1000AU
>1000AU
Total Beef
000
000
000
000
000
000
000
000
000
000
0 00
0 00
000
000
000
300-IOOOAU
>1000 AU
Total Veal
0 30 4
'000
000
000
020
000
000
ooo
1
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0 '
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
All
71
37
18
0
0
17
9
6
0
0
2
1
1
40
7
0
0
0
0
0
2
1
0
2
1
167
49
216
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
35
0
0
0
2
0
0
0
-------
Table D-2(b)
Option 2
. Estimating the Number of Farms
Under Each AeUeyability Criteria
Farm and Enterprise Stress
Farm Count by Category
Sector/Model
PA Region
Medium 1
Medium!
Medium3
Large 1
SO Region
Medium I
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large 1
Dairy- Flush
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
. Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Lnrge 1
SO Region
Medium i
Medium 2
Medium 3
Large 1
MA Region
Medium 1
Medium 2
Medium 3
Large I
Dairy- Hose
PA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
CE Region
Medium 1
Medium 2
Medium 3
Large 1
SO Region
Medium 1
Medium 2
Medium 3
Urgel
MA Region
Medium 1
Medium 2
Medium 3
Large 1
1L
1
1
0
10
0 ,
0
0
0
0
0
0
0
4
I
1
24
12
4
1
2
6
2
1
16
6
2
I
3
13
5
I
2
4
1
1
8
0
35
13
2
2
6
2
1
5
6
2
1
, 1
39
14
3
2
2L
0
0
0
12
0
0
0
0
0
0
0
0
5
2
2
87
14
5
1
7
8
3
2
42
5
2
1
10
16
6
1
8
S
2
2
29
0
42
IS
2
7
8
3
1
14
S
2
I
3
48
17
4
8
3L
0
0
0
3
0
0
0
0
0
0
0
0
1
1
1
31
4
2
0
3
2
1
0
17
2
I
0
4'
5
2
0
3
1
1
1 '
10
0
13
5
1
3
2
I
0
6'
2
1
0
I
14
5
1
3
1M
1
2
1
20
0
0
0
0
0
0
0
0
7
3
3
48
24
9
1
5
13
5
2
33
11
4
2
7
26
9
2
5
7
3
3
16
0
71
25
4
5
13
S
2
11
11
4
2
2
77
28
6
5
2M
0
1
0
24
0
0
0
0
0
0
0
0
10
4
4
174
28
10
1
13
16
6
3
85
10
4
2
20
32
12
2
16
10
4
4
59
0
83
30
4
14
16
6
3
28
10
4
2
6
96
35
7
16
3M 1H 2H
0 1 0
0 1 0
000
5 10 12
000
000
000
000
000
000
000
0-0 0
300-1000AU
>1000AU
Total Heifer
345
1 1 2
1 1 2
63 24 87
8 12 14
345
0 I 1
527
568
223
1 1 2
33 16 42
365
1 2 2
1 1 1
7 3 10
9 13 16
356
1 1 I
628
345
1 1 2
1 1 2
21 8 29
000
25 35 42
9 13 15
1 2 2
527
568
223
1 1 1
11 5 14
365
1 2 2
1 1 1
2 1 3
28 39 48
10 14 17
234
628
300-1000AU
>1000AU
• Total Dairy
3H
0
0
0
3
0
0
0
0
0
0
0
0
1
1
1
31
4
2
0
3
2
1
0
17
2
1
0
4
5
2
0
3
1
1
1
10
0
13
5
1
3
2
1
0
6
2
1
0
1
14
5
1
3
All
4
7
3
97
0
0
0
0
0
0
0
0
230
242
472
41
15
15
569
120
43
7
47
67
24
13
301
50
18
8
68
, 134
48
10
52
41
15
15
190
0
358
129
19
48
67
24
12
100
50
18
7
23
404
146
31
52
1,948
1,450
3398
No. of Distress by Category (Farm Level)
1L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
,0
0
0
0
0
0
0
0
3L 1M 2M
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
. 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3M 1H 2H
0 1 0
000
000
5 0 12
000
000
000
000
000
000
000
000
300-1000AU
>1000AU
Total Heifer
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
0 0 ' 0
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
300-1000AU
»1000AU
Total Dairy
3H
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
b
0
. 0
0
0
0
0
0
0
0
0
0
0
AU
3
1
0
22
0
0
0
0
0
0
0
0
41
22
63
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
No. of Distress by Cat. (Farm plus Enterprise)
1L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2L
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3L 1M 2M 3M 1H 2H 3H
0
0
0
.3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
'0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
100100
000000
000000
0 0 5 0 12 3
000000
000000
000000
000000
0 0 0 00 0
000000
000000
000000
300-1000AU
>1000AU
Total Heifer
000000
000000
000000
000000
000000
000000
000000
000000
000000
000000
000000
0 0 0 00 0
000000
000000
000000
o' o o o o o
000000
000000
000000
000000
000000
°0 0 0 0 0 0
000000
000000
000000
000000
000000
000000
000000
000000
000000
0 0 0 0 ' 0 0
000000
000000
000000
000000
000000
000000
000000
000000
300-1000AU
>1000AU
Total Dairy
All
3
'l
0
22
0
0
0
0
0
0
0
0
41
22
63
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-2(b)
Option 2
Estlnullns the Number of Farms
Under Eack Aciieyablllty Criteria
Farm and Enterprise Stress
SKttr/MMltl • 1L :L 3L 1M 2M 3M IH 2H 3H
Htt»Ll4ttea(Gtn»d
Lattcl
UrpJ
CERtiJea (TTIad
Larjsl
Ur|c2
Moiltml
Mcd»a2
Medina]
Urjel
Urj.2
H.t»rH(GFC.at)
MWRttlo
Medium 1
Medium 2
Medina]
Urj.1
Lirje2
10
5
3
8
6
I
1
7
5
41
15
7
27
19
S
1
8
6
22
10
6
20
14
1
0
0
4
3
50
18
35
25
1
0
0
2
2
2
1
0
4
3
S
3
2
10
7
11
5
3
25
18
2 2 21 4 3
2 1 10 4 2
1 1 6 2 I
8 7 16 16 14
6 5 12 12 10
21352
11231
38 11 13 77 22
23 1 9 55 16
7 7 82 15 14
6 4 30 11 7
3 2 15 S 4
27 22 54 54 45
19 16 39 38 32
3 2 11 74
21242
46 13 16 91 27
33 10 11 65 19
4 2 21 8 5
2 1 12 4 3
20 16 39 39 33
14 12 28 28 24
10211
10121
00110
23 7 8 46 13
17 5 6 33 10
9 8 100 18 17
7 4 37 13 9
35 29 70 69 58
25 21 50 50 42
10211
10111
00010
14 4 5 29 8
10 3 4 21 6
42495
32364
00000
10 6 9 19 11
7 4 6 14 S
1 1 11 2 2
11521
10311
10 9 21 21 17
7 6 15 15 12
2 2 23 4 4
2 1 11 4 3
11622
25 21 50 50 42
18 15 36 36 30
10
5
3
8
6
1
1
7
5
41
15
7
27
19
5
I
8
6
10
6
20
14
1
0
0
4
3
50
18
35
25
1
0
0
2
2
2
1
0
4
3
5
3
2
10
7
11
5
3
25
18
2
2
1
8
6
2
2
1
38
28
7
6
3
27
19
3
2
46
33
4
2
20
14
1
1
0
23
17
9
7
35
25
1
1
0
14
10
4
3
0
10
7
1
1
1
10
7
2
1
1
25
18
2
1
.1
7
5
1
1
11
8
7
4
2
22
16
2
2
13
10
2
1
16
12
0
0
0
7
5
8
4
29
21
0
0
0
4
3
2
2
0
6
4
1
1
0
9
6
2
1
1
21
15
AH
56
32
19
92
66
20
19
11
225
161
221
97
47
305
219
44
31
15
267
192
66
39
223
160
7
7
4
135
97
269
119
58
394
283
7
5
1
84
60
35
25
0
78
56
29
16
10
118
84
61
34
20
284
203
No. ofDistress by Cateeorv (Farm Level)
1L 2L 3L 1M 2M 3M IH 2H 3H
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0.
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
23
17
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
7
5
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
46
33
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
13
10
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
9
0
0
0
0
0
0
0
0
0
0
g
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
o
0
0
0
g
0
0
0
0
0
0
0
23
17
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
g
0
0
0
g
0
0
0
0
0
0
0
7
5
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
All
0
0
t
0
0
Q
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
119
85
0
0
g
0
0
0
t
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
No.
ofDistress by Cat. (Farm plus Enterprise)
1L 2L 3L 1M 2M 3M IH 2H 3H
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
o
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
23
17
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
g
0
0
0
g
0
0
0
0
0
0
0
7
S
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
g
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
46
33
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0 ,
0
0
0
0
0
0
13
10
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
23
17
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
0
7
5
0
0
g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
An
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
g
0
0
0
0
0
0
II
119
85
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
Table D-2(n)
Option 1
Estimating the Number of Farms
Under Each Achlevablllty Criteria
Farm and Enterprise Stress
Sector/Model
Hogs Evaporate
CE Region (GF)
Large 1
Large 2
Broilers
SO Region
Medium 1
Medium 2
Mediums
Large I
Large 2
MA Region
Medium I
. Medium 2
Medium3
Large 1
Large 2
Layers (Wet)
SO Region
Mediums
Large 1
Farm Count by Category
IL 2L
2 6
2 4
2 14
1 23
I 21
3 126
2 73
1 5
1 9
1 9
4 54
2 31
1 3
7 43
3L
3
2
7
9
8
46
26
6
6
6
27
15
3
46
1M 2M
5 11
4 8
S 28
2 46
2 42
6 252
3 146
2 11
2 18
2 18
7 108
4 62
1 5
14 86
3M IH 2H
626
5! 2 4
300-1000AU
>1000AU
Total Hog
14 2 14
18 1 23
16 1 21
91 3 126
53 2 73
11 1 5
12 1 9
12 1 9
53 4 54
31 2 31
300-1000AU
>1000AU
Total Broiler
5 1 3
91 7 43
300-1000AU
>1000 AU
3H
3
2
7
9
8
46
26
6
6
6
27
15
3
46
Total Wet Layer
Layers (Dry)
SO Region
Medium 1
Medium 2
Medium 3
Large 1
Large 2
MW Region
Medium 1
Medium 2
Mediums
Large 1
Large 2
0 1
0 0
0 0
3 27
0 3
0 1
0 0
0 0
8 46
1 7
1
0
0
28
3
1
0
0
49
7
1 2
0 1
0 0
7 55
1 6
I 2
0 I
0 0,
15 91
2 14
1 0 1
1 0 0
0 00
56 3 27
603
I 0 1
1 0 0
000
97 8 46
IS 1 7
300-1000AU
=•1000 AU
1
0
0
28
3
1
0
0
49
7
Total Dry Layer
Turkeys
MA Region
Medium 1
Medium 2
Medium 3
Large 1
MW Region
Medium 1
Medium 2
Medium 3
Large 1
0 2
0 1
0 0
• 1 24
0 1
0 1
0 0
2 33
1
0
0
16
1
0
0
22
0 3
0 2
0 1
2 48
0 3
0 2
0 1
3 66
202
1 0 1
1 00
32 1 24
1 0 1
1 0 1
1 0 0
43 2 33
300-1000AU
=•1000 AU
Total Turkey
.
1
0
0
16
I
0
0
22
All
45
32
1,484
3,924
5,408
90
133
120
698
404
48
64
64
336
194
520
1,632
2,152
24
383
24
383
407
8
4
0
235
25
8
4
1
407
62
26
729
755
11
6
3
163
9
5
3
225
37
388
425
No. of Distress by Category (Farm Level)
'IL 2L 3L
00 0
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
0,0 0
000
1M 2M 3M IH 2H
0
0
3
2
0
6
0
0
0
0
0
0
0
0
0
p
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
00 00
0000
300-1000AU
>1000AU
Total Hog
0020
0010
0010
0030
0020
0000
0000
0000
0000
0000
300-1000AU
>1000AU
Total Broiler
0000
0000
300-1000AU
=-1000 AU
Total Wet Layer
•0000
0000
0000
0000
0000
0000
00 0 0
0000
0000
0000
300-1000AU
>1000AU
Total Dry Layer
0000
0000
0000
0000
0000
0000
0000
0000
300-1000AU
=-1000 AU
Total Turkey
3H
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
AU
p
0
0
204
204
5
4
1
8
2
0
0
0
0
0
10
10
19
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
No. of Distress by Cat. (Farm plus Enterprise)
IL 2L 3L IM 2M 3M IH 2H
0 00 0_ 0 0 00
00000000
300-1000AU
>IOOOAU
Total Hog
00030020
00,020010
0 0 0-0 0 01 0
00060030
00000020
00000000
O'OOO'QOOO
00000000
00000000
00000000
300-1000AU
>1000AU
Total Broiler
00000000
ooo'ooooo
300-1000AU
>UOOAU
Total Wet Layer
00000000
00000000
00000000
00000000
00000000
00000000
00000000
00000000
00000000
00000000
300-1000AU
>1000AU
Total Dry Layer
00000000
00000000
00000000
00000000
00000000
00000000
00000000
00000000
300-1000AU
>1000AU
Total Turkey
3H
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
All
0
0
0
204
204
5
4
1
8
2
10
10
19
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
-------
APPENDIX E
COST-EFFECTIVENESS ANALYSIS
As part of the process of setting effluent limitations guidelines (ELG) and developing standards,
EPA uses cost-effectiveness calculations to compare the efficiencies of regulatory options for removing
priority and nonconventional pollutants.' Although not required by the Clean Water Act, a cost-
effectiveness (C-E) analysis offers a useful metric to compare the efficiency of alternative regulatory
options in removing pollutants and to compare the proposed technology option with other regulatory
..alternatives that EPA considered.2
The American Society of Agricultural Engineers (ASAE) reports that the constituents present in
livestock and poultry manure include boron, cadmium, calcium, chlorine, copper, iron, lead, magnesium,
manganese, molybdenum, nickel, potassium, sodium, sulfur, zinc, nitrogen and phosphorus species, total
suspended solids, and pathogens. Of these pollutants, EPA's standard C-E analysis is suitable to analyze
only the removals of metals and metallic compounds. EPA's standard C-E analysis does not adequately
address removals of nutrients, total suspended solids, and pathogens. To account for the estimated
removal of nutrients and sediments under the final rule, the Agency developed an alternative approach to
evaluate the pollutant removal effectiveness for nutrients and sediment relative to the cost of these
pollutant removals. For this rule, EPA estimates the expected percentage reductions in pathogens from
agricultural runoff but does not compare these removals to the costs of the regulatory controls.
The C-E analysis conducted for this rule evaluates the cost-effectiveness of removing select
nonconventional and conventional pollutants, including nitrogen, phosphorus, and sediments. For this
analysis, sediments are used as a proxy for total suspended solids. This analysis compares the estimated
compliance cost per pound of pollutant removed to a recognized benchmark, such as EPA's benchmark
for conventional pollutants or other criteria for existing treatment, as reported hi available cost-
effectiveness studies. The research in this area has mostly been conducted at municipal facilities,
including publicly owned treatment works (POTWs) and wastewater treatment plants (WWTPs).
Additional information is available based on the effectiveness of various nonpoint source controls and
BMPs and other pollutant control technologies that are commonly used to control runoff from
agricultural lands. Benchmark estimates were used to evaluate the efficiency of the final rule in
removing a range of pollutants. This approach also allowed for an assessment of the types of
management practices that will be implemented to comply with the final regulations.
1 A list of priority ("toxic") and conventional pollutants is provided at 40 CFR Part 401. There are more
than 120 priority pollutants, including metals, pesticides, and organic and inorganic compounds. Conventional
pollutants include biological oxygen demand (BOD), total suspended solids (TSS), pH, fecal coliform bacteria, and
oil and grease. Nonconventional pollutants comprise all other pollutants, including nutrients; that is, they do not
include conventional and priority pollutants.
2EPA defined cost-effectiveness similarly for Phase II of the Storm Water rule (USEPA, 1999f) and
examined the incremental annualized cost of each pollution control option to the incremental pound of TSS
removed annually.
E-l
-------
The organization of this section is as follows. Section E.I provides an introduction and describes
the types and concentrations of pollutants found in animal manure and wastewater. Section E.2
summarizes EPA's estimated baseline loadings and removals of metals, nutrients, total suspended solids,
and pathogens from feedlot and land application areas, for selected regulatory alternatives. Section E.3
presents an analysis of the cost-effectiveness of loadings reductions of nutrients and total suspended
solids and compares the overall effectiveness of the final regulations to other options considered by EPA
during the development of this rulemaking. Section E.5 concludes with a discussion of EPA's analysis
that uses a standard C-E approach to analyze a subset of metallic compounds that are found in animal
manure and wastewater.
More detail on the environmental damages associated with livestock and poultry operations and
the pollutants in animal manure is provided in the Environmental Assessment (USEPA, 2000b) and the
Benefits Analysis (USEPA, 2002k). Section 5.4 of this report summarizes EPA's estimates of the loading
reductions for these pollutants. Additional information on EPA's estimated loadings and removals under
post-compliance conditions is provided in the Development Document (USEPA, 2000a) and also in the
Benefits Analysis (USEPA, 2002k).
E.1 POLLUTANTS OF CONCERN
E.I.I Introduction
Manure and wastewater from aiJmal feeding operations have the potential to contribute
pollutants such as nutrients (e.g., nitrogen and phosphorus), organic matter, sediments, pathogens, metals
and metallic compounds, hormones, antibiotics, and ammonia to the environment (USEPA, 2000g;
USDA and USEPA, 1999). Additional information on the pollutants in animal manure and on water
quality impairment and risks associated with manure discharge and runoff is provided in Section 5 of the
proposed rule preamble and in the Environmental Assessment (USEPA, 2000g).
National and local studies have confirmed the presence of manure pollutants in U.S. waters.
EPA's 1998 National Water Quality Inventory (USEPA, 2000h), prepared under section 305(b) of the
Clean Water Act, presents information on impaired water bodies based on reports from the states.
Agricultural operations, including animal feeding operations, are considered a significant source of water
pollution in the United States (USEPA, 2000h). As shown in Table E-l, the agricultural sector, including
crop production, pasture and range grazing, concentrated and confined animal feeding operations, and
aquaculture, is the leading contributor to identified water quality impairments in the nation's rivers and
streams, and the nation's lakes, ponds, and reservoirs. Agriculture is also identified as the fifth leading
contributor to identified water quality impairments in the nation's estuaries (USEPA, 2000h). These data
also confirm that water quality concerns tend to be greatest in areas where crops are intensively
cultivated and where livestock operations are concentrated.
Table E-l also lists the leading pollutants that impair surface water quality in the United States,
as identified in the 1998 Inventory. Livestock and poultry operations are a potential source of all of
these, but they are most commonly associated with nutrients, pathogens, oxygen-depleting substances,
and solids (siltation). Animal operations are also a potential source of other leading causes of water
quality impairment, such as metals and pesticides, and they can contribute to the growth of noxious
aquatic plants due to the discharge of excess nutrients. Animal operations can also contribute loadings of
E-2
-------
priority toxic organic chemicals and oil and grease, but most likely to a lesser extent than they contribute
to loadings of other leading pollutants.
Table E-2 presents additional summary statistics from the 1998 Inventory. These data indicate
that agriculture contributes to the impairment of at least 170,000 river miles, 2.4 million lake acres, and
almost 2,000 estuarine square miles. Animal feeding operations are a subset of the agriculture category.
The portion of impairment attributable to animal agriculture nationwide is unknown, because not all
states and tribes identified sources and tribes identify specific agricultural activities contributing to water
quality impacts on rivers and streams. States that specifically report potential water quality impairment
attributable to animal feeding operations in the 1998 Inventory are: Hawaii, Illinois, Kansas, Louisiana,
Michigan, Minnesota, Mississippi, Montana, Nebraska, Ohio, Oklahoma, Rhode Island, South Carolina,
Tennessee, Virginia, West Virginia, Wisconsin, and Wyoming. Impairment due specifically to land
application of manure is not reported. For rivers and streams, estimates from these states indicate that 16
percent of the total reported agricultural sector impairment is from the animal feeding operation industry
(including feedlots, animal holding areas, and other animal operations), and 17 percent of the agricultural
sector impairment is from both range and pasture grazing. For lakes, ponds, and reservoirs, estimates
from these states indicate that 4 percent of the total reported agricultural sector impairment is from the
animal feeding operation industry and 39 percent of the agricultural sector impairment is from both range
and pasture grazing.
£.1.2 Pollutant Concentrations in Animal Manure and Wastewater
Table E-3 lists the reported amounts of macro- and micro-nutrients in livestock and poultry
waste, along with documented levels of other inorganic and metallic constituents. As shown, the ASAE
reports that the constituents present hi livestock and poultry manure include: boron, cadmium, calcium,
chlorine, copper, iron, lead, magnesium, manganese, molybdenum, nickel, potassium, sodium, sulfur,
zinc, nitrogen and phosphorus species, total suspended solids (TSS), and pathogens (ASAE, 1993).
Other research conducted by various land grant universities reports that arsenic, selenium, and other
constituents are also present in some animal manures (NCSU, 1994; Sims, 1995).
Concentrations shown in Table E-3 are reported in pounds per 1,000 pounds of live animal
weight per day and vary by animal species. As shown in Table E-3, poultry manure typically has a
higher nutrient content than most other farm animal manure and wastewater. Actual nutrient values of
manure depend on many factors, including animal size, maturity, and species; health and diet of the
animals; and the feed composition and protein content of the ration fed (USDA, 1992). Additional
details on the constituents in animal manure are provided in the Environmental Assessment (USEPA,
2000b) and the Development Document (USEPA, 2000a).
E-3
-------
Table E-l. Leading Sources and Pollutants of Water Quality Impairment in the United States, 1998
Rank
Rivers & Streams
Lakes, Ponds, & Reservoirs
Estuaries
Sources ^
1
2
3
4
5
Agriculture (59%)
Hydromodification (20%)
Urban Runoff/storm sewers
(11%)
Municipal point sources (10%)
Resource extraction (9%)
Agriculture (31%)
Hydromodification (15%)
Urban runoff/storm sewers (12%)
.Municipal point sources (1 1%)
Atmospheric deposition (8%)
Municipal point sources
(28%)
Urban runoff/storm sewers
(28%)
Atmospheric deposition
(23%)
Industrial discharges (15%)
Agriculture (15%)
Pollutants "'
1
2
3
4
5
Siltation (38%)
Pathogens (36%)
Nutrients (29%)
Oxygen-depleting substances
(23%)
Metals (21%)
Nutrients (44%)
Metals (27%)
Siltation (15%)
Oxygen-depleting substances
(14%)
Suspended solids (10%)
Pathogens (47%)
Oxygen-depleting substances
(42%)
Metals (27%)
Nutrients (23%)
Thermal modifications (18%)
Source: USEPA, 2000h. Figure totals exceed 100 percent because water bodies may be impaired by more than one
source or pollutant.
"•"Fraction of impairment attributed to each source is shown in parentheses. For example, agriculture is listed as a
source of impairment in 59 percent of impaired river miles. The portion of "agricultural" impairment attributable to
animal waste (as compared to crop production, pasture grazing, range grazing, and aquaculture) is not specified.
'•'Percent impairment attributed to each pollutant is shown in parentheses. For example, siltation is listed as a cause
of impairment in 51 percent of impaired river miles.
Table E-2. Summary of Statistics from the National U.S. Water Quality Impairment Survey, 1998
Total Quantity in U.S.
Rivers
3,662,255 miles
Lakes, Ponds, and
Reservoirs
41. 6 million acres
Estuaries
90,465 square miles
Waters Assessed
23% of total
(840,402 miles)
42% of total
(17.4 million acres)
32% of total
(28,687 square miles)
Quantity Impaired by AH
Sources
35% of assessed
(291,263 miles)
45% of assessed
(7.9 million acres)
44% of assessed
(12,482 square miles)
Quantity Impaired by
Agriculture ^
59% of impaired
(170,750 miles)
31% of impaired
(2,417,801 acres)
15% of impaired
(1,827 square miles)
Source: USEPA, 2000h.
•'AFOs are a subset of the agriculture category. Summaries of impairment by non-agricultural sources are not
presented here.
E-4
-------
Table E-3. Nutrients, Metals, and Pathogens in Livestock and Poultry Manures
Constituent
Mass of animal
Manure (wet basis)
Urine
Density (Ibs/ft3)
Total Solids
Volatile Solids
BOD (5-day)
COD (5-day)
PH
Nitrogen (Total Kjeldahl)
Nitrogen (Ammonia)
Phosphorus (Total)
Orthophosphorus
Potassium
Calcium
Magnesium
Sulfur
Sodium
Chloride
Iron
Manganese
Boron
Molybdenum
Zinc
Copper
Cadmium
Nickel
Sector
Beef
Dairy
Veal
Hog
Broiler
Layer
Turkey
(average pounds per 1 ,000 pounds live animal weight per day)
793.7
58
.- 18
1000
8.5
7.2
1.6
7.8
7.0
3.40e-01
8.60e-02
9.2e-02
3.0e-02
2.1e-01
1.4e-01
4.9e-02
4.5e-02
3.0e-02
7.8e-03
1.2e-03
8.8e-04
4.2e-05
l.le-03
3.1e-04
1410.9
86
26
990
12.0
10.0
1.6
11.0
7.0
4.50e-01
7.90e-02
9.4e-02
6.1e-02
2.9e-01
1.6e-01
7.1e-02
5.1e-02
5.2e-02
1.3e-01
1.2er02
1.9e-03
7.1e-04
7.4e-05
1.8e-03
4.5e-04
3.0e-06
2.8e-04
200.6
62
1000
5.2
2.3
1.7
5.3
8.1
2.70e-01
1.20e-01
6.6e-02
2.8e-01
5.9e-02
3.3e-02
8.9e-02
3.3e-04
1.3e-02
4.8e-05
134.5
84
39
990
11.0
8.5
3.1
8.4
7.5
5.20e-01
2.90e-01
1.8e-01
1.2e-01
2.9e-01
3.3e-01
7.0e-02
7.6e-02
6.7e-02
2.6e-01
1.6e-02
1.9e-03
3.1e-03
2.8e-05
5.0e-03
1.2e-03
2.76-05
992.1
85
1000
22.0
17.0
16.0
1.10e+00
3.0e-01
4.0e-01
4.1e-01
1.5e-01
8.1e-02
1.5e-01
3.6e-03
9.8e-04
4.0
64
970
16.0
12.0
3.3
11.0
6.9
8.40e-01
2.10e-01
3.0e-01
9.0e-02
3.0e-01
1.3e+00
1.4e-01
1.4e-01
l.Oe-01
5.6e-01
6.0e-02
l.Oe-03
1.8e-03
3.0e-04
1.9e-02
8.3e-04
3.8e-05
2.5e-04
4.0
47
... 1000
12.0
9.1
2.1
9.3
6.20e-01
8.00e-02
2.3e-01
2.4e-01
6.3e-01
7.3e-02
6.6e-02
7.5e-02
2.4e-03
1.5e-02
7.1e-04
E-5
-------
Table E-3. Nutrients, Metals, and Pathogens in Livestock and Poultry Manures (continued)
Constituent
Lead
Arsenic
Total coliform
bacteria (colonies)
Fecal coliform
bacteria (colonies)
Fecal streptococcus
bacteria (colonies)
Sector
Beef
Dairy
Veal
Hog
Broiler
Layer
Turkey
(average pounds per 1,000 pounds live animal weight per day)
na
29
13
14
na
500
7.2
42
na
8.4e-05
6.9e-04
21
8
240
4.8e-04
7.4e-04
5.5e-06
50
3.4
7.4
na
0.62
Source: ASAE, 1993. Arsenic values are from NCSU, 1994. Converted from reported (lb./yr./1,000 Ib. animal
weight) values of 0.002 (layers), 0.176 (broilers), and 0.252 (hogs). All values are in pounds unless otherwise
noted.
E.2 ESTIMATED POLLUTANT REMOVALS
For this analysis, EPA has estimated the expected reduction of selected pollutants for each of the
regulatory options considered. These estimates measure the amounts of nutrients, sediments, and metals
originating from animal production areas that are removed under a post-regulation scenario (as compared
to a baseline scenario) and do not reach U.S. waters. Additional information on EPA's estimated
loadings and removals under post-compliance conditions is provided in the Development Document
(USEPA, 2002) and the Benefits Analysis (USEPA, 2002k) that support the rulemaking.
USDA estimates that in 1997 manure generation from all livestock and poultry production
totaled 1.1 billion tons, of which about one-half (0.5 billion tons of manure) was generated by operations
with confined animals, using an approach described in Kellogg et al. (2000,2002) and Lander (1998).3
More information on these estimates are presented in the rulemaking record. Table E-4 shows these
estimates broken out by major subcategory.
Of this total, USDA estimates that operations that confine livestock and poultry animals generate
about 500 million tons of manure annually (as excreted). This compares to EPA estimates of about 0.15
billion tons (wet weight) of human sanitary waste produced annually in the United States, assuming a
U.S. population of 285 million and an average waste generation of about 0.518 tons per person per year.
By this estimate, all confined animals generate 3 times more raw waste that is generated by humans in the
United States. EPA is regulating close to 60 percent of all manure generated by operations that confine
animals. Of the estimated amount of nutrients generated by these operations that is in excess of cropland
USDA's estimates do not include manure generated from other animal agricultural operations, such as
sheep and lamb, goats, horses, and other miscellaneous animal species.
E-6
-------
needs, EPA's regulation will account for nearly 70 percent of manure generated by these operations. For
more information on EPA's human waste estimates, see information in the record (USEPA, 2002m).4
Section 5.4 of this report summarizes EPA's estimates of the loading reductions for these
pollutants. The series of summary tables in that section show EPA's aggregated estimates of loadings
from all contributions, including the land application area and the production area. Results are shown for
operations with more than 1,000 AU and a subset of affected operations with between 300 and 1,000 AU
that are defined as CAFOs under the existing NPDES regulations. Post-regulatory conditions are
modeled by EPA and expressed in terms of baseline loadings and reductions compared to baseline
conditions (pre- versus post-regulatory). Loadings and reductions are modeled for total nitrogen, total
phosphorus, and TSS. Under this approach, EPA also simulates loadings and reductions for six selected
metallic
-------
loading reductions adjusted by the delivery rates (expressing the change between edge-of-field and at-
stream concentrations) to determine the at-stream loading reductions for use in the cost-effectiveness
analysis. This allows EPA to differentiate the cost-effectiveness among the four broad sector groups.
E3 COST-EFFECTIVENESS ANALYSIS: NUTRIENTS AND SEDIMENTS
For this analysis, EPA estimated average cost-effectiveness values that reflect the increment
between no revisions to the current regulations and the final regulatory requirements in the final
regulations. Estimates reflect the cost-effectiveness of removing selected non-conventional and
conventional pollutants, including nitrogen, phosphorus, and sediments. For this analysis, sediments are
used as a proxy for TSS. All costs are expressed in pre-fpc 2001 dollars. Estimated compliance costs
used to calculate the cost-effectiveness of the final regulations include total estimated costs to CAFOs
and costs to the permitting authority.
This analysis does not follow the methodological approach of a standard C-E analysis. Instead, it
compares the estimated compliance cost per pound of pollutant removed to a recognized benchmark,
such as EPA's benchmark for conventional pollutants or other criteria for existing treatment, as reported
in available cost-effectiveness studies. A review of this literature is provided in Section E.3.1 and is
based on an assessment of the types of management practices that would be implemented to comply with
the final regulations. Section E.3.2 presents the results of EPA's analysis and compares these results
obtained for the final regulations with other regulatory alternatives considered by EPA during the
development of this rulemaking.
E.3.1 Review of Literature
To evaluate the cost per pound removal of nutrients and sediments, EPA reviewed the available
information on pollutant removal costs for nutrients and sediments. This research can be broadly
grouped according to estimates derived for industrial point sources and various nonpoint sources,
including agricultural operations. In general, the point source research provides information on
technology and retrofitting costs—and in some cases, cost per pound of pollutant removed—at municipal
facilities, including POTWs and WWTPs. This research differs from other cost-effectiveness estimates,
because it uses actual cost data collected at a particular facility undergoing an upgrade. Other cost-
effectiveness information is available based on the effectiveness of various nonpoint source controls and
best management practices (BMPs) and other pollutant control technologies that are commonly used to
control runoff from agricultural lands. Typically, this information uses a modeling approach and
simulates costs for a representative facility.
For this analysis, EPA assumes the following benchmark values to evaluate cost-effectiveness.
For nitrogen, EPA uses a cost-effectiveness benchmark established by the Agency's Chesapeake Bay
Program to assess the costs to WWTPs to implement system retrofits to achieve biological nutrient
removal. This nitrogen benchmark estimate is approximately $4 per pound of nitrogen removed. For
phosphorus, EPA assumes a cost-effectiveness benchmark of roughly $10 per pound based on a review of
values reported in the agricultural research of the costs to remove phosphorus using various nonpoint
source controls and management practices. For sediments, EPA uses a POTW benchmark for
conventional pollutants removed (total suspended solids and biological oxygen demand) of about $0.73
per pound. More information on these benchmark values is as follows.
E-8
-------
Table E-4 summarizes the cost-effectiveness values for nutrients and sediments reported in the
studies that EPA reviewed for its analysis. A wide range of costs per pound of pollutant removed is
estimated by those studies where estimates span both point sources and nonpoint sources, as well as
those where estimates span a range of municipal, urban, and agricultural practices. Annualized costs also
vary widely depending on various factors, such as the type of treatment system or practice evaluated; and
whether the costs are evaluated as a retrofit to an existing operation or as construction of a new facility.
A series of case studies were compiled by researchers at Virginia Tech, who evaluated total costs
for biological nutrient removal (BNR) retrofits at WWTPs throughout the Chesapeake Bay watershed
(Randall et al., 1999). These case studies were compiled to estimate a range of costs per pound of
nitrogen removed at these facilities. This research was commissioned by EPA's Chesapeake Bay
Program and was conducted with the assistance of the Maryland Department of the Environment and the
Public Utilities Division of Anne Arundel County. As part of this work, BNR retrofit costs were
estimated for 51 WWTPs located in Maryland, Pennsylvania, Virginia, and New York. The final report
hi this series compares these costs to the projected change in effluent total nitrogen concentrations,
assuming that the influent flow meets the design or projected flow after 20 years (Randall et al., 1999).
As shown in Table E-4, this study concludes that the costs of nitrogen removal are very plant-specific,
with the costs per pound of addition nitrogen removal ranging from $0.79 per pound to $5.92 per pound
(Randall et al., 1999).5 The range of these estimates is comparatively narrow given that the study
examines a single retrofit category across similar facilities. The time frame for this analysis ranges from
1995 to 1998 according to the available case study data for each WWTP. A 20-year capital renewal
period is assumed; interest and inflation rates of 6 and 3 percent, respectively, are used (Randall, 2000).
The primary emphasis in this study is nitrogen, since the cost to upgrade for phosphorus removal is both
configuration-and site-specific (Randall, 2000).6
Based on this analysis and other data from the Maryland Department of the Environment, EPA's
Chesapeake Bay Program Office has derived a cost-effectiveness value for BNR of $3.64 per pound of
nitrogen removed, as shown in Table E-4 (Wiedeman, 1998). Based on this information and the results
of the Randall study, EPA's cost-effectiveness analysis assumes that an estimated cost to remove
nitrogen of less than $4 per pound demonstrates cost-effectiveness.
A number of other studies have been conducted to assess the cost-effectiveness of various state-
level programs to reduce nutrients in Wisconsin (NEWWT, 1994), Vermont (LCBP, 2000), and North
Carolina (Tippett and Dodd, 1995). In Wisconsin, a series of studies were conducted to compare the
cost-effectiveness of point and nonpoint source controls across 41 subwatersheds in the Fox-Wolf
watershed (NEWWT, 1994). These studies estimated the cost of reducing phosphorus and TSS loads
from municipal treatment facilities and agricultural sources. Baseline projections were compared to
necessary reductions to meet future water quality objectives, as mandated by that State's current
regulations. The base year for the analysis is 1990. Phosphorus removal costs for rural sources are
5The costs per pound of additional nitrogen removed were flow-weighted to determine the average for each
state and for all plants evaluated.
A
6For conventional plug-flow activated sludge configurations, all that is required for phosphorus removal is
the installation of relatively low-cost baffles and mixers; for oxidation ditches, the addition of an anaerobic reactor
separate from the ditch is needed (Randall, 2000).
E-9
-------
estimated at $9.64 per pound, whereas municipal treatment facilities are associated with an average
annual cost of $165 per pound of phosphorus removed (NEWWT, 1994).
The Lake Champlain Basin Program (LCBP) conducted a similar study to evaluate costs to meet
Vermont's water quality goals. The study estimated phosphorus removal costs ranging from $270 to
more than $1,000 per pound at a large municipal facility, compared to $440 to $544 per pound of
phosphorus removed using agricultural BMPs (LCBP, 2000). The base year for this analysis is 1995.
Another study by Research Triangle Institute assessed the cost-effectiveness of agricultural BMPs for
North Carolina's nutrient trading program. Estimated costs ranged from $2.72 to $135.17 per pound of
phosphorus removed using anaerobic lagoons, and $0.36 to $34.27 per pound of phosphorus removed for
land application practices (Tippett and Dodd, 1995). Estimated costs reflect the wide range of costs
associated with land application, given preexisting practices at different types of operations. Costs
summarized for this analysis span 1985 to 1994. Estimated values are shown in Table E-4. Observations
by researchers at Virginia Tech who estimated removal costs for nitrogen at WWTPs conclude that it will
cost about the same to remove a pound of phosphorus as it costs to remove a pound of nitrogen, if
removing only one nutrient. If the facility is upgraded to remove both nitrogen and phosphorus, the cost
typically will be only slightly more than the cost to remove nitrogen alone (Randall, 2000).
For this analysis, EPA assumes a benchmark of $10 per pound to remove phosphorus. This
estimate is a conservative estimate given the range of estimates in the literature (Table E-4). Since the
2001 Proposal, EPA has obtained additional research estimates that further justify use of the benchmark
value for phosphorus. Faeth (2000) measures the cost per pound of phosphorus removed for controls
under different policy scenarios for both point source and agricultural conservation practices.7 Estimates
are based on three case studies: Minnesota River, Saginaw Bay, and Rock River. For point sources,
Faeth estimates a range of costs from $10.40 to $23.90 per pound of phosphorus removed, averaging
about $18 per pound removed. Estimates for agricultural sources range from $9.50 to $16.30 per pound
of phosphorus removed, averaging $ 10.50 per pound removed.
EPA's benchmark to compare the potential costs per pound of sediments removed is the cost
reasonableness test the Agency established in developing technology-based effluent limits for
conventional pollutants (see 51 FR 24982). This benchmark measures the cost per pound of TSS and
BOD removed for an "average" POTW with a flow of 2.26 million gallons per day (USGPO, 1986).8
Indexed to 2001 dollars, these costs are about $0.73 per pound of TSS and BOD removed. EPA used this
benchmark to evaluate the estimated cost per pound of TSS removed by municipalities in a recent EPA
rulemaking, which estimated the range of costs for stormwater controls to be between $0.04 to $0.18 per
pound of TSS removed (USEPA, 1999'f). The Northeast Wisconsin Water for Tomorrow studies
estimate average cost to reduce TSS of $0.008 per pound removed from rural land and $4.61 per pound
removed at municipal treatment faculties (NEWWT, 1994).
7 Point source performance requirements and conventional subsidies for agriculturalJBMPs, respectively.
8The technologies used for secondary treatment at POTWs removes both TSS and BOD at the same time.
Estimating only the tons of TSS removed from secondary treatment is not possible.
E-10
-------
Table E-4. Summary of Pollutant Removal Cost Estimates and Benchmarks
Type of
Pollutant
Total
Nitrogen
era)
Total
Phosphorus
(TP)
Total
Suspended
Solids
(TSS)
Low
Estimate
High
Estimate
($ per pound removed)
$0.79
-
$0.91
$0.09
$5.76
$10.38
$9.64
$270.34
$439.99
:$2.72
$0.36
$0.01
.
$0.04
$5.92
$3.64
$9.53
$2.18
$16.29
$23.89
$165.00
$1,179.35
$544.32
$135.17
$34.27
$4.61
$0.25 '
$0.18
Treatment
Type
WWTPs
WWTPs
Ag lagoon
Ag land application
Conventional subsidies for
agricultural BMPs
PS performance requirements
Ag (low) to municipal (high)
Large PS facility (0.2 mg/L)
Agricultural BMPs
Ag lagoon
Ag land application
Ag.(low) to municipal (high)
POTWs(BODandTSS)
Urban Stormwater Controls
Literature
Sources
Randall et al, 1999
Wiedeman, 2000
Tippett and Dodd, 1995 .
Tippett and Dodd, 1995
Faeth, 2000
Faeth, 2000
NEWWT, 1994
LCBP, 1995
LCBP, 1995
Tippett and Dodd, 1995
Tippett and Dodd, 1995
NEWWT, 1994
USGPO, 1986
USEPA, 1999f
"'TSS and BOD removals (1976 dollars). Indexed to 2001 dollars, costs are about $70 per pound removed.
Full citations are provided in references. Time frames of dollar values shown vary by source (shown below).
Notes summarize timeframe of analysis, study assumptions (where available), and range of sources/treatment.
Faeth. P. (2000'): Case-studies in Minnesota River, Saginaw Bay, Rock River. Study include estimates under
permit trading scenarios (not shown in table).
Randall et al. (1999): 1995-1998; 6% interest and 20-year capital renewal; BNR retrofits at WWTP only.
NEWWT (1994): 5% interest and 20-year capital renewal; low bound is agricultural BMPs and high bound is
municipal treatment facilities.
Tippett and Dodd (1995): No discount rate was applied, and annual cost equals total lifetime costs adjusted by
design life (varies by practice); "Ag lagoon" signifies aerobic lagoon and "Ag land" is land application (both with
varying increasing overapplication of land applied manure under preexisting conditions). Cost-effectiveness values
that assume direct discharge of animal wastes are not shown.
LCBP (2000): 1995: No discount rate was applied, and annual cost equals total lifetime costs adjusted by design life
(varies by practice); low bound is agricultural BMPs and high bound is larger industrial point sources.
E-ll
-------
£3.2 Cost-Effectiveness Results
Table E-5 shows the results of EPA's cost-effectiveness analysis for across all subcategories
under both Option 1 and Option 2. Results are shown in terms of the average cost-effectiveness,
reflecting the increment between no regulation and these two regulatory options. For this rule, EPA
estimates an average cost-effectiveness of nutrient removal ranging from about $2 per pound to $3 per
pound of nitrogen removed (pre-tax, 2001 dollars) between Option 1 and Option 2. For phosphorus
removal, removal costs range from about $6 per pound to $7 per pound of phosphorus removed under
these two options. All values are based on approximated "at stream" concentrations.
EPA's estimated cost-effectiveness to remove nitrogen falls within the estimated range of
removal costs and is less than the average benchmark value assumed for this rule. For phosphorus, EPA
assumed a cost-effectiveness benchmark of roughly $10 per pound based on a review of values reported
in the agricultural research of the costs to remove phosphorus using various nonpoint source controls and
management practices. EPA's estimated cost-effectiveness to remove phosphorus under this rule also
falls below the $10 per pound benchmark value, indicating that the requirements are cost-effective. This
is particularly true when compared to the reported cost to remove phosphorus at industrial point source
dischargers, where reported average costs are twice that for agricultural sources and often exceed $100
per pound of phosphorus removed. For sediments, EPA's estimated per-pound removal cost is low
compared to EPA's POTW benchmark for conventional pollutants for some options. Based on these
results, EPA concludes that these regulatory options demonstrate cost-effectiveness.
Table E-5 shows the re,7ults of EPA's analysis by major subcategory groupings (cattle, dairy,
hogs, poultry) for both Option 1 and Option 2. As shown, removal costs vary by commodity sector. In
general, the cost to remove a pound of nitrogen or phosphorus is greatest in the hog and dairy sectors.
Given estimates of generally lower removal costs for nutrients, Option 1 may be considered more
cost-effective than Option 2 (where removal costs are estimated to be higher). See Table E-5 and E-6.
Results shown in these tables also present the incremental cost-effectiveness of Option 2 relative to
Option 1. Incremental cost-effectiveness is the appropriate measure for comparing one regulatory
alternative to another for the same subcategory. In general, the lower the incremental C-E value, the
more cost-efficient the regulatory option is in removing pollutants. As shown in the table, Option 1 may
be considered more cost-efficient relative to Option 2 since the incremental cost between Option 2 from
Option 1 is higher than that the average cost-effectiveness for Option 1.
The results presented here do not show the average or incremental cost-effectiveness estimates
for other regulatory options considered by EPA during the development of this rulemaking, including
Option 3 and Option 5. This analysis was provided in the Proposal EA evaluating these options,
indicating that these alternative options were less cost-effective and less cost-efficient than both Option 1
or Option 2. These general conclusions should hold for the final rule analysis as well. For the final rule,
the total costs of Options 3 and 5 are higher than that estimated for Option 2 (see cost estimates provided
in Table 3.5 in Section 3 of this report); also EPA does not expect a corresponding substantial change in
the estimated pollutant reductions for these options, as compared to Option 2 (see summary tables
presented in Section 5.4 of this report). Given generally higher costs and roughly similar reductions for
these alternative options, as compared to Option 2, these options are likely less cost-effective and less
cost-efficient at removing nutrients than both Option 1 and Option 2.
E-12
-------
Table E-6 shows the results of EPA's cost-effectiveness analysis of removing sediments. Under
Option 2, EPA estimates the cost-effectiveness of sediment removal at $0.30 per pound (pre-tax, 2001
dollars). This estimated per-pound removal cost is low compared to EPA's POTW benchmark for
conventional pollutants of about $0.70 per pound of TSS and BOD removed. Sediment removal costs
under Option 1, however, are considerably greater than for Option 2 (because of much lower estimated
removals for that option, see summary tables in Section 5.4). The average cost-effectiveness for this
option is estimated at nearly $2.70 per pound of sediment removed (thus exceeding EPA's benchmark).
Table E-S. Cost-Effectiveness Results: Nutrients ($2001), Option 1 & Option 2
Option/
Scenario
np_A0i
Cost "
(Smill.)
Nitrogen
Removals
(mill. Ibs.)
Avg. C-E
Increm. C-E
($/lb. removed)
Phosphorus
Removals
(mill. Ibs.)
Avg. C-E
Increm.
C-E
($/lb. removed)
Option 1: All Subcategories
>1000A
300-1,000 AU
>300 AU
$115.5
$19.1
$134.5
72.6
4.8
77.4
$1.59
$3.98
$1.74
—
—
—
20.8
1.3
22.1
$5.55
$14.28
$6.07
--
• _.
Option 1: Individual Sectors
Cattle "
Dairy
Hog
Poultry "
$22.3
$71.0
$8.8
$32.4
36.7
15.3
0.3
25.0
$0.61
$4.65
$32.92
$1.30
—
—
—
—
11.9
3.5
0.1
6.7
$1.87
$20.40
$105.26
$4.83
—
—
—
—
Option 2: All Subcategories
>1000 A
300-1,000 AU
>300 AU
$278.3
$37.7
$316.0
83.4
6.0
89.5
$3.34
$6.25
$3.53
$15.00
$15.11
$15.02
42.9
4.1
47.0
$7.03
$10.93
$7.34
$8.67
$8.80
$8.69
Option 2: Individual Sectors
Cattle "
Dairy
Hog
Poultry "
$93.9
$150.2
$33.0
$38.9
39.0
16J
4.0
30.3
$2.41
$9.32
$8.18
$1.28
$32.14
$94.02
$6.43
$1.22
17.8
5.9
7.3
16.3
$5.29
$26.00
$8.04
$2.54
$12.20
$34.51
$6.02
$0.75
Source: USEPA. "Incremental C-E" measures Option 2 as incremental to Option 1.
M Costs are pre-tax and indexed to 2001 dollars using the Construction Cost Index (ENR, 2000,2002).
w "Cattle" includes beef, heifer, and veal operations. "Poultry" includes broiler, egg, and turkey operations.
E-13
-------
Tahlo F-fi Cost-Effectiveness Results: Sediments ($2001), Option 1 & Option 2
Option/
Scenario
Total
Cosf
(Smill.)
Sediments
Removed
(million Ibs.)
Average
Cost-Effectiveness
Incremental
Cost-Effectiveness
(average $ per pound removed)
Option 1: All Subcategories
>1000 AU
300-1,000 AU
>300 AU
• $115.5
$19.1
$134.5
1,327.8
7.1
1,334.9
$0.09
$2.69
$0.10
Option 2: All Subcategories
>1000 AU
300-1,000 AU
>300 AU
$278.3
$37.7
$316.0
1,626.6
85.3
1,711.9
$0.17
$0.44
$0.18
—
—
—
$0,54
$0.24
$0.48
Source: USEPA.
"Costs are pre-tax and indexed to 2001 dollars using the Construction Cost Index (ENR, 2000,2002).
E.4 COST-EFFECTIVENESS ANALYSIS: TOXIC POLLUTANTS
EPA decided not to conduct a more traditional C-E analysis for selected toxic pollutants for the
final regulations, given that these compounds are present in trace amounts in animal manure (see Table
E-3). Nevertheless, this section provides a brief summary of EPA estimates of the weighted pound-
equivalent removals for selected toxic pollutants. These estimates provide a means to evaluate the
appropriateness of whether EPA should conduct a more traditional C-E analysis for selected toxic
pollutant removals given that the principal pollutants of concern for this rule are nutrients and sediments.
This analysis follows the guidelines of the standard C-E analysis commonly used by EPA to
compare the efficiency of regulatory options for effluent guidelines in removing priority and non-
conventional pollutants. More detailed information is provided in the Proposal EA (USEPA, 2001a).
EPA's standard C-E analysis evaluates cost-effectiveness as the incremental and average annualized cost
of a pollution control option in an industry (or industry subcategory) per incremental and total pound
equivalent of pollutant (i.e., pound of pollutant adjusted for toxicity) removed by that control option.
This analysis involves the following seven steps:
1. Determine the pollutants of concern (priority or other pollutants).
2. Estimate relative toxic weights for these pollutants.
3. Define the regulatory pollution control options.
4. Calculate pollutant removals for each control option.
5. Determine the total annualized cost for each control option.
6. Calculate cost-effectiveness values (and adjust to 1981 dollars).
7. Compare cost-effectiveness values.
For this discussion, EPA addresses only steps 1 and 2. However, Section 5.3 of this report
summarizes how the pollutant loadings estimated for the final regulations are calculated for each animal
E-14
-------
sector under each regulatory option for comparison with baseline loadings (steps 3 and 4). For more
information, see the Development Document (USEPA, 2002). Total costs of the rule are presented in
Section 3.3 (step 5).
For this C-E analysis, EPA identified six toxic pollutants of concern (step 1), including arsenic,
zinc, copper, cadmium, nickel, and lead. Factors considered in selecting these pollutants included
toxicity, frequency of occurrence in wastestream effluent, and amount of pollutant in the waste stream
(USEPA, 2002). As shown in Table E-3, this is a subset of all the toxic compounds reported to be
present in farm animal manures (which vary by animal type). Therefore, the cost-effectiveness results
presented here are conservative (i.e., a higher per-pound removal value is estimated than would be the
case if all metals were considered in this analysis).
In C-E analyses, pollutant removals are measured in toxicity normalized units called "pounds-
equivalent," where the pounds-equivalent removed for a particular pollutant is determined by multiplying
the number of pounds of a pollutant removed by each option by a toxocity weighting factor (TWF) for
each pollutant. These factors are used to account for differences in toxicity among pollutants and to
adjust the estimated pollutant loading values to account for the fact that different pollutants have
different potential effects on human and aquatic life (e.g., a pound of zinc in an effluent stream has a
different effect than a pound of arsenic).
The TWF is the sum of two criteria-weighted ratios: the "benchmark/old" copper criterion divided
by the human health criterion for the particular pollutant and the "benchmark/old" copper criterion
divided by the aquatic chronic criterion. TWFs for pollutants are derived using ambient water quality
criteria and toxicity values.9 The factors are standardized by relating them to a "benchmark" toxicity
value that was based on the toxicity of copper when the methodology was developed.10 For most
pollutants, TWFs are derived from chronic freshwater aquatic criteria. In cases where a human health
criterion has also been established for the consumption offish, the sum of both the human and aquatic
criteria are used to derive toxic weighting factors. More information is in Appendix E of the Proposal
EA.
Table E-7 presents the TWFs for the regulated pollutants used in this C-E analysis (step 2) and the
resultant pound-equivalent estimates for the six metallic compounds (cadmium, copper, nickel, lead, zinc,
and arsenic). These estimates are measured in terms of in-stream concentration and have been adjusted
from EPA's estimated "edge-of-field" estimates assuming that about 70 percent of land applied manure
reached U.S. waters. As was d one for nutrients and sediments, this estimate is based on extensive
simulations of EPA's water quality model developed for this rulemaking. This analysis indicates that
roughly 70 percent of all land applied manure metal constituents reach U.S. waters (measured as rivers
and streams). For more information, see Appendix E of the Proposal EA and also the Benefits Analysis
(USEPA, 2000d, 2002k).
9Human health and aquatic chronic criteria are maximum contamination thresholds. Units for criteria are
micrograms of pollutant per liter of water. Most values are those reported in the toxicology lite'rature.
'"Although the water quality criterion has been revised (to 12.0 ug/L), all C-E analyses for effluent
guideline regulations continue to use the "old" criterion of 5.6 ug/L as a benchmark so that cost-effectiveness values
can continue to be compared to those for other effluent guidelines. Where copper is present in the effluent, the
revised higher criterion for copper results in a TWF for copper of 0.467 rather than 1.0.
E-15
-------
The resultant weighted pound-equivalent removals of these pollutants are less 200,000 pounds, or
less than one-tenth of one million pounds-equivalent (Table E-7). Table E-7 shows results for both
Option 1 and Option 2. The magnitude of these reductions is low compared to those estimated for other
effluent guideline regulations where priority pollutants are the primary pollutants of concern. These
findings are consistent with the fact that these substances exist in trace amounts in animal manure and
wastewater. Table E-3 shows estimates by ASAE of the concentration of these pollutants in animal
waste.
Table E-7. Total Metal Removals ("At Stream" Concentrations)
Metal
Zinc
Copper
Cadmium
Nickel
Lead
Arsenic
Total
TWF
0.05
0.63
2.60
0.11
2.20
4.00
NA
Option 1
Lb.
Lb.-Eq.
Option 2 •
Lb.
Lb.-Eq.
(millions of pounds or pounds-equivalent)
0.0905
0.0174
0.0009
0.0080
0.0059
0.0042
0 1270
0.0043
0.0110
0.0024
0.0009
0.0131
0.0167
0.0484
0.0936
0.0194
0.0013
0.0091
0.0081
0.0085
0.1401
0.0044
0.0122
0.0035
0.0010
0.0178
0.0341
0.0730
Source: TWFs are calculated by EPA and are based on freshwater chronic criteria for copper (USEPA, 2000j).
Pound removals are estimated by EPA (USEPA, 2002). Pounds-equivalent are calculated by multiplying the
estimated pound of removals by the TWFs shown here.
E-16
------- |