Economic Analysis of Air Pollution
Regulations: Off-Site Waste and Recovery
Operations
Final Report
March 1996
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Innovative Strategies and Economics Group
Research Triangle Park, NC 27711
-------
PREFACE
In reviewing the regulatory alternatives analyzed in this
report, the Agency developed revised levels of control to ensure
consistent, adequate, and reasonable controls for each emissions
point. These revised levels were proposed on October 13, 1994
(refer to 59 FR 51913). Based on public comments received by the
EPA at Proposal as well as the EPA's evaluation of additional
information obtained after proposal, certain requirements of the
rulemaking have been changed from those proposed. Thus, the
current form of the regulation is considerably different from the
Regulatory Alternatives analyzed in the body of this report.
Changes in the regulation since the analysis was performed
The economic analysis findings EPA presents in this report
are for more than 700 facilities conducting off site waste
operations and recovery that are or will be classified as major
or area sources. Subsequent to the preparation of this economic
analysis, EPA decided to limit the applicability of the proposed
regulations just to major sources--off site waste and recovery
operations with the potential to emit at least 9,7 Mg {10 tons)
per year of any one hazardous air pollutant, or at least 22.7 Mg
(25 tons) of any combination of hazardous pair pollutants. This
decision to drop area sources for the regulatory scope cuts by
over two thirds the number of facilities potentially affected
because of their off-site waste and recovery operations (some
facilities may not be major sources because of their off-site
waste operations but may be major sources because of other on-
site activities). Overall, the number of facilities affected by
the regulation is expected to be considerably smaller than the
number for which this analysis was performed. Consequently,
estimates of national costs, emissions reductions, facility
closures, process shutdowns, and many other regulatory impacts
are overstated in the following pages.
In addition to the change in the scope of the regulation
-------
made prior to proposal, the major changes incorporated into the
final rule clarify the applicability of the rule to off-site
waste and recovery operations, change the volatile organic
concentration action level, delete land disposal units as
affected sources, add more alternatives for controlling HAP
emissions from tanks and containers, and add a selection of
alternative test procedures for determining the average HAP
concentration. Also, EPA has made many changes to the specific
air emission control requirements to clarify EPA1s intent in the
application and implementation of these requirements and to make
these requirements consistent and up-to-date with EPA decisions
made for other related NESHAP and RCRA air standards. Overall,
the effect of these changes is expected to reduce the economic
impacts of the final rule relative to the impacts described in
this report. For a detailed description of the changes in the
rule since proposal, see section VI of the Preamble to the final
rule,
Analysis of Impacts for Facilities Projected to be Unprofitable
Under the Proposed Rule
The Agency is particularly concerned about facilities
projected to become unprofitable under the pre-proposal analysis.
Accordingly, their situation has been more closely examined for
this report. Ten facilities were projected to become
unprofitable; six or seven of them, privately-owned OWR
facilities, may close as a result of the pre-proposal costs.
Their data were closely examined to determine whether they were
likely to be major sources; they were not. Thus, the only costs
these facilities are likely to incur as a result of the revised
rule are those needed to demonstrate that they are not subj ect to
the regulation. The economic model was re-run, using the pre-
proposal costs for most facilities, but for the ten facilities
proj ected to become unprofitable, using the estimated costs of
monitoring and record-keeping to demonstrate that they are not
major sources. Thus, the re-analysis does not completely reflect
-------
the impacts of the revised rule, because impacts on all
facilities except these ten were evaluated based on their
proposed rule costs.
Even with these relatively minor costs of compliance, the
ten facilities are still projected to become unprofitable. There
are several reasons for this. First, all the facilities were
just barely breaking even at baseline. These ten facilities were
estimated by the Agency to have the highest per-unit costs of
production in the markets they participate in. For many of these
markets, no independent price information was available; in that
case, the price was set equal to the highest unit cost. Thus,
due to the modeling approach and limited data, these facilities
were estimated at baseline to be making little or no profit. The
with-regulation profits of the ten facilities range from -$4,500
to -$5,000. Economic theory would predict that facilities making
a loss will close. Thus, even with reduced costs, six or seven
of these facilities may close.
However, the Agency does not expect that these relatively
small losses will necessarily lead to closures, at least in the
short run, for the reason that the costs of closing the
facilities may exceed the costs of keeping them open. There are
costs associated with closing facilities, both dollar costs and
opportunity costs. The dollar costs include closure and post -
closure costs required to restore the site under the facilities'
Resource Conservation and Recovery Act {RCRA) permits. These
costs can amount to several hundred thousand dollars. Even after
the buildings and equipment are sold for scrap, the costs of
closure may be sufficiently high to discourage facilities
incurring small losses from closing. Potentially even more
important, however, are the opportunity costs. Once a facility
has shut down, significant expense is required to re-start it.
Facilities allowing their RCRA permit to lapse may incur
significant costs modifying it if the facility is re-activated.
Thus, facility owners hesitate to close facilities incurring
-------
small losses, recognizing that if they choose to re-open it will
be difficult arid costly. It should be noted that the Agency has
made no estimate of these opportunity costs for these facilities
-------
TABLE OF CONTENTS
Section Page
1 INTRODUCTION AND SUMMARY 1-1
1.1 Background 1-1
1.2 Analytical Approach 1-3
1.3 Summary of Results 1-4
1.3.1 Estimated Impacts on Markets
and Facilities 1-5
1.3.2 Impacts on Employment and Economic
Welfare 1-6
1.3.3 Company-Level Impacts 1-7
1.3.4 Regulatory Flexibility Impacts 1-8
2 DEMAND FOR OWR SERVICES 2-1
2.1 Demand for Waste Services 2-1
2.1.1 Types of OWR Services Affected by
this Regulation 2-2
2.1.2 Data Sources 2-2
2.1.3 Industries Demanding OWR
Services 2-3
2.2 Trends in the Demand for OWR Services 2-7
2.2.1 The Land Disposal Restrictions (LDR).... 2-7
2.2.2 The Toxicity Characteristics Leachate
Procedure (TCLP) Test 2-8
2.2.3 Pollution Prevention 2-9
2.2.4 Evidence from the Toxics Release
Inventory (TRI) 2-9
2.2.5 Other Evidence of Trends in Demand for
OWR Services 2-10
2.3 Demand for Management of Specific Types
of Waste 2-11
2.4 Characteristics of Demand as Reflected by
the Market Model 2-14
3 SUPPLY OF OWR SERVICES 3-1
3.1 Description of Suppliers 3-2
3.1.1 Data Limitations 3-2
iii
-------
TABLE OF CONTENTS (continued)
Section Page
3.2 Types of OWR Services 3-3
3.3 Commercial Status 3-4
3.4 Quantities of Waste Managed by OWR
Facilities 3-11
3.5 Location of OWR Facilities 3-14
3.6 Facility Size 3-14
3.6.1 Facility Throughput 3-14
3.6.2 Number of Employees 3-18
3.6.3 Facility Revenues 3-19
3.7 Company Financial Profile 3-22
3.7.1 Data Sources 3-22
3.7.2 Company Size Distribution 3-26
3.7.3 Vertical and/or Horizontal
Integration 3-29
3.7.4 Cost of Capital and Capital
Structure 3-32
4 DEVELOPMENT OF THE OWR INDUSTRY BASELINE 4-1
4.1 Baseline Facility Conditions 4-2
4.1.1 Estimating Baseline Quantities 4-3
4.1.2 Estimating Baseline Costs 4-5
4.1.3 Estimating Baseline Prices 4-7
4.2 Baseline Company Financial Conditions 4-9
4.2.1 Financial Ratio Analysis 4-12
4.2.1.1 Profitability 4-15
4.2.1.2 Market Value 4-20
4.2.2 Bankruptcy Analysis 4-22
5 THE OFF-SITE WASTE OPERATIONS STANDARD 5-1
5.1 Controls for Emission Point Categories 5-2
5.1.1 Regulatory Baseline 5-2
5.1.2 Emission Point Category Floor 5-2
5.2 Regulatory Alternatives Selected for
Analysis 5-3
5.3 Costs of Regulatory Alternatives 5-5
5.3.1 Estimated Facility Compliance Costs 5-5
5.3.2 Fixed Costs 5-9
5.4 Compliance Costs of Each Regulatory
Alternative, by Waste Type 5-10
5.5 Enhanced Monitoring Costs 5-27
iv
-------
TABLE OF CONTENTS (continued)
Section Page
6 IMPACTS OF THE REGULATORY ALTERNATIVES 6-1
6.1 Market Impacts 6-2
6.1.1 Analytical Method used to Estimate
Market Impacts of Regulatory
Alternatives 6-3
6.1.2 Scope of Market Analysis 6-3
6.1.3 Baseline Quantities of OWR Services 6-5
6.1.3.1 Facility Supply 6-5
6.1.3.2 Market Supply 6-8
6.1.3.3 Implications of the
Assumptions 6-8
6.2 Compliance with the Standard 6-9
6.3 New Market Equilibrium Prices and
Quantities 6-10
6.3.1 Model Description 6-10
6 . 4 Results 6-13
6.4.1 Market and Facility Impacts of the
Regulatory Alternatives 6-13
6.4.1.1 Changes in Price and
Quantity 6-13
6.4.1.2 Facility Closures and
Process Shut-Downs 6-30
6.4.2 Employment Impacts 6-34
6.4.3 Economic Welfare Impacts 6-35
6.5 Company Impacts 6-3 9
6.5.1 Owners' Responses 6-40
6.5.2 Impacts of the Regulation 6-49
6.5.2.1 Changes in the Cost of Capital
and Capital Structure 6-50
6.5.2.2 Changes in Financial Status. . . . 6-62
6.5.2.3 Projected Financial Failure. . . . 6-70
6.6 Initial Regulatory Flexibility Analysis 6-70
6.6.1 Potentially Affected Entities 6-71
6.6.2 Distribution of Impacts 6-72
6.6.3 Mitigating Measures 6-84
REFERENCES R-l
v
-------
TABLE OF CONTENTS (continued)
Appendices Page
A List of SIC Codes Provided to Respondents
to the National Survey of Hazardous Waste
Treatment, Storage, Disposal, and Recycling
Facilities A-l
B Program Defining Waste Forms B-l
C Elasticity of Demand for Off-site Waste
and Recovery Operations C-l
D Financial Analysis Method D-l
E Estimating Companies' Weighted Average
Cost of Capital E-l
F Estimating Facilities' Baseline Waste
Management Quantities F-l
G Technique for Estimating Facilities'
Average Variable Costs G-l
H Documentation and Summary of Methods Used
to Impute Missing Financial Statement Values H-l
vi
-------
LIST OF FIGURES
Number Page
3-1 Size distribution of potentially affected companies.. . 3-27
3-2 Share of commercial versus noncommercial waste
treatment services 3-30
3-3 Share of total receipts from waste treatment and
all other activities 3-31
4-1 Treatment categories most commonly used to manage
each waste form 4-4
4-2 Percentage of firms equal to or below the industry
benchmark ratio: return on sales 4-16
4-3 Percentage of firms equal to or below the industry
benchmark ratio: return on equity 4-18
4-4 Percentage of firms equal to or below the industry
benchmark ratio: return on assets 4-20
6-1 Off-site waste flows to a sample OWR process,
incineration 6-6
6-2 The effect of the emissions standard on the market
for OWR service i 6-11
6-3 Change in consumer surplus with regulation 6-36
6-4 Change in producer surplus with regulation 6-37
6-5 Characterization of owner responses to regulatory
actions 6-47
6-6 Marginal cost of capital schedule 6-53
6-7 Projected share of compliance capital costs by
type of financing 6-59
6-8 Percentage of firm financial ratios equal to or below
the industry lower quartile ratio: return on sales.. . 6-67
6-9 Percentage of firm financial ratios equal to or below
the industry median quartile ratio: return on sales... 6-67
6-10 Percentage of firm financial ratios equal to or below
the industry lower quartile ratio: return on equity... 6-68
6-11 Percentage of firm financial ratios equal to or below
the industry median quartile ratio: return on equity.. 6-68
6-12 Percentage of firm financial ratios equal to or below
the industry lower quartile ratio: return on assets... 6-69
6-13 Percentage of firm financial ratios equal to or below
the industry median quartile ratio: return on assets.. 6-69
vii
-------
viii
-------
LIST OF TABLES
Number Page
2-1 1986 Waste Generation by SIC Code, by Treatment
Location 2-5
2-2 Waste Forms for Which OWR Services Are Demanded 2-13
2-3 Treatment Processes at OWR Facilities 2-14
3-1 Waste Type Definitions 3-5
3-2 Number of Facilities Treating Waste, by Process
and Commercial Status 3-9
3-3 Quantities of Waste Managed at OWR Facilities,
by Process and Commercial Status 3-12
3-4 Location of OWR Facilities, by State 3-15
3-5 Facility Size by Throughput 3-16
3-6 Employment at OWR Facilities 3-20
3-7 Facility Commercial OWR Revenues 3-21
3-8 Data Sources 3-24
3-9 Size Distribution of Potentially Affected Companies.. . 3-27
3-10 Average Size of OWR Facility by Company Size 3-28
3-11 Distribution of Firms by Number of OWR Facilities
Owned 3-29
3-12 Summary Statistics by Firm Size Category of Weighting
Factors Used to Calculate Firms' Baseline WACC 3-35
3-13 Summary Statistics by Firm Size Category of Firms'
Baseline WACC 3-36
4-1 Estimated Aggregate Quantities of Each Waste Form
Processed in Each Treatment Category by the 710
OWRs That Responded to the TDSR Survey 4-3
4-2 Model Processes Used to Estimate Costs 4-6
4-3 Estimated Market Prices for Management of 60
Waste Types Profiled 4-10
4-4 Baseline Financial Ratio: Return on Sales 4-15
4-5 Baseline Financial Ratio: Return on Equity 4-17
4-6 Baseline Financial Ratio: Return on Assets 4-19
4-7 Baseline Financial Ratio: Market-to-Book Ratio 4-21
4-8 Baseline Bankruptcy Prediction 4-24
5-1 Emission Point Control Options 5-4
5-2 OWR Standard Regulatory Alternatives Selected for
Economic Analysis 5-6
5-3 National Compliance Costs and Emissions by
Regulatory Alternative 5-7
ix
-------
LIST OF TABLES (continued)
Number Page
5-4 Compliance Costs, Regulatory Alternative 1 by
Waste Management Process 5-11
5-5 Compliance Costs, Regulatory Alternative 2 by
Waste Management Process 5-14
5-6 Compliance Costs, Regulatory Alternative 3 by
Waste Management Process 5-17
5-7 Compliance Costs, Regulatory Alternative 4 by
Waste Management Process 5-20
5-8 Compliance Costs, Regulatory Alternative 5 by
Waste Management Process 5-23
6-1 Variables Used in the OWR Model 6-4
6-2 Price and Quantity at Baseline and Under
Regulatory Alternative 1, by OWR Process 6-14
6-3 Price and Quantity at Baseline and Under
Regulatory Alternative 2, by OWR Process 6-17
6-4 Price and Quantity at Baseline and Under
Regulatory Alternative 3, by OWR Process 6-20
6-5 Price and Quantity at Baseline and Under
Regulatory Alternative 4, by OWR Process 6-23
6-6 Prices and Quantities of OWR Services
at Baseline and Under Regulatory Alternative 5 6-26
6-7 Closures Under Each Regulatory Alternative 6-31
6-8 Changes in Employment Under the Regulatory
Alternatives (for 551 Commercial Facilities) 6-35
6-9 Changes in Economic Welfare with the Regulatory
Alternatives 6-40
6-10 Projected Change in Revenue 6-43
6-11 Projected Change in Operating Costs 6-44
6-12 Projected Capital Compliance Costs 6-45
6-13 Projected Change in Firm Value 6-52
6-14 Number of Firms with Compliance Capital Costs (CC)
Above the Retained Earnings Breakpoint (B) 6-55
6-15 Estimated With-Regulation WACC 6-60
6-16 Estimated Change in the Cost of Capital 6-61
6-17 Baseline and With-Regulation Financial Ratio:
Return on Sales 6-64
6-18 Baseline and With-Regulation Financial Ratio:
Return on Equity 6-65
6-19 Baseline and With-Regulation Financial Ratio:
Return on Assets 6-66
6-20 Annual Compliance Costs as a Percentage of
Baseline Waste Treatment Costs 6-75
6-21 Annual Compliance Costs as a Percentage of
Baseline Production Costs 6-77
6-22 Annual Compliance Costs as a Percentage of Sales:
Excluding Firms with Zero Compliance Costs 6-80
6-23 Annual Compliance Costs as a Percentage of Sales:
Including Firms with Zero Compliance Costs 6-82
x
-------
SECTION 1
INTRODUCTION AND SUMMARY
This report analyzes the economic and financial impacts
projected to result from a national emission standard for
hazardous air pollutants (NESHAP) for the control of hazardous
air pollutant (HAP) emissions from off-site waste operations
that are major sources under Section 112 of the Clean Air Act
(the Act) as amended in 1990. Facilities performing off-site
waste operations are referred to in this report as off-site
waste and recovery (OWR) facilities. The rulemaking
specifically addresses organic HAP emissions from OWR
facilities that receive waste from off site.
1.1 BACKGROUND
The Clean Air Act Amendments of 1990 (P.L.101-549)
establish a list of 189 HAPs and gives the Administrator of
the Environmental Protection Agency (EPA) the authority to
revise and update the list as necessary. The Act also
requires the EPA to develop and publish a list of all
categories and subcategories of major and area sources of
HAPs. A current list of these source categories, including
OWR facilities, was published in the Federal Register
(July 16, 1992) (57 FR 31576). The Act calls for the
development of standards to control HAP emissions from these
source categories over the 10-year period starting November
1990 .
The off-site waste operation NESHAP will regulate organic
HAP emissions from facilities that receive waste from off site
for the purpose of treatment, storage, recovery, recycling,
and/or disposal. Facilities excluded from the scope of this
1-1
-------
regulation include facilities that manage only waste generated
on site, publicly owned treatment works (POTWs), hazardous
waste incinerators, sewage sludge incinerators, municipal
waste combustors, landfills, and site remediation activities.
The NESHAP, while it will reduce releases of HAPs and
therefore protect the health of the public and the
environment, will also increase the cost of performing OWR
services. The increased costs of waste management operations
resulting from complying with the regulation may reduce the
profits of OWR facilities. Economic theory suggests that the
increased costs will, to some extent, be passed on the OWR
facilities' customers in higher prices for their services.
Thus, the regulation is expected to result in higher prices
for OWR services and a smaller overall quantity of those
services being performed.
At some affected facilities, increased costs in some
processes may mean that those processes are no longer
profitable and should be shut down. The shutting down of
processes, or fixed compliance costs not directly related to
individual processes, may cause some whole facilities to
become unprofitable. If this occurs, facilities may close.
Both process closures and facility closures will lead, at
least in the short run, to decreased employment. Unemployment
results in real costs to the unemployed individual and to
society. In addition, lost income in the communities where
the facilities are located may cause repercussions throughout
the community.
The purpose of this analysis is to estimate the changes
in prices and quantities in affected markets for OWR services,
the changes in profitability of OWR processes and facilities,
and the closures, if any, of OWR processes and facilities.
Special attention is paid to the impacts of the regulation on
small businesses and communities. Information from the
economic analysis enables EPA to ensure that regulations not
only will be cost-effective but also will not unnecessarily
impose a disproportionate burden on anyone. For this
1-2
-------
analysis, costs were estimated and impacts assessed assuming
that all OWRs facilities including both major and area
emissions sources, will be affected. If only major sources
are affected, the economic impacts will be much lower than
estimated here.
1.2 ANALYTICAL APPROACH
The Agency has identified 725 OWR facilities expected to
be affected by this regulation, including 86 major sources and
639 area sources. Data were provided for 710 of them from the
National Survey of Hazardous Waste Treatment, Storage,
Disposal, and Recycling Facilities (TSDR Survey) and the
National Survey of Hazardous Waste Generators (GENSUR)
describing the quantities of waste they process in each of 60
waste management processes in 1986. Prices for these
processes were also provided by this survey and updated to
reflect 1991 prices. Costs of the waste management operations
were estimated using an engineering cost approach and
similarly were updated to reflect 1991 prices. For the other
15 facilities, data on 1989 quantities and costs of waste
management were provided by the Centralized Waste Treatment
Industry Survey (CWT Survey), and the costs were updated to
1991 prices.
A market simulation model was developed to estimate
facility and market responses to the compliance costs.
Changes in prices and quantities in each of the 60 waste
management markets were estimated under each of five
regulatory alternatives. Process and facility closures under
each regulatory alternative were estimated. Facility impacts
were aggregated to estimate impacts on the companies owning
affected OWR facilities. Impacts on communities on which
affected OWR facilities are located were evaluated.
1-3
-------
1.3 SUMMARY OF RESULTS
Complying with the regulatory alternatives increases the
cost of providing OWR services at each affected OWR facility.
The magnitude of the increase in costs depends on
• the waste management processes present at the
facility,
• the waste types treated in each process,
• the number and type of emission points present at each
process, and
• the baseline level of control for each emission point.
Facilities may perform off-site waste operations on a
commercial or noncommercial basis. Commercial OWR facilities
accept waste from off-site generators that are not under the
same ownership as the OWR facility. Noncommercial OWR
facilities accept waste only from off-site facilities under
the same ownership as the OWR facility. Only commercial OWR
facilities incurring compliance costs are assumed to adjust
their output of OWR services to maximize their profits in
response to the compliance costs. The off-site noncommercial
operations, which may also incur increased costs, are assumed
to be viewed as part of company overhead, similar to a company
legal or accounting division. It is assumed that
noncommercial OWR operations will continue at their
unregulated level; the costs of complying with the regulation
will be absorbed by the entire company. On-site waste
operations are not affected by the regulation.
Facilities providing commercial OWR services are assumed
to compare the average variable cost (AVC) of providing those
services (including the AVC of complying with the regulatory
alternative being analyzed) with the market price (P) for the
services. If AVC < P, the facility will continue to provide
that service at its unregulated level. If, on the other hand,
AVC > P, the facility will find provision of that OWR service
unprofitable and will shut down that process. In addition to
1-4
-------
requiring that P > AVC for each OWR service at each facility,
the analysis checks to see that the facility as a whole is
profitable, taking into account fixed costs (annualized
capital costs) of complying with the regulation. Facilities
that are unprofitable are assumed to shut down. These
adjustments in output decrease the supply of the OWR service,
and the interaction of supply and demand for the service
results in a new, higher price for the service. The model
solves iteratively for the ultimate with-regulation
equilibrium values of price and quantity in each OWR market,
and determines which facilities will close processes or shut
down entirely.
Based on the results of the market/facility model, the
Agency then estimates changes in employment and economic
welfare resulting from the regulatory alternative. Changes in
company financial status are assessed, including a
distributional analysis that examines impacts on companies of
various sizes.
1.3.1 Estimated Impacts on Markets and Facilities
The regulatory alternatives increase the prices of
affected OWR services and decrease the quantities provided.
Regulatory Alternative 1 (RA1) imposes costs in only 10
markets: the markets for landfilling and underground
injection of five waste forms. Price increases range from
less than 0.01 percent of baseline price to more than 40
percent of baseline price. Because of the very low elasticity
of demand for OWR services, quantities of OWR services fall by
less than 0.01 percent in all affected markets under RA1. No
facilities are projected to close under RA1, but four OWR
process lines are shut down (one process is shut down at each
of four facilities).
1-5
-------
Under Regulatory Alternatives 2 through 5 (RA2 through
RA5), almost all markets are affected, and compliance costs
are somewhat higher than under RA1. Under these regulatory
alternatives, some markets are unaffected or experience very
small changes. The most severely affected market (in
percentage terms), underground injection of inorganic solids,
experiences a 181 percent increase in price and a 48 percent
decrease in quantity processed annually under RA4 and RA5.
The next largest percentage increase in price under RA2
through RA5 is experienced in the market for reuse as fuel of
inorganic solids, which incurs an increase of 15.2 percent to
30.2 percent. The market for fuel blending of inorganic
solids experiences the second largest percentage decrease in
annual quantity, 0.63 percent under RA2 through RA5.
The total annual quantity of waste processed commercially
at OWR facilities decreases by 21.7 Mg under RA1, by 1,548 Mg
under RA2, by 1,677 Mg under RA3, by 1,581 Mg under RA4, and
by 1,592 Mg under RA5. These quantities represent at most
0.009 percent of the 18,999,437 Mg of waste estimated to be
managed commercially each year at OWR facilities at baseline.
Ten facilities, all of which were just breaking even at
baseline, become unprofitable and six or seven facilities may
shut down under RA2 through RA5. None of the facilities
projected to close are major sources. However, it is not
conclusive from the data whether or not these OWR facilities
projected for closure are co-located at major sources. If so,
they would still be subject to this regulation. Process
closures, including those at closed facilities, range from 90
under RA2 to 112 under RA5, out of a total of 1,636 viable
commercial OWR processes at baseline.
1.3.2 Impacts on Employment and Economic Welfare
Employment is estimated to decrease by 272 to 278
employees out of a total of 951,000 employed at affected OWR
facilities at baseline. Economic welfare is anticipated to
decrease by between $87 million and $107 million per year.
These estimated decreases in economic welfare represent the
1-6
-------
net effect of changes in prices, quantities, and profits in
all the affected markets. They must be combined with changes
in welfare associated with the environmental benefits
resulting from the regulatory alternatives to get a complete
assessment of the effect of the regulation on overall well-
being .
1.3.3 Company-Level Impacts
Companies that own the OWR facilities are legal business
entities that have the capacity to conduct business
transactions and make business decisions that affect the
facility. Thus, the legal and financial responsibility for
compliance with a regulatory action rests with the owners of
the OWR facility. The analysis of the company-level impacts
of the OWR regulation involves identifying and characterizing
affected entities, assessing their response options and
characterizing the decisionmaking process, and analyzing the
impacts of those decisions.
The company-level analysis is based on the assumption
that owners respond to the regulation by installing and
operating pollution control equipment, discontinuing regulated
processes within the facility, or closing the facility. Under
each of these three options identified for analysis, affected
firms will potentially experience changes in the costs of
providing waste treatment services as well as changes in the
revenues generated by providing these services. The cost
impacts associated with the response options include the costs
of installing and operating control equipment, closure costs,
and change in baseline production costs that occur because of
a change in the quantity of waste services provided. The
revenue impacts associated with the regulation stem from
changes in the market price due to a shift in the supply of
waste treatment services. These cost and revenue impacts may
result in a change in the financial status of the firm or even
financial failure of the firm.
Financial ratio impacts provide a measure of the change
in financial status due to the regulation. To compute the
1-7
-------
with-regulation financial ratios, pro-forma income statements
and balance sheets reflecting the with-regulation condition of
affected firms were developed based on projected regulatory
cost and revenue impacts. Profitability is the most commonly
used measure of the firm's performance. Three profitability
measures were estimated: return on sales (ROS), return on
equity (ROE), and return on assets (ROA). For most of the
firms in this analysis, profits either remain unchanged (no
revenue or cost impacts) or decrease in response to the
regulation. For a few firms, however, profits actually
increase in response to the regulation. Increasing profits
occur where positive revenue impacts (price increases that
more than offset the quantity decreases) exceed any cost
impacts. Under each of the regulatory alternatives,
profitability ratios decline from baseline levels for small
firms with less than $6 million in annual receipts.
Profitability ratios for larger firms are generally unchanged
from baseline or only slightly lower because of regulation.
Thus, the regulation is likely to have the greatest impact on
small firms.
A composite ratio of financial condition, called the Z-
score, was also computed to characterize the financial impact
of the regulation on potentially affected firms. The Z-score
is a multi-discriminant function used to assess bankruptcy
potential.1 Data were sufficient to project bankruptcy
potential for only 154 of the potentially affected firms
identified in this analysis. The analysis estimated that
approximately 23 out of these 154 firms are likely to
experience bankruptcy in the absence of the regulation.
However, no additional financial failures due to the
regulation were projected for these firms.
1.3.4 Regulatory Flexibility Impacts
The Regulatory Flexibility Act of 1980 (RFA) requires
that Federal agencies consider whether regulations they
develop will affect small entities (which may include
nonprofit organizations, small governmental jurisdictions, and
1-8
-------
small businesses) .2 Under the RFA, for a rule to be proposed,
EPA must prepare an initial Regulatory Flexibility Analysis,
or certify that the proposed rule is not expected to exert "a
significant economic impact on a substantial number of small
entities." In keeping with this requirement, this analysis
identifies potentially affected small entities, reports the
distribution of impacts across affected entities of all sizes,
and identifies mitigating measures considered for small
entities. For this analysis, firms with revenues less than $6
million per year are considered small.
The EPA specifically identified 388 firms that own 621
potentially affected OWR facilities. These 388 firms include
110 small businesses that own 112 OWR facilities. However,
this analysis does not include the following:
• facilities that treat exclusively nonhazardous waste,
and
• facilities that treat exclusively on site wastes.
Because of resource constraints, data required to identify all
potentially affected facilities and the entities that own them
were not collected. Consequently, the precise number of
potentially affected entities and the share of small entities
that incur an economic impact are unknown.
The distribution of impacts presented in this report is
based on the 388 potentially affected firms identified for
analysis. EPA provides guidelines for defining a "significant
economic impact."3 Impacts may be considered significant
whenever any of the following criteria are satisfied:
• Annual compliance costs increase total costs of
production for small entities for the relevant process
or product by more than 5 percent.
• Compliance costs as a percentage of sales for small
entities are at least 10 percent higher than
compliance costs as a percentage of sales for large
entities.
• Capital costs of compliance represent a significant
portion of capital available to small entities,
1-9
-------
considering internal cash flow plus external financing
capabilities.
• The requirements of the regulation are likely to
result in closures of small entities.
EPA computed the distribution of impacts on companies of all
sizes using the measures described above.
Annual compliance costs were computed as a percentage of
baseline production costs using two alternative methods to
determine whether the first criterion identified above is
satisfied. Under the first method, annual compliance costs
are computed as a percentage of baseline waste treatment
production costs. Under the second method EPA computes annual
compliance costs as a percentage of total production costs.
Impacts measured using the first method are the greatest
for firms with $6 million to $1 billion in annual revenues.
Under RA1, only two companies are projected to incur
compliance costs that will increase their baseline waste
treatment costs by more than 5 percent. This number jumps to
over 100 under the other regulatory alternatives. If the
relevant measure of baseline costs is total costs of
production (under the second method) rather than waste
treatment costs, the impacts are highest for small firms with
less than $6 million in annual receipts. Virtually all of the
firms projected to incur annual compliance costs totaling more
than 5 percent of their baseline production costs are small
firms. Under RA1, only one small firm has estimated annual
compliance costs greater than 5 percent of baseline total
production costs. Under the more stringent regulatory
alternatives, this number jumps to between 20 and 30. Only
two large firms are projected to incur compliance costs
greater than 5 percent of baseline production costs.
The second measure identified above is a relative measure
designed to compare the impacts for small entities to those
for larger entities. Annual costs as a percentage of sales
average less than 1 percent for large firms. This percentage
1-10
-------
compares to impacts ranging from about 4 percent under RA1 to
175 percent under RA5 for small firms.
The criterion for significant impacts under the third
measure identified above is not as straightforward as the
criterion given for each of the first two measures. The
relevant measure of the "capital available" is not explicitly
stated in the guidance. Furthermore, no specific numerical
benchmark is provided to determine whether the capital costs
of regulation represent a "significant" portion of capital
available to the firm. One measure of the capital available
to companies is the retained earnings breakpoint. This
breakpoint refers to the capital available to the firm
assuming that the firm does not issue new equity or change its
capital structure. Between 20 and 50 percent of the firms
with compliance capital costs have costs that exceed the
retained earnings breakpoint. However, these firms represent
less than 3 percent of all potentially affected firms under
RA1 and between 12 and 30 percent of all potentially affected
firms under the most stringent alternatives. Small firms fare
slightly worse than large firms under all of the regulatory
alternatives except RA1.
The final measure states that impacts are significant if
the proposed rule is likely to result in the closure of small
entities. No plant closures are projected under RA1.
However, 10 plants are projected to close under each of the
other regulatory alternatives. A plant closure does not
necessarily translate into a financial failure for large,
multi-facility companies. However, for small, single-facility
companies, plant closure is likely to be synonymous with
financial failure. Of the 10 plants projected to close, three
are owned by small, single-facility companies.
The initial Regulatory Flexibility Analysis indicates
that businesses of all sizes will experience impacts because
of the regulation. However, the impacts on small businesses
are generally greater than the impacts on larger entities.
The EPA is particularly concerned about these impacts on small
1-11
-------
entities. To address these concerns, several measures
designed to mitigate the impacts on small entities were
considered.*
Subsequent to the economic impact analysis reported in this document,
EPA decided to limit the applicability of the proposed regulations just to
major sources — off-site waste operations with the potential to emit at
least 9.7 Mg (10 tons) per year of any one hazardous air pollutant, or at
least 22.7 Mg (25 tons) per year of any combination of hazardous air
pollutants. This decision to drop area (smaller) sources from the
regulatory scope will cut the number of affected facilities by a
substantial but unknown amount. The amount is unknown because some
that may not be major sources because of their off-site waste
not described in data sources currently available to EPA.
Also, EPA decided to limit applicability of the proposed
to facilities accepting from off site at least 1 Mg of organic compounds
listed as hazardous air pollutants. This means that over 100
owned by large businesses, and an unknown owned by
small businesses, will be exempt from the
1-12
-------
SECTION 2
DEMAND FOR OWR SERVICES
Waste is generated during the course of nearly all of
life's activities. For example, producing goods and services
almost always involves the simultaneous production of waste
materials. During the process of manufacturing goods or
providing services, the material inputs that are not embodied
in the products become waste. Environmental regulations
require that these wastes, once generated, be treated and
disposed of in an environmentally sound manner.
2.1 DEMAND FOR WASTE SERVICES
The demand for waste services is a derived demand since
waste is a by-product of manufacturing or other production
activities. For example, the higher the demand for plastic
wrap, the greater the quantity of plastic wrap produced, and,
in turn, the greater the quantity of by-products of plastic
wrap manufacturing that must be treated and disposed.
Producers generating waste have three choices when they
determine how to treat and dispose of the waste properly.
First, they may invest in capital equipment and hire labor to
manage the waste on site, that is, at the same site where it
is generated. For large volumes of waste, this is often the
least expensive way to manage the waste because producers can
avoid the cost of transporting it. Managing waste on site
also enables producers to manage their ultimate liability
under environmental laws.
Another choice is for producers to treat waste on site
initially and then to send it off site for ultimate treatment
and disposal; this method is known as on site/off site.
2-1
-------
Finally, producers may choose to send some or all of the waste
they generate directly to another site, a method that is
called off-site. The producers of waste who choose either the
on site/off-site or the off-site method create the demand for
OWR facilities.
2.1.1 Types of OWR Services Affected by this Regulation
The regulation addresses all facilities accepting waste
from off site for management, except the following types of
facilities:
• municipal landfills,
• incinerators,
• site remediation, and
• POTWs.
Therefore, OWR facilities affected by this regulation include
hazardous waste management facilities, oil re-refining
facilities, off-site wastewater treatment facilities,
industrial landfills, and so on. Because of data limitations,
this analysis estimated impacts on only two of those
categories: hazardous waste management facilities and off-
site wastewater treatment facilities.
2.1.2 Data Sources
Most of the data used for this analysis came from three
sources:
• the TSDR Survey,4
• the GENSUR Survey,5 and
• the CWT Survey.6
EPA's Office of Solid Waste and Emergency Response conducted
the GENSUR and TSDR Surveys in 1987 and 1988. Their goal was
to collect 1986 data from a sample of hazardous waste
generators and all hazardous waste treatment, recycling, or
disposal facilities regulated by the Resource Conservation and
Recovery Act (RCRA). Together the surveys provide a detailed
portrait of the types of facilities generating and managing
wastes in 1986, the types of waste generated, and ways in
which those wastes were managed. The TSDR Survey is a census
of all RCRA-regulated facilities that treated, disposed, or
2-2
-------
recycled hazardous waste in 1986 and a 50 percent sample of
all facilities that stored hazardous waste in RCRA-permitted
units in 1986, but did not treat, dispose, or recycle on site.
This survey provides information about the types of waste
management operations a facility has on site; the quantities
of waste managed in each operation; and the source of those
wastes (generated on site, generated off site by facilities
under the same ownership, or generated off site by facilities
not under the same ownership). The GENSUR provides, among
other things, a detailed characterization of the hazardous
wastes generated in 1986 and where and how they were treated,
disposed, or recycled.
EPA's Office of Water conducted the CWT Survey in 1991
and 1992 to collect 1989 data about facilities that accept
waste from off site for treatment and that discharge water
either directly or indirectly to surface water. These data
were collected to support the development of an effluent
guideline for that industry. Approximately 83 percent of the
facilities covered by the CWT Survey were also contacted for
the TSDR and GENSUR Surveys.
2.1.3 Industries Demanding OWR Services
Data from GENSUR can be used to characterize the
generators of hazardous waste by industry and to profile the
types of waste generated. This extensive survey database
gives the most detailed information on the generation of waste
available. The survey was designed to collect information on
the generation of wastes defined as hazardous under Subtitle C
of RCRA. Thus, this pattern of generation by industry may not
correspond to the generation pattern for the customers of OWR
facilities because their customers include generators of
nonhazardous wastes. Some overall patterns, however, may be
instructive.
Each RCRA regulated facility's Standard Industrial
Classification (SIC) code was identified from its response to
Question 17 of the TSDR Survey. Non-RCRA-regulated facilities
primary SIC code was identified from their responses to
2-3
-------
Question N.2 of the CWT Survey. For a complete list of 4-
digit SIC codes provided to TSDR Survey respondents see
Appendix A. Table 2-1 shows SIC codes and the quantities of
waste those industries generate and ultimately send off site
for treatment, recovery, and/or disposal. This is the portion
of total waste generated in 1986 that was managed off site.
Two types of treatment locations are specified: Off Site Only
and On Site/Off Site. As explained earlier, wastes that, once
generated, are sent directly to an off-site management
facility are called Off Site Only. Wastes generated and
treated initially on site, then sent off site for additional
treatment or disposal, are called On Site/Off Site. Most of
the first page of the table shows wastes shipped off site
without prior treatment, while the remaining rows at the
bottom and the second page show wastes shipped off site after
initial on-site treatment.
Clearly, many manufacturing industries send waste off
site for management and/or recovery as shown in Table 2-1.
The most frequently appearing SIC codes are those in the 2800s
(chemicals manufacturing) and the 3300s (primary metals
manufacturing). Industrial organic chemicals (2869) ships the
greatest quantity of waste off site, followed by plastics and
resins (2821), inorganic pigments (2816), and semiconductor
manufacturing (3674). The SIC code with the most generators
is plating and polishing (3471) . Other industries with many
generators include electronic components (3679) and
semiconductors (3674). Wastes shown in Table 2-1
2-4
-------
TABLE 2-1. 198 6 WASTE GENERATION BY SIC CODE,
BY TREATMENT LOCATION
Quantity
Quantity sent
Treatment
SIC
generated
off site
Number of
location
code
(103 Mg)
(103 Mg)
generators
Off site
2 816
3,816.7
3,816.7
1
only
2821
308.1
308.1
2
3851
288.4
288.4
1
2813
24 9.3
55.8
1
3484
176.9
176.9
5
28 69
101.6
101.2
8
2911
31.6
31.2
16
2833
20.1
20.1
2
287 9
16.0
16.0
2
3644
15.7
15.7
1
4 931
14.0
14.0
9
3317
9 . 8
9 . 8
4
4 953
8 . 8
8 . 8
22
3714
7 . 5
2 . 9
6
3721
5 . 8
5 . 8
6
3471
4 . 9
4 . 9
29
3600
4 . 7
4 . 5
14
5983
3 . 2
3 . 2
7
2819
3 . 1
3 . 1
5
3661
2 . 3
2 . 3
7
28 99
2 . 2
2 . 2
14
3441
2 . 2
2 . 2
9
44 63
2 . 0
2 . 0
1
3312
1 . 9
1 . 9
6
3452
1 . 8
1 . 8
15
367 9
1 . 3
1 . 3
14
3585
1 . 2
1 . 2
2
3728
1 . 1
1 . 1
4 9
347 9
1 . 0
1 . 0
5
1311
1 . 0
1 . 0
4
5171
1 . 0
1 . 0
21
All other
52.4
52 . 0
SICs, off
site only
Off site
5,157.7
4 , 958 . 7
total, only
On site, then
28 69
14 , 637 . 0
10,674.1
165
off site
2821
9,028.9
9,000.8
71
3674
7,985.1
2,843.3
151
3361
4,514.2
3 . 9
5
3714
3,264.9
816.5
123
2611
2,899.1
2,899.1
8
(continued)
2-5
-------
TABLE 2-1. 198 6 WASTE GENERATION BY SIC CODE,
BY TREATMENT LOCATION (continued)
quantity
Uuantity
sent or r
Treatment
SIC
generated
site
Number of
location
code
(103 Mg)
(103
Mg)
generators
On site, then off
'2 8 19
2,368.2
1,
009.4
40
site (cont. )
3312
2,306.8
644.4
78
28 65
2,290.4
1,
811.4
31
2911
2,170.7
891.0
132
3429
2,056.5
62 . 1
51
3585
1,880.1
19.3
32
2800
1,574.6
63.3
41
3700
1,364.5
1,
364.5
1
9511
1,323.4
1,
323.4
13
3711
1,102.6
736.0
66
3471
942.2
116.8
352
4 953
843.5
7 97.2
4 9
3573
828.4
34.5
63
3321
758.2
23.4
11
367 9
757.0
747.8
256
347 9
631.2
571.8
133
28 99
607.9
293.2
93
3815
583.3
0 . 9
5
3291
575.0
3 . 9
16
2842
571.0
571.0
13
3721
517.1
525.4
59
2834
475.2
475.1
53
3691
37 6.6
19.6
27
307 9
371.0
13.9
156
3341
345.2
342.0
43
3713
332.1
2 . 3
3
287 9
283.4
29.9
46
3548
179.8
0 . 1
1
3678
170.3
170.3
34
3531
170.2
1 . 5
8
3639
169.3
169.3
4
7391
159.1
10.6
125
3316
156.6
155.6
13
3452
150.4
134.6
40
7535
142.7
1 . 9
1
34 97
138.6
138.6
2
3592
122.9
15.1
6
3552
122.0
0 . 4
15
3351
120.2
4 . 3
22
3825
105.0
102.9
10
3317
98.4
52 . 0
36
2542
96.1
0 . 0
2
All other SIC
2,209.9
2,
020.0
codes, on then off
On then off total
76,000.7
41,
163.0
Total waste in 1986
5 9 0,935.1
46,
121.8
2-6
-------
may be doublecounted; that is, the quantities generated at a
facility are listed on a waste-specific basis. At some
facilities, wastes generated by the treatment of other wastes
are listed separately, so the summed waste quantities for the
facility may exceed the total quantity of raw waste generated.
Thus, the total quantity of waste generated by a particular
SIC code may be overstated.
These quantities do not correspond exactly to the
quantity of waste management demanded by generators from OWR
2-7
-------
2-8
-------
facilities in 1986. Some of the wastes in Table 2-1 sent off
site were sent for management at facilities not covered by
this NESHAP. Also, some of the wastes treated in off-site
waste operations covered by this NESHAP are not hazardous
under RCRA and thus would not appear in Table 2-1. But the
overall patterns of generation by SIC code shown in Table 2-1
are expected to be similar to the patterns of waste generation
for wastes being managed at OWR facilities.
Of 678 million Mg of EPA-regulated hazardous waste
generated in 1986, only 46 million Mg were sent off site.
Thus, the vast majority of the volume of RCRA hazardous waste
generated in 1986 was treated and disposed on site and is
outside the scope of this analysis. Relying on on-site
treatment is typical of waste management patterns: to avoid
transportation costs, the largest volume wastes are treated on
site. Waste that is sent off site for management tends to be
relatively low in volume although it may be highly toxic.
2.2 TRENDS IN THE DEMAND FOR OWR SERVICES
The data described above reflect demand for hazardous
waste management services in 1986. They demonstrate that the
demanders of OWR services are diverse, including most
manufacturing and many service sectors. This pattern is
probably true for all waste as well and is probably still
true today. The overall quantity of OWR services demanded and
the pattern of off-site waste management, however, have
probably changed since 1986.
The late 1980s were a period of transition for the waste
management industry, particularly the RCRA hazardous waste
industry. Several regulatory and policy changes combined to
change the framework for waste generation and management.
2.2.1 The Land Disposal Restrictions (LDR)
First, regulations authorized by the Hazardous and Solid
Waste Amendments to RCRA and promulgated by EPA since 198 6
prohibit the land disposal of hazardous waste unless hazardous
2-9
-------
chemicals and characteristics have been removed, reduced, or
stabilized to the greatest extent possible or unless EPA
determines on a site-specific basis that there will be no
migration of hazardous constituents from the land disposal
unit. Beginning in July 1987, wastes banned from land
disposal in California were subject to these national
restrictions (LDR). By August 1988, the most hazardous 33
percent of RCRA hazardous wastes were banned; beginning in
June 1990, the "second third" of RCRA hazardous wastes were
banned. In May 1991, the final third were banned from land
disposal. Thus, the LDR (or "land ban") has changed the
pattern of hazardous waste management, increasing the amount
of treatment prior to disposal. In addition, smaller
quantities of some types of waste will be land-disposed (waste
that must be thermally treated, for example), while greater
quantities of other wastes will be land-disposed (such as
wastewater treatment sludges, which must now be mixed with
stabilizing agents). The average per-unit costs of waste
management have increased.
2.2.2 The Toxicity Characteristic Leachate Procedure
(TCLP) Test
In addition to the LDR, the introduction of the TCLP test
to determine if a waste is toxic under RCRA changed the
classification of many wastes from nonhazardous to hazardous.
Since September 1990, facilities have been required to use
this test rather than the extraction procedure (EP) leaching
test to determine whether wastes are hazardous. The most
notable distinction between the tests is that the EP test
estimates the leaching of metals only while the TCLP also
estimates the leaching of organic compounds. Many organic
chemicals will ultimately be added to the characteristic list
of RCRA hazardous wastes as a result of this rule change.
Facilities managing these wastes must now have a RCRA permit.
Thus, the TCLP increases the demand for RCRA-permitted OWR
services relative to other, non-RCRA-permitted types of waste
management because these wastes can no longer be treated by a
2-10
-------
POTW or disposed in a municipal landfill without prior
treatment.
2.2.3 Pollution Prevention
Another recent policy change is EPA's and state agencies'
greatly increased emphasis on pollution prevention.
Generators are encouraged to modify their processes, improve
their housekeeping, increase their reuse and recycling of
production by-products, and generally reduce the amount of
waste they release to the environment. Many facilities have
found cost-effective ways to modify their operations and
decrease the quantity of waste they generate for a given level
of production of their primary good or service. This trend
has, other things equal, reduced the demand for OWR services.
To assess the overall trend in the demand for OWR
services, EPA would need a time-series database giving several
years' data about the quantity of waste sent off site for
management each year. Unfortunately, no database corresponds
exactly to the data needed. No national data source provides
time-series information about the quantity of RCRA-regulated
waste sent off site for management. Because of the lack of
detailed national time-series data on hazardous waste
generation and management, quantifying the overall trend in
demand for OWR services over the past five years is
impossible. If the increasingly stringent regulation of
pollution releases to the environment has dominated, the
quantity of waste that must be managed by specialists (OWR
facilities) for a given level of production may have
increased. If, on the other hand, the emphasis on pollution
prevention has dominated, a given level of production may have
resulted in a smaller quantity of waste being generated, and
the demand for OWR services may have declined.
2.2.4 Evidence from the Toxics Release Inventory (TRI)
The TRI does provide a time series of data on releases of
materials, but the materials are chemicals of concern rather
than RCRA-regulated wastes. Many of the TRI chemicals, if
discarded, are RCRA-regulated hazardous wastes. Thus, the TRI
2-11
-------
database does provide information from which inferences may be
drawn about the quantities of waste being generated.
A recent study done for EPA's Office of Pollution
Prevention and Toxics assesses the changes in reported TRI
releases and transfers between 1989 and 1990.7 This study
collected data from a sample of TRI-reporting facilities to
attempt to quantify the changes in releases and transfers
reported in TRI between 1989 and 1990, and to assess the
contribution of "real" changes in releases as opposed to
"paper" changes in releases. Real changes in releases
represent actual changes in the physical quantities of a
chemical sent off site. Paper changes, on the other hand,
represent changes in reported quantities of chemicals released
that are not actual changes in physical releases but occur
because of changes in measurement or data errors.
A sample of facilities was drawn from the population of
facilities in two-digit SIC codes between 20 and 39 that
reported releases in the TRI in both 1989 and 1990. Based on
survey results, the target population reported a 15.4 percent
decrease in TRI releases and transfers between 1989 and 1990.
Of the 15 percent, approximately half (6.9 percentage points)
is attributed to source reduction. The rest is attributed to
measurement changes, changes in production, and other factors.
Based on these results, it appears likely that, overall, the
demand for OWR services may be declining.
2.2.5 Other Evidence of Trends in Demand for OWR Services
Anecdotal evidence abounds that indicates a declining
demand for OWR services, especially for hazardous waste OWR
services. Numerous case studies have been performed
documenting pollution prevention activities and the resulting
decreases in quantities of waste being generated. For
example, Motorola, in conjunction with two U.S. Department of
Energy laboratories, developed a no-clean soldering process
for circuit board production that eliminates all solvent
cleaning, eliminates the use of chlorofluorocarbons (CFCs),
speeds up production, decreases energy use, reduces production
2-12
-------
costs, and produces reliable hardware.8 Additionally, in a
recent assessment of pollution prevention in the chemicals
industry for INFORM, Dorfman, Muir, and Miller cite dozens of
examples of companies making changes to production processes,
inputs, or products to reduce their waste generation. DuPont,
for example, reduced solvent waste at their Deepwater, New
Jersey, Chambers Works plant by approximately 40 million
pounds per year. Most of their pollution prevention
activities involve in-process recycling. The company
estimates that these activities save DuPont $3.75 million each
year. Dow Chemical's Pittsburg, California, plant modified
its inputs and production processes and reduced its waste
generation by approximately 12 million pounds per year.9
A recent article in the Wall Street Journal stated that,
contrary to concerns in the late 1980s, hazardous waste
disposal capacity seems abundant:
Existing dumps have about 50 years of capacity
left. . . . Licensed hazardous waste
incinerators ran at 74 percent of capacity in
1990. . . . Hazardous waste disposal capacity
went from a feared shortage to an actual glut
in part because companies . . ., facing rising
disposal costs and potential cleanup
liability, overhauled production methods to
reduce waste volume.10
For all of the reasons cited above, it is probable that
the pattern and total volume of OWR demanded in 1991 are very
different from that reported in the TSDR/GENSUR database. No
data sources reflect OWR demand in 1991; the data used in this
analysis, although out of date, are the best available.
2.3 DEMAND FOR MANAGEMENT OF SPECIFIC TYPES OF WASTE
Generators of wastes demand the management of the wastes
they generate by OWR facilities. For example, a generator may
produce wastewater contaminated with metals, sludges or
solids, or spent solvents as a result of the production of
2-13
-------
other goods or services. The generator demands the
management of a particular type of waste. Over 400 specific
RCRA waste codes describe hazardous wastes of particular
types. In addition, many other wastes are not hazardous under
RCRA. For simplicity, this analysis grouped the wastes into
six general types, or waste forms. Table 2-2 defines these
waste forms.
2-14
-------
TABLE 2-2. WASTE FORMS FOR WHICH OWR SERVICES ARE DEMANDED
Waste
Waste
description
form
code
Definition
1
B J / -Bb b
Inorganic solids
A10
Incinerator ash
All
Solidified treatment residuals
2
B20-B35
Inorganic sludges
3
B77-B78
Biological treatment or sewage
sludge
B19
Lime sludge without metals
AO 5
Wastewater or aqueous mixture
4
B58-B70
Organic liquids
AO 1
Spent solvents
A02
Other organic liquid
5
B28
Degreasing sludge with metals
B36
Soil contaminated with organics
B71-B90
Organic sludges and solids
AO 3
Still bottoms
AO 4
Other organic sludge
AO 6
Contaminated soil or cleanup
residue
6
B57
Inorganic gases
B91
Organic gases
AO 7
Other F or K waste3 exactly as
described
AO 8
Concentrated off-spec or discarded
product
AO 9
Empty containers
A12
Other treatment residue
A13
Other untreated wastes
a Wastes whose RCRA codes begin with F or K.
2-15
-------
TABLE 2-3. TREATMENT PROCESSES AT OWR FACILITIES
McLllcLCJ S1LLS11 L
process number
Process description
1
incineration
2
Reuse as fuel
3
Fuel blending
4
Solidification stablization
5
Solvent recovery
6
Metals recovery
7
Wastewater treatment
8
Landfill disposal
9
Underground injection
10
Other waste management
process
Appendix B provides more detailed information about the
specific wastes included in each waste form.
Within each waste form, some of the specific wastes may
be suitable for management using one waste management process
while other wastes are suitable for management using other
processes. This analysis assumed that the process used to
manage a particular waste is a function of its
characteristics. Waste of Form 1 that is incinerated is
assumed to be different from waste of Form 1 that is
landfilled or that undergoes wastewater treatment. Thus, the
specific waste types for which OWR services are demanded are
described by the combination of the waste form and the
treatment process. Table 2-3 lists the types of OWR
management processes included in the analysis.
Waste type (i_j) = waste of Form i managed in process j
i 1, . . . , 6
j = 1,..., 10
2-16
-------
Because ten waste management processes and six waste forms are
being analyzed, the analysis groups waste into a total of 60
individual waste types for which waste management services are
demanded.
Only commercially treated wastes constitute a demand in
the market for OWR services although noncommercial off-site
waste management activities are also subject to this
regulation. The regulation does not affect the wastes that
are generated and treated on site.
2-17
-------
2.4 CHARACTERISTICS OF DEMAND AS REFLECTED BY THE MARKET
MODEL
As explained above, waste management is an input into the
production of other goods and services, whose production
simultaneously creates waste. The demand for the OWR input is
derived from the demand for the other goods and services. In
Q D = Y -PE , (2-1)
1i
the market model, the demand for OWR services is given by
where Y is a constant parameter and E is the elasticity of
market demand of waste management operations.
The price elasticity of demand (which is referred to as
the elasticity of demand from here on) measures the
responsiveness of demand for a service to changes in its
price. It is defined as the percentage change in the quantity
demanded of a service divided by the percentage change in its
price.
Economic theory states that the elasticity of the derived
demand for an input is a function of the following:
• demand elasticity for the final good it will be used
to produce,
• the cost share of the input in total production cost,
• the elasticity of substitution between this input and
other inputs in production, and
• the elasticity of supply of other inputs.11,12,13
As explained in Appendix C, the magnitude of the elasticity of
demand for OWR services depends on the cost share of OWR
services in the production of the generators' primary goods
and services. Other analyses done on the OWR industry show
that the cost share for waste management is usually very
small, frequently hundredths of a percent of total production
costs. Accordingly, the elasticity of demand for waste
2-18
-------
management is expected to be small. A uniform -0.1 elasticity
of demand is assumed for each of the types of OWR services.
2-19
-------
SECTION 3
SUPPLY OF OWR SERVICES
OWR services are waste management services performed at
facilities that accept waste from off site (i.e., generated at
other facilities). While some waste is generated at these
facilities as a result of the treatment of other waste (and,
in some cases, as the result of manufacturing), much of the
waste treated there is generated elsewhere and transported to
the OWR facility for treatment and/or disposal. Producers of
OWR services include both RCRA-regulated hazardous waste
management facilities and non-RCRA-regulated off-site waste
management facilities.
The EPA believes that organic HAP air emissions from the
hazardous waste management activities at RCRA-regulated waste
management facilities provide the best estimate available for
organic HAP emissions from OWR facilities.14 Another type of
facility believed to emit organic HAPs in fairly large
quantities is off-site wastewater treatment facilities that
are not RCRA-regulated. Because these two types of facilities
are believed to be the major OWR emitters of organic HAPs, the
economic impact analysis treats these facility types in the
greatest detail. Other types of OWR activities (such as
industrial landfills or oil re-refiners) are discussed
qualitatively.
OWR facilities differ widely from one another in terms of
their size, the types of waste management services they offer,
and their profitability. They differ in terms of their
ownership type and the financial health of the companies
owning them. This section profiles the suppliers of OWR
services.
3-1
-------
3.1 DESCRIPTION OF SUPPLIERS
As described in Section 2, the regulation affects all
facilities that accept waste from off site for management,
with a few exceptions. OWR facilities thus include hazardous
waste management facilities, off-site wastewater treatment
facilities, oil re-refining facilities, industrial landfills,
and so on. The impact analysis focuses on RCRA-regulated
hazardous waste management facilities and non-RCRA-regulated
off-site wastewater treatment facilities because the Agency
believes that these two subsets represent the most significant
sources of organic HAP air emissions and because the data on
these two subsets are the most complete. Using the TSDR and
GENSUR Surveys, EPA collected the data that form the basis for
characterizing RCRA-regulated facilities that manage hazardous
wastes from off site. This analysis also used data from the
CWT Survey.
Of the 87 facilities identified by the CWT Survey, 72
also are covered by the TSDR/GENSUR database. Only 15 of the
CWT facilities were not also RCRA-regulated in 1986. For the
72 for which data are contained in both data sources, TSDR and
GENSUR data were used to characterize their waste management
operations because those data are more detailed. For the 15
CWT-only facilities, data from the CWT Survey were used.
3.1.1 Data Limitations
The data used to characterize the supply of OWR services
in 1991 combine data collected in 1986 and data collected in
1989. The 1989 data have been checked to ensure that they are
still reasonably accurate. The 1986 data, on the other hand,
may be very out of date. In particular, the LDR, or "land
ban," discussed in Section 2, have significantly transformed
the pattern of management for organic waste forms. Wastes
that were legally managed in land-based operations in 1986
must now be managed in a different way. Some waste management
operations are no longer used to manage hazardous wastes, such
3-2
-------
as surface impoundments, waste piles, and land treatment. In
an attempt to make the data correspond to current practices,
wastes that were reported in the TSDR/GENSUR as going to those
OWR operations were reassigned to landfills. Other
discrepancies, such as assigning organics to land-based
management operations still in use but not legal for organics,
have not been corrected because no data exist to indicate the
relative quantities of those wastes now managed in other
practices.
The TSDR/GENSUR database, although out of date, still
represents the most recent and detailed characterization of
hazardous waste management practices. For this reason, it
forms the basis for characterizing waste management patterns
in the absence of the regulations. However, recognizing its
shortcomings is important, so they will be noted as relevant
throughout this document.
3.2 TYPES OF OWR SERVICES
To be subject to the regulation, facilities must accept
waste from off site. Generally, they also treat at least some
waste that is generated on site. They offer waste generators
the service of managing their wastes that, for the purposes of
this analysis, fall into one of six general waste forms:
• inorganic solids,
• inorganic sludges,
• aqueous liquids or sludges,
• organic liquids,
• organic sludges or solids, and
• other wastes.
These waste forms were further divided based on treatability,
as discussed in Section 2. Thus, for each of the six waste
forms, as many as 10 waste types reflect how the waste is
treated.
3-3
-------
Each OWR facility may manage those wastes in one of the
following waste management processes (not all general waste
types are managed in all processes):
• incineration,
• reuse as fuel,
• fuel blending,
• solidification and stabilization,
• solvent recycling,
• metals recovery,
• wastewater treatment,
• landfill disposal,
• underground injection, and
• other waste management.
For purposes of this analysis, the Agency assumed that
each waste form and management operation constitute a unique
waste management service that is marketed. This assumption
reflects the belief that the wastes within each broad waste
form are in fact quite variable and that different waste
management operations would be appropriate for different
wastes within the broad category. Therefore, for example, the
Agency believes that organic liquid waste treated in
incineration is really a different waste than organic liquid
waste treated in wastewater treatment. Because there are six
waste forms, each of which may be managed in each of 10
processes, the model estimates market effects in each of 60
markets.
3-4
-------
T
¦e
T
'2
'3
'4
'5
'6
'7
'8
'9
1
1
'2
'3
'4
'5
'6
'7
'8
'9
1
1
'2
'3
'4
'5
'6
'7
'8
'9
1
TABLE 3-1. WASTE TYPE DEFINITIONS
bel _Lii_L L_loii:
waste form
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
Inorganic
process
Aqueous liquids or sludges Incineration
Aqueous liquids or sludges Reuse as fuel
Aqueous liquids or sludges Fuel blending
Aqueous liquids or sludges Solidification/stabilization
Aqueous liquids or sludges Solvent recovery
Aqueous liquids or sludges Metals recovery
Aqueous liquids or sludges Wastewater treatment
Aqueous liquids or sludges Landfill disposal
Aqueous liquids or sludges Underground injection
Aqueous liquids Other waste management
process
Waste management process
solids
Incineration
solids
Reuse as fuel
solids
Fuel blending
solids
Solidification/stabilization
solids
Solvent recovery
solids
Metals recovery
solids
Wastewater treatment
solids
Landfill disposal
solids
Underground injection
solids
Other waste management
process
sludges
Incineration
sludges
Reuse as fuel
sludges
Fuel blending
sludges
Solidification/stabilization
sludges
Solvent recovery
sludges
Metals recovery
sludges
Wastewater treatment
sludges
Landfill disposal
sludges
Underground injection
sludges
Other waste management
(continued)
3-5
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
1
TABLE 3-1. WASTE TYPE DEFINITIONS (continued)
uerini
waste
tion
form
Waste management process
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
Organic
liquids
liquids
liquids
liquids
liquids
liquids
liquids
liquids
liquids
liquids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
sludges
or
solids
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
wastes
wastes
wastes
wastes
wastes
wastes
wastes
wastes
wastes
wastes
Incineration
Reuse as fuel
Fuel blending
Solidification/stabilization
Solvent recovery
Metals recovery
Wastewater treatment
Landfill disposal
Underground injection
Other waste management
process
Incineration
Reuse as fuel
Fuel blending
Solidification/stabilization
Solvent recovery
Metals recovery
Wastewater treatment
Landfill disposal
Underground injection
Other waste management
process
Incineration
Reuse as fuel
Fuel blending
Solidification/stabilization
Solvent recovery
Metals recovery
Wastewater treatment
Landfill disposal
Underground injection
Other waste management
process
3-6
-------
Table 3-1 shows the waste type definitions; each market
analyzed represents supply and demand for management of one
waste type.
3.3 COMMERCIAL STATUS
OWR facilities accept waste from off site for treatment,
storage, and disposal or for recycling; that is, they manage
waste that was generated at other facilities. An OWR facility
may or may not be owned by the same company that generates the
waste. OWR facilities fall into one of three commercial
status categories:
3-7
-------
3-8
-------
• commercial--facilities that accept waste from off-site
generators not under the same ownership as their
facility;
• noncommercial--facilities that accept waste only from
off-site generators under the same ownership as their
facility; and
• mixed commercial and noncommercial--facilities that
treat waste generated by other facilities under the
same ownership as their facility and also accept waste
from off-site generators not owned by the same
company.
Commercial waste treatment facilities are specialists in
waste treatment; it is their business. They generally do not
have manufacturing or other activities on site. They offer
one or more waste management services on a commercial basis
and accept waste from customers that are not part of the same
company. They compete with other commercial or mixed
commercial and noncommercial OWR facilities offering the same
services. Only waste that is managed commercially passes
through the market for OWR services.
Noncommercial waste treatment facilities are typically
located at manufacturing sites. The noncommercial waste
treatment operations at these sites manage waste generated on
site and also manage waste generated at other sites owned by
the same company. Because of the potentially large
liabilities associated with hazardous waste, companies
sometimes choose to manage their waste internally rather than
employ commercial waste management services. To take
advantage of economies of scale in waste management
operations, they may choose to centralize their waste
management operations. For such facilities, managing waste
generated by off-site facilities under the same ownership is
frequently regarded as a "cost of doing business," similar to
centralized accounting or legal services provided for the
entire company by a company division. The facilities may
receive revenues directly for the treatment services (usually
at a lower price than would be charged by a commercial
3-9
-------
treater), or they may be reimbursed for expenses. Changes in
the quantities of waste managed noncommercially do not affect
the market for OWR services.
Finally, some facilities offer both commercial and
noncommercial services. Generally, these facilities have
excess treatment capacity and choose to use it to manage waste
generated by facilities not under the same ownership. These
facilities are referred to as mixed commercial and
noncommercial OWR facilities.
In addition to managing wastes generated off site on a
commercial, noncommercial, or mixed commercial and
noncommercial basis, most OWR facilities manage waste
generated on site. Some treatment processes generate
residuals, which are new wastes that are usually smaller in
volume and/or less toxic than the original waste, but which
must still be managed as hazardous wastes. Such residuals
include stabilized sludges from wastewater treatment, still
bottoms from solvent recovery, and scrubber water from
incineration. Also, many OWR facilities are also
manufacturing sites, and the manufacturing activities generate
waste that must be managed.
The TSDR Survey includes information about the commercial
status of facilities. In each treatment process
questionnaire, facilities were asked for the quantity of waste
managed in each process that is generated on site and treated
on site, the quantity that is received from another off-site
facility under the same ownership and treated on site, and the
quantity received from an off-site facility not under the same
ownership and treated on site.
3-10
-------
Table 3-2
3-11
-------
TABLE 3-2. NUMBER OF FACILITIES TREATING WASTE, BY
PROCESS AND COMMERCIAL STATUSa
Wds Le
type
Commercial
Noncommercial
On site
Total
U-L 1
22
2b
25
35
Q1 2
9
18
10
26
Q1 3
7
4
8
11
Q1 4
23
8
13
24
Q1 5
14
7
8
20
Q1 6
26
10
14
30
Q1 7
27
28
31
50
Q1 8
46
40
40
68
Q1 9
2
1
1
2
Q1 10
25
22
33
44
Q2 1
12
13
14
21
Q2 2
9
18
10
26
Q2 3
7
0
3
7
Q2 4
19
6
11
20
Q2 5
4
2
1
6
Q2 6
14
5
8
18
Q2 7
37
32
31
60
Q2 8
37
33
31
55
Q2 9
1
0
1
1
Q2 10
18
18
29
37
Q3 1
19
21
22
32
Q3 2
13
20
12
31
Q3 3
29
5
13
32
Q3 4
26
9
14
27
Q3 5
29
11
10
37
Q3 6
19
10
13
26
Q3 7
78
67
65
113
Q3 8
37
34
33
56
Q3 9
9
6
7
10
Q3 10
31
25
37
52
(continued)
3-12
-------
TABLE 3-2. NUMBER OF FACILITIES TREATING WASTE,
BY PROCESS AND COMMERCIAL STATUSa (continued)
Wds Le
type
Commercial
Noncommercial
On site
Total
q4 1
2b
32
32
4S
Q4 2
36
23
16
56
Q4 3
66
14
33
71
Q4 4
23
7
15
24
Q4_5
98
33
27
117
Q4 6
10
5
6
13
Q4~7
38
32
32
61
Q4 8
34
32
29
51
Q4 9
8
6
5
9
Q4 10
32
27
39
56
Q5 1
22
26
26
37
Q5 2
24
21
13
42
Q5 3
43
11
21
47
Q5 4
28
7
16
29
Q5 5
60
15
16
67
Q5 6
10
5
6
13
Q5 7
23
27
30
44
Q5 8
38
39
34
60
Q5 9
4
4
3
6
Q5 10
24
25
36
48
Q6 1
18
20
22
32
Q6 2
15
23
15
36
Q6_3
14
6
13
19
Q6 4
25
6
15
26
Q6~5
24
12
12
33
Q6 6
20
6
10
24
Q6~7
52
41
44
83
Q6 8
43
35
33
63
Q6 9
5
5
5
7
O6~10
129
146
272
341
a As noted in Section 3.2, the majority of the data used to construct
this table come from the TSDR/GENSUR database and reflect waste
management patterns in 1986. Regulatory and other changes since
1986 have resulted insignificant changes in both the quantities and
patterns of hazardous waste management. Thus, the patterns
reflected in Tables 3-2 and 3-3 may no longer be accurate. They do
reflect the best and most current data available to the Agency.
3-13
-------
shows the number of facilities managing each type of waste
commercially and the number of facilities managing each type
noncommercially on an off-site basis, as well as the number of
facilities generating each waste type on site and managing it
on site. Waste type Qi_j represents waste of form i managed
in process j, as defined in Table 3-1.
3-14
-------
3-15
-------
OWR services offered on a commercial basis are shown in the
first column. This column represents the numbers of
facilities active in each OWR market at baseline. The second
column shows the number of facilities offering OWR services on
a noncommercial basis. The third column shows the number of
wastes generated on site and treated on site. Finally, the
total column shows the number of facilities managing each
waste form in each process, regardless of the source of the
waste. Note that the individual columns do not sum to the
total because one facility may manage the same waste form in
the same process on a commercial, noncommercial, and on-site
basis. Summing across the columns would triple-count that
facility.
3.4 QUANTITIES OF WASTE MANAGED BY OWR FACILITIES
Table 3-3 provides quantities of each waste type managed
in 1986.
3-16
-------
T
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
3-3. QUANTITIES OF WASTE MANAGED AT OWR FACILITIES,
BY PROCESS AND COMMERCIAL STATUSa
coiningrciai woncoiiiiiiyi'ciai on yiiy iot^tT
(Mg) (Mg) (Mg) (Mg)
6,
6 b 9
13,b8b
1,681
9 b 6
1,702
2 0 1
107
389
12
053
12
548
392
0
43
435
38,
992
338
62
970
102
299
3,
841
9
653
4
503
234,
918
39,344
139
394
413
656
9,
247
6,561
181
503
197
311
1,004,
531
76,658
8, 672
851
9,754
040
74
1
11
86
5,
4 97
1,702
350
824
358
023
853
138
906
634
907
626
8,
351
4 61
12
075
20
888
16,
7 97
0
607
17
405
87,
618
1,367
147
409
236
395
4,
720
132
93
4
946
9,
894
263
120
470
130
628
101,
757
23,172
2,175
835
2,300
7 64
688,
666
45,257
8,707
414
9,441
337
2,
382
0
1
852
4
235
84,
814
170
126
357
211
341
15,
417
6,626
1,427
131
1,449
173
22,
600
107,836
62
586
193
023
15,
364
30
8
333
23
727
78,
025
278
68
594
146
897
13,
444
26,065
2
870
42
379
52,
135
2,080
134
605
188
820
2,945,
628
29,274,964
49,328
691
81,549
282
454,
460
69,621
679
314
1,203
395
234,
539
131,783
1,528
316
1,894
638
181,
833
36,837
4,766
706
4,985
375
124,
216
38,090
2,384
496
2,546
802
196,
986
5,942
313
408
516
335
1,427,
190
3,239
43
731
1,474
160
20,
738
64
146
941
167
743
1,353,
433
104,770
177
765
1, 635
969
4,
647
4 9
20
194
24
889
139,
811
9,046
5,413
749
5,562
606
125,
291
9,142
634
048
768
480
11,
685
2,404
4
158
18
248
40,
902
762
129
344
171
008
(continued)
3-17
-------
TABLE 3-3. QUANTITIES OF WASTE MANAGED AT OWR FACILITIES,
BY PROCESS AND COMMERCIAL STATUSa (continued)
way to
commercial
Noncommercial
on sits
Total
type
(Mg)
(Mg)
(Mg)
(Mg)
Q5 1
35,207
11,714
1, 622, 216
1,669,137
Q5 2
97,654
1,155
1,395,629
1,494,438
Q5 3
1,198,104
3,696
10,660
1,212,460
Q5 4
139,339
601
162,745
302,685
Q5 5
1,136,392
4,439
3,186
1,144,017
Q5 6
6,719
323
23,610
30,652
Q5 7
64,459
2,490
2,417,021
2,483,969
Q5 8
503,721
144,653
3,683,509
4,331,883
Q5 9
7,968
26,076
283,650
317,694
Q5 10
19,841
270
6,686,798
6,706,908
Q6 1
11,283
7,764
2,954,280
2,973,327
Q6 2
7,392
1,661
67,411
76,463
Q6 3
3,720
577
10,395
14,692
Q6 4
69,718
55
69,125
138,898
Q6 5
7,465
757
142,157
150,379
Q6 6
126,200
1,235
96,970
224,406
Q6 7
2,869,826
1,
689,773
55,343,005
59,902,603
to
-------
Several overall observations should be made about this
table. First, the table shows the total quantities of each
waste type managed in 1986 at OWR facilities that will be
affected by the regulation. Of that quantity, the wastes
shown in the first two columns originate off site and are thus
subject to the regulation. A share of the waste shown in the
third column, derived from the treatment of off-site waste, is
also covered by this regulation. Only the treatment of
commercial waste, shown in the first column, is traded in the
market. The first column thus represents the quantity
supplied in each waste management market. Of specified waste
types (not counting "other") aqueous waste managed in
wastewater treatment is the highest volume category, both for
commercial waste management and overall. This is reasonable
because aqueous waste is usually relatively dilute and
correspondingly high in volume. The second largest quantity
of waste managed commercially in 1986 is organic liquids
managed in fuel blending.
3-19
-------
3-20
-------
Historically, more waste is generated and managed on site
than is sent off site for management. Because the waste
management facilities subject to this regulation are only
those that accept waste from off site, this pattern is not
true for some of the waste types they manage. For many of the
waste types shown in Table 3-3, the largest share of the waste
managed at OWR facilities comes from off-site facilities not
under the same ownership; that is, it is managed commercially.
3.5 LOCATION OF OWR FACILITIES
OWR facilities are located in 46 states and Puerto Rico.
The states with the highest concentration of waste management
facilities are California, Ohio, Texas, and Michigan. Table
3-4
3-21
-------
TABLE 3-4. LOCATION OF OWR FACILITIES, BY STATE
d la le
W umbei
teicenL
AK
3
0 . 41
AL
11
1. 52
AR
7
0. 97
AZ
10
1.38
CA
74
10.21
CO
2
0.28
CT
22
3. 03
DE
2
0.28
FL
13
1.79
GA
13
1.79
HI
3
0 . 41
IA
8
1.10
ID
2
0.28
IL
33
4 . 55
IN
26
3.59
KS
6
0.83
KY
16
2 .21
LA
17
2 . 34
MA
10
1.38
MD
9
1.24
MI
31
4 .28
MN
14
1. 93
MO
17
2 . 34
MS
6
0.83
MT
2
0.28
NC
17
2 . 34
ND
1
0 .14
NE
1
0 .14
NH
1
0 .14
NJ
32
4 . 41
NV
2
0.28
NY
36
4 . 97
OH
57
7.86
OK
13
1.79
OR
4
0 . 55
PA
33
4 . 55
PR
8
1.10
RI
6
0.83
SC
18
2 . 48
TN
10
1.38
TX
54
7 . 45
UT
8
1.10
VA
17
2 . 34
VT
2
0.28
WA
16
2 .21
WI
20
2 .76
WV
12
1.66
Total
725
100.00
3-22
-------
shows the number of facilities located in each state.
Since OWR facilities offer different services, facilities
located near one another may not be in the same markets.
Likewise, an OWR facility may compete with facilities located
a long distance away, if the services offered are similar.
Section 4 examines the structure of the markets in which OWR
facilities interact.
3.6 FACILITY SIZE
Facility size can be defined in terms of total quantity
of waste treated (throughput), number of employees, or total
revenues and costs. OWR facilities vary widely in size, no
matter which measure is used. This section examines facility
size using each definition in turn.
3.6.1 Facility Throughput
3-23
-------
Table 3-5
3-24
-------
TABLE 3-5. FACILITY SIZE BY THROUGHPUT
3-ba. Total Quantity ot waste Managed
Number
Percent
0 Mg or missing response
4
0 . 6
500 Mg or less
174
24 . 0
501 to 1,000 Mg
54
7.4
1,001 to 50,000 Mg
332
45.8
50,001 to 1,000,000 Mg
122
16.8
Over 1,000,000 Mg
39
5.4
Total
725
100.0
3-5b. Quantity of Waste Generated
on Site and Managed
on Sitea
Number
Percent
0 Mg or missing response
213
29.4
1 to 100 Mg
123
17 . 0
101 to 50 0 Mg
66
9.1
501 to 10,000 Mg
141
19.4
10,000 to 100,000 Mg
93
12 . 8
Over 10 0,000 Mg
89
12.3
Total
7~2~5
100.0
3-5c. Quantity of Noncommercial Waste Managed at OWR
Facilities
Number
Percent
0 Mg or missing response
351
48.5
1 to 10 Mg
92
12 . 7
11 to 100 Mg
85
11. 7
101 to 50 0 Mg
59
8 .1
501 to 1,000 Mg
19
2 . 6
Over 1,000 Mg
119
16.4
Total
725
100.0
3-5d. Quantity of Commercial Waste
Managed at OWR
Facilities
Number
Percent
0 Mg or missing response
275
37.9
1 to 100 Mg
57
7 . 9
101 to 50 0 Mg
73
10 .1
501 to 5,000 Mg
129
17 . 8
5,001 to 10,000 Mg
43
5.9
Over 10,000 Mg
148
20.4
Total
725
100.0
Includes waste generated by manufacturing and waste
management.
3-25
-------
shows the number of OWR facilities in various size
categories, defined by facility throughput. OWR facilities
responding to the TSDR Survey were asked to list the total
quantity of waste managed on site for three "where-was-it-
generated" categories:
• waste that was managed on site and was also generated
on site,
• waste that was managed on site but was generated off
site at a facility under the same ownership as the OWR
facility, and
• waste that was managed on site but was generated
off site at a facility not under the same ownership as
the OWR facility.
Facilities included in the analysis include 710 with data
from the TSDR Survey and 15 with data from the CWT Survey. Of
these 725 facilities, 721 reported positive quantities treated
or recovered on site. These 721 facilities reported total
quantities managed on site ranged from a fraction of a metric
ton to 89.4 million Mg. As shown in Table 3-5a, only 39
facilities reported managing more than 1 million Mg of
hazardous waste in 1986; 178 facilities reported managing less
than 500 Mg on site in 1986. Only 54 facilities managed
between 501 and 1,000 Mg, while 332 managed between 1,001 and
5 0,000 Mg.
Of the 725 facilities in the database, 512 report
managing some positive quantity of waste that was also
generated on site. The quantities of waste generated range
from fractions of a Mg to 88.9 million Mg (see Table 3-5a).
As described above, many facilities that manage waste from off
site also manufacture products at the same site and generate
waste in their manufacturing processes. Not all facilities
reporting on-site generation are manufacturing sites, however.
As noted earlier, most waste treatment processes generate
waste in the course of treating it. For example, incineration
generates ash; wastewater treatment generates sludge; solvent
recovery generates still bottoms. Thus, almost all waste
3-26
-------
management facilities are also waste generators. Table 3-5b
shows the number of facilities managing waste generated on
site.
Accepting waste from off-site qualifies facilities for
coverage under the regulation. There are two categories of
off-site waste:
• off-site waste generated by other facilities under the
same ownership as the OWR facility (waste accepted on
a noncommercial basis) and
• off-site waste generated by a facility not under the
same ownership as the OWR facility (waste accepted on
a commercial basis).
Table 3-5c shows numbers of facilities treating various
quantities of off-site noncommercial waste, while Table 3-5d
shows numbers of facilities treating various quantities of
off-site commercial waste. Only 384 facilities report
managing positive quantities of off-site waste on a
noncommercial basis while 450 facilities manage positive
quantities of off-site waste commercially. Overall,
facilities tend to manage larger quantities of waste on a
commercial basis than on a noncommercial basis.
Quantities of noncommercial waste range from fractions of
a Mg to 18.7 million Mg. Many facilities accept only small
quantities of off-site noncommercial waste; 236 of the 374
accept less than 500 Mg, and only 119 facilities manage more
than 1,000 Mg of noncommercial off-site waste.
Quantities of commercial waste managed range from a
fraction of a Mg to 4.2 million Mg; 148 facilities manage more
than 10,000 Mg.
3.6.2 Number of Employees
OWR facilities were asked in the TSDR, GENSUR, and CWT
Surveys to list the number of employees they had in several
employment categories: waste management, production,
administrative, and total. Table 3-6 gives employment
information for OWR facilities. For the 551 facilities
3-27
-------
providing employment data, employment at OWR facilities ranged
from one employee to 45,000 employees. Nearly 50 percent of
facilities had fewer than 100 employees. Most commercial
waste management facilities with no nonwaste-based
manufacturing on site have relatively few employees. The
facilities with large numbers of employees include
manufacturing facilities in the chemicals and refining
industries and a Naval base. Frequently, their waste
management operations are fairly small. Table 3-6a
3-28
-------
TABLE 3-6. EMPLOYMENT AT OWR FACILITIES
3-6a. Total Employment
Number
Percent
25 or fewer
137
25.2
26 to 100
122
22 . 4
101 to 500
103
18. 9
501 to 1,000
44
8 .1
1,001 to 5,000
81
14 . 9
Over 5,000
57
10 . 5
Total
544
100 . 0
3-6b. Waste
Management Employment
Number
Percent
5 or fewer
181
34.0
6 to 10
120
22 . 5
11 to 20
97
18 . 2
21 to 100
112
21. 0
Over 100
23
4.3
Total
533
100 . 0
3-6c. Other
Employment
Number
Percent
10 or fewer
113
21. 2
11 to 25
61
11. 5
26 to 100
88
16.5
101 to 1,000
133
25.2
1,001 to 5,000
81
15.1
Over 5,000
56
10 . 5
Total 5^2 100 .IT
3-29
-------
shows the pattern of total employment at OWR facilities.
As Table 3-6b indicates, waste management employment is
much less than total employment for some facilities.
Employment in this category ranges from one to 2,000; 50
percent of facilities have fewer than ten employees and 75
percent have 20 or fewer employees in waste management
operations. Other (nonwaste-management) employment varies
widely, ranging from zero to 44,991, as Table 3-6c
demonstrates. Many OWR facilities specialize in waste
management and have relatively few employees in the "other"
category. Thus, more than 30 percent of facilities have 25 or
fewer nonwaste-management employees, and 50 percent have fewer
than 120. At the other end of the spectrum are large
manufacturing or federal facilities, for whom waste management
is a small share of the total employment. Thus, more than 25
percent of facilities have more than 1,000 "other" employees,
and 5 percent have more than 22,000.
In addition to being a measure of facility size,
facility-level employment is of interest to the Agency
because, if production falls at a facility as a result of a
regulation, some of its employees may become unemployed. As
residents of the community, these people who are now
unemployed would consume fewer goods and services, thereby
affecting the economic health of the entire community.
Unemployment results in real costs are discussed in Section
6.4.
3.6.3 Facility Revenues
Facility size may also be defined in terms of facility
revenues. Facility revenues were estimated for all OWR
3-30
-------
facilities with commercial operations by multiplying the
quantity of waste managed commercially in each process times
the price per Mg for managing waste in that process, and
summing across all the commercial processes at the facility.
Obviously, facilities may obtain revenues from other sources
(manufacturing operations, noncommercial OWR operations), but
the Agency has no data on those revenues. Of 725 OWR
facilities, 275 have no commercial operations on site and
therefore no commercial revenues. For the remaining 450
facilities, estimated OWR commercial revenues range from less
than $100 to more than $3 billion. Table 3-7 shows facility
revenues from commercial OWR operations.
As shown in Table 3-7, more than 22 percent of OWR
facilities have commercial revenues less than $250,000.
Approximately 40 percent of facilities have commercial
revenues less than $1 million. Approximately 24 percent have
revenues between $5 million and $20 million. Only 14 percent
have revenues exceeding $20 million.
Revenues are also important in defining company size.
Section 4.2 discusses company revenues.
TABLE 3-7. FACILITY COMMERCIAL OWR REVENUESa
Number ui =
facilities Percent
Less than $250,000 KT3 22. 9
$250,000 to $1 million 88 19.6
$1 million to $5 million 89 19.8
$5 million to $20 million 107 23.8
Over $20 million 63 14.0
a 275 OWR facilities have no commercial OWR revenues.
3-31
-------
3.7 COMPANY FINANCIAL PROFILE
OWR facilities, which include a site of land with plant
and equipment, combine inputs (materials, energy, and labor)
to produce outputs (waste treatment services, clean solvents,
and residuals). Companies that own the OWR facilities are
legal business entities that have the capacity to conduct
business transactions and make business decisions that affect
the facility. The terms facility, establishment, and plant
are synonymous in this analysis and refer to the physical
location where waste treatment and disposal services are
performed. Likewise, the terms company and firm are
synonymous and refer to the legal business entity that owns
one or more facilities. Section 3.7.1 of this report
describes the data sources used to compile the company
financial profile. Following the description of data sources,
the population of potentially affected companies is described
using three characteristics:
• company size expressed in annual receipts,
• degree of vertical and/or horizontal integration, and
• cost of capital and capital structure.
Each of these characteristics influences how a regulatory
action affects firms and how the company-level analysis is
approached.
3.7.1 Data Sources
Of the 725 OWR facilities initially identified as
affected by the proposed regulation, 61 are owned by
government entities and are therefore excluded from the
company-level impacts analysis. The Agency identified 406
companies as owners of the remaining 664 OWR facilities.
Analysis of the financial impacts of the regulation on these
406 companies using the techniques adopted for this analysis
involves comparing these companies' baseline financial
statements with Agency projections of their financial
3-32
-------
statements after the regulation is in place. Income
statements and balance sheets are the two basic financial
statements kept by firms. The former reports the results of a
firm's operation during a period of time--usually 1 year. The
latter is a statement of the financial condition of the firm
at a point in time--usually December 31, or the last day of
the firm's fiscal year. These sources of data were not
available from reliable published sources for all firms
included in this analysis.* Data collection efforts for each
of the 406 potentially affected companies identified for this
analysis correspond to one of the following four approaches:
• Obtain complete (or nearly complete) financial
statements from reliable published sources.
• Identify the company's SIC code and obtain a point
estimate for the company's level of sales or assets
from published sources. Assign a financial health
indicator (above average, average, or below average)
to each company and construct the company's financial
statements using published financial ratios for an
"above average," "average," or "below average" company
in the corresponding industry (SIC code).
• Identify the company's SIC code and assume that the
company's only source of revenue is commercial sales
of OWR services at the market prices used for the
facility-level analysis. Assign a financial health
indicator (above average, average, or below average)
to each company and construct the company's financial
statements using published financial ratios for an
"above average," "average," or "below average" company
in the corresponding industry (SIC code).
• Exclude from the company-level impacts analysis
because of insufficient knowledge of company finances.
For a more detailed description of how financial statements were
constructed for companies with limited financial information available from
published sources, please turn to Appendix D.
3-33
-------
Table 3-8
3-34
-------
TABLE 3-8. DATA SOURCES
uaia source
£ 1IIIIS
£dClllLIBS
Type oi uaLa
Dun and Bradstreet Dun's Market Identifiers
2
2
Complete
(1993)
financial
statements
Moody's Industrial Manual (1992)
100
240
Complete
financial
statements
Waste Treatment Industry Questionnaire
58
144
Nearly complete
financial
statements
Ward's Business Directory ot U.S. Private
b b
114
Annual sales or
total assets
Business America Online (1993-94)
47
51
Annual sales
range, number of
employees
Other commercial operations
9'/
9'/
Facility level
revenues
Other noncommercial operations
16
16
No financial data
Subtotal
406
6 64
—
Government-owned facilities
61
—
Total
406
725
—
Other sources:
1992-1993.
Disposal, and Recycling Facilities. EPA Computer Database. Durham, NC. 1986.
Who Owns Whom? Dun & Bradstreet. New York, Dun & Bradstreet. 1990.
(EPA, 1989)
and Public Companies (1993)
-------
presents the sources of company-level financial information
used in this analysis, the number of firms and associated
facilities for which each source was used, and the types of
data available from each.
3-36
-------
Two of the sources identified in Table 3-8, Moody's
Industrial Manual15 and Dun's Market Identifiers,16 contain
complete financial statements for 102 firms. However, two of
these firms are excluded from this analysis because they are
foreign based and have different accounting practices from
U.S. firms. Data gathered through the CWT Survey are
sufficient to construct nearly complete financial statements
for another 58 firms. Consequently, complete (or nearly
complete) financial data are available for only 158 of the
potentially affected companies.
Financial statements were constructed using the approach
described in Appendix D for another 133 firms using total
revenues and/or total assets data available from Ward's
Business Directory of U.S. Private and Public Companies17 and
Business America Online.18
Company-level data are unavailable for the remaining 113
facilities. However, rough estimates of facility-level
revenues for commercial facilities are available from the
estimates of baseline quantities and prices described in
Section 4.* The remaining 113 facilities include 97
commercial facilities and 16 noncommercial facilities.
Financial statements were constructed for the firms that own
the 97 commercial facilities using the estimated facility-
level revenues and the approach described above. Implicit in
the methodology is the assumption that these firms own only
one facility and that firm-level revenues equal facility-level
waste management revenues. The 16 noncommercial facilities
and the firms that own them are not included in the company-
level analysis because data on revenues at either the company-
or facility-level are unavailable.
The 388 companies evaluated in this analysis include the
following:
The revenue estimates used for these 97 firms were obtained by
multiplying estimated waste quantities from the 1986 TSDR/GENSUR-databases
times the corresponding average prices for each waste from Table 4-3.
3-37
-------
• 158 for which financial statements were available from
published sources,
• 133 for which company-level revenues or total assets
are used in combination with D&B data to construct
financial statements, and
• 97 for which facility-level revenues are used in
combination with D&B data to construct financial
statements.
The baseline financial profile that follows is based on these
388 companies.
3.7.2 Company Size Distribution
The first characteristic by which companies are described
is company size expressed in annual receipts. Firm size is
likely to be a factor in the distribution of the regulatory
action's financial impacts. Grouping the firms by size
facilitates the analysis of small business impacts.
Furthermore, reporting the distribution of impacts by size
category helps ensure that sensitive, proprietary data are not
revealed for an individual firm.
The financial impacts of a regulatory policy depend not
only on the size distribution of potentially affected firms
but also on the size distribution of the potentially affected
facilities owned by these firms. For example, a firm with six
uncontrolled facilities with average annual receipts of $1
million per facility may face approximately six times the
control capital requirements of a firm with one uncontrolled
facility whose receipts total $6 million per year.
Alternatively, two firms with the same number of facilities
facing approximately the same control capital costs may be
affected very differently financially if one firm is
significantly larger than the other.
3-38
-------
TABLE 3-9. SIZE DISTRIBUTION OF POTENTIALLY AFFECTED
COMPANIES19"25
company size _lii
annual receipts
($106)
Number of
companies
To Lai annual
receipts ($106)
fiveiaye annual
receipts per
company ($106)a
<6
110
207
1.9
6 to 60
93
1, 882
20.2
60 to 1,000
80
26,319
329.0
Over 1,000
105
1,236,640
11,777.5
Total
388
1.2 65.049
3.2 60.4
a Computed by dividing total annual receipts by the number of
companies.
Potentially affected firms range in size from $100,000 to
over $116 billion in annual receipts. Table 3-9 shows the
size distribution of potentially affected companies by annual
receipts. Firms in the largest receipts category account for
approximately 98 percent of receipts for all potentially
affected firms. Figure 3-1
3-39
-------
shows the size distribution of potentially affected companies
in percentage terms. Ninety percent of the (smallest) firms
account for only about 20 percent of total annual receipts.
Conversely 10 percent of the (largest) firms account for about
80 percent of total annual receipts.
Firms may differ in size for one or both of the following
reasons:
• Potentially affected facilities vary widely by
receipts. All else being equal, firms with large
facilities are larger than firms with small
facilities.
• Firms vary in the number of facilities they own. All
else being equal, firms with more facilities are
larger than those with fewer facilities.
Table 3-10 shows the average size OWR facility (measured
in annual receipts) represented in each company size category.
Two estimates of facility receipts are presented in
Table 3-10. The first column of facility receipts corresponds
to commercial waste treatment only. The second column
corresponds to commercial as well as noncommercial waste
TABLE 3-10. AVERAGE SIZE OF OWR FACILITY BY COMPANY SIZE
C J 13* if" a'26'27
L'OilLjJd.Iiy Size ±L i
annual rvi
($l'0Twv"^1
Onl>
, Commercial
"operations
i„ommer uidl and
noncommercial
operations
<6
2. 9
X)
6 to 60
12 . 6
15 . 9
60 to 1,000
20. 9
166 . 0
Over 1,000
92 . 4
840.5
a All dollar figures expressed in $1991.
Figure 3-1. Size distribution of potentially affected companies.
3-40
-------
treatment. (Note that noncommercial waste treatment is valued
using market prices.) On average, large firms own larger
facilities based on the measure of facility receipts that
reflects both commercial and noncommercial waste treatment.
However, most of the output for facilities owned by firms in
the largest size category is from noncommercial waste
treatment. Consequently, facility receipts from commercial
waste treatment decline as firm size increases for firms over
$600 million in annual receipts.
Table 3-11 shows the distribution of firms by the number
of OWR facilities owned. Over three-fourths of the firms in
this analysis own only one OWR facility. Only two firms in
the smallest size category own more than one facility, and no
firms in the smallest size category own more than two
facilities. At the other end of the spectrum, approximately
40 percent of the firms in the largest size category own more
than one facility. Firms in the two largest size categories
account for over 85 percent of the multi-facility firms in
this analysis. Unaffected facilities (facilities that do not
perform off-site waste management) are not reflected in the
distributions shown in Tables 3-10 and 3-11.
TABLE 3-11.
DISTRIBUTION OF FIRMS BY NUMBER OF OWR
FACILITIES OWNED28"34
. . Number ui
Company size at ^ . , . ,
,c t . , facilities owned
baseline by ~.
, ^ per firm
volume of
annual
receipts (106)a
2
3
Total Total number Average
number of of number of
firms in facilities facili-
4 or size in size ties/
more category category firmb
<6
108
2
0
0
110
112
1. 02
6 to 60
85
5
0
3
93
121
1.30
60 to 1,000
57
9
4
10
80
171
2 .14
Over 1,000
61
18
11
15
105
239
2 .28
Total
311
34
15
28
388
643
1.66
All dollar figures expressed in $1991.
Computed by dividing total number of facilities by the total
number of firms in each size category.
3-41
-------
3.7.3 Vertical and/or Horizontal Integration
Vertical integration is a potentially important dimension
in firm-level impacts analysis because the regulation could
affect a vertically integrated firm on several levels. For
example, the regulation may affect companies for whom waste
treatment is not the company's primary focus but rather is an
input into the company's other production processes such as
chemical manufacturing. Consequently, vertically integrated
companies tend to have proportionately more noncommercial
waste treatment services than those for whom waste treatment
is their primary business.
Figure 3-2 shows the value of commercial waste treatment
services compared to the value of noncommercial waste
treatment services for firms in each size category.
Noncommercial waste treatment services are valued at market
prices for the purposes of comparison. Noncommercial waste
treatment services account for more than 90 percent of total
waste treatment services in the largest size category compared
to approximately 40 percent of total waste treatment services
Figure 3-2. Share of commercial versus noncommercial waste
treatment services.
3-42
-------
in the smallest size category and 20 percent of total OWR
services in the second smallest size category. This
difference in the share of noncommercial waste treatment is
evidence that larger firms tend to be more vertically
integrated than smaller firms. A regulation that increases
the cost of waste treatment for vertically integrated firms
will also affect the cost of producing the primary products.
This cost increase may be reflected in higher prices for the
primary products. Horizontal integration is also a potentially
important dimension in firm-level impact analysis, because a
diversified firm may own facilities in unaffected industries.
This type of diversification would help mitigate the financial
impacts of the regulation.
Figure 3-3 shows the share of total receipts from
business activities other than commercial waste treatment for
firms in each receipts size category. Firms in the two
largest size categories receive more than 90 percent of their
Figure 3-3. Share of total receipts from waste treatment
and all other activities.
3-43
-------
revenues from activities other than waste treatment. As noted
above, this high degree of diversification will help mitigate
the financial impacts of the regulation for large firms.
Firms with $6 million to $60 million in annual receipts
receive approximately 75 percent of their receipts from waste
treatment, and firms in the smallest size category receive
less than 20 percent of their revenues from activities other
than waste treatment. Consequently, smaller firms are likely
to be more directly affected by the regulation because a
higher proportion of their revenues are from waste treatment.
3.7.4 Cost of Capital and Capital Structure
A firm's cost of capital and its capital financing policy
will potentially affect the firm-level responses to the
regulation and the magnitude of the financial impacts
associated with those responses. This section presents a
framework for estimating the firm-specific cost of capital
used to evaluate investment decisions and a description of
capital structure employed by potentially affected firms.
In making investments, companies generally use two
sources of funds: equity and debt. Each source differs in
its exposure to risk, its taxation, and its cost. Equity
financing involves obtaining additional funds from owners:
proprietors, partners, or shareholders. Partners and
shareholders, in turn, can be existing owners or new owners.
Obtaining new capital from existing owners can be further
dichotomized into internal and external financing. Using
retained earnings is equivalent to internal equity financing.
Obtaining additional capital from the proprietor, one or more
existing partners, or existing shareholders constitutes
external equity financing. Debt financing involves obtaining
additional funds from lenders who are not owners; they include
buyers of bonds, banks, or other lending institutions.
EPA's CWT Survey contains firm-specific data on the cost
of capital used to evaluate investments in pollution control
equipment for a portion of the firms included in this
3-44
-------
analysis.35 To estimate the cost of capital for the remaining
firms, the weighted average costs of equity and debt financing
(after tax) were computed using information from firms'
financial statements and assumptions grounded in financial
theory. The cost of debt financing was estimated for these
firms using the following equation:
WACC = Wd (1 -1) *Kd + We-Ke, (3-1)
where
WACC = weighted average cost of capital
Wd = weighting factor on debt
t = marginal effective State and Federal corporate
tax rate averaged for U.S. firms
Kd = the cost of debt or interest rate
We = weighting factor on equity.
Ke = cost (required rate of return) of equity
This formula implicitly assumes that investments in pollution
control equipment are similar in risk to other projects that
the company has taken or is considering. In addition, the
formula assumes that the method of financing for control
equipment is similar to other investments by the firm.
To estimate the WACC, first values for Kd and Ke were
estimated. All else being equal, the cost of both debt and
equity capital is generally higher for firms in below-average
financial condition than for firms in above-average financial
condition. This analysis estimated the cost of debt for firms
in above-average, average, and below-average financial health
categories to be 8.29 percent, 9.16 percent, and 12.91
percent, respectively. However, because debt interest
payments are deductible for State and Federal income tax
purposes, a more meaningful measure of the cost of debt
financing is the after-tax cost of debt capital. The after-
3-45
-------
tax debt costs used in this analysis for firms in three
different financial health conditions are
• 5.78 percent for firms in above-average financial
condition,
• 6.38 percent for firms in average financial condition,
and
• 9.00 percent for firms in below-average financial
condition.
The Agency used the Capital Asset Pricing Model described
in detail in Appendix E, and assumptions based on data
obtained from the literature to estimate the cost of equity
capital for firms in each of three financial conditions. The
following equity capital costs were chosen as most
appropriate:
• 14.57 percent for firms in above-average financial
condition,
• 15.96 percent for firms in average financial
condition, and
• 19.88 percent for firms in below-average financial
condition.
Next, the weighting factors for debt (Wd) and equity (We)
were calculated for each company. These weights reflect the
share of firm assets that are financed with debt and equity.
The theoretically correct weights are target weights rather
than historical weights. Target weights reflect individual
firms' subjective preferences in the tradeoff between the tax
advantages of debt financing vs. the financial distress costs
associated with higher levels of debt.* For this analysis the
Agency assumed that the capital structure witnessed for firms
at baseline approximates their target or optimal capital
structure and that firms minimize their cost of capital at
baseline. Furthermore, it was assumed that book-value weights
*See Appendix E for a more detailed discussion of a firm's optimal
capital structure.
3-46
-------
TABLE 3-12. SUMMARY STATISTICS BY FIRM SIZE CATEGORY OF
WEIGHTING FACTORS FOR DEBT USED TO CALCULATE FIRMS'
BASELINE WACC36"43
Number of
observations
Mean
Standard
deviation
Quartiles
Upper
Median
Lower
Company size in annual receipts ($10b/year)
$60 to
$0 to $6 $6 to $60 $1, 000 Over $1,0 00
110
0.2751
0 .1554
0.3364
0.2745
0.166
93
0.2977
0.188
0 . 375
0 .2679
0 .166
0.2888
0.2082
0.3823
0.2682
0 .166
105
0 .3945
0.1986
0.5317
0.379
0 .2691
approximate market-value weights in instances where market
value weights are not available.
Table 3-12 summarizes the capital structure of
potentially affected firms in this analysis. The debt-to-
firm-value ratios summarized in Table 3-13 are the weighting
factors for debt (Wd) used to compute the WACC. The equity
weighting factors are simply 1 - Wd. Some of the potentially
affected firms in this analysis have a Wd greater than 100
percent, indicating that the book value of equity is actually
negative. It was assumed that the correct Wd for these firms
is 0 percent, reflecting the assumption that the debtholders
are, in effect, the owners of the firm. Consequently, the
required return is equal to Ke with We at 100 percent.
A real (inflation-adjusted) cost of capital is desired,
so employing the gross national product (GNP) implicit price
deflator for the 10-year period 1983 to 1992 adjusts nominal
rates to real rates. Using an adjustment factor of 3.72
percent assumes that the inflation premium on real rates is
the actual rate of inflation averaged over the last 10 years.44
3-47
-------
TABLE 3-13
SUMMARY STATISTICS BY FIRM SIZE CATEGORY OF
FIRMS' BASELINE WACC45"52
Number of
observations
Mean
Standard
deviation
Quartiles
Upper
Median
Lower
Company size in annual receipts ($10b/year)
$60 to
$0 to $6 $6 to $60 $1, 000 Over $1,0 00
110
0.0988
0 .0194
0.103
0.0963
0 .0875
93
0.0968
0.0178
0.103
0 .0955
0.0869
0 .0904
0.0186
0.1015
0.0926
0.0816
105
0.083
0.0185
0.0932
0.0822
0.0687
Table 3-13 summarizes the baseline WACC for potentially
affected firms as reported in the CWT Survey or estimated as
described above.
3-48
-------
SECTION 4
DEVELOPMENT OF THE OWR INDUSTRY BASELINE
Estimating the impacts of the regulatory alternatives on
the OWR facilities managing the 60 waste types introduced in
Section 2 of this report requires detailed information about
the quantity of individual types of waste that are treated at
each OWR facility, as well as an understanding of how the
average costs of treating different types of waste may vary.
Much of the waste managed at some OWR facilities is
either generated on site or is generated at off-site
facilities owned by the same company as the OWR facility. For
several reasons, EPA chose to analyze the impacts of the
regulatory alternatives on commercial OWR activities
separately from its analysis of impacts on noncommercial OWR
services. Many companies owning OWR facilities treating off-
site noncommercial waste may elect to continue treating those
wastes regardless of the profitability of their commercial
waste management operations (if any) and the increased costs
of treating the off-site noncommercial wastes. Also,
facilities may or may not receive revenue for managing
noncommercial waste. Thus, although the analysis of impacts
on commercial OWR services estimates impacts for each facility
managing off-site waste commercially, the increased costs of
noncommercial OWR services were assumed to be felt by the
company as a whole. Most of the computations described in
this section were performed for all affected facilities.
This section profiles baseline conditions at the facility
level, market level, and the company level.
4-1
-------
4.1 BASELINE FACILITY CONDITIONS
Baseline conditions at the facility level can be
characterized in terms of the quantity of specific waste types
managed at each OWR facility, the costs associated with
treating or disposing of each waste type managed, and the
market prices charged for each management service provided
commercially.
4.1.1 Estimating Baseline Quantities
Three sources of information were used to estimate the
baseline quantity of individual waste types managed at
affected OWR facilities. Baseline quantities managed at the
710 RCRA-regulated facilities were estimated by combining
information from the TSDR and GENSUR Surveys. As described in
Section 2 of this report, the TSDR Survey provides the total
quantity of waste managed commercially and noncommercially in
each treatment process at each facility but does not provide
any information on the characteristics of specific waste
streams managed in each process. The GENSUR, on the other
hand, offers a detailed characterization of wastes generated
in 1986 and identifies the quantity of each waste sent off
site for management. The GENSUR also asks generators to
identify the OWR facilities to which each waste stream was
sent as well as for the generators' best guess of which
treatment, recovery, or disposal processes would be used to
manage each waste stream at the destination OWR facility.
The Agency employed a very elaborate approach (described
in great detail in Appendix F) to combine useful information
from both surveys to prepare its best estimate of the quantity
of each of the 60 waste types described in Section 2 that was
managed, commercially and noncommercially, at each OWR
facility. In this approach, the Agency used waste form
information from the GENSUR to disaggregate the total process
quantities reported in the TSDR Survey into different waste
types based on composition. Table 4-1
4-2
-------
TABLE 4-1. ESTIMATED AGGREGATE QUANTITIES OF EACH WASTE FORM
PROCESSED IN EACH TREATMENT CATEGORY BY THE 710 OWRs THAT
RESPONDED TO THE TSDR SURVEY (Mg)
Piuuybb MJ-Lill i MJ-Lill 2 MJ-Lill J MJlill *4 MJlill J MJlill U TUldl
Q1 1,702,201 907,625 1,449,173 2,546,803 1,669,137 2,973,327 11,248,266
Q2 12,548 20,887 193,023 516,336 1,494,438 76,463 2,313,695
Q3 436 17,404 23,726 1,474,160 1,212,459 14,692 2,742,877
Q4 102,299 236,395 146,897 167,743 302,685 138,899 1,094,918
Q5 4,504 4,946 42,380 1,635,969 1,144,017 150,379 2,982,195
Q6 413,656 130,628 188,821 24,890 30,651 224,405 1,013,051
Q7 197,312 2,300,764 56,502,062 5,562,605 2,483,969 59,902,603 126,949,315
Q8 9,754,040 9,441,337 1,203,394 768,480 4,331,883 40,262,473 65,761,606
Q9 86 4,234 1,894,638 18,248 317,694 609,535 2,844,435
Q10 358,023 211,342 4,985,376 171,007 6,706,910 37,431,697 49,864,355
Total 12,545,105 13,275,561 66,629,490 12,886,241 19,693,843 141,784,473 266,814,713
-------
presents the
-------
estimates for the 710 RCRA-regulated OWR facilities. Figure
4-1 presents the same information graphically. Approximately
half of the 266,814,713 Mg of waste that was reportedly
managed in regulated processes at affected RCRA-regulated OWR
facilities was managed using wastewater treatment (process Q7)
and about a quarter was managed in OWR facility landfills
(process Q8).
All waste quantity information for the 15 non-RCRA
140
130
100
SO
U3
o
60
40
£0
Form 1
Form 2
Form 3
Form 4
Form 5
Form 6
Figure 4-1. Treatment categories most commonly used to manage each
waste form.
4-5
-------
wastewater treatment OWR facilities was obtained from the 1989
CWT Survey conducted by EPA's Office of Water. These
facilities manage an estimated 22,067,009 Mg of waste from off
site annually. The Agency assumes that all of this waste is
of Form 3 and is managed in wastewater treatment (process Q7).
4.1.2 Estimating Baseline Costs
Process-specific waste management costs were estimated
using production and cost functions developed by Research
Triangle Institute (RTI) and published in A Profile of the
Market for Hazardous Waste Management Services for EPA's
Office of Air Quality Planning and Standards. The waste
treatment categories for which production and cost functions
were developed include rotary kiln/hearth incineration,
chemical precipitation, chemical stabilization/fixation, steam
stripping, and landfills. Using these functions, the Agency
estimates baseline cost per Mg of treatment that vary with the
quantity treated. Appendix G provides a more detailed
description of these production and cost functions and their
use in estimating costs per Mg for each process at each OWR
facility.
4-6
-------
Table 4-2
4-7
-------
TABLE 4-2. MODEL PROCESSES USED TO ESTIMATE COSTS
ulnlk LreaLmenL Pioceaa used iui inpuL idcLui quanLiLy
category and cost estimation
Ql
Incineration
Rotary kiln/hearth incineration
Q2
Reuse as fuel
Rotary kiln/hearth incineration without
fuel as a required inputa
Q3
Fuel blending
Chemical precipitation without
chemicals as required inputs13
Q4
Solidification
Chemical stabilization/fixation
Q5
Solvent recovery
Steam stripping
Q6
Metals recovery
Chemical precipitation with doubled
lime and polymer requirements0
Q7
Wastewater treatment
Chemical precipitation
Q8
Landfills
Landfills
Q9
Underground injection
Underground injection
Q10
Other
Average unit costs of all other
processes
a Fuel is omitted from the list of input factors because the wastes
managed in this process have a high enough Btu content to fuel the
kiln or furnace.
b A production function specifically for fuel blending was not
available. Fuel blending generally involves storage tanks with
mixing and transfer capabilities. If chemicals are not included,
the remaining input requirements of labor, electricity, water, and
indirect operation and maintenance (O&M) are roughly comparable to
a chemical precipitation process.
c The greater the concentration of the waste stream processed, the
greater the chemical requirements for chemical precipitation.
4-8
-------
identifies which of these production and cost functions was
used to estimate costs for each of the 10 OWR treatment
processes affected by the proposed regulation. Each
production function was used to estimate the quantity of each
management process input that is required to treat, recover,
or dispose of 1 Mg of waste; the required input quantity per
unit of waste throughput as specified as a function of the
waste volume managed. The Agency has limited information
about how the required quantity of each input to a given
treatment process may vary across each of the six waste forms
potentially managed in the given process. Because of these
data limitations, the Agency used a single production function
to estimate input requirements for each waste form managed in
each treatment process at each facility. The estimated
4-9
-------
quantity of each required input to a given treatment process
will vary across each waste form managed in the process,
because the input requirements are estimated as a function of
the quantity managed. Input requirements for individual waste
forms were estimated separately for each treatment process,
based on the volume of each waste form managed in each
process.
After identifying the input quantities needed to manage 1
Mg of each waste form in each process at a given OWR facility,
the Agency calculates the average variable cost per Mg of each
waste type managed at the facility by multiplying the relevant
input quantities by mid-year 1991 input factor prices for each
input to the process, and then summing across all process
inputs. Total variable costs of managing each of the 60 waste
types at each facility were calculated by multiplying the
estimated cost per Mg by the facility's total throughput
volume (Mg) of the corresponding waste type.
4.1.3 Estimating Baseline Prices
For this analysis, the Agency grouped the 27,000 OWR
transactions identified from the 1986 GENSUR and TSDR Surveys
into 60 competitive markets for OWR services. Modeling the
OWR industry as a competitive market assumes that individual
facilities are price-takers not price-setters. Each waste
type (waste form-treatment category combination) was assumed
to be a homogeneous service with a single market price. Thus
the Agency selected 60 market prices for the 60 waste types
defined in this analysis. This simplifying assumption
recognizes the competitive forces at work in the OWR industry
but doesn't account for the complexity of actual operations at
OWR facilities. In fact, OWR facilities may set prices on a
batch-by-batch basis, based on the characteristics of each
batch accepted, such as the following:
• concentration (percentage of solids),
• percentage of oil,
• percentage of total organic carbon,
4-10
-------
• content of various metals, and
• Btu content.
In addition, the per-batch price of a given waste type
may vary based on the way it is packaged upon delivery to the
OWR facility. For example, a batch of waste of a given volume
and constituent make-up will generally be accepted at a
somewhat lower price if it is delivered to an OWR facility in
bulk form aboard a tanker or a dump-truck, than if it is
packaged in 55 gallon drums. A batch will be accepted at an
even higher price per megagram if it is delivered as the
residue left in "empty" 5 or 1 gallon containers, as lab-
packs, or in small vials. The market prices chosen for this
analysis reflect the prices of managing representative wastes
when delivered in bulk form.
Therefore, although all wastes of a given waste type are
similar, enough difference in the constituent make-up within
each market exists that a wide range of competitive prices may
actually be charged for managing wastes treated here as
homogeneous. The price information that was available from
the TSDR Survey was found to be incorrect, either because it
had never been satisfactorily verified or because prices have
changed considerably since 1986.
To estimate the "market price" for waste management in
each of the 60 markets, the Agency performed a statistical
comparison of all wastes managed in each of the 60 OWR markets
in terms of the constituent characteristics listed above. The
Agency then identified a model waste for 48 of the 60 markets
and asked several OWR facilities how much they would charge to
accept each of the model wastes that they are equipped to
manage.53 Interpretation of the responses received from
industry representatives was the basis for choosing market
prices for the six waste forms managed in each of the
following processes:
• incineration,
• reuse as fuel,
4-11
-------
• fuel blending,
• solidification/stabilization,
• solvent recovery,
• metals recovery,
• wastewater treatment, and
• landfills.
The estimated market prices for each of the waste forms
managed with underground injection were determined by setting
the market price of managing each waste form equal to the
estimated unit cost of the highest cost facility in operation
at baseline. The market prices for managing each of the six
waste forms with "other treatments" were estimated by
averaging the chosen market prices for managing the
corresponding waste form in the other nine processes.
In simplifying the complex pricing mechanism at work in
this industry to a single market price per Mg for each of the
60 OWR services, the Agency recognizes that the analysis may
be understating the waste management revenues (and costs) of
facilities that accept wastes not delivered in bulk form. EPA
also may over- or underestimate revenues from waste management
at facilities that specialize in treating wastes that differ
significantly from our model wastes. Table 4-3
4-12
-------
TABLE 4-3. ESTIMATED MARKET PRICES FOR MANAGEMENT OF 60 WASTE
TYPES PROFILED
lAlcLS LS Lyjre-
McLl! Ks L p 1! j_ C S (, y /
Incinerated wastes
pl_l
p2_l
p3~l
p4_l
p5~l
p6 1
3, 528
3, 528
2,072
2,072
3, 528
3, 528
00
00
00
00
00
00
Wastes reused as fuel
pl_2
p2~2
p3_2
p4_2
p5~2
p6 2
654
830
047
331
654
830
00
00
00
00
00
00
Wastes blended for fuel
pl_3
p2_3
p3_3
p4_3
p5_3
p6 3
64
64
047
331
195
191
00
00
00
00
00
00
Solidified wastes
pl_4
p2_4
p3~4
p4_4
p5~4
p6 4
388
388
388
682
682
682
00
00
00
00
00
00
Wastes managed in solvent recovery
pl_5
p2_5
p3_5
p4_5
p5_5
p6 5
275
240
047
928
933
268
00
00
00
00
00
00
(continued)
4-13
-------
TABLE 4-3. ESTIMATED MARKET PRICES FOR MANAGEMENT OF 60 WASTE
TYPES PROFILED (continued)
lAlcLS LS Lyjre-
McLl! Ks L p 1! j_ C S (, y /
Wastes managed in metals recovery
pl_6
p2_6
p3_6
p4_6
p5_6
p 6 6
495
426
550
125
880
125
00
00
00
00
00
00
Wastes managed in wastewater treatment
pl_7
p2_7
p3_7
p4_7
p5_7
p6 7
817
555
211
206
654
276
00
00
00
00
00
00
Wastes landfilled
pl_8
p2_8
p3_8
p4_8
p5_8
p6 8
251
303
481
550
550
661
00
00
00
00
00
00
Underground injected wastes
pl_9
p2_9
p3_9
p4_9
p5_9
p6 9
28
03
52
75
75
52
Wastes managed with other types of treatment
p_110 1,
p_210 1,
p_310
p_410
p_510 1,
p 610 1,
015
028
768
672
289
225
00
00
00
00
00
00
4-14
-------
lists the selected market prices for management of each of
the 60 waste types modeled in this analysis.
4.2 BASELINE COMPANY FINANCIAL CONDITIONS
Several firms in this analysis reported very low earnings
or net losses for the period 1987 through 1991. Factors that
may contribute to this poor performance include the following:
• a changing regulatory environment, including
regulations affecting hazardous waste generators as
well as regulations affecting waste treaters;
• uneven demand patterns due to recessionary pressures
that resulted in less waste generation and delay in
cleanup activities;
• increased source reduction and recycling;
4-15
-------
4-16
-------
• uncertainty regarding costs; and
• new competitive forces in the industry, including the
threat of entry by large generators and other
nontraditional players.54
According to a recent Standard and Poor's report, the
industry's overall credit quality has improved in the last few
years, and the industry is expected to rebound.55 This
analysis evaluated the baseline financial status using data
from the firm's financial statements reported for the period
1989 through 1992. Consequently, potentially affected firms
are likely to be in better baseline financial condition than
this analysis indicates.
Baseline financial condition was evaluated using
financial ratio analysis. Financial ratio analysis is a
widely accepted way of summarizing the financial condition of
a firm using statistics reported on the firm's financial
statements. In addition, the financial failure was predicted
using a multidiscriminant function called the Z-score.56 The
Z-score is a measure used to assess bankruptcy potential
developed specifically for manufacturing firms.
4.2.1 Financial Ratio Analysis
Financial ratios are computed using data contained in
company financial statements. As mentioned in Section 3.7.1,
authentic financial statements were available from reliable
published sources for only 158 of the companies included in
this company-level impacts analysis. The financial statement
data used for each of the remaining 230 potentially affected
firms were constructed from a single point estimate of the
target company's level of sales (or in some cases assets) and
published financial ratios of the "statistically typical"
company in each of three financial health categories (above
average = 75th percentile, average = median, or below
average = 25th percentile) for the target firm's SIC code.
Each of these 230 firms was assigned to its financial health
category at random, in such a way as to have a realistic
4-17
-------
distribution of firms in each of the financial health
categories for each SIC code, but not necessarily to have an
accurate assessment of each firm's financial health. Thus,
for over half of the companies for which impacts are assessed
in this analysis, the Agency is using baseline financial data
that, while not accurate for individual firms, are
representative of actual baseline financial conditions among
firms potentially affected by the regulation.
The five fundamental types of financial ratios each
address a specific component of a firm's financial well-being.
The five areas of company finances for which financial ratios
are most commonly used are the following:
• liquidity: the ability of a firm to meet its near-
term financial obligations as they come due;
• asset management: the efficiency with which a firm
uses its resources to generate revenues;
• debt management: the degree to which a firm uses debt
(vs. equity) to finance its operations;
• profitability: comprehensive measures of firm
operating efficiency that compare a firm's net income
(profits or losses) to other financial stocks (such as
assets or equity) or flows (such as annual sales) that
result from the interplay of the firm's historical
liquidity, asset management, and debt management
decisions; and
• market value: a comparison of measures of a firm's
past performance (book value) with indicators of
investors' expectations of its potential for future
cash flows (market value).
The first three types of financial ratios listed are
ambiguous indicators of a firm's overall financial well-being.
They are difficult to interpret when considered in isolation
of other indicators of financial health. Potential creditors,
for example, might offer preferential credit to a firm with a
low debt-to-total-assets ratio (one of the more common debt
management ratios), while a potential stockholder might prefer
a higher value for that same ratio, in expectation of greater
4-18
-------
returns on his investment due to the tax advantages of debt
financing. Profitability ratios and market value ratios, on
the other hand, are much clearer indicators of a firm's
financial health. Higher values for profitability ratios are
unambiguously preferred over lower values. For this reason,
the Agency has limited its analysis of individual financial
ratios to profitability and market-value ratios. The Agency
has also investigated a composite measure of financial
condition, called the Z-score, which simultaneously addresses
firm liquidity, asset management, debt management,
profitability, and market value to provide a discrete
indicator of firms' financial viability. Section 4.2.2
discusses the baseline analysis of affected firms' Z-scores.
The analysis evaluates the baseline financial status of
potentially affected firms by comparing the firms' financial
ratios with specific industry benchmark ratios such as those
reported in Dun & Bradstreet's Industry Norms and Key Business
Ratios. Tables H-l and H-2 in Appendix H contain the
benchmark ratios for profitability (by SIC code) used to
evaluate the financial condition of potentially affected
firms. Where specific industry benchmarks are not available,
benchmarks reported for SIC 4953, Refuse Systems, were used.
The firms evaluated for this analysis are larger on
average than those used to compute the benchmark ratios
reported in Tables H-l and H-2. Although most financial
ratios are generally insensitive to differences in size, some
industry ratios may not represent appropriate benchmarks for
evaluation because of the size differences. In addition, SIC
4953 (the default industry classification) represents firms
involved in waste disposal, sewage treatment and disposal, and
other waste treatment processes not directly affected by the
OWR regulation. Notwithstanding these qualifications, an
evaluation of the baseline financial condition of potentially
affected firms is useful. In particular, a comparison of the
4-19
-------
baseline ratios and the "with-regulation" ratios may provide
insight into the financial impacts of the regulation.
4.2.1.1 Profitability. Profitability is the most
comprehensive measure of the firm's performance because it
measures the combined effects of liquidity, asset management,
and debt management. Several ratios are commonly used to
measure profitability, including return on sales (ROS), return
on equity (ROE), and return on assets (ROA). For all these
measures, higher values are unambiguously preferred over lower
values.
ROS, computed by dividing net income or net loss by
annual sales, shows the operating efficiency of the firm.
Negative values result if the firm experiences a loss. Median
ROS values reported in Table 4-4 range from a 3.2 to 5.5
percent. Mean ROS values range from -21 percent to 4.1
percent. Under both measures, firms in the smallest size
TABLE 4-4. BASELINE FINANCIAL RATIO: RETURN ON
SALES57"64
Firm size in annual receipts ($10b/year)
$60 ITo
Statistic
$0 to $6
$6 to $60
$1,000
Number ot observations
Mean (percent)
Standard deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
TTIT
4 ,
18 ,
T3
-12 . 0
66.0
6.7
3.3
1.3
8D
-21.40
132.00
5.85
3.20
0.40
Over
$1,000
TTT3
0.04
25 .10
5.90
3.50
-0.40
Notes:
1. The ROS ratio is a measure of a firm's profitability and is
computed by dividing net income by sales revenue. A value of 10
percent indicates that net income is equal to 10 percent of
sales. Negative values indicate net losses.
2. High ratios indicate that the firm is operating efficiently.
4-20
-------
category have the highest ROS. The mean profit-to-sales ratio
is lower than the median for all four firm size categories,
and for very large firms the difference is substantial. This
substantial difference indicates that the distribution
contains one or more outlier firms with very negative ROS
values. Consequently, the median is a better measure of
central tendency.
Figure 4-2 compares the ROS values computed for
potentially affected firms with industry-specific benchmark
(median and lower quartile) values. Approximately 60 to 70
Figure 4-2. Percentage of firms equal to or below the industry
benchmark ratio: return on sales.
1. The ROS ratio is a measure of a firm's profitability. It is
the ratio of a company's net income to its total sales,
expressed as a percentage. For example, a value of 6.5
indicates that a company's net income is equal to 6.5 percent
of its total sales. A high ROS value is preferable to a
lower value.
2. Each company's ROS ratio is compared to the Dun & Bradstreet
published median and lower quartile benchmarks for companies
sharing the same SIC code. If the SIC code is not known, the
company ratio is compared to the benchmark ratios for SIC
4-21
-------
percent of firms in all size categories have ROS ratios that
are equal to or below the industry median benchmarks. Firms
in the two smallest size categories performed slightly better
than firms in the larger size categories.
The second profitability ratio referred to above, ROE, is
computed by dividing net income or loss by owners' equity and
measures the return on capital invested by the owners of the
firm. Table 4-5 reports a statistical summary of ROE values
for potentially affected firms in each size category. Median
values range from 9.5 to 22.4 percent. Mean values are much
more variable and range from -61.4 percent to a +41.9 percent.
Again, the presence of outliers makes the median values the
preferred measure.
TABLE 4-5. BASELINE FINANCIAL RATIO: RETURN ON EQUITY65"72
J? _l Jim size ±n d.iiiiud.1 leueipLa I u : / y ecu )
i?bU Uo Over
Statistic $0 to $6 $6 to $60 $1,000 $1,000
Mumber or observations 1U9 9"2 7~7 1U4
Mean (percent) 41.9 -61.4 -55.9 2.1
Standard deviation 236.4 323.8 341.2 61.2
(percentage points)
Quartiles (percent)
Upper 25.8 25.5 17.2 15.4
Median 20.4 14.4 9.5 9.9
Lower 7.6 5.1 1.2 1.2
Notes :1. The ROE ratio is a measure of a firm's profitability and
is computed by dividing net income by the owners' equity
A value of 20 percent indicates that net income is equal
to 20 percent of the owners' equity. Negative values
indicate net losses.
2. High ratios indicate that the firm is operating efficiently.
4-22
-------
Figure 4-3 shows the share of firms with ROE values equal
to or below the industry median benchmark and the industry
lower quartile benchmark values. Approximately 40 percent of
the firms in the two smallest size categories have ROE values
equal to or below the industry median benchmark. Larger firms
are not performing as well with 66 to 78 percent equal to or
below the industry benchmark.
ROA, the final measure of profitability, is net profit or
loss divided by total assets. ROA measures how efficiently a
firm is using its assets to earn a return. Table 4-6 reports
TABLE 4-6. BASELINE FINANCIAL RATIO: RETURN ON
ASSETS73"80
j_'1J l!ivi sizs in annual rscsipLS ^ $ 1 u1'/1'ysar )
$"6"0 To uver
Statistic $0 to $6 $6 to $60 $1,000 $1,000
Number otrobservatioos« 37T0 9"3 8D TTJ5
I •Af
Mean (per"e©rtt) l'JK'l -6.4 -11.1 1.1
Standard deviation 35.6 64.5 63.8 20.9
(percentape pointy)
Quartilesk (percent1**!1*
Upper 17.1 12.7 10.1 6.4
Median 11.0 7.3 5.8 3.5
Lower 2.6 1.8 0.5 -0.6
Notes:
1. The ROA ratio is a measure of a firm's profitability and is
computed by dividing net income by total assets. A value of 15
percent indicates that net income is equal to 15 percent of
total assets. Negative values indicate net losses.
2. High ratios indicate that the firm is operating efficiently.
Figure 4-3. Percentage of firms equal to or below the industry
benchmark ratio: return on equity.
1. The ROE ratio is a measure of a company's profitability. It
is the ratio of a company's net income to its total net
worth, expressed as a percentage. For example, a value of
3.9 indicates that a company's net income is equal to 3.9
percent of its total net worth. A high ROE value is
preferable to a lower value.
2. Each company's ROE ratio is compared to the Dun & Bradstreet
published median and lower quartile benchmarks for companies
sharing the same SIC code. If the SIC code is not known, the
company ratio is compared to the benchmark ratios for SIC
code 4953: Refuse Systems.
4-23
-------
Figure 4-4. Percentage of firms equal to or below the industry
benchmark ratio: return on assets.
the distribution of ROA values for potentially affected firms.
Median values range from 3.5 for firms in the largest size
category to 11 percent for firms in the smallest size
category. Figure 4-4 shows the share of firms performing
equal to or below the industry benchmarks for ROA. Again, a
higher proportion of large firms is below the benchmark,
indicating that small firms appear to be performing better on
average than large firms.
4-24
-------
4.2.1.2 Market Value. Market value ratios indicate
investors' expectations regarding the firm's past performance
and future cash flows. Generally, if a firm's financial
ratios in each of the other four categories of performance are
good, then the market value ratios will also be good. The
market-value-of-equity to book-value-of-equity ratios are
particularly useful for evaluating investors' expectations.
Market-to-book ratios less than one clearly indicate that
investors believe the firm's value is deteriorating.
Conversely, ratios greater than one indicate that investors
believe that the firm's operations are adding value to the
firm.
1. The ROA ratio is a measure of a company's profitability. It
is the ratio of a company's net income to its total assets,
expressed as a percentage. For example, a value of 4.3
indicates that a company's net income is equal to 4.3 percent
of its total assets. A high ROA value is preferable to a
lower value.
2. Each company's ROA ratio is compared to the Dun & Bradstreet
published median and lower quartile benchmarks for companies
sharing the same SIC code. If the SIC code is not known, the
company ratio is compared to the benchmark ratios for SIC
4-25
-------
Table 4-7 reports market-to-book ratios for firms in the
two largest size categories only because very few firms in the
other size categories have publicly traded stock.
Consequently, stock price data are largely unavailable for
firms in the two smallest size categories. The quartile
values for firms with $60 million to $1 billion in sales range
from 1 for the lower quartile to 5.57 for the upper quartile.
This difference indicates that investors value most of the
potentially affected firms in this size category at about 100
TABLE 4-7. BASELINE FINANCIAL RATIO: MARKET-TO-BOOK RATIO81"88
j_'1J l!ivi sizs in annual rscsipLS ^ $ 1 u1'/1'ysar )
$"6"0 to Over
Statistic $0 to $6 $6 to $60 $1,000 $1,000
Mumber or 0 0 7 4~5
observations
Mean N/A N/A 3.32 1.99
Standard deviation N/A N/A 2.25 1.38
(percentage points)
Quartiles
Upper N/A N/A 5.57 2.12
Median N/A N/A 3.68 1.62
Lower N/A N/A 1.02 1.21
Notes:
1. The market-value-of-equity to book-value-of-equity ratio is a
measure of the firm's market value and is computed by dividing
average price per share by net worth per share.
2. Values above one indicate that investors value the firm above
the book value of its equity. Conversely, values below one
indicate that investors value the firm below the book value of
its equity.
3. Values are not reported for the $6 to $60 million firm size
category because data are available for only one firm in this
category.
4-26
-------
percent to 557 percent of the firm's book value. Quartile
values for the largest size category range from 1.21 to 2.12.
Investors value these firms at about 121 percent to 212
percent of book value. Benchmark values are not reported for
this ratio.
4.2.2 Bankruptcy Analysis
A composite ratio of financial condition, called the Z-
score, was also computed to characterize baseline financial
conditions of potentially affected firms. Developed
specifically for manufacturing firms, the Z-score is a multi-
discriminant function used to assess bankruptcy potential.89
It simultaneously addresses liquidity, asset management, debt
management, profitability, and market value.
The function is given in Eq. (4-4) :
Z = 1 . 2X, + 1 . 4X2 + 3 . 3X3 + 0 . 6X4 + 0 . 9 9 9X5 (4-4)
where
Z = overall index
X-l = working capital/total assets
X2 = retained earnings/total assets
X3 = earnings before interest and taxes/total assets
X4 = market value of equity/book value of total debt
X5 = sales/total assets.
The market value component (X4) uses stock price data.
Consequently, the Z-score is only applicable to firms with
publicly traded stock. This analysis used a modified function
developed for private firms referred to as the Z"-score, given
in the following equation:
Z" = 6.56X, + 3.2 6X2 + 6.72X3 + 1.05X4 (4-5)
where Z" is the overall index, Xx through X3 are as defined for
Z above, and X4 is net worth to total liabilities.
Taken individually, each of the ratios given above is
higher for firms in good financial condition and lower for
firms in poor financial condition. Consequently, the greater
4-27
-------
a firm's bankruptcy potential, the lower its discriminant
score. A Z-score below 1.81 indicates that bankruptcy is
likely, and a score above 2.99 indicates that bankruptcy is
unlikely. Z-scores between 1.81 and 2.99 are indeterminate.
Similarly, a Z"-score below 1.10 indicates that bankruptcy is
likely, and a score above 2.60 indicates that bankruptcy is
unlikely. Z"-scores between 1.10 and 2.60 are indeterminate.
4-28
-------
Table 4-8
4-29
-------
TABLE 4-8. BASELINE BANKRUPTCY PREDICTION
i±±m size ±n d.iiiiud.1 leceipLs I u : / y ecu ) ''
Bankruptcy $0 ITo $60 ITo Over
prediction $6 $6 to $60 $1,000 $1,000 Total
Publ±cly traded
companies3
Likely
0
0
2
9
11
Indeterminate
0
1
1
22
24
Unlikely
0
0
5
14
19
Subtotal
0
1
8
45
54
Other companies13
L±kely
1
2
4
6
12
Indeterminate
0
7
5
11
23
Unlikely
10
11
17
26
65
Subtotal
11
20
26
43
100
All companies
L±kely
1
2
6
15
23
Indeterminate
0
8
6
33
47
Unlikely
10
11
22
40
84
Subtotal
11
21
34
88
154
a Bankruptcy prediction is based on the Z-score for companies with
publicly traded stock. If a company's Z-score is less than 1.81,
the model predicts that bankruptcy is likely. If a company's Z-
score is greater than 2.99, the model predicts that bankruptcy is
unlikely. Z-scores between 1.81 and 2.99 fall in the
indeterminate range, and the model makes no prediction for these
companies.
b Bankruptcy prediction is based on the Z"-score for companies that
do not issue publicly traded stock. If a company's Z"-score is
less than 1.10, the model predicts that bankruptcy is likely. If
a company's Z"-score is greater than 2.60, the model predicts that
bankruptcy is unlikely. Z"-scores between 1.10 and 2.60 fall in
the indeterminate range, and the model makes no prediction for
these companies.
4-30
-------
shows the distribution of publicly traded firms by Z-score
prediction and the distribution of firms that do not issue
publicly traded stock by Z"-score prediction. Financial
failure is predicted for less than approximately 10 percent of
firms in the two smallest size categories. By contrast,
bankruptcy is predicted for approximately 15 to 17 percent of
the firms in the two largest size categories. Overall, the
model predicts that approximately one in seven potentially
affected firms is likely to fail even without the regulation.
These predicted failure rates do not compare favorably with
average reported failure rates for the U.S. The 1990 failure
rate averaged 0.92 percent for all manufacturing firms, 0.49
percent for all service firms, and 0.76 percent for all U.S.
firms.90 As noted in the previous section, firms in the waste
treatment business performed poorly during the 1987 to 1990
time period. Consequently, it is not surprising that the
predicted failure rates computed for the waste treatment firms
in this analysis are significantly higher than average 1990
rates for U.S. firms in general.
4-31
-------
SECTION 5
THE OFF-SITE WASTE OPERATIONS STANDARD*
Off-site waste operations (OWO) comprise one of the major
source categories of HAPs established under Section 112 of the
Clean Air Act, as shown in the current list of source
categories provided in the Federal Register notice entitled
"Initial List of Categories of Sources Under Section 112(c) (1)
of the Clean Air Act Amendments of 1990" (57 FR 3176, July 16,
1992). The Act calls for the development of standards to
control HAP emissions from these source categories and
subcategories over the ten-year period starting November 1990.
A major source is defined as any stationary source, or
group of stationary sources (including all emission points and
units located within a contiguous area and under common
control) of air pollution, that emits or has the potential to
emit, considering controls, 10 tons or more per year of any
one HAP or 25 tons or more per year of any combination of
HAPs .
The Act requires EPA to establish air emissions standards
for each major source category and to promulgate emission
standards based on the level of control that would be obtained
through air emissions standards. To that end, EPA has
developed five regulatory alternatives whose impacts must be
analyzed.
*This section describes the OWR standard that is
evaluated in this report. It was changed somewhat prior to
proposal. For the details of the rule the Agency is
promulgating, please see the preface.
5-1
-------
5.1 CONTROLS FOR EMISSION POINT CATEGORIES
The regulatory alternatives establish controls for
emissions from five categories of emission points present at
OWR facilities:
• tanks,
• wastewater treatment,
• process vents,
• waste transfer, and
• equipment leaks.
Each regulatory alternative represents a unique
combination of controls specified for each emission point
category. Waste management practices were simulated by
emission point category using organic HAP composition data
from the GENSUR and site-specific information on waste
management operations from the TSDR Survey.
5.1.1 Regulatory Baseline
The regulatory baseline represents the reductions in
organic HAP emissions at the affected OWR facility due to the
operation of air emission controls that will be used in the
absence of any regulation being applicable to the facilities.91
These controls include controls reported to be in place at OWR
facilities in 1986 and controls resulting from the
implementation of promulgated RCRA air standards and Clean Air
Act standards applicable to waste management activities at OWR
facilities. These applicable regulations include RCRA Air
Standards for TSDF Facility Process Vents and Equipment Leaks
and the NESHAP for Benzene Waste Operations.
5.1.2 Emission Point Category Floor
The Act requires that regulations for existing sources be
at least as stringent as the average emission limitation
achieved by the best-performing 12 percent of existing sources
in a source category. This level of control is referred to as
the MACT "floor" for the source category. For the OWR
regulation, an individual "floor" is defined for each of the
five emission point categories. The floor determination is
5-2
-------
based on the organic HAP air emission controls used under the
regulatory baseline at the individual OWR locations listed in
the computer model database. The control option representing
the floor for each of the five emission point categories is
listed below:
• Tanks--The tank control option at the floor is the use
of fixed-roof tanks for wastes with a volatile organic
HAP concentration equal to or greater than 10 ppmw.
• Wastewater Treatment--The wastewater treatment control
option at the floor is the absence of organic HAP air
emission controls.
• Process Vents--The process vent control option at the
floor is determined to be control of treatment units
with total organic mass emissions equal to or greater
than 3 tons per year by connecting the process vents
to an add-on organic control device with at least a 95
percent organic emission control efficiency.
• Waste Transfer--The waste transfer control option at
the floor is determined to be the absence of organic
HAP air emission controls.
• Equipment Leaks--The equipment leaks control option at
the floor is determined to be control of emissions
from leaks in equipment handling waste streams with
total organic concentrations equal to or greater than
10 percent by implementing leak detection and repair
(LDAR) work practices that follow the procedures
specified in the rules for New Source Performance
Standards (NSPS). The organic control efficiency
assigned to this LDAR program is 70 to 75 percent,
depending on the volatility of the organics in the
waste stream.92
5.2 REGULATORY ALTERNATIVES SELECTED FOR ANALYSIS
Ten candidate regulatory alternatives were developed,
representing combinations of varying control levels at each of
the five emissions categories. For each emissions category,
several possible levels of control were specified. Table 5-1
5-3
-------
J_!_i 1LI L O O X U iTTT
point
TABLE 5-1. EMISSION POINT CONTROL OPTIONS
U l!J i'i L1! 1
option Description
>0.75 psia
>0.1 psia
Baseline
Tanks
Wastewater
treatment
-------
shows the alternative levels o
emissions point category.93 For
except process vents, the floor
control suggested for each
each emissions point category
is at least as stringent as
5-5
-------
the baseline, and two or three increasingly stringent levels
of control above the floor are specified. Regulatory
alternatives may be selected by combining varying levels of
control at each emissions point category.
The five regulatory alternatives represent combinations
of the individual emission point control options for impacts
analysis. Table 5-2
5-6
-------
5-7
-------
shows the levels of control characterizing each emissions
point category for each regulatory alternative.94 Thus, the
five regulatory alternatives combine the following control
options for each emissions point category:
(1)
"Floor" Tl,
WW1,
PV1,
WT1,
and
ELI;
(2)
T2,
WW1,
PV1,
WT2,
and
EL2 ;
(3)
T2,
WW2,
PV1,
WT3,
and
EL2 ;
(4)
T3,
WW2,
PV1,
WT3,
and
EL3 ;
(5)
T3,
WW 4,
PV1,
WT3,
and
EL3 .
5.3 COSTS OF REGULATORY ALTERNATIVES
Emissions and compliance costs are estimated for the
baseline and each of the five regulatory alternatives.
Nationwide emissions and costs are shown in Table 5-3.
5-8
-------
TABLE 5-3. NATIONAL COMPLIANCE COSTS AND EMISSIONS
BY REGULATORY ALTERNATIVE ($1991)
KcyulaLuiy nlLcina L± vc
Variable I 2 3 T
Total
b3,U U U
1U,8 /b,UUU
16,913,UUU
22,866,UUU
33,496,UUU
annualized cost
Total capital
3,166,683
19,13b,677
27,236,438
40,Obi,246
bl,80b,019
investment
Annual
233,166
b,2b9,213
12,787,333
16,820,084
2b,762,816
operating costs
Emissions
31,910
.12,217 .
4,809.
3, 649
3, b44
cn
i
-------
A detailed description of the assumptions and analyses used
to develop these costs may be found in Appendix C of the
Background Information Document.
5.3.1 Estimated Facility Compliance Costs
For analysis of impacts by OWR process, facility-specific
compliance costs and emissions are computed by OWR process for
the baseline and each regulatory alternative for 464
facilities with detailed waste characterization data. The
costs and emissions are estimated based on the larger of the
following two quantities:
• the quantity the OWR facility reported in its TSDR
Survey response as being managed in that process; or
• the quantity that waste generators reported sending to
that OWR facility in their Generator Survey responses.
This approach ensures that the analysis will not underestimate
the costs or emissions associated with each process. For
purposes of estimating national costs and emissions, the
actual location of management is unimportant.
For the purpose of estimating facility-specific impacts
of the regulatory alternatives, however, the actual location
of waste management is critical. For this purpose, the
quantity of waste managed in a given process is assumed to be
the OWR facility's reported quantity from the TSDR Survey.
In many cases, the two quantities mentioned above are
close to equal. The Agency believes that the TSDR Survey
quantity of waste managed most accurately reflects the
quantity the OWR facility actually managed. Generators of
waste may have sent the waste directly to an OWR facility, and
the generators may know that ultimately it was managed in a
given process. A comparison of the quantities of waste
reported as being managed at a facility in a given process in
the Generator Survey and the TSDR Survey reveals that in some
instances the quantity reported in the Generator Survey
exceeds the quantity reported in the TSDR Survey. There are
even instances in which the Generator Survey reports waste
being sent to an OWR facility for management in a process that
5-10
-------
the OWR facility does not report having on site in its TSDR
Survey response. This discrepancy results in compliance costs
being estimated for processes that facilities do not report
having on site in the TSDR Survey. Such cases probably
reflect waste brokerage. Many OWR facilities accept waste
from off site, then broker the waste to other OWR facilities
for management in processes that they do not offer. In such
cases, it is not the broker OWR facility that will incur the
compliance costs but the managing OWR facility. It was
necessary, therefore, to attempt to estimate costs of
compliance for the managing facilities.
To estimate the quantity of waste managed in each process
at each OWR facility, the Agency used the following approach:
1. When compliance costs were estimated for on-site
processes of one of the 464 facilities, those
compliance costs were allocated to the waste types
managed in the process based on the relative
quantities of each of those waste types.
2. When compliance costs were estimated for processes
that the facility did not report having on site, the
wastes were assumed to be brokered, and sent to one of
the 246 facilities for which no facility-specific
compliance costs were provided.
3. For 246 facilities for which no waste characterization
was available in the GENSUR database, but for which
process quantities were available from their TSDR
responses, costs and emissions were estimated for each
process for the group of 246 facilities together.
These costs and emissions, by process, together with
the costs and emissions for brokered wastes, were
allocated across waste types and processes at the 246
facilities, based on the relative quantities of each
waste form sent off site for management at unnamed OWR
facilities.
5.3.2 Fixed Costs
In addition to the ten waste management processes
described above, emissions and compliance costs were
estimated for storage operations and for discharge to POTWs or
surface water. No controls are applied to discharge
emissions, so no costs are incurred. For storage, on the
5-11
-------
other hand, controls are imposed and costs are incurred. This
analysis assumes that waste storage is not a service that is
traded in the market. That is, facilities store wastes until
they have enough to make a batch or a shipment. In addition,
they do not charge the generators separately for storing the
wastes; rather, it is part of the overall costs of treating,
recycling, or disposing of the waste. The compliance costs
associated with controlling emissions from storage units is
assumed to be a fixed cost, unrelated to the quantities
managed in other processes, or even in the storage units
themselves. This is a simplifying assumption that allows the
model to treat the costs as facility-wide costs of doing
business; if the facility operates other processes and stores
waste at all, the costs are incurred. Unlike compliance costs
associated with the operation of other waste management
processes, storage compliance costs do not enter into the
decision of how much waste to manage in each process; they
only affect overall facility profitability. Section 6 offers
further discussion of the model's treatment of fixed costs.
5.4 COMPLIANCE COSTS OF EACH REGULATORY ALTERNATIVE,
BY WASTE TYPE
Compliance costs by waste type (unique waste form/waste
management process combination), for each regulatory
alternative, are shown in Tables 5-4
5-12
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
1
1
it
T5
26
11
24
20
30
50
68
2
41
21
26
7
20
6
18
60
55
1
34
32
TABLE 5-4. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 1 BY
WASTE MANAGEMENT PROCESS ($1991)
TOLd.1 d-iiiiUdiiizBU. Aiiiiud.1 opeidLiny dim-
costs Totdl cdpitdl costs maintenance costs
Dtal
Mean
Total
Mean
Total
Mean
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
191
47
18,994
279
1,398
21
81
40
479
240
35
18
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
673
12
4, 005
73
295
5
194
4, 194
24,959
24,959
1, 838
1, 838
0
0
0
0
0
0
0
0
0
0
0
0
-------
1
2
'3
'4
'5
'6
1
'8
'9
1
1
2
'3
'4
'5
'6
1
'8
'9
ie
32
31
32
27
37
26
98
56
10
49
45
56
71
24
17
13
61
51
9
51
TABLE 5-4. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 1 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
TOLdi aiiiiuaii^OT-
costs
to Lai capiiai
costs
Annual opBiaLiny ancF
maintenance costs
Total
Mean
Total
Mean
Total
Mean
0
0
0
0
0
0
0
104,098
359,392
0
0
0
0
0
0
0
0
4, 632
16,487
0
0
0
0
0
0
0
0
1,859
35,939
0
0
0
0
0
0
0
0
91
1, 832
0
0
0
0
0
0
0
0
619,546
2,138,906
0
0
0
0
0
0
0
0
27,566
98,122
0
0
0
0
0
0
0
0
11,063
213,891
0
0
0
0
0
0
0
0
541
10,902
0
0
0
0
0
0
0
0
45,617
157,493
0
0
0
0
0
0
0
0
2,029
7, 225
0
0
0
0
0
0
0
0
815
15,749
0
0
0
0
0
0
0
0
40
803
0
-------
TABLE 5-4. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 1 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
TOLdl dliliUdll IZtJO-
costs
TOLdl CdpiLdl
costs
Aiiiiudi opeidLiny diicF
maintenance costs
Market Total
Pi
l-l
Mean
Total
Mean
Total
Mean
Number of
facilities
3-10
&
l-l
2, 27{
13^24'
2, 2(
221
13,13;
5,
99*
1'
96'
on
I
Ui
3-10
storage
Total
6:
5, 06:
513,391
72:
3(
30, i:
3,055,44
4, 30:
2'
2,21?
224,978
31'
25(
71 (
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
T5
26
11
24
20
30
50
68
2
41
21
26
7
20
6
18
60
55
1
34
TABLE 5-5. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 2 BY
WASTE MANAGEMENT PROCESS ($1991)
i'Oldl dlili Udll IZBU. 'i'OLdl CdpiLdl AliliUdl opeidliny dim
costs costs maintenance costs
Total Mean Total Mean Total Mean
26,420
755
57,709
1, 649
18,204
520
929
36
2,086
80
632
24
306
28
832
76
193
18
8,391
350
20,789
866
6, 428
268
5,268
263
12,387
619
3, 535
177
29
1
37
1
24
1
0
0
0
0
0
0
176,180
2,591
331,519
4,875
129,632
1,906
362
181
726
363
261
130
9,178
224
18,149
443
6, 637
162
5, 310
253
11,418
544
3, 685
175
19,597
754
44,515
1, 712
13,259
510
2, 862
409
7,360
1, 051
1, 864
266
13,659
683
33,843
1, 692
10,464
523
10,138
1, 690
24,397
4,066
6,714
1,119
6
0
8
0
5
0
0
0
0
0
0
0
57,450
1,045
112,703
2,049
41,511
755
13,264
13,264
33,720
33,720
9, 052
9, 052
102,186
3, 005
196,185
5,770
74,614
2, 195
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
Lit
37
31
32
27
37
26
98
56
10
49
45
56
71
24
17
13
61
51
9
51
TABLE 5-5. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 2 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
TOLd.1 dliliUdlll^BU. TOLd.1 Cd.pi Ld± AliliUdl opeidLiny dlicr
costs costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
202,034
6, 314
374,859
11,714
148,662
4, 646
286,257
9, 234
639,432
20,627
195,216
6,297
41,239
1,289
100,578
3, 143
27,261
852
14,212
526
35,212
1,304
10,888
403
52,234
1, 412
137,721
3, 722
33,768
913
1
0
1
0
1
0
0
0
0
0
0
0
562,604
10,047
1,336,112
23,859
401,312
7,166
812,531
81,253
2,625,861
262,586
515,066
51,507
225,327
4,599
431,900
8,814
164,628
3,360
1, 016,202
22,582
2,288,376
50,853
690,386
15,342
1,059,442
18,919
2,380,179
42,503
720,560
12,867
714,580
10,065
1,735,791
24,448
473,836
6,674
7, 425
309
18,397
767
5, 688
237
2,990,192
25,557
7,215,339
61,670
1,979,330
16,917
1
0
1
0
1
0
0
0
0
0
0
0
23,280
456
62,760
1, 231
15,551
305
54,995
6, 111
134,027
14,892
37,955
4,217
32,655
640
65,280
1,280
23,466
460
-------
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
li-
TT
42
47
29
67
13
44
60
6
44
32
36
37
26
33
24
83
63
7
TABLE 5-5. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 2 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. cosfs-
'i'Oldl Cd.piLd.1
costs
Aiiiiud.1 opeidLiny diicF
maintenance costs
Total
272,032
348,166
515,425
21,543
423,375
8
0
92,271
42,076
12,285
55,477
965
6, 016
25,680
14,350
19
0
56,173
9, 625
133,596
156,810
10,732,638
Mean
7, 352
8,290
10,966
743
6, 319
1
0
1, 538
7,013
279
1, 734
27
163
Total
590,516
766,434
1,168,380
53,376
974,644
10
0
185,677
107,165
25,419
121,862
2,168
15,384
63,625
34,939
25
0
112,930
34,933
262,623
376,078
25,386,400
Mean
15,960
18,248
24,859
1, 841
14,547
1
0
3, 095
17,861
578
3,808
60
416
2, 447
1, 059
1
0
1, 793
4, 990
1,026
Total
187,955
239,044
352,812
16,503
288,059
6
0
66,203
28,718
8,768
38,126
657
3, 875
19,674
9, 450
16
0
40,103
5, 819
96,704
103,372
7,276,154
Mean
5,080
5, 692
7,507
569
4,299
0
0
1,103
4,786
199
1, 191
18
105
757
286
1
0
637
831
378
435
1
0
892
1, 375
522
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
T5
26
11
24
20
30
50
68
2
41
21
26
7
20
6
18
60
55
1
34
TABLE 5-6. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 3 BY
WASTE MANAGEMENT PROCESS ($1991)
i'Oldl dliliUdlll^BU. COSLS 'i'OLdl CdpiLdl AliliUdl OpBIdLlIiy dlTTX
costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
26,397
754
57,654
1, 647
CO
CO
! 1
CO
! 1
520
928
36
2,084
80
631
24
306
28
833
76
193
18
8, 391
350
20,789
866
6, 428
268
5,279
264
12,456
623
3, 538
177
29
1
37
1
24
1
19,004
380
1, 950
39
18,790
376
174,576
2, 567
329,023
4,839
128,384
1,888
362
181
726
363
261
130
12,826
313
25,295
617
9,290
227
5, 306
253
11,408
543
3, 682
175
19,577
753
44,466
1, 710
13,246
509
2,878
411
7, 454
1, 065
1,869
267
13,659
683
33,843
1, 692
10,464
523
10,125
1,687
24,409
4,068
6, 702
1,117
6
0
8
0
5
0
257,085
4, 285
109,297
1, 822
245,084
4,085
55,737
1, 013
110,034
2,001
40,178
731
13,105
13,105
33,416
33,416
8, 936
8, 936
146,904
4, 321
283,747
8,346
107,124
3,151
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
Hit
"37
31
32
27
37
26
113
56
10
49
45
56
71
24
117
13
61
51
9
51
TABLE 5-6. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 3 BY
WASTE MANAGEMENT PROCESS ($1991)
i'Oldl dlili Udll I^BU. COSLS 'i'OLdl Cd.pi Ldl AliliUdl OpeidLlIiy dliU.
costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
201,942
6, 311
374,638
11,707
148,602
4, 644
285,957
9, 224
638,708
20,603
195,020
6,291
41,255
1,289
100,673
3, 146
27,266
852
14,212
526
35,212
1, 304
10,888
403
52,259
1, 412
138,017
3, 730
33,762
912
1
0
1
0
1
0
6,470,219
57,259
2,186,389
19,349
6
,229,432
55,128
562,282
10,041
1,335,553
23,849
401,069
7, 162
810,191
81,019
2,621,228
262,123
513,374
51,337
95,438
1, 948
185,484
3, 785
69,441
1, 417
1,015,547
22,568
2,286,794
50,818
689,956
15,332
1,059,019
18,911
2,379,158
42,485
720,282
12,862
715,056
10,071
1,742,786
24,546
473,624
6, 671
7, 425
309
18,397
767
5,688
237
2,991,119
25,565
7,224,182
61,745
1
,979,355
16,918
1
0
1
0
1
0
465,050
7, 624
43,929
720
460,227
7, 545
23,167
454
62,581
1, 227
15,463
303
54,754
6, 084
133,566
14,841
37,780
4,198
38,852
762
77,572
1, 521
27,959
548
-------
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
it.
TT
42
47
29
67
13
44
60
6
44
32
36
37
26
33
24
83
63
7
TABLE 5-6. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 3 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. cosfs-
'i'Oldl Cd.piLd.1
costs
Aiiiiud.1 opeidLiny diicF
maintenance costs
Total
271,837
347,982
515,730
21,543
424,397
8
180,438
91,506
41,588
16,895
55,426
964
6, 036
25,680
14,363
19
209,261
55,779
9, 624
205,658
157,109
18,328,068
Mean
7, 347
8,285
10,973
743
6, 334
1
4, 101
1, 525
6, 931
384
1, 732
27
163
Total
590,045
765,990
1, 170, 265
53,376
981,298
10
131
184,480
106,235
34,481
121,738
2, 165
15,506
63,625
35,019
25
124,680
112,272
34,931
403,382
377,931
27,871,383
Mean
15,947
18,238
24,899
1, 841
14,646
1
3
3, 075
17,706
784
3,804
60
419
2, 447
1,061
1
1, 502
1, 782
4, 990
1,576
Total
187,827
238,923
352,911
16,503
288,359
6
180,424
65,609
28,362
12,116
38,093
656
3, 882
19,674
9, 454
16
195,573
39,803
5, 818
149,125
103,467
14,598,
Mean
5,076
5,689
7,509
569
4,304
0
4, 101
1, 093
4, 727
275
1,190
18
105
757
286
1
2, 356
632
831
583
435
1
2, 521
885
1, 375
803
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
it.
T5
26
11
24
20
30
50
68
2
41
21
26
7
20
6
18
60
55
1
34
TABLE 5-7. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 4 BY
WASTE MANAGEMENT PROCESS ($1991)
i'Oldl dliliUdlll^BU. COSLS 'i'OLdl CdpiLdl AliliUdl OpBIdLlIiy dlTTX
costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
58,449
1, 670
129,809
3, 709
39,967
1,142
2,021
78
4,396
169
1, 395
54
572
52
1, 440
131
373
34
17,760
740
44,002
1, 833
13,606
567
7,329
366
16,570
828
5, 003
250
188
6
241
8
155
5
19,010
380
1, 965
39
18,794
376
321,549
4, 729
655,300
9, 637
228,821
3, 365
385
193
760
380
278
139
11,365
277
23,619
576
8, 052
196
8,107
386
17,534
835
5, 611
267
39,032
1, 501
85,947
3,306
26,795
1, 031
5, 222
746
12,671
1,810
3,470
496
26,444
1, 322
65,520
3,276
20,260
1,013
12,515
2,086
29,357
4, 893
8, 388
1,398
41
2
52
3
34
2
257,103
4,285
109,343
1, 822
245,096
4, 085
105,701
1, 922
220,545
4,010
74,393
1, 353
17,193
17,193
38,760
38,760
12,149
12,149
117,709
3, 462
236,520
6, 956
84,442
2,484
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
ili-
"37
31
32
27
37
26
113
56
10
49
45
56
71
24
117
13
61
51
9
51
TABLE 5-7. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 4 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. COSLS 'i'OLdl CdpiLdl AliliUdl OpBIdLlIiy dlTTX
costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
274,104
8,566
536,457
16,764
197,725
6,179
574,646
18,537
1,250,421
40,336
396,614
12,794
74,076
2, 315
178,788
5, 587
48,967
1, 530
29,159
1,080
72,247
2, 676
22,340
827
80,477
2,175
199,200
5, 384
53,269
1,440
4
0
6
0
4
0
6,470,478
57,261
2,187,251
19,356
6,
229,658
55,130
610,733
10,906
1,434,995
25,625
434,945
7, 767
931,423
93,142
2,762,963
276,296
608,748
60,875
261,428
5, 335
526,712
10,749
187,349
3, 823
1,863,319
41,407
4,224,657
93,881
1,
261,822
28,041
1,610,338
28,756
3,583,539
63,992
1,
100,123
19,645
1,298,857
18,294
3,026,143
42,622
874,705
12,320
15,556
648
38,541
1, 606
11,918
497
4,117,674
35,194
9,795,741
83,724
2,
739,781
23,417
6
0
8
1
5
0
465,091
7, 624
44,031
722
460,253
7, 545
46,900
920
112,343
2,203
31,942
626
64,912
7, 212
146,602
16,289
45,706
5,078
58,297
1,143
122,941
2,411
40,956
803
-------
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
it.
TT
42
47
29
67
13
44
60
6
44
32
36
37
26
33
24
83
63
7
TABLE 5-7. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 4 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. COSLS
'i'Oldl Cd.piLd.1
costs
Aiiiiud.1 opeidLiny diicF
maintenance costs
Total
461,867
632,931
889,394
42,933
932,816
47
180,462
191,606
54,575
17,536
96,281
19,983
11,276
38,509
18,964
107
209,288
113,385
13,868
184,613
211,973
24,197,590
Mean
12,483
15,070
18,923
1,480
13,923
4
4, 101
3, 193
9,096
399
3, 009
555
305
1, 481
575
4
2, 522
1,800
1, 981
721
Total
1,015,058
1,374,417
1,965,230
106,374
2,033,140
61
190
406,087
123,463
37,281
213,123
44,062
28,016
95,413
45,097
140
124,747
244,855
38,968
384,963
475,505
40,694,126
Mean
27,434
32,724
41,813
3, 668
30,345
5
4
6, 768
20,577
847
6,660
1, 224
757
3, 670
1,367
6
1, 503
3,887
5,567
1,504
Total
317,345
437,244
613,391
32,893
647,019
39
180.439
134,108
38,541
12,340
65,937
13,710
7,340
29,504
12,620
88
195,590
78,531
9, 198
130.440
144,468
18,644,694
Mean
8, 577
10,411
13,051
1,134
9, 657
3
4,101
2, 235
6, 423
280
2, 061
381
198
1, 135
382
4
2, 357
1,247
1, 314
510
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
it.
T5
26
11
24
20
30
50
68
2
41
21
26
7
20
6
18
60
55
1
34
TABLE 5-8. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 5 BY
WASTE MANAGEMENT PROCESS ($1991)
i'Oldl dliliUdlll^BU. COSLS 'i'OLdl CdpiLdl AliliUdl OpBIdLlIiy dlTTX
costs maintenance costs
Total Mean Total Mean Total Mean
58,449
1, 670
129,809
3,709
39,967
1,142
2, 021
78
4,396
169
1, 395
54
572
52
1, 440
131
373
34
17,760
740
44,002
1, 833
13,606
567
7, 329
366
16,570
828
5, 003
250
188
6
241
8
155
5
45,629
913
1, 965
39
45,413
908
321,549
4, 729
655,300
9, 637
228,821
3, 365
385
193
760
380
278
139
11,365
277
23,619
576
8, 052
196
8,107
386
17,534
835
5,611
267
39,032
1, 501
85,947
3, 306
26,795
1, 031
5, 222
746
12,671
1,810
3, 470
496
26,444
1, 322
65,520
3,276
20,260
1,013
12,515
2,086
29,357
4, 893
8, 388
1,398
41
2
52
3
34
2
886,662
14,778
1,978,275
32,971
669,456
11,158
105,701
1, 922
220,545
4,010
74,393
1, 353
17,193
17,193
38,760
38,760
12,149
12,149
117,709
3, 462
236,520
6, 956
84,442
2, 484
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
lit.
"37
31
32
27
37
26
113
56
10
49
45
56
71
24
117
13
61
51
9
51
TABLE 5-8. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 5 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. COSLS 'i'OLdl CdpiLdl AliliUdl OpBIdLlIiy dlTTX
costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
274,104
8,566
536,457
16,764
197,725
6, 179
574,646
18,537
1,250,421
40,336
396,614
12,794
74,076
2, 315
178,788
5,587
48,967
1, 530
29,159
1,080
72,247
2, 676
22,340
827
80,477
2,175
199,200
5,384
53,269
1,440
4
0
6
0
4
0
6,470,478
57,261
2,187,251
19,356
6, 229, 658
55,130
610,733
10,906
1,434,995
25,625
434,945
7,767
931,423
93,142
2,762,963
276,296
608,748
60,875
261,428
5, 335
526,712
10,749
187,349
3, 823
1,863,319
41,407
4,224,657
93,881
1,261,822
28,041
1,610,338
28,756
3,583,539
63,992
1,100,123
19,645
1,298,857
18,294
3,026,143
42,622
874,705
12,320
15,556
648
38,541
1, 606
11,918
497
4,117,674
35,194
9,795,741
83,724
2,739,781
23,417
6
0
8
1
5
0
465,091
7, 624
44,031
722
460,253
7, 545
46,900
920
112,343
2,203
31,942
626
64,912
7,212
146,602
16,289
45,706
5,078
58,297
1, 143
122,941
2,411
40,956
803
-------
1
2
3
4
5
6
7
8
9
1
1
2
3
4
5
6
7
8
9
lit.
"37
31
32
27
37
26
113
56
10
49
45
56
71
24
117
13
61
51
9
51
TABLE 5-8. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 5 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. COSLS 'i'OLdl CdpiLdl AliliUdl OpBIdLlIiy dlTTX
costs maintenance costs
Total
Mean
Total
Mean
Total
Mean
274,104
8,566
536,457
16,764
197,725
6, 179
574,646
18,537
1,250,421
40,336
396,614
12,794
74,076
2,3315
178,788
5,587
48,967
1, 530
29,159
1,080
72,247
2, 676
22,340
827
80,477
2,175
199,200
5,384
53,269
1,440
4
0
6
0
4
0
17,824,793
157,742
12,051,363
106,649
16,500,220
146,020
610,733
10,906
1,434,995
25,625
434,945
7,767
931,406
93,141
2,762,931
276,293
608,735
60,874
261,428
5, 335
526,712
10,749
187,349
3, 823
1,863,319
41,407
4,224,657
93,881
1,261,822
28,041
1,610,338
28,756
3,583,539
63,992
1,100,123
19,645
1,298,857
18,294
3,026,143
42,622
874,705
12,320
15,556
648
38,541
1, 606
11,918
497
4,117,674
35,194
9,795,741
83,724
2,739,781
23,417
6
0
8
1
5
0
1,152,511
18,894
1,839,979
30,164
950,488
15,582
46,900
920
112,343
2,203
31,942
626
64,911
7,212
146,600
16,289
45,705
5,078
58,297
1, 143
122,941
2,411
40,956
803
-------
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
it.
TT
42
47
29
67
13
44
60
6
44
32
36
37
26
33
24
83
63
7
TABLE 5-8. COMPLIANCE COSTS, REGULATORY ALTERNATIVE 5 BY
WASTE MANAGEMENT PROCESS ($1991) (continued)
i'Oldl dliliUdlll^BU. COSLS
'i'Oldl Cd.piLd.1
costs
Aiiiiud.1 opeidLiny diicF
maintenance costs
Total
461,867
632,931
889,394
42,933
932,816
47
300,222
191,606
54,575
17,536
96,281
19,983
11,276
38,509
18,964
107
958,958
113,385
13,866
184,613
211,973
37,764,913
Mean
12,483
15,070
18,923
1,480
13,923
4
6, 823
3, 193
9,096
399
3, 009
555
305
1, 481
575
4
11,554
1,800
1, 981
721
Total
1,015,058
1,374,417
1,965,230
106,374
2,033,140
61
190
406,087
123,463
37,281
213,123
44,062
28,016
95,413
45,097
140
2,176,476
244,855
38,964
384,963
475,505
56,274,810
Mean
27,434
32,724
41,813
3, 668
30,345
5
4
6, 768
20,577
847
6,660
1, 224
757
3, 670
1,367
6
26,223
3,887
5,566
1,504
Total
317,345
437,244
613,391
32,893
647,019
39
300,199
134,108
38,541
12,340
65,937
13,710
7,340
29,504
12,620
88
719,991
78,531
9, 196
130,440
144,468
30,500,615
Mean
8, 577
10,411
13,051
1,134
9, 657
3
6, 823
2, 235
6, 423
280
2, 061
381
198
1, 135
382
4
8, 675
1,247
1, 314
510
-------
through 5-8. The total columns show the total compliance
costs (total annualized costs, total capital costs, or annual
operating and maintenance costs) associated with managing the
waste type. The Mean column shows the average cost incurred
by OWR facilities managing that waste type. The columns for
number of facilities show the number of facilities managing
that waste type on site. For the first regulatory
alternative, compliance costs for many of the waste types are
zero although facilities do offer that OWR service. For the
more stringent regulatory alternatives, processes managing
almost all waste types incur compliance costs.
The reader may notice that the total compliance costs
reported in Tables 5-4 through 5-8 slightly exceed the totals
reported in Table 5-3. The national compliance cost estimate
in Table 5-3 resulted from an estimate of quantities that
required considerable adjustment for use in a facility-
specific analysis. In addition, because of the assumptions
used in initially assigning facility-specific compliance costs
(that waste generators accurately reported where and how waste
was treated), some facilities were assigned compliance costs
for OWR processes they do not have.
5-29
-------
5-30
-------
5-31
-------
5-32
-------
5-33
-------
5-34
-------
5-35
-------
5-36
-------
5-37
-------
5-38
-------
5-39
-------
5-40
-------
5-41
-------
5-42
-------
5-43
-------
5-44
-------
The Agency assumed that the generators correctly reported
the process used but that the OWR facility initially receiving
the waste then brokered it to another OWR facility for
treatment.
Based on that assumption, all such compliance costs were
summed by process and shared out proportionally to the off
site quantity treated among facilities that
• accept waste from off site for management using that
process and
• already incur compliance costs associated with the
process.
These adjustments result in a very different pattern of
facility-specific wastes and compliance costs and also result
in a slight escalation of compliance costs. The most precise
national total is that shown in Table 5-3.
5.5 ENHANCED MONITORING COSTS
In addition to the costs of installing and operating air
pollution controls, OWR facilities are expected to incur costs
associated with enhanced monitoring of their processes and
controls to ensure that compliance is attained. Final
estimated enhanced monitoring costs were not available for
inclusion in this economic impact assessment. However, draft
national costs for enhanced monitoring have been estimated,
which total $1.3 million under RA1, $3.6 million under RA2,
$3.9 million under RA3, $4.2 million under RA4, and $4.3
million under RA5. Dividing these total costs by the 725
affected facilities gives an average enhanced monitoring cost
per facility of $1,800 under RA1, $5,000 under RA2, $5,300
under RA3, $5,800 under RA4, and $5,900 under RA5. Obviously,
the actual facility-specific monitoring costs will vary widely
depending on the processes each facility has on site.
5-45
-------
SECTION 6
IMPACTS OF THE REGULATORY ALTERNATIVES
The OWR operations standard will generally increase the
costs of performing various OWR services. The regulatory
alternatives will increase the costs of waste management and
recovery processes at most OWR facilities, depending on
• the waste management and/or recovery processes present
at the facility,
• the waste types treated in each process,
• the number and type of emission points present at each
process, and
• the baseline level of control for each emission point.
For each regulatory alternative to be analyzed,
compliance costs were estimated for each process, based on
facility-specific information and process models developed for
the analysis. The regulatory alternatives and the compliance
costs are described in detail in Section 5. The EPA expects
that most facilities affected by the standard will be required
to undertake capital investments and annual operating and
maintenance expenses to comply with the standard.
Compliance costs are expected to result in changes in
behavior at OWR facilities as owners of affected facilities
attempt to maximize profits. This analysis assumed that, at
baseline, the markets for OWR services were in equilibrium.
The increased costs associated with affected waste management
operations will result in a decrease in the market supply of
affected OWR services because facilities will now be willing
to treat smaller quantities at a given price than they were
6-1
-------
before incurring the compliance costs. Thus, there will be a
new, higher equilibrium price for each OWR service and a
smaller total quantity of each service being provided, other
market forces remaining equal.
Under the "with-regulation" conditions, some facilities
may find that certain services are no longer profitable for
them to perform. Other facilities may find that they can no
longer earn enough revenue from all their OWR operations to
cover their costs and may choose to close all their waste
management operations. Such changes in facility activities
result in changes in employment at the facility, that, in
turn, impose costs on not only the workers directly affected
but also the communities in which they live.
Finally, changes in the revenues received and costs
incurred by facilities for OWR services will, in turn, change
the financial status of the companies owning the OWR
facilities. Some companies may be pushed into financial
difficulties as a result of the changing profitability of the
facilities they own.
This section estimates the impacts that could result from
the various regulatory alternatives. First, the section
describes the market model used to estimate changes in
equilibrium price and quantity in each OWR service market as a
result of each regulatory alternative. Then, it describes the
effects of complying with the standard. Next, this section
addresses the new market equilibrium prices and quantities.
Finally, it describes the results of the analysis.
6.1 MARKET IMPACTS
As described earlier, the model has 60 markets for
differentiated OWR services, where each market is
characterized by a unique waste form-waste management process
combination. Each OWR facility participates in one or more of
the OWR service markets. The increased costs of OWR services,
resulting from the regulatory alternatives, cause
6-2
-------
disequilibrium in the markets for OWR services. The prices
and quantities of OWR services adjust until a new equilibrium
quantity is found in all markets.
The following section describes the model used to
estimate the changes in price and quantity that occur in each
market. Then it summarizes the impacts estimated using the
model.
6.1.1 Analytical Method Used to Estimate Market Impacts of
Regulatory Alternatives
As described above, complying with the regulatory
alternatives is expected to increase the cost of providing OWR
services, causing the supply of OWR services to decrease,
other market forces remaining equal. The interaction of the
reduced market supply with market demand will result in new,
higher equilibrium prices for OWR services and lower
equilibrium quantities of the services being provided. The
OWR market model attempts to quantify the changes in market
price and quantity for each affected waste management market,
and to estimate the number of processes and facilities
projected to close as a result of the standard.
6-3
-------
TABLE 6-1. VARIABLES USED IN THE OWR MODEL
Commodities in the model
Wastes managed at facility j (j subscript suppressed)
Qi j Waste form i accepted for management in process j
i waste forms 1 through 6, where
i=l inorganic soils
i=2 inorganic sludges
i=3 aqueous liquids or sludges
i=4 organic liquids
i=5 organic sludges or solids
i=6 other wastes
j treatment processes 1 through 10, where
j=l incineration
j=2 reuse as fuel
j=3 fuel blending
j=4 solidification/stabilization
j=5 solvent recovery for reuse
j=6 metals recovery for reuse
j=7 wastewater treatment
j=8 landfill disposal
j=9 underground injection
j — 10 other treatment
Total Wastewater treated on site (Q7)
Q7=S(Ql_7,...,Q6_7)
Prices in the model
Pi j Price for treatment process j of waste form i;
i=l,...,6; j=l,...,10
6-4
-------
Table 6-1 lists the commodities and prices included in the
model.
6.1.2 Scope of Market Analysis
Facilities that accept waste from off site for treatment,
storage, disposal, or recycling are covered by this
regulation. As shown in Table 6-1, OWR services include
incineration, reuse as fuel, fuel blending, solidification and
stabilization, solvent or liquid organic recovery for reuse,
metals recovery for reuse, wastewater treatment, landfill
disposal, disposal in an underground injection well, or other
treatment and recovery, each of which may be performed on one
of six waste forms. The list of commodities and prices in
Table 6-1 is based on the categories of waste management
operations for which quantity data are provided from the TSDR
and GENSUR databases. There are other types of waste
management activities for which no data are available in the
TSDR/GENSUR database, such as waste oil re-refiners and
industrial subtitle D landfills. These types of waste
6-5
-------
management operations will be addressed in a qualitative
manner, because no data sources have been identified that
would enable the Agency to quantify their impacts.
As shown in Figure 6-1
6-6
-------
6-7
-------
a typical OWR facility accepts wastes of various forms from
off site into assorted waste management processes. Some of
these processes produce salable products. Some of them result
in the generation of wastewater, which must then be treated.
In addition, possibly some wastes generated on site must be
treated but are not affected by this regulation. All of these
wastes pass through the facilities' waste management
operations, but only the wastes accepted from off-site
facilities not under the same ownership enter markets for
waste management services.
6.1.3 Baseline Quantities of OWR Services
The basic approach being used to model the supply of OWR
services is a stepped supply function of the type the Agency
has used frequently in the past. The market supply of each
type of OWR service equals the sum of all the quantities
supplied by facilities offering the service on a commercial
basis. The market is assumed to accept waste management
services in order of "lowest cost first." Facility supply, in
turn, is assumed to be a perfectly elastic function of the
costs of treatment. Because the facility is constrained not
to offer more than its capacity output of each service and is
assumed to be producing at capacity at baseline, this
assumption causes the facility to offer the baseline quantity
supplied of each service, if it produces any of the OWR
service at all. A more detailed characterization follows.
6.1.3.1 Facility Supply. Each facility is assumed to
solve a constrained optimization problem in each market, where
the objective function for facility k (k subscript suppressed)
is
n = TR - TC, or
n = £pi:Qi: - £ci:(Qi:), i=l, . . . , 6; j=l,...,10 (6-1)
subject to 0 < Qi: < Qji-capaCity
6-8
-------
where
n = profit,
TR = total revenue,
TC = total costs,
P = price to manage waste form i in process j,
Q = quantity of waste from i managed in process j, and
C±j = cost of managing waste i in process j (a function
of the quantity managed).
The subscript indicates waste form i managed in OWR process j.
The profit function may be expanded to include other costs and
other revenues, which would not vary with output and would be
assumed constant throughout the analysis. (They include, for
example, income from other waste management operations not in-
scope for the OWR regulation, interest income and expense,
selling and general administrative expenses, depreciation, and
so on.)
In the analysis, this optimization decision is equivalent
to each facility's selecting the optimal quantity supplied of
each waste management service, given its costs and the market
price, and subject to the constraints that output of each
service must be nonnegative and less than or equal to
capacity. Thus, if the price of an OWR service is less than
its average variable cost at a facility, the facility will not
provide the service. If, on the other hand, the price exceeds
the average variable cost, the facility will produce at its
capacity (baseline) level.
The operational model introduces a very small slope into
the horizontal section of the facility's step. This slope
makes it possible to solve for a unique quantity of output for
the marginal facility. Thus each facility solves for the
optimal unconstrained quantity of each service it wishes to
provide, using the following expression:
Qi: = (Pi: (AVC±j - a-AVCi:) ).(Qi:_baseline / a-AVCi:), (6-2)
where
6-9
-------
Qij
optimal quantity supplied of OWR service ij
.i-baseline
baseline quantity of OWR service ij
price of OWR service ij
AVC1:
average variable cost of OWR service ij, and
a»AVC±j
the vertical displacement from AVC±j at the
vertical intercept of the AVC1: curve.
This expression, if AVC±j < P1:, will yield a very large Q±j.
The facility is then constrained to produce its capacity
(baseline) quantity. If, on the other hand, AVC±j > P±j, the
expression returns a negative Qi:, and the facility is then
constrained to produce Qi: = 0.
The facility is assumed to face production constraints,
such that each service must be operating at or below its
capacity and the quantities of each product or service
produced must be nonnegative. As described above, "a" is
chosen to yield an almost infinitely elastic supply function
for the facility. In this analysis, the Agency used a value
of "a" equal to 0.0000001.
6.1.3.2 Market Supply. Market supply of service ij is
given by summing the quantities of waste treatment services
supplied by each of the k facilities:
The above specification of market supply represents a
modified "stepped supply function" in each market. Each
facility is assumed to be producing at capacity, and its
average variable cost is assumed (nearly) constant at all
output levels. Thus, the facility will either produce service
ij at capacity (if P±j > AVC±j) or it will not produce at all
6.1.3.3 Implications of the Assumptions. The result of
this construction of market supply is that all the adjustments
in output resulting from changes in market conditions occur at
Qm = ECL--
IJ k k,J
(if P±j < AVC±j) .
6-10
-------
the margin (the facilities with the highest AVC1:) . In this
case, for example, reductions in output will start with the
highest cost producer. If the reduction in equilibrium
quantity exceeds the output of the highest cost producer, that
facility will shut down process i, and the next highest AVC
facility will reduce its output of process ij. This
construction, therefore, overstates the impact on the marginal
facilities and understates the impact on inframarginal
facilities.
6.2 COMPLIANCE WITH THE STANDARD
Facilities subject to the standard will invest in capital
equipment and modify their processes that manage in-scope
wastes. Thus, the compliance costs will increase the AVC of
each affected process. Both fixed and variable compliance
costs were estimated for each facility, broken down by the
service categories affected. The fixed types of compliance
costs include the costs of installed capital equipment. The
variable costs of compliance include annual operating and
maintenance costs associated with the emissions controls.
Variable compliance costs were allocated to each process and
to each waste form within each process, as described in
Section 5. Compliance will increase the AVC of each affected
process. The variable compliance costs will affect the
profitability of each affected process and will therefore
affect the process-closure decision. The fixed compliance
costs (capital, land, and RCRA modification costs) will be
added to the other fixed costs experienced by the facility.
These will therefore be considered by the facility in
evaluating whether the entire facility can profitably remain
in operation.
6-11
-------
6.3 NEW MARKET EQUILIBRIUM PRICES AND QUANTITIES
The model determines new equilibrium prices and
quantities in each of the 60 markets.
6.3.1 Model Description
As described above, the compliance costs increase the
costs of doing the in-scope waste management services,
shifting each facility's AVC1: upward, and therefore shifting
upward the market supply curve for OWR process ij. In terms
of the equation for optimal Q±j, above, the AVC±j terms now
include the average variable cost of complying with the
regulation. At the baseline prices for these services,
therefore, Q1:D exceeds Qi:s. In Figure 6-2
6-12
-------
Figure 6-2. The effect of the emissions standard on the
market fo§-6t$R service i.
-------
at Pi-)1, the quantity demanded is Qij1, but with the regulation
in place, the quantity supplied is only Q1:2. A price-setting
algorithm is used to adjust the price (upward, if market
demand exceeds market supply). Specifically, the analysis
employs a price- setting algorithm proposed by Kimball and
Harrison95 that is used in computable general equilibrium
models. The price revision rule is
Pi: = Pij(old) • (Q1:D / Qi:s)b. (6-3)
The parameter b was set equal to 1 initially but can be
adjusted to give bigger or smaller price adjustments in
response to a given level of excess demand or excess supply,
as needed. The magnitude of the price revision, for a given
ratio of Q1:D and Q1:S, is determined by the b parameter: a high
value causes more extreme variations in price than a small
value. New market Qi:D's will be determined based on the new
market prices and the market elasticity of demand. Each
facility now faces a new market price for each process it
supplies. Each facility determines its profit-maximizing set
of Qij ' s (which will either be baseline quantity or zero) .
These are summed to the market level to find market supply.
Again, market supply and demand are compared. For each market
for which market supply and market demand are not equal, the
6-14
-------
market's price-setting algorithm returns a new price, and so
on, until all the markets are in equilibrium, at points such
as (Pij*, Qij*) in Figure 6-2.
As noted above, the quantity supplied of each service by
each facility will either be zero or the baseline quantity,
except for the marginal facility. Those facilities for which
the new AVC (with compliance costs) exceeds the new price will
stop offering that service. In other words, they will shut
down that process.
The analysis also requires that the facility as a whole
be profitable for production of any of its services to
continue. Thus, after each facility has selected its profit-
maximizing level of output for each service, the facility is
checked for profitability, taking into account fixed revenues
and fixed costs. Facilities that are not profitable will shut
down all their operations; their quantity supplied for all
services is set to zero, and the analysis continues. This
constitutes a facility shut down.
As shown in Figure 6-2, the Agency expects the market
prices to increase and the quantity supplied to decrease in
each of the affected waste management markets as a result of
the regulation. Because of the relatively low elasticity of
demand being assumed, the price is generally expected to
increase by almost as much as the costs have increased for the
marginal facility. For some inframarginal facilities, it is
possible that the price increase will exceed the compliance
cost increase. Thus, some facilities will actually find some
processes more profitable with the regulation in effect.
Once the estimation of changes in output, process shut
downs, and facility shut downs was completed, the Agency
projected changes in employment based on baseline employment
data given in the two surveys and on estimating reductions in
employment proportional to the reductions in output projected
by the model.
6-15
-------
6.4 RESULTS
The following section summarizes the results of the OWR
economic impact assessment model. Impacts estimated include
changes in prices and quantities of OWR services, facility and
process closures, changes in employment, and changes in
economic welfare.
6.4.1 Market and Facility Impacts of the Regulatory
Alternatives
6.4.1.1 Changes in Price and Quantity. The compliance
costs associated with the regulatory alternatives mean that
the cost of providing OWR services is higher with the
regulation than without. This increase in costs results in
decreased supply in affected OWR markets. As facilities
respond to their increased costs, some may decide to produce
fewer of some OWR services or to produce none at all. At
existing prices, the demand for these services exceeds the
supply, and the price of the services increases. The
interaction of the forces of supply and demand in the markets
will result in with-regulation equilibria characterized by
higher market prices and smaller quantities in affected
markets.
Tables 6-2 through 6-6
6-16
-------
TABLE 6-2. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 1, BY OWR PROCESS
Regulatory
- _ " I.--' ¦¦
Baseline
1
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q1 1
3,528.00
6,659
3,528.00
6,659
Q1 2
1 , 654 . 00
107
1 , 654 . 00
107
Q1 3
64.00
392
64.00
392
Q1 4
388.00
38,992
388.00
38,992
Q1 5
275.00
3,841
275.00
3,841
Q1 6
495.00
234,918
495.00
234,918
Q1 7
817.00
9,247
817.00
9,247
Q1 8
251.00
1,004,531
251.02
1,004,518
Q1 9
8.28
74
12.12
74
Q1 10
1,015.00
5,497
1,015.00
5,497
Q2 1
3,528.00
853
3,528.00
853
Q2 2
1,830.00
8, 351
1,830.00
8, 351
Q2 3
64.00
16,797
64.00
16,797
Q2 4
388.00
87,618
388.00
87,618
Q2 5
240.00
4,720
240.00
4,720
Q2 6
426.00
9,894
426.00
9,894
Q2 7
555.00
101,757
555.00
101,757
Q2 8
303.00
688,666
303.00
688,666
Q2 9
7.03
2, 382
7.03
2, 382
Q2 10
1,028.00
84,814
1,028.00
84,814
Q3 1
2,072.00
15,417
2,072.00
15,417
Q3 2
1,047.00
22,600
1,047.00
22,600
Q3 3
1,047.00
15,364
1,047.00
15,364
Q3 4
388.00
78,025
388.00
78,025
Q3 5
1,047.00
13,444
1,047.00
13,444
Q3-6
550.00
52,135
550.00
52,135
(continued)
6-17
-------
TABLE 6-2. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 1, BY OWR PROCESS (continued)
ReyuldLoiy :
Baseline Alternative 1
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q3 7
211.00
2, 945
628
211.00
2, 945
628
Q3 8
481.00
454
460
481.00
454
460
Q3 9
8.52
234
539
8. 97
234
539
Q3 10
768.00
181
833
768.00
181
833
Q4 1
2
,072.00
124
216
2,
072.00
124
216
Q4 2
331.00
196
986
331.00
196
986
Q4 3
331.00
1,427
190
331.00
1,427
190
Q4 4
682.00
20
738
682.00
20
738
Q4_5
928.00
1, 353
433
928.00
1, 353
433
Q4 6
125.00
4
647
125.00
4
647
Q4~7
206.00
139
811
206.00
139
811
Q4 8
550.00
125
291
550.02
125
290
Q4 9
8 . 75
11
685
8. 95
11
685
Q4 10
672.00
40
902
672.00
40
902
Q5 1
3
,528.00
35
207
3,
528.00
35
207
Q5 2
1
,654.00
97
654
1,
654.00
97
654
Q5 3
195.00
1,198
104
195.00
1,198
104
Q5 4
682.00
139
339
682.00
139
339
Q5 5
933.00
1,136
392
933.00
1,136
392
Q5 6
880.00
6
719
880.00
6
719
Q5 7
1
,654.00
64
459
1,
654.00
64
459
Q5 8
550.00
503
721
550.04
503
714
Q5 9
8 . 75
7
968
9.88
7
968
Q5 10
1
, 289.00
19
841
1,
289.00
19
841
(continued)
6-18
-------
TABLE 6-2. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 1, BY OWR PROCESS (continued)
Regulatory
Baseline Alternative 1
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q6 1
3, 528 . 00
11,283
3,528.00
11,283
Q6 2
1,830.00
7,392
1,830.00
7,392
Q6_3
191.00
3,720
191. 00
3,720
Q6 4
682.00
69,718
682.00
69,718
Q6~5
268.00
7, 465
268.00
7, 465
Q6 6
125.00
126,200
125.00
126,200
Q6~7
1,276.00
2,869,826
1,276.00
2,869,826
Q6 8
661.00
2,308,437
661.00
2,308,437
Q6 9
8.52
4,580
8. 63
4,580
Q6 "10
1,225.00
612,957
1,225.00
612,957
6-19
-------
TABLE 6-3. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 2, BY OWR PROCESS
Key uldLuiy-
Baseline Alternative 2
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Ql 1
3 , 52b . (JO
6,659
3 , 550 . 2(J
6,659
Q1 2
1,654.00
107
1,905.17
107
Ql 3
64 .00
392
69.39
390
Ql 4
388.00
38,992
393.48
38,920
Ql 5
275 .00
3, 841
285.29
3, 841
Ql 6
495.00
234,918
495.00
234,918
Ql 7
817.00
9,247
817.03
9,247
Ql 8
251.00
1,004,531
251.05
1,004,518
Ql 9
8.28
74
23.33
39
Ql 10
1, 015 .00
5, 497
1, 020 .41
5, 497
Q2 1
3,528.00
853
3,955.11
847
Q2 2
1,830.00
8, 351
1,838.86
8, 351
Q2 3
64 .00
16,797
64 .07
16,795
Q2 4
388.00
87,618
389.26
87,583
Q2 5
240 .00
4, 720
240 .00
4, 720
Q2 6
426.00
9, 894
427.20
9, 894
Q2 7
555.00
101,757
555.01
101,757
Q2 8
303.00
68 8,666
303 .45
688,407
Q2 9
7.03
2, 382
7.03
2,382
Q2 10
1,028.00
84,814
1,028.00
84,814
Q3 1
2,072.00
15,417
2,083.12
15,416
Q3 2
1, 047 .00
22,600
1,051.27
22,600
Q3 3
1, 047 .00
15,364
1,048.92
15,356
Q3 4
388.00
78,025
389.37
77,986
Q3 5
1, 047 .00
13,444
1, 057 . 02
13,439
Q3 6
550.00
52,135
550.04
52,135
(continued)
6-20
-------
TABLE 6-3. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 2, BY OWR PROCESS (continued)
Key uld Luiy
Baseline Alternative 2
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q3 7
211.00
2
, 945
628
211.01
2
,945,602
Q3 8
481.00
454
460
481.23
454,428
Q3 9
8.52
234
539
8.99
234,539
Q3 10
768.00
181
833
773.98
181,833
Q4 1
2
,072.00
124
216
2,073.25
124,210
Q4 2
331.00
196
986
335.56
196,607
Q4 3
331.00
1
, 427
190
331.00
1,
427,190
Q4 4
682.00
20
738
695 .18
20,684
Q4_5
928.00
1
, 353
433
929.17
1,
353,234
Q4 6
125.00
4
647
126.53
4, 647
Q4~7
206.00
139
811
206.00
139,811
Q4 8
550.00
125
291
553.76
125,168
Q4 9
8 . 75
11
685
8.96
11,685
Q4 10
672.00
40
902
673.26
40,902
Q5 1
3
,528.00
35
207
3,530.33
35,207
Q5 2
1
,654.00
97
654
1,655.32
97,654
Q5 3
195.00
1
, 198
104
195.00
1,
198,103
Q5 4
682.00
139
339
683.83
139,284
Q5 5
933.00
1
, 136
392
933.50
1,
136,309
Q5 6
880.00
6
719
880.88
6, 719
Q5 7
1
,654.00
64
459
1,654.01
64,459
Q5 8
550.00
503
721
550 .15
503,714
Q5 9
8 . 75
7
968
9. 93
7, 968
Q5 10
1
, 289.00
19
841
1,295.22
19,841
(continued)
6-21
-------
TABLE 6-3. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 2, BY OWR PROCESS (continued)
Key uldLuiy
Baseline Alternative 2
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q6 1
3, 528 . 00
11,283
3,593.28
11,253
Q6 2
1,830.00
7,392
1,839.42
7, 392
Q6 3
191.00
3,720
192.99
3, 718
Q6 4
682.00
69,718
684.27
6 9,689
Q6 5
268.00
7, 465
268.94
7, 463
Q6 6
125.00
126,200
125.08
126,200
Q6 7
1,276.00
2,869,826
1,276.00
2,869,825
Q6 8
661.00
2,308,437
661.01
2,308,437
Q6 9
8.52
4,580
8.85
4, 580
06 10
1.225.00
612.957
1.225.59
612.915
6-22
-------
TABLE 6-4. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 3, BY OWR PROCESS
Key uldLuiy
Baseline Alternative 3
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q1 1
3,528.00
6, 659
3,539.95
6, 659
Q1 2
1,654.00
107
2,154.23
107
Q1 3
64 . 00
392
68.82
390
Q1 4
388.00
38,992
394.32
38,920
Q1 5
275.00
3,841
280 . 42
3, 841
Q1 6
495.00
234,918
495.00
234,918
Q1 7
817.00
9,247
820.62
9,246
Q1 8
251.00
1,004,531
251.09
1,004,349
Q1 9
8.28
74
14.36
74
Q1 10
1,015.00
5, 497
1,017.88
5, 497
Q2 1
3, 528 . 00
853
3,888.62
847
Q2 2
1,830.00
8, 351
1,834.71
8, 351
Q2 3
64 . 00
16,797
64 . 08
16,795
Q2 4
388.00
87,618
389.39
87,583
Q2 5
240.00
4,720
240.00
4, 720
Q2 6
426.00
9, 894
426.64
9, 894
Q2 7
555.00
101,757
555.43
101,755
Q2 8
303.00
688,666
303.44
688,407
Q2 9
7.03
2,382
7.03
2, 382
Q2 10
1,028.00
84,814
1,028.00
84,814
Q3 1
2,072.00
15,417
2,078.32
15,416
Q3 2
1,047.00
22,600
1,049.27
22,600
Q3 3
1,047.00
15,364
1,048.92
15,356
Q3 4
388.00
78,025
389.63
77,986
Q3 5
1,047.00
13,444
1,054.02
13,439
Q3 6
550.00
52,135
550.09
52,135
(continued)
6-23
-------
TABLE 6-4. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 3, BY OWR PROCESS (continued)
ReyuldLoiy AlLenidLive
Baseline 3
OWR Price Quantity Price Quantity
market ($1991) (Mg) ($1991) (Mg)
Q3 7
211.00
2, 945
628
211.04
2, 945
602
Q3 8
481.00
454
460
481.28
454
428
Q3 9
8.52
234
539
9.01
234
539
Q3 10
768.00
181
833
771.17
181
833
Q4 1
2,
072.00
124
216
2, 073 .16
124
210
Q4 2
331.00
196
986
335.53
196
607
Q4 3
331.00
1, 427
190
331.00
1, 427
190
Q4 4
682.00
20
738
697 .42
20
684
Q4_5
928.00
1, 353
433
929.26
1, 353
234
Q4 6
125.00
4
647
125 .81
4
647
Q4~7
206.00
139
811
206.20
139
808
Q4 8
550 . 00
125
291
554.54
125
168
Q4 9
8 . 75
11
685
8.97
11
685
Q4 10
672.00
40
902
673.46
40
902
Q5 1
3,
528.00
35
207
3,529.88
35
207
Q5 2
1,
654.00
97
654
1, 655 .45
97
654
Q5 3
195.00
1,198
104
195.00
1,198
103
Q5 4
682.00
139
339
684.22
139
284
Q5 5
933.00
1, 136
392
933.45
1, 136
377
Q5 6
880.00
6
719
880 .47
6
719
Q5 7
1,
654 . 00
64
459
1,654.81
64
455
Q5 8
550.00
503
721
550 .15
503
714
Q5 9
8 . 75
7
968
9.97
7
968
Q5 10
1,
289.00
19
841
1, 297 . 84
19
803
(continued)
6-24
-------
TABLE 6-4. PRICE AND QUANTITY AT BASELINE AND UNDER
REGULATORY ALTERNATIVE 3, BY OWR PROCESS (continued)
Key uldLuiy
Baseline Alternative 3
OWR
Price
Quantity
Price
Quantity
market
($1991)
(Mg)
($1991)
(Mg)
Q6 1
3, 528 . 00
11,283
3,606.63
11,253
Q6 2
1,830.00
7, 392
1,835.00
7,392
Q6 3
191.00
3, 720
192 .54
3, 718
Q6 4
682.00
69,718
684.54
69,689
Q6 5
268.00
7, 465
268.88
7, 463
Q6 6
125.00
126,200
125.05
126,200
Q6 7
1,276.00
2,869,826
1,276.06
2,869,810
Q6 8
661.00
2,308,437
661.01
2,308,437
Q6 9
8.52
4, 580
9.16
4,580
06 10
1.225.00
612.957
1, 225 .71
612.915
6-25
-------
show the effects of the regulatory alternatives on market
TABEBBEE 6 6 6 6 PPPKffiCr.PiTOBWgnggfflfflTOYTIffiff^RHKRWWNKKffWW.FINflF.P
AT f$®S nfiffi d^ie d)
key ulalkte^ilMta^yaLi^
M.lteaxfe±tLiTee 44
PFffiftirafcpTOE
Q®sra1mlHi Jty
PrftSfcaExse
({ffiiii/njTiii in 111 ii i
rwHfflttfefflt
($$»»»))
(H®W
($$($a®PM)
»»)
WlTK
33
£> 2>$ SS1ES8Q fflffl
2, 2 |S JB fl 15$
3 33^®®iaa3
2,
(MM
l^tSKffiaQ®®
454Jifti®
1 AIP®M11?2
45®,3^1M8
OTB.3E8
nrusw nan
M8®aa®®
q no ERffissn ffiirm
2333i?®®S
"R R Q'SRQ£f)TlCiiEl ran
ospray
1
t j3 2 JzrispuPLi IUJUU
823®!lfQ®®
Z J5 a ^£2>al$ EPa-i®
2, appwiae'
a aap^sta (tuuuo
i, 83BEiaa($6
/I. jl|j>vy 1 Tlfrol)/)
OMM
2 5 ffi (fflffl
l^paapwssa
R.ro@a»w
CWMCT
9292mm
i,
92a2a®si
1, 31^®^SM0
OMLi®
U
0 2L2 282.0>Q ®®
61i i MB$5P
i2az«Maa9
61 ^.T^mw
0»I71
3,
5 29 ®(2@Q (fflffl
139£8J$HS
3,39®®®! 32)2
13 9L,3®$M®
om 2®
1,
8 3.Q 88E8®Q fflffl
l^mSRSlB
12a,^3S«
Q»393
64 8 (3685 D®
lS;jLig5'®5'
6% mm 6
1 Slffiia.'TO®
mzm
388 (fflffl
83QfBffgffll2
8 Sffi'SB (2® 6
ao84g$^zs
QSS2515
CWWS.'cTE
3
1
2§0$a®Q®®
£ 1 fj ®®
l^SQ 2M
970ffi§®»®
3,3jea®s®®7
1, ipSSTOffiO
31,3®02®
(MST/Ss
ggg.m
519 3i>@>0>Q ®®
368®ffl®Q®®
UflWWJWCHP
688»®S®$S
isssaaao
e®®saffi®3
1, llgM)2^pi5®
CM2959
9 3 9 0 ®Q ®CB
1,l?f3®»SS2
9333731)34
i, n3a^M®
Q^LGBO
1,
oa§®MQ®®
84^ii®ia
1 A9»S®fflfflI)5
8ۤ^ai^
CM3171
2;
0Eg®Q?®Q®®
iE^s§aaf
2,2®$®Si?fi7
Q®2S2
1,
oa^®acyQ®®
20 3^10 mi®
1,195)0510221
5 0
1,
0 4.7, ©GIB'S D®
i5 73-®§$®a
iA0«asa®®3
13],
QS33M)
1
3283ffi®Q®®
7 8 9 5?®# ®^l
1,2$® 92^2.2
2 97,E%m4ffL
Q3235 5
1,
o 4.7, otacy. o o
13, 4L4H .414
1 A0®'5.7Q2)2
13],33«31
Q3236 6
550 503® . 0 0
52, 524 1735
55® 0221
(coatia^ia^
(continued)
6-26
-------
prices and quantities. These tables show the baseline price
and quantity, and the price and quantity under each regulatory
alternative, for each of 60 OWR markets. RA1 imposes
compliance costs only in markets for landfilling and
underground injection services. Price increases range from
$0.02 per Mg for landfilling organic solids and organic solids
and sludges to $3.84 per Mg for underground injection of
inorganic solids. No market experiences a quantity decrease
of more than 0.01 percent, because of the low price
elasticities of demand being used in the model.
6-27
-------
6-28
-------
6-29
-------
6-30
-------
6-31
-------
6-32
-------
6-33
-------
6-34
-------
6-35
-------
6-36
-------
6-37
-------
6-38
-------
6-39
-------
6-40
-------
6-41
-------
Under RA2 through 5, markets for most OWR services are
affected. Under RA2, some markets are unaffected and others
experience price increases of only pennies per Mg. On the
other hand, some markets, such as the markets for underground
injection of inorganic solids and the market for reuse as fuel
of inorganic solids, experience relatively large percentage
changes in price and quantity under RA2. A 181 percent
increase in price and a 48 percent decrease in quantity are
projected to occur in the market for underground injection of
inorganic solids. This market has only two facilities
participating in it. In fact, the market is unlikely to
exist, because solids would have to be diluted enough to be
pumpable before being injected underground. Thus, other
disposal methods would likely be less costly. The market
price for reuse of inorganic solids as fuel increases by 15.2
percent, the next largest percentage increase in price. The
next largest percentage decrease in quantity treated is a 0.63
percent decrease in the quantity of fuel blending of inorganic
solids. Overall, the quantity of waste managed in OWR
operations is projected to decrease by 0.008 percent (1,548.4
Mg) under RA2.
Under RA3, the quantity of waste managed in OWR
operations is projected to fall by 1,677 Mg or 0.009 percent.
The price of underground injection of inorganic solids is
projected to increase by 73 percent, while the quantity of
inorganic sludges incinerated experiences the largest
percentage decrease, 0.78 percent.
RA4 and RA5 produce very similar results. Under RA4, the
overall quantity of waste managed in OWR operations is
projected to decline by 1,581 Mg; under RA5 it is projected to
decline by 1,592 Mg. Both quantities constitute approximately
0.008 percent of baseline commercial OWR quantities. The
market for underground injection of inorganic solids is
projected to incur a 182 percent increase in price and a 48
percent decrease in quantity under both RA4 and RA5. The next
largest impacts are projected to occur in the markets for
6-42
-------
reuse of inorganic solids as fuel (a 15.2 percent increase in
price) and fuel blending of inorganic solids (a 0.63 percent
decrease in quantity).
6.4.1.2 Facility Closures and Process Shut-Downs.
Another measure of the economic impact of a regulation is the
number of facility closures it causes. If a facility's
compliance costs associated with a regulatory alternative
raise the average variable cost of providing an OWR service
above its market price, it is no longer profitable for the
facility to offer that service. This is defined as a process
shut-down at that facility. At a facility that shuts down one
or more OWR processes, other activities may continue. On the
other hand, the entire facility may become unprofitable. This
may occur for one of two reasons:
• all the processes at a facility become unprofitable;
or
• the processes remain profitable, but the annualized
capital costs cause the facility as a whole to be
unprofitable.
Thus, the model identifies both processes and facilities that
become unprofitable under various regulatory alternatives.
Table 6-7
6-43
-------
TABLE 6-7. CLOSURES UNDER EACH REGULATORY ALTERNATIVE
Ktt.1 Rao Rh4 RaIT
Unprofitable
facilities
0
10
10
10
10
Process shut-downs
at
facilities remaining
open
Q1 1
--
1
1
1
1
Q1 2
--
--
--
--
--
Q1 3
--
1
1
1
1
Q1 4
--
2
2
4
4
Q1 5
—
—
—
--
—
Q1 6
--
--
--
1
1
Q1 7
--
2
4
5
5
Q1 8
1
1
4
1
1
Q1 9
--
1
--
1
1
Q1 10
--
1
1
1
1
Q2 1
--
2
2
2
2
Q2 2
--
--
--
--
--
Q2 3
--
1
1
1
1
Q2 4
--
3
3
3
3
Q2 5
—
—
—
—
—
Q2 6
--
--
--
--
--
Q2 7
--
2
4
4
5
Q2 8
--
3
3
--
--
Q2 9
--
--
--
--
--
Q2 10
--
3
3
3
3
Q3 1
--
1
1
1
1
Q3 2
—
—
—
—
—
Q3 3
--
1
1
--
--
Q3 4
--
2
2
3
3
Q3 5
--
1
1
1
1
Q3 6
--
--
--
--
--
(continued)
6-44
-------
TABLE 6-7. CLOSURES UNDER EACH REGULATORY ALTERNATIVE
(continued)
kAi
Rn^
Rao
ra4
RA5
Unprofitable
0
10
10
10
10
facilities
Q3 7
--
2
2
2
2
Q3 8
--
6
6
7
7
Q3 9
--
--
--
--
--
Q3 10
--
1
1
1
1
Q4 1
--
2
2
3
3
Q4 2
--
1
1
1
1
Q4 3
--
--
--
--
--
Q4 4
--
3
3
3
3
Q4_5
--
3
3
4
4
Q4 6
--
--
--
--
--
Q4~7
--
2
3
4
4
Q4 8
1
3
3
5
5
Q4 9
--
--
--
--
--
Q4 10
--
1
1
2
2
Q5 1
--
2
2
4
4
Q5 2
--
--
--
--
--
Q5 3
--
1
1
1
1
Q5 4
--
3
3
3
3
Q5 5
--
2
1
2
2
Q5 6
--
--
--
1
1
Q5 7
--
2
4
4
4
Q5 8
1
1
1
1
1
Q5 9
1
1
1
1
1
Q5 10
--
1
2
1
1
(continued)
6-45
-------
TABLE 6-7. CLOSURES UNDER EACH REGULATORY ALTERNATIVE
(continued)
kki
k
k/u
kM
kA5
Unprofitable
facilities
0
10
10
10
10
Q6 1
--
4
4
4
4
Q6 2
--
--
--
--
--
Q6 3
--
2
2
2
2
Q6 4
--
3
3
3
3
Q6 5
--
9
9
9
9
Q6 6
--
--
--
--
--
Q6 7
--
2
5
5
5
Q6 8
—
—
—
—
—
Q6 9
--
--
--
--
--
Q6 10
--
5
5
5
5
Total process
4
90
102
111
112
closures
6-46
-------
shows the number of facility and process closures projected
to occur under each regulatory alternative. If either all the
commercial processes at a facility are shut down or the fixed
costs are so high that the facility becomes unprofitable as a
whole even though all of its OWR processes are profitable, the
model predicts a facility closure.
The impacts predicted by the model to result from the air
emission standards reflected by RA1 through RA5 range from no
facilities becoming unprofitable under RA1 to 10 facilities
becoming unprofitable under each of the other RAs. Although
the model operates as though all 10 of the unprofitable
facilities will cease operations, several are government-owned
or captive facilities, which are unlikely to close. Thus, of
the 10 unprofitable facilities, under RA3 through RA5, at most
six are likely to be facility closures. The number of process
6-47
-------
6-48
-------
6-49
-------
closures ranges from four under RA1 to 90 under RA2, 102 under
RA3, 111 under RA4, and 112 under RA5. This count of process
shut-downs includes both process closures at facilities that
remain in operation and process closures associated with
facility closures. Thus, only a few facilities are predicted
to close, and under the most stringent regulatory
alternatives, fewer than 7 percent of commercial processes
that at least broke even at baseline are predicted to become
unprofitable.
For facilities that remain in operation, profits may
change as a result of the regulatory alternatives. These
facilities may experience decreases in profitability, if
market prices do not increase as much as their average
variable costs have increased, or they may experience
increased profitability if prices increase by more than their
average variable costs. The column labeled "Change in
producer surplus" in Table 6-9 (discussed in Section 6.4.3)
shows the estimated changes in profits experienced under each
regulatory alternative.
6.4.2 Employment Impacts
Because of the changes in the quantity of off-site
commercial waste being managed (described in the previous
section), changes in employment at OWR facilities are also
predicted to result from the regulatory alternatives. Data on
employment in hazardous waste management operations and other
operations (e.g., manufacturing, administrative) were provided
in both the TSDR Survey and the CWT Survey. Employment data
were provided by 551 of the 725 OWR facilities under analysis.
Using these baseline data and predicted changes in the
quantities of waste managed at OWR facilities, the model
predicts changes in employment resulting from each regulatory
alternative.
Under the assumption that noncommercial waste management
operations (both on site and off site) will continue at their
baseline levels under the regulatory alternatives, the
projected changes on the total quantity of waste managed equal
6-50
-------
the changes in commercial waste management projected by the
market model. Changes in employment (direct job loss)
resulting from a regulatory alternative were computed using
the following formula:
^withRA ^baseline
' total waste managedwithRA x
total waste managed
baseline
(6-4)
Table 6-8 shows the predicted job losses at OWR
facilities under each regulatory alternative. Of 951,216
workers reported to be employed at baseline by the 551
facilities giving employment information, approximately 275
employees are expected to be displaced at OWR facilities under
all of the regulatory alternatives.
6.4.3 Economic Welfare Impacts
The value of environmental improvements that result from
regulatory policy can be measured against the change in
economic welfare resulting from the costs of compliance.
Welfare impacts resulting from the regulatory controls on the
OWR industry will accrue to the consumers and producers of OWR
services. Consumers of OWR services experience welfare
impacts due to the adjustments in prices and quantities of OWR
services caused by imposing the regulations. Producer welfare
impacts result from the changes in profits associated with the
additional costs of production and the corresponding market
adjustments. This section describes the theoretical methods
TABLE 6-8. CHANGES IN EMPLOYMENT UNDER THE REGULATORY
ALTERNATIVES (FOR 551 COMMERCIAL FACILITIES)
ReyuldLoiy AlLenidLive
Job lusaea
RA1
272
RA2
275
RA3
278
RA4
276
RA5
276
6-51
-------
of applied welfare economics used to evaluate public policies
and the specific approach used to estimate changes in economic
welfare resulting from the OWR regulatory alternatives.
The economic welfare implications of the post-compliance
market price and quantity changes in the markets for OWR
services are measured by estimating changes in the net
benefits of consumers and producers resulting from the price
and quantity changes.
6-52
-------
Contains Data for
Postscript Only.
Figure 6-4. Change in producer surplus with regulation.
Figures 6-3 and 6-4 depict the changes in welfare by
measuring the changes in consumer surplus and producer
surplus. In essence, the demand and supply curves previously
used as predictive devices are now being used as a valuation
Contains Data for
Postscript Only.
Figure 6-3. Change in consumer surplus with regulation.
6-53
-------
tool.
This method of estimating the post-regulatory change in
economic welfare divides society into consumers and producers.
In a market environment, consumers and producers of the
service being traded derive welfare from the transaction.
Consumer surplus is defined as the difference between the
maximum amount consumers are willing to pay for an amount of a
good or service and the amount they actually pay. Consumer
surplus is measured as the area under the demand curve and
above the price of the product. Similarly, the difference
between the minimum amount producers are willing to accept for
a given amount of the good or service and the price they
actually receive is referred to as producer surplus. Producer
surplus is measured as the area above the supply curve and
below the price. These areas may be thought of as consumers'
net benefits of consuming the good or service and producers'
net benefits of producing it.
In Figure 6-3, baseline equilibrium occurs at the
intersection of the demand and supply curves for a given OWR
service. Baseline equilibrium price is Px and baseline
equilibrium quantity is Qx. The increased cost of production
with the regulation will cause the market supply curve to
shift upward to Sy . The new equilibrium price of the OWR
service is P2. Higher prices for OWR services mean less
welfare for the consumers of the service, all else being
unchanged. In Figure 6-3, area A represents the dollar value
of the annual net loss in consumers' benefits with the
increased price of OWR services. The rectangular portion
represents the loss in consumer surplus on the quantity still
consumed, Q2, while the triangular area represents the
foregone surplus resulting from the reduced amount of the OWR
service consumed.
As discussed previously, OWR services are intermediate
goods that contribute to the production of other goods and
services. This study does not assess economic impacts or
6-54
-------
TABLE 6-9. CHANGES IN ECONOMIC WELFARE WITH THE REGULATORY
ALTERNATIVES
olidiiyti ±n olidiiyti ±n olidiiyti ±n
Regulatory consumer producer surplus economic welfare
Alternative surplus
RA1 -155,347 -86,855,094 -87,010,491
RA2 -9,328,426 -95,057,764 -104,386,190
RA3 -9,505,124 -95,145,454 -104,650,578
RA4 -11,327,708 -96,169,797 -107,497,505
RA5 -11.333.814 -96.0 35 .168 -107.3 68.982
changes in welfare in the markets for the goods and services
in whose production OWR services are an input. Rather, this
study focuses on changes in economic welfare resulting from
impacts in the markets for OWR services.
In addition to the changes in consumers' welfare,
producers' welfare also changes with the regulations. With
the increase in market prices for OWR services, producers
receive higher revenues for the quantity still purchased, Q2.
In Figure 6-4, area B represents the increase in revenues due
to this increase in prices. The difference in the areas under
the two supply curves up to the original market price, area C,
measures the loss in producer surplus, which includes the loss
associated with the quantity no longer produced. The net
change in producers' welfare is calculated as area B - C.
The change in economic welfare attributable to the
compliance costs associated with the regulatory alternatives
is the sum of consumer and producer surplus changes. The
change is (-A) + (B - C).
As shown in Table 6-9, the changes in consumer surplus
are relatively small, ranging from a decrease of $155,000
under RA1 to a decrease of $11,334,000 under RA5. The changes
in producer surplus are much larger, ranging from a decline of
$86,855,000 under RA1 to a decline of $96,170,000 under RA4.
The overall changes in economic welfare range from a decline
6-55
-------
of $87,010,000 under RA1 to a decline of $107,498,000 under
RA4. The changes in economic welfare are very similar under
RA4 and RA5: declines of $107,498,000 and $107,369,000,
respectively.
This analysis measures changes in economic welfare
associated with the production and consumption of OWR
services. The reader may notice that these numbers are
considerably higher than the national costs shown in Table
5-3. The national annual costs measure the economic impacts
incurred by the regulated industry. The welfare impacts
reported in Table 6-9 include not only those costs but also
changes in welfare incurred by the industry's customers and
others in society. These social costs should be compared with
estimated benefits--the value of the reduced levels of air
pollution resulting from the regulation--to assess the overall
net impact of the regulation on society's welfare.
6.5 COMPANY IMPACTS
The legal and financial responsibility for compliance
with a regulatory action rests with the owners of the OWR
facility who must bear the financial consequences of their
decisions. Thus, an analysis of the company-level impacts in
the context of EPA regulations involves identifying and
characterizing affected entities, assessing their response
options and modeling or characterizing the decision-making
process, and analyzing the impacts of those decisions.
Sections 3.7 and 4.2 of this report identify the affected
entities and characterize them according to relevant
characteristics including size, degree of horizontal or
vertical integration, capital structure, and baseline
financial condition. In this section, EPA addresses the other
components of an analysis of company-level impacts. First,
this section identifies the owners' response options and
characterizes their decision-making process. It then presents
6-56
-------
the company-level impacts including potential changes in the
capital structure and cost of capital, changes in financial
status, and financial failure.
6.5.1 Owners' Responses
Companies have many options in deciding how to respond to
the proposed regulatory alternatives. For some companies,
some compliance approaches may be more profitable than
installing the control equipment upon which the Agency's
compliance costs are based. These other possible responses
include the following:
• complying with the regulation via process and/or input
substitution (as opposed to installing the Agency's
prescribed control equipment),
• ceasing to accept troublesome wastes from off-site for
treatment in one or more of the processes they offer,
and
• choosing another--less costly--control technology that
would meet the emissions control requirements of the
regulation.
The Agency lacks sufficient information, however, to evaluate
facility and market impacts of complying with the alternative
approaches. Consequently, the company-level analysis is based
on the assumption that owners are limited to the following
three response options:
• discontinuing regulated processes within the facility
if the owners expect them to become unprofitable,
• closing the facility if all OWR processes are expected
to become unprofitable, and
• installing and operating the specific control
technologies on which the Agency has based its costs
of compliance for each OWR process that owners
continue to offer with the regulation in place.
Limiting owners' response options to the three listed above
enables the Agency to model the financial impacts of the
regulation in a systematic way that is logically consistent
across all facilities owned by companies included in this
6-57
-------
analysis. The impacts presented in this analysis are perhaps
best interpreted as an upper bound on expected impacts,
because other approaches to compliance may be less costly for
some facility owners.
The market model developed in Section 6.3.1 simulates
facility and market impacts under the three response options
listed above. Under each of these options affected firms will
potentially experience changes in the costs of providing waste
treatment services as well as changes in the revenues
generated by providing these services. The cost impacts
associated with the response options include the costs of
installing and operating control equipment, closure costs, and
changes in baseline production costs that occur because of a
change in the quantity of OWR services provided. The revenue
impacts associated with the regulation stem from the combined
effects of changes in the quantity of OWR services provided by
facilities owned by each affected company and changes in
market prices for OWR services that result from a shift in the
market supply of waste treatment services.
This analysis assumed that the owners of an affected
facility will select the course of action from the response
options listed that maximizes the value of the firm, subject
to uncertainties regarding actual costs of compliance,
behavior changes among OWR service demanders, and the response
behaviors of other firms. Each owner's expected cost and
revenue impacts will motivate the changes in operations that
they make to their baseline OWR operations. The Agency has no
way of knowing the types of assumptions individual OWR owners
will make to predict the behavior changes of OWR demanders and
of other OWR service providers. Owner expectations as to the
direction and magnitude of price and quantity changes that the
proposed regulatory alternatives would cause in each OWR
service market will vary from one owner to the next with
differences in their knowledge of the following:
• their customers' elasticities of demand for the
services they offer,
6-58
-------
• their competitors' baseline costs of providing
service,
• their competitors' costs of complying with the
regulation for each service they offer, and
• economic theory.
The Agency assumed for this analysis that the assumptions
governing demanders' and competitors' behavior changes in the
market model mirror OWR facility owners' expectations of their
responses. Thus, we assumed that the market model correctly
identifies the appropriate response, from the three response
options identified for this analysis, that profit-maximizing
firms would choose for each OWR service offered at each of
their OWR facilities.
Tables 6-10 through 6-12
6-59
-------
TABLE 6-10. PROJECTED CHANGE IN REVENUE ($/year)
i±±m size ±n d.iiiiud.1 leceipLs $ I u : / y edi ^
$60 to Over
$0 to $6 $6 to $60 $1,000 $1,000
Regulatory Alternative
Reg
Alt 1
Facilities with costs
8
13
10
7
Mean
1,060
4, 722
4, 911
4,045
Standard deviation
1,860
7,610
6, 912
7, 713
Quartiles
Upper
1, 792
4, 564
6, 626
7,176
Median
102
1,190
1,894
186
Lower
26
734
66
36
Reg
Alt 2
Facilities with costs
106
78
48
39
Mean
1, 704
18,082
85,840
64,317
Standard deviation
19,101
64,867
199,131
287,378
Quartiles
Upper
3, 037
21,200
59,204
7, 516
Median
777
6, 525
18,858
1,715
Lower
132
501
1, 434
59
Reg
Alt 3
Facilities with costs
107
80
49
39
Mean
680
20,008
7 9,699
70,186
Standard deviation
18,467
72,359
170,489
294,526
Quartiles
Upper
3, 068
21,470
52,282
17,472
Median
846
6, 354
18,005
1, 850
Lower
217
427
927
72
Reg
Alt 4
Facilities with costs
106
79
49
39
Mean
2, 381
23,317
101,677
77,713
Standard deviation
23,283
N/A
231,120
320,017
Quartiles
Upper
3, 999
23,610
60,837
20,736
Median
1, 038
6,069
16,881
2,219
Lower
177
505
1,746
251
Reg
Alt 5
Facilities with costs
106
79
49
39
Mean
2, 383
23,267
101,739
77,729
Standard deviation
23,283
77,962
231,181
320,016
Quartiles
Upper
3, 999
23,610
60,837
20,736
Median
1, 063
6,069
16,881
2,219
Lower
177
399
1.746
251
6-60
-------
TABLE 6-11
PROJECTED CHANGE IN OPERATING COSTS ($/year)
J? _L JLIll Size ±11 dliliUdl
e±pLa \ $ I u : / y edif
$60 to
Regulatory Alternative $0 to $6 $6 to $60
$1,000
Over
$1,000
Reg Alt 1
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 2
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 3
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 4
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 5
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
1
43
N/A
4
191
264
2
3,819
5,386
1
-7,894
N/A
43
43
43
337
68
45
7,627
3,819
10
-7,894
-7,894
-7,894
39
-729
31,250
29
-3,051
42,125
24
1,262,832
4,696,779
19
666,671
2,061,244
1,187
117
-38
4,415
616
32
84,869
7,624
630
76,790
2,081
32
41
-982
32,867
31
502
44,770
26
1,163,756
4,514,095
19
1,131,549
2,642,722
1,521
171
-26
6,372
1,201
32
89,556
3,081
450
172,314
3,302
47
44
4,019
57,789
33
7,920
52,089
30
2,796,727
13,526,758
22
1,194,588
3,379,758
1,393
122
3
8,083
1,013
64
116,449
5,677
387
133,527
3,115
294
44
4,032
57,789
33
11,406
54,557
30
2,796,773
13,526,749
22
1,221,699
3,429,232
1,393
122
3
15,386
702
28
116,449
5,677
387
141,602
3,115
294
6-61
-------
TABLE 6-12
Regulatory
PROJECTED CAPITAL COMPLIANCE COSTS ($/year)
jjii'in in annual ree^ipm (SiU'Vy^ai1) =
Over
$0 to $6 $6 to $60 $60 to $1,000 $1,000
Reg Alt 1
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 2
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 3
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 4
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
Reg Alt 5
Facilities with costs
Mean
Standard deviation
Upper
Medi an
Lower
3
9,431
16,158
28,089
191
14
86
68,416
75,645
156,313
21,473
3,176
195,158
265,776
574,000
21,232
2,
93
235,604
318,146
693,922
31,644
7,858
93
235,733
318,053
693,922
31,644
7,903
133,736
185,179
167,957
79,321
359
113,925
108,372
195,993
100,925
31,857
1,070,94
0
N/A
1,070,94
0
1,070,94
0
1,070,94
0
65
66
84
134
,280
287,243
292,
770
190
,234
677,134
363,
484
179
,210
179,210
358,
420
82
,447
179,210
179,
210
6
, 354
27,593
179,
210
69
69
88
236
,937
561,176
7 66,
723
418
,664
977,570
875,
921
250
,998
596,922
1,193
CO
81
,906
596,922
4
6
, 395
10,290
596,
922
27 6,
933
71
73
92
300
,820
661,085
94 6,
197
507
,408
1,188,638
1,313
,28
O
400
,255
736,660
o
130
,015
736,660
1,011
, 68
11
, 755
7,161
6
736,
660
145,
706
71
73
92
311
, 865
800,713
996,
106
579
,531
1,594,949
1,348
,43
O
400
,255
736,660
o
130
,015
736,660
1,374
,16
12
,773
12,261
4
736,
660
221 .804
6-62
-------
summarize the projected revenue and cost impacts for
potentially affected firms in each size category. The
distribution of impacts reported in Tables 6-10 through 6-12
excludes firms that are not projected to incur impacts.
Revenue impacts are generally positive, indicating that the
projected price increases more than offset the corresponding
quantity decreases for most firms. Where product line or
facility shut down occurs, the revenue losses associated with
these decisions are included in the estimated revenue impacts.
The operating cost impacts reflect both increases in
production costs associated with operating control equipment
as well as decreases in baseline production costs due to a
reduction in the quantity of waste treatment services
provided. Consequently, the net change in operating
6-63
-------
6-64
-------
6-65
-------
cost impacts may be negative, indicating a net reduction in
baseline operating costs, or positive, indicating an increase
in operating costs over the baseline values. Typically,
however, firms with a net reduction in operating costs also
incur a loss in revenue that more than offsets the operating
cost savings. Thus, the impact on a firm's bottom line may be
negative (cost increases that exceed revenue increases) or
positive (revenue increases that exceed cost increases). For
most firms in this analysis, cost increases exceed revenue
increases.
The with-regulation prices of the relevant waste
treatment services are market-determined and estimated using a
market model based on the principles of microeconomics. These
market-price estimates were assumed to match each OWR owner's
expectations of the with-regulation equilibrium prices for
each OWR service. The Agency then modeled each owner's
decisions by comparing Agency estimates of the facility-
specific average total avoidable cost (ATAC) of providing each
treatment service to the corresponding with-regulation
equilibrium price estimates. Figure 6-5
6-6 6
-------
Contains Data for
Postscript Only.
Figure 6-5. Characterization of owner responses
to regulatory actions.
6-67
-------
shows the decision process. In this context, ATAC includes
all costs that would fall to zero if the facility were to
discontinue operations in the given OWR service and reflects
any post-closure costs as well as the salvage value of assets.
Debt obligations, which must be met regardless of whether the
facility continues to operate, are not included in ATAC. If
the expected with-regulation price for a particular service is
less than the ATAC for that service, the firm maximizes the
present value of the facility by exiting the market for that
service. If the expected with-regulation price is lower than
the corresponding ATAC for all OWR services that the OWR
facility offered at baseline, the firm maximizes its present
value by discontinuing all regulated operations within the
facility or by closing the facility altogether. These
decisions are referred to as voluntary exit decisions, because
owners of the firm, as opposed to creditors, make the exit
decision. Exit
6-68
-------
may take the form of liquidation of assets, a distressed sale
of the facility to another firm, or conversion of the facility
or production lines within the facility to other uses.
The with-regulation prices of the relevant waste
treatment services are market-determined and are estimated
using a market model based on the principles of micro-
economics. To model the owners' decisions, the with-
regulation price of waste treatment services was compared to
the average total avoidable cost (ATAC) of providing these
services. Figure 6-5 shows the decision process. In this
context, ATAC includes all costs that fall to zero when the
facility discontinues operations and reflects any post-closure
costs as well as the salvage value of assets. Debt
obligations, which must be met regardless of whether the
facility continues to operate, are not included in ATAC. If
the persistent with-regulation price is less than ATAC, the
firm maximizes its present value by discontinuing regulated
operations within the facility or closing the facility. This
decision is referred to as voluntary exit because owners of
the firm, as opposed to creditors, make the exit decision.
Exit may take the form of liquidation of assets, a distressed
sale of the facility to another firm, or conversion of the
facility or production lines within the facility to other
uses.
If price is greater than or equal to ATAC, the firm will
likely implement the cost-minimizing compliance option and
continue to operate the facility. As long as the firm
continues to meet its debt obligations, operations will
continue. However, if the firm cannot meet its interest
payments or is in violation of its debt covenants, the firm's
creditors take control of the exit decision and forced exit
may occur. If the market value of debt (DM) under continued
operations is greater than the liquidation value of debt (DL) ,
creditors will probably allow the facility to continue to
operate. Under these conditions, creditors may renegotiate
the terms of debt. Either way the owners will implement the
6-6 9
-------
profit-maximizing compliance option and continue to operate
the facility. If, however, the market value of debt under
continued operations is less than its liquidation value,
involuntary exit will result and the facility will discontinue
operations. Exit will likely take the form of liquidation of
assets or distressed sale of the facility.
In the decision-making process outlined above, current
owners either implement the profit-maximizing compliance
option and continue to operate the facility, discontinue the
regulated operations or close the facility voluntarily, or
close the facility involuntarily. The first two outcomes are
the result of operating decisions by the owners of the firm.
The decision to continue to operate may be accompanied by a
change in the cost of capital, capital structure, and
financial status of the firm. The market model described in
Section 6.3.1 projects the second decision identified above
(facility or product line closure). This decision will
certainly result in a change in the financial status of the
firm and may result in the financial failure of the firm. The
last outcome is the result of a decision by the firm's
creditors. This decision will result in a change in the
financial status of the firm and may result in financial
failure. Indeed, in the case of a single-facility firm, this
last outcome is synonymous with financial failure. The
impacts of the regulation evaluated in the following section
include the projected changes in the cost of capital and
capital structure, changes in financial status, and projected
financial failure for the potentially affected firms
identified for analysis.
6.5.2 Impacts of the Regulation
This analysis evaluated the change in financial status by
first projecting the change in the cost of capital and the
capital structure for potentially affected firms. Next, the
with-regulation financial ratios of potentially affected firms
were computed and compared to industry benchmarks and the
corresponding baseline ratios. (See Section 4.2 for a
6-70
-------
description of the financial ratios used in this analysis.)
Finally, the analysis projected financial failure due to the
regulation based on Z-score ratios.
Three firms are excluded from the distribution of impacts
presented in this section. These firms are single-facility
firms that own a facility projected to close because of the
regulatory impacts. As noted above, facility closure is
synonymous with firm financial failure for single-facility
firms. Thus, the projected with-regulation annual sales and
operating costs are zero. Estimation of with-regulation
capital structure, cost of capital, and financial ratios for
these firms is meaningless and, in some cases, impossible.
Consequently, the impacts presented in this section are based
on 385 of the 388 firms identified as potentially affected
firms for this analysis.
6.5.2.1 Changes in the Cost of Capital and Capital
Structure. Investments in pollution control equipment
required to comply with the regulation will potentially reduce
the debt capacity of the firm, change its capital structure,
and increase its cost of capital. This section describes the
framework used for projecting the impacts of the regulation on
the firm's capital structure and its cost of capital. In
addition, estimates of the change in firm-specific costs of
capital due to the regulation are presented.
In financial theory, the value of an investment is
measured as the present value of its future cash flows. The
cash flows associated with an investment in pollution control
equipment are generally negative. Thus, pollution control
investments tend to reduce the firm's value.* Furthermore,
'"Reduce" here means reduce from what the firm's value would be
if there were no legal requirement to invest in pollution control
equipment. However, the promulgation of a regulation should trigger
a reassessment of the value of an affected firm's facilities. Thus,
if there is a regulation, and the alternative to control equipment
is facility shut-down, and shut-down would be very costly, then
investment in pollution control equipment probably would increase
the firm's value.
6-71
-------
pollution control investments generally reduce the debt
capacity of potentially affected firms by reducing the firm's
profitability and, thus, the overall ability of the firm to
support debt service.96 The change in firm value can be
estimated using the following equation:
AV = K + S (R + 0)/(1+r) (6-5)
where
AV = the change in firm value,
K = the installed capital costs of the regulation,
R = the change in the firm's annual revenue stream,
0 = the change in the firm's annual operating cost cash
flows, and
r = the firm's WACC.
Table 6-13
6-72
-------
TABLE 6-13. PROJECTED CHANGE IN FIRM VALUE
.t urn
yizy in diniudi iHUHipL
y (^io
) year)
Regulatory Alternative
$0 to $6
$6 to $60
$60 to $3
.,000
Over $1,00 0
Reg
Alt 1
icilities with costs
9
14
12
7
Mean
7, 049
-13,982
"4,
897
-107,280
Standard deviation
13,388
84,772
105,
857
322,368
Quartiles
Upper
2, 149
13,440
22,
224
4, 862
Median
707
7, 563
1,
487
2,213
Lower
60
497
6
160
Reg
Alt 2
icilities with costs
108
86
72
93
Mean
-38,219
141,072
-5,249,
574
-1,617,476
Standard deviation
165,482
941,356
33,962,
759
11,081,905
Quartiles
Upper
5, 217
73,374
231,
918
-3,815
Median
-1,833
468
-172,
409
-196,673
Lower
-60,062
-89,213
-202,
629
-393,382
Reg
Alt 3
icilities with costs
108
88
74
96
Mean
-162,608
57,929
-5,405,
348
-3,943,032
Standard deviation
302,869
920,687
33,466,
742
19,989,673
Quartiles
Upper
5, 700
60,457
150,
978
-3,281
Median
-2,795
96
-499,
353
-652,403
Lower
-343,624
-107,719
-662,
328
-793,842
Reg
Alt 4
icilities with costs
108
90
76
98
Mean
-214,563
-3,901
-13,780,
000
-4,527,209
Standard deviation
432,848
942,791
101,650,
000
22,768,127
Quartiles
Upper
3, 183
44,545
99,
889
-3,817
Median
-8,274
-5,265
-623,
067
-801,705
Lower
-348,660
-137,244
-816,
524
-1,056,274
Reg
Alt 5
icilities with costs
108
90
76
98
Mean
-214,733
-38,401
-13,930,
000
-4,719,627
Standard deviation
432,835
803,897
101,640,
000
23,673,921
Quartiles
Upper
3, 183
44,545
99,
889
-7,508
Median
-8,465
-5,273
-623,
067
-805,129
Tiower
-348.663
-137.244
-81 6.
52 4
-1.562.243
6-73
-------
reports the change in firm value estimated in this manner.
Firm value actually increases for some firms because of an
increase in their revenue stream that exceeds the costs
incurred because of the regulation. However, most firms
experience a reduction in value because of the regulation.
Firms may issue new debt or equity depending on the
magnitude of the compliance capital requirements relative to
the value of the firm's earnings. If an affected firm has no
unused debt capacity and is making no other investments
besides the investment in pollution control equipment, it
would be forced to retire existing debt in response to the
regulation to maintain its target capital structure. In
practice, however, firms will likely be carrying out other
investment and financing programs along with the pollution
control requirements. Rather than retiring existing debt, the
firm would change its financing mix to issue more equity and
less debt than otherwise. If an affected firm has unused debt
capacity, it will potentially use this capacity to finance the
required investment in pollution control equipment. However,
using this debt capacity potentially displaces investment in
other assets that increase the firm's value rather than
decrease it.
6-74
-------
For this analysis, it was assumed that a firm has access
to capital from three sources: debt, new internal equity
(current portion of retained earnings), and new external
equity. To project the financing mix used for pollution
control investments, EPA must make assumptions regarding the
firm's capital structure policy, dividend policy, and the
relative cost of capital raised from each of the three
sources.
Responses to the regulatory requirements hinge on the
cost of new, or marginal, capital. Thus, the relevant costs
of capital are not historical but rather the marginal costs of
new funds that must be raised to finance the control
equipment. Capital structure theory holds that a specific
breakpoint exists in the firm's marginal cost of capital (MCC)
schedule as shown in Figure 6-6. The point labeled "B" in the
figure illustrates the increase in the firm's WACC when the
firm raises new external equity to meet its capital require-
ments while maintaining an optimal capital structure. This
breakpoint is referred to as the retained earnings breakpoint
in financial literature97 and is identified using the following
equation:
Figure 6-6. Marginal cost of capital schedule.
6-75
-------
B = RE/S (6-6)
where
B = the retained earnings breakpoint,
RE = the current year's retained earnings, and
S = the share of total firm value represented by
equity.
The breakpoint is based on several assumptions:
• The firm's current capital structure is optimal, and
new capital will be raised if necessary to maintain
this optimal capital structure.
• New equity could come from one of two sources: the
part of this year's profits that management decides to
retain (internal) or the sale of new stock (external).
• If the cost of equity obtained through retained
earnings = ke, the cost of equity obtained through the
issuance of new stock is ke + flotation (transaction)
costs.
The MCC schedule jumps at the point where the firm must raise
new external equity capital to meet its investment
requirements. Table 6-14
6-76
-------
TABLE 6-14. NUMBER OF FIRMS WITH COMPLIANCE CAPITAL COSTS
(CC) ABOVE THE RETAINED EARNINGS BREAKPOINT (B)
Firm size in annual receipts ($10b/year)
$60 to Over
Regulatory Alternative $0 to $6 $6 to $60 $1, 000 $1,000
Reg Alt 1
Number with CC
Number with CC > B
Share with CC > B
Reg Alt 2
Number with CC
Number with CC > B
Share with CC > B
Reg Alt 3
Number with CC
Number with CC > B
Share with CC > B
Reg Alt 4
Number with CC
Number with CC > B
Share with CC > B
Reg Alt 5
Number with CC
Number with CC > B
Share with CC > B
3
1
33.33s
86
27
31.40s
35
39.7%
93
37
39.78s
93
38
40 . 86s
6
2
33.33'
65
12
18.46'
69
16
23.19'
71
16
22.54s
71
16
22.54s
4
2
50 .00^
66
16
24 ,24s
69
20
28 . 9 9'
73
20
27 . 74s
73
21
28 . 77s
1
0
0%
84
26
30.95s
28
31. li
92
32
34 . 7i
92
32
34 . 7i
6-77
-------
shows the number and share of firms in each size category
with capital costs of compliance that exceed the retained
earnings breakpoint. An estimated 20 to 40 percent of the
firms projected to incur capital costs because of the
regulation will incur costs above their retained earnings
breakpoint. To maintain their current capital structure,
these firms must issue new external equity to finance the
compliance capital costs.
Empirical evidence shows that capital structure can vary
widely from the theoretical optimum and yet have little impact
on the value of the firm.98 Thus, firms typically focus on a
"prudent" level of debt rather than on setting a precise
optimal level. Brigham and Gapinski define a prudent level of
debt as one that captures most of the (tax) benefits of debt
financing yet keeps financial risk at a manageable level,
ensures financing flexibility, and maintains a favorable
credit rating. For this analysis, it was assumed that the
industry benchmark reflecting the 75th percentile for the debt
6-78
-------
ratio (corresponding to the lower quartile debt ratio in
Appendix H) represents the upper bound of prudent debt
financing.
The debt ratio is similar to other debt management
financial ratios in that it is used to indicate the degree to
which a firm uses debt (versus equity) to finance operations.
The debt ratio is computed as total liabilities divided by
total assets. The 75th percentile debt ratio for firms in the
Refuse Systems industry (SIC 4953) is 68 percent. Thus, it
was assumed that firms in this SIC will seek to maintain a
level of debt that is equal to or below 68 percent of the
firm's with-regulation value. This assumption has several
implications for modeling decisions regarding the financing
mix chosen to cover the compliance capital costs. First, it
was assumed that firms with a baseline debt-to-firm value
ratio greater than the industry benchmark use equity financing
exclusively. Furthermore, this analysis assumes that the
maximum portion of compliance capital costs financed through
debt is computed based on the following formula:
where
DMax = [ (D/V) L0 • (VB + AV) ] - Db (6-7)
DMax = the maximum level of new debt used to finance
compliance capital costs,
(D/V)lq = the industry-specific lower quartile debt
ratio,
VB = the baseline value of the firm,
AV = the change in the value of the firm because of
regulation, and
Db = the baseline book value of long-term debt.
The baseline value of the firm (VB) is computed as the sum of
the market value of equity (measured as average share price
times average number of shares outstanding) and the book value
of long-term debt. Where data on share prices and number of
shares outstanding are not available, the value of equity is
measured as total assets minus total liabilities.
6-79
-------
Equation (6-7) above defines the estimated maximum amount
of new debt issued to cover the compliance capital costs.
However, a firm may employ a level of new debt that is less
than DMax in response to the regulation. In particular, where
the firm's baseline D/V ratio is less than the (D/V)LQ ratio,
it was assumed that the firm issues new debt up to a level
equivalent to its baseline D/V ratio times the installed
capital cost. Thus the share of the compliance capital costs
financed through debt does not exceed the firm's baseline D/V
ratio and may be less than the D/V ratio where the product of
D/V and the compliance capital costs exceed DMax.
Compliance capital costs that are not financed using debt
are financed using internal or external equity funds.
External equity refers to newly issued equity shares.
Internal equity includes the current portion of the firm's
retained earnings that are not distributed in the form of
dividends to the owners (shareholders) of the firm. This
analysis assumed that the firm retains 100 percent of its
earnings unless data on dividends paid out are available.
Because data on dividends are generally available only for
large, publicly traded firms, the analysis implicitly assumed
that firms that are not publicly traded and small firms retain
a larger share of their earnings. This assumption is not
unreasonable because firms that are not publicly traded and
small firms, in particular, do not typically have a consistent
dividend payout policy. Thus, these firms are more likely to
retain a larger share of their earnings when faced with
regulatory cost than are publicly traded firms that are
potentially concerned about the signal that a change in
dividend policy sends to investors. This situation is
particularly true when the cost of new equity is higher than
the cost of current retained earnings due to flotation costs
(see Figure 6-6).
Flotation costs associated with new equity increase the
effective cost of these funds. It was assumed that flotation
costs for new equity average approximately 1 percent."
Because new equity is more costly than retained earnings, it
was assumed that firms use all of their available internal
6-80
-------
equity capital to finance the compliance capital costs before
issuing new equity. Figure 6-7
6-81
-------
Figure 6-7. Projected share of compliance capital
costs by t§p^2of financing.
-------
shows the projected share of capital costs financed through
debt, retained earnings, and new equity.
As companies raise larger and larger sums of capital
during a given time period, the costs of both debt and equity
components may begin to rise, and as this occurs, the WACC
also rises. This increase in the cost of capital is shown as
an upward slope beyond the RE breakpoint in the hypothetical
marginal cost of capital schedule contained in Figure 6-6.
This upward sloping cost curve reflects the assumption that
investors' demand for securities is downward sloping. An
estimated elasticity of demand is required to project the
change in the cost of equity resulting from an increase in the
number of shares issued. However, estimating company-specific
elasticities is beyond the scope of this analysis. This
analysis assumed that the price elasticity of demand for an
individual firm's securities is 0.5. In other words, for each
1 percent increase in the quantity of shares outstanding, the
price of each share decreases by 0.5 percent. This decrease
in price is reflected in a corresponding increase in the
required return, or cost, of equity.
Under the assumptions regarding capital structure policy,
the share of debt in the firm's capital structure does not
change appreciably. Consequently, EPA does not project a
change in the cost of debt due to the regulation. Using the
baseline debt and equity weights (which are assumed to be the
firm's target weights), the baseline cost of debt, and the
with-regulation cost of equity, EPA computed a with-regulation
WACC.
The estimated baseline and with-regulation WACC are
reported in Table 6-15.
6-83
-------
TABLE 6-15. ESTIMATED WITH-REGULATION WACC
i±±m size ±n d.iiiiud.1 leceipLs $ I u : / y edi ^
$60 to Over
$0 to $6 $6 to $60 $1,000 $1,000
Regulatory Alternative
Facilities with costs
Reg Alt 1
Mean (percent)
Standard deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 2
Mean (percent)
Standard deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 3
Mean (percent)
Standard deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 4
Mean (percent)
Standard deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 5
Mean (percent)
Standard deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
9. 91
1. 96
10.30
9. 63
8 . 75
12 .20
7 . 53
11. 77
9. 95
9. 05
14 . 98
15. 09
12 . 34
10 .17
9. 05
15. 74
16. 94
12 . 54
10 .17
9. 05
15. 74
16. 94
12 . 54
10 .17
9. 05
9.70
1.81
10.30
9.55
8.69
75
83
10.30
9.56
8.69
10 ,
9,
10 ,
9,
30
59
69
83
89
31
59
69
83
89
10.31
9.59
8.69
9.05
1.87
10.16
9.27
8 .17
14
80
10.16
9.33
8.27
19
81
10.21
9.33
8.27
19
81
10.21
9.33
8.27
20
81
10.21
9.33
8.35
8.30
1.85
9.32
8.22
6.87
8.43
1.88
9.38
8 .42
6.87
8 .44
1.88
9.38
8 .42
6.87
8.46
1.88
9.38
8 .42
6.87
8.46
1.88
9.38
8 .42
6.87
6-84
-------
Table 6-16 reports the estimated change in the cost of
TABLE 6-16. ESTIMATED CHANGE IN THE COST OF CAPITAL
i±±m size ±n d.iiiiud.1 leceipLs $ I u : / y edi)
$60 to Over
Regulatory Alternative $0 to $6 $6 to $60 $1, 000 $1,000
Facilities with costs 110 93 80 105
Reg Alt 1
Mean (percent) 0.03 0.02 0.02 0
Standard deviation 0.30 0.14 0.12 0
(percentage points)
Quartiles (percent)
Upper 0 0 0 0
Median 0 0 0 0
Lower 0 0 0 0
Reg Alt 2
Mean (percent) 2.32 0.08 0.10 0.13
Standard deviation 7.18 0.24 0.24 0.25
(percentage points)
Quartiles (percent)
Upper 0 0 0 0
Median 0 0 0 0
Lower 0 0 0 0
Reg Alt 3
Mean (percent) 5.10 0.14 0.15 0.14
Standard deviation 14.89 0.37 0.31 0.26
(percentage points)
Quartiles (percent)
Upper 1.38 0 0.01 0
Median 0 0 0 0
Lower 0 0 0 0
Reg Alt 4
Mean (percent) 5.86 0.16 0.16 0.16
Standard deviation 16.75 0.41 0.32 0.27
(percentage points)
Quartiles (percent)
Upper 1.73 0 0.01 0.38
Median 0 0 0 0
Lower 0 0 0 0
Reg Alt 5
Mean (percent) 5.86 0.16 0.17 0.16
Standard deviation 16.75 0.41 0.33 0.27
(percentage points)
Quartiles (percent)
Upper 1.73 0 0.04 0.38
Median 0 0 0 0
Lower 0 0 0 0
6-85
-------
capital due to the regulation. The estimated average change
in WACC is less than 1 percentage point for firms in the three
largest size categories under all regulatory alternatives.
The estimated average change in WACC for firms in the smallest
size category ranges from less than
6-86
-------
6-87
-------
6-88
-------
1 percentage point under RA1 to approximately 6 percentage
points under RA5.
6.5.2.2 Changes in Financial Status. Financial ratio
impacts provide a measure of the change in financial status
due to the regulation. To compute the with-regulation
financial ratios, pro-forma income statements and balance
sheets reflecting the with-regulation condition of affected
firms were developed based on projected regulatory cost
impacts (including compliance costs and any change in baseline
operating costs due to a change in output level) and revenue
impacts (based on the with-regulation price and quantity
projected using the market model). Table H-6 in Appendix H
shows the adjustments made to the baseline financial
statements to develop the with-regulation financial statements
used for this analysis.
Profitability is the most commonly used measure of the
firm's performance. Three profitability measures were
estimated for this analysis: ROS, ROE, and ROA. Each of
these measures uses net profit as the numerator of the ratio,
and high values are unambiguously preferred over low values.
Changes in net profit arise from the combination of the change
in annual revenue and the change in costs. The change in
costs includes any reductions in baseline operating costs due
to a reduction in the quantity of waste treated, increased
operating costs resulting from regulatory requirements, a
depreciation expense associated with the pollution control
equipment, and any interest expense resulting from the
regulation. The depreciation expense is computed based on an
assumed 10 percent depreciation allowance (see Appendix H).
For most of the firms in this analysis, profits either remain
unchanged (no revenue or cost impacts) or decrease in response
to the regulation. For a few firms, however, profits actually
increase in response to the regulation. Profits increase when
positive revenue impacts (price increases that more than
offset the quantity decreases) exceed any cost impacts.
The regulatory alternatives may also affect the denomi-
nator of the profitability ratios. Sales (in the ROS ratio)
may increase or decrease, depending on the relative magnitude
6-89
-------
of the price and quantity effects. Assets increase for those
firms that must purchase control equipment and remain
unchanged for the balance of the firms. Equity either remains
unchanged (for firms that do not purchase control equipment)
or increases (for firms that do purchase control equipment).
Equity is measured as total assets less total liabilities.
Total assets increase by an amount equal to the installed
capital costs of the control equipment. However, total
liabilities only increase by the portion of the capital costs
financed through debt. All else being equal, the increase in
equity or assets results in a lower profitability ratio.
The baseline and with-regulation profitability measures
are reported in Tables 6-17 through 6-19
6-90
-------
TABLE 6-17. BASELINE AND WITH-REGULATION FINANCIAL RATIO:
RETURN ON SALES100"107
i±±m size ±n d.iiiiud.1 leceipLs $ I u : / y edi)
Regulatory Alternative and $60 to Over
statistic
$0 to $6
$6 to $60
$1,000
$1,000
Baseline
Mean (percent)
4.2
-12 . 4
-21. 4
0.0
Median (percent)
5.5
3.3
3.2
3.5
Reg Alt 1
Mean (percent)
4.2
-12 . 4
-21. 4
0.0
Median (percent)
5.5
3.3
3.2
3.5
Reg Alt 2
Mean (percent)
3.7
-12 .1
-21. 4
0.0
Median (percent)
5.1
3.7
3.2
3.5
Reg Alt 3
Mean (percent)
2.6
-12 .1
-21. 4
0.0
Median (percent)
4.3
3.8
3.2
3.5
Reg Alt 4
Mean (percent)
2.2
-12 .1
-21. 6
0.0
Median (percent)
4.2
3.9
3.2
3.5
Reg Alt 5
Mean
2.2
-12 .1
-21. 6
0.0
Median
4.2
3.9
3.2
3.5
Notes:
1. The return on sales ratio is a measure of a firm's
profitability and is computed by dividing net income by
sales revenue. A value of 10 percent indicates that net
income is equal to 10 percent of sales. Negative values
indicate net losses.
2. High ratios indicate that the firm is operating efficiently.
6-91
-------
TABLE 6-18. BASELINE AND WITH-REGULATION FINANCIAL RATIO:
RETURN ON EQUITY108"115
i_i_rm size _lii annual
/year >
Regulatory Alternative and
$60 to
Over
statistic
$0 to $6 $6 to $60
$1,000
$1,000
Baseline
Mean (percent)
41.9 -61.4
-55. 9
2 .1
Median (percent)
20.4 14.4
9.5
9.9
Reg Alt 1
Mean (percent)
41.5 -60.8
-53. 8
2.0
Median (percent)
20.4 14.4
9.4
9.8
Reg Alt 2
Mean (percent)
38.3 -56.0
-53. 8
2.0
Median (percent)
14.8 14.3
9.4
9.8
Reg Alt 3
Mean (percent)
35.8 -51.4
-53.5
2.0
Median (percent)
13.7 13.9
9.3
9.8
Reg Alt 4
Mean (percent)
34.5 -50.2
-53.5
2.0
Median (percent)
13.5 13.7
9.1
9.8
Reg Alt 5
Mean (percent)
28.1 -49.5
-53. 6
2.0
Median (percent)
13.5 13.7
9.1
9.8
Notes:
1. The return on equity
ratio is a measure of a
firm's
profitability and is
computed by dividing net income by
owner's equity. A value of 20 percent indicates that net
income is equal to 20 percent of owner's equity. Negative
values indicate net losses.
2. High ratios indicate that the firm is operating efficiently.
6-92
-------
TABLE 6-19. BASELINE AND WITH-REGULATION FINANCIAL RATIO:
RETURN ON ASSETS116"123
i _ljliil size
±n annual
±ece±pLa \i?lu
¦/ year >
Regulatory Alternative and
$60 to
Over
statistic
$0 to $6
$6 to $60
$1,000
$1,000
Facilities with costs
110
93
80
105
Baseline
Mean (percent)
13.1
-6 . 4
-11.1
1.1
Median (percent)
11. 0
7.3
5.8
3.5
Reg Alt 1
Mean (percent)
13.1
-6 . 4
-11.1
1.1
Median (percent)
11. 0
7.3
5.8
3.5
Reg Alt 2
Mean (percent)
10. 9
-6.5
-11. 2
1.1
Median (percent)
9.8
7 . 4
5.8
3.5
Reg Alt 3
Mean (percent)
10 .1
-6 . 4
-11. 2
1.1
Median (percent)
9.1
7 . 4
5.8
3.5
Reg Alt 4
Mean (percent)
9.5
-6 . 4
-11. 3
1.1
Median (percent)
8.6
7.2
5.6
3.5
Reg Alt 5
Mean (percent)
9.5
-6 . 4
-11. 3
1.1
Median (percent)
8.6
7.2
5.6
3.5
Notes:
1. The return on assets ratio is a measure of a firm's
profitability and is computed by dividing net income by
total assets. A value of 15 percent indicates that net
income is equal to 15 percent of total assets. Negative
values indicate net losses.
2. High ratios indicate that the firm is operating efficiently.
6-93
-------
Mean values are considerably lower than corresponding
median values reported for firms in the two middle size
categories. This difference is due to a small number of firms
in each of these size categories that report large losses in
the baseline. The presence of these "outlier" firms makes the
median values a better measure of central tendency than the
mean values. Under each of the regulatory alternatives,
profitability ratios decline from baseline levels for firms in
the smallest size category. Profitability ratios for larger
firms are generally unchanged from baseline or only slightly
lower due to regulation. Thus, the regulation is likely to
have the greatest impact on small firms. However, small firms
have the highest baseline profitability ratios. Although
their profitability is eroded somewhat because of the
regulation, small firms still have higher profitability ratios
on average than the larger firms in this analysis even with
the regulation.
Figures 6-8 through 6-13 show the share of firms whose
profitability ratios are below the benchmarks for their
industry. Compared to firms in the three largest size
categories, a larger proportion of small firms shift below the
industry benchmarks as a result of the regulation. However, a
smaller proportion of these small firms are below their
6-94
-------
industry benchmarks in the baseline. Consequently, even with
Contains Data for
Postscript Only.
Figure 6-8. Percentage of firm financial ratios equal to
or below the industry lower quartile ratio: return on sales.
Contains Data for
Postscript Only,
Figure 6-9. Percentage of firm financial ratios equal to
or below the industry median quartile ratio: return on sales.
Notes for Figures 6-8 and 6-9:
1. The ROS ratio is a measure of a firm's profitability. It is the ratio of a
company's net income to its total sales, expressed as a percentage. For
example, a value of 6.5 indicates that a company's net income is equal to 6.5
percent of its total sales. A high ROS value is preferable to a lower value.
2. Each company's ROS ratio is compared to the D&B published median and lower
quartile benchmarks for companies sharing the same SIC code. If the SIC code
is not know, the company ratio is compared to the benchmark ratios for SIC code
6-95
-------
6-9 6
-------
6-97
-------
6-98
-------
6-9 9
-------
Contains Data for
Postscript Only.
Figure 6-10. Percentage of firm financial ratios equal to
or below the industry lower quartile ratio: return on equity.
Contains Data for
Postscript Only.
Figure 6-11. Percentage of firm financial ratios equal to
or below the industry median quartile ratio: return on equity.
Notes for Figures 6-10 and 6-11:
1. The ROS ratio is a measure of a company's profitability. It is the ratio of a
company's net income to its total net worth, expressed as a percentage. For
example, a value of 3.9 indicates that a company's net income is equal to 3.9
percent of its total net worth. A high ROS value is preferable to a lower
value.
2. Each company's ROS ratio is compared to the D&B published median and lower
quartile benchmarks for companies sharing the same SIC code. If the SIC code
is not know, the company ratio is compared to the benchmark ratios for SIC code
6-100
-------
6-101
-------
Contains Data for
Postscript Only.
Figure 6-12. Percentage of firm financial ratios equal to
or below the industry lower quartile ratio: return on assets.
Contains Data for
Postscript Only.
Figure 6-13. Percentage of firm financial ratios equal to
or below the industry median quartile ratio: return on assets.
6-102
-------
Notes for Figures 6-12 and 6-13:
1. The ROS ratio is a measure of a company's profitability. It is the ratio of a
company's net income to its total assets, expressed as a percentage. For
example, a value of 4.3 indicates that a company's net income is equal to 4.3
percent of its total assets. A high ROS value is preferable to a lower value.
2. Each company's ROS ratio is compared to the D&B published median and lower
quartile benchmarks for companies sharing the same SIC code. If the SIC code
is not know, the company ratio is compared to the benchmark ratios for SIC code
6-103
-------
the regulation, small firms tend to have better profitability
ratios on average than larger firms.
6.5.2.3 Projected Financial Failure. With-regulation Z-
scores were computed to assess the probability that the
regulation will result in financial failure or bankruptcy for
potentially affected firms. The baseline analysis estimated
that approximately 23 out of 154 firms are likely to
experience some form of financial failure. No additional
financial failures resulting from the regulation are projected
for these 154 firms. However, this does not necessarily mean
that none of the potentially affected firms will experience
financial failure. Of particular concern to EPA are the small
firms identified in this analysis. The financial ratios
estimated above indicate that small firms may be more affected
by the regulation than larger firms. However, data were
sufficient to compute Z-scores for only 11 of the 110 small
firms in this analysis.
6.6 INITIAL REGULATORY FLEXIBILITY ANALYSIS
The Regulatory Flexibility Act of 1980 (RFA) requires
that Federal agencies consider whether regulations they
develop will affect small entities (which may include
nonprofit organizations, small governmental jurisdictions, and
small businesses) .124 If the proposed rule is likely to have a
significant adverse economic impact on a substantial number of
small entities, a Regulatory Flexibility Analysis is required.
The Act allows some flexibility in defining small entities and
determining what a substantial number and significant impact
are.
Small businesses are identified by Small Business
Administration (SBA) general size standard definitions. For
SIC code 4953, Refuse Systems, small business concerns are
those receiving less than $6 million/year, averaged over the
most recent 3 fiscal years (Code of Federal Regulation, 1991).
Small government entities are defined in the RFA as those with
populations less than 50,000.
6-104
-------
The EPA (1982) provides guidelines for determining when a
"substantial number" of these small entities have been
"significantly affected." This EPA guidance states that a
"substantial number" is "more than 20 percent of these (small
entities) affected for each industry the proposed rule would
cover." However, each office may develop its own criterion
for defining a substantial number.
Under the RFA, for a rule to be proposed, EPA must
prepare an initial Regulatory Flexibility Analysis or certify
that the proposed rule is not expected to exert "a significant
economic impact on a substantial number of small entities."
In keeping with this requirement, the following sections
identify potentially affected small entities, report the
distribution of impacts across affected entities of all sizes,
and identify mitigating measures considered for small
entities.
6.6.1 Potentially Affected Entities
The impacts of the regulation may be direct or indirect
in nature. Direct impacts include impacts on the owners of
OWR facilities. Indirect impacts of the regulation include
impacts on consumers of the services offered by OWR facilities
(generators of hazardous waste) and suppliers of equipment and
services to these facilities. Hazardous wastes are generated
during the production process for many intermediate and final
products. A regulation that increases the costs of waste
disposal may increase the cost of producing these products.
However, projecting the impacts on all generators of hazardous
waste is beyond the scope of this analysis. In addition,
firms that supply services and equipment to potentially
affected entities but do not own a plant may actually benefit
from the regulation because demand for air pollution control
technology and equipment increases. Consequently, this
analysis is limited to directly affected entities.
Directly affected entities include governmental
jurisdictions and companies that own an OWR facility. Only 61
of the 725 potentially affected OWR facilities identified for
this analysis are owned by government entities. Almost all of
the government-owned facilities are owned by the Federal
6-105
-------
government, and none are owned by a small government entity.
Consequently, this analysis focuses on impacts incurred by
potentially affected companies. Directly affected companies
range from some of the largest companies in the U.S. to very
small, single-facility waste treatment firms.
The EPA specifically identified 388 firms that own 621
potentially affected OWR facilities. These 388 firms include
110 small businesses that own 112 OWR facilities. Excluded
from this analysis, however, are the following facilities:
• facilities that treat only nonhazardous waste and the
entities that own them and
• facilities that treat only on-site wastes.
The size exemption, in particular, potentially reduces the
share of small potentially affected entities that actually
incur costs due to the regulation. Because of resource
constraints, data required to identify all potentially
affected facilities and firms, including those that treat only
nonhazardous wastes, are below the HAP emission criterion, or
treat only on-site wastes, were not collected. Consequently,
the number of potentially affected entities and the share of
small entities that incur an economic impact are unknown. The
distribution of impacts presented in the following section is
based on the 388 firms identified for this analysis.
6.6.2 Distribution of Impacts
Affected entities typically incur two types of costs
because of the regulation: capital and operating. The
capital cost is an initial lump sum associated with purchasing
and installing pollution control equipment. Operating costs
are the annually recurring costs including costs associated
with operation and maintenance of the control equipment,
personnel training costs, emission monitoring costs, and
reporting and recordkeeping costs. Firms may elect to secure
a loan or redirect funds from other uses to cover the initial
and recurring costs. Part or all of the increase in costs may
be passed along to customers in the form of increased prices.
Directly affected companies face different prevailing
economic and financial conditions, and these differing
6-106
-------
conditions lead to different burdens. For example, firms can
experience different degrees of effects because of differences
in their cost structures, tax rates, technologies, past
investments in air pollution control equipment, size, and
degree of horizontal or vertical integration. Furthermore,
differences in local market conditions and contractual
arrangements, financial status, and method of financing result
in differing levels of impacts.
EPA provides guidelines for defining a "significant
economic impact." Impacts may be considered significant
whenever any of the following criteria are satisfied:
• annual compliance costs increase total costs of
production for small entities for the relevant process
or product by more than 5 percent;
• compliance costs as a percentage of sales for small
entities are at least 10 percent higher than
compliance costs as a percentage of sales for large
entities;
• capital costs of compliance represent a significant
portion of capital available to small entities,
considering internal cash flow plus external financing
capabilities; and
• the requirements of the regulation are likely to
result in closures of small entities.
This analysis computed the distribution of impacts on
companies of all sizes using the measures described above.
Annual compliance costs as a percentage of baseline
production costs were computed using two alternative methods
to determine whether the first criterion identified above is
satisfied. Under both methods, annual compliance costs were
computed as the sum of annualized capital costs of compliance
and annual operating costs of compliance. Capital compliance
costs were annualized using the estimated company-specific
with-regulation WACC over a 20-year time horizon. Annual
compliance costs computed in this manner were then divided by
two different estimates of the relevant baseline production
costs. Under the first method, annual compliance costs were
first divided by the baseline waste treatment production
costs. This quotient was then multiplied by 100 to present
6-107
-------
annual compliance costs as a percentage of baseline waste
treatment production costs. However, it may be argued that
the relevant process or product is broader than waste
treatment alone, particularly for companies that treat waste
on a noncommercial basis. For example, for companies that
treat waste generated as a result of a production process such
as chemical manufacturing, the relevant measure of production
costs should potentially include total production costs.
Therefore, under the second method, annual compliance costs as
a percentage of baseline production costs were computed using
total baseline production costs--not just waste treatment
costs.
Table 6-20
6-108
-------
TABLE 6-20. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
BASELINE WASTE TREATMENT COSTS
J? _lJim size ±n d.iiiiud.1 mceipLs
($106/year)
Regulatory Alternative
$60 to
Over
and statistic
$0 to $6
$6 to $60
$1,000
$1,000
Reg Alt 1
Number with costs
3
7
4
1
Number >5%
1
1
0
0
Mean (percent)
2.19
3. 05
0.05
1. 60
Standard deviation
3.79
5. 61
0.09
N/A
(percentage points)
Quartiles (percent)
Upper
6.57
4 . 81
0.10
N/A
Median
0.00
0.04
0.00
1. 60
Lower
0.00
0.00
0.00
N/A
Reg Alt 2
Number with costs
85
66
66
84
Number >5%
26
27
25
30
Mean (percent)
22 .99
152.20
82 . 34
28. 65
Standard deviation
117.95
1,034.91
543.05
142.77
(percentage points)
Quartiles (percent)
Upper
7.53
11. 95
11. 88
3.78
Median
1.56
1.59
1. 64
0 . 47
Lower
0.30
0.37
0.16
0.03
Reg Alt 3
Number with costs
87
70
69
88
Number >5%
30
29
31
27
Mean (percent)
124 .09
482.37
248.22
90 .76
Standard deviation
702 .47
3, 350 .76
1,765.55
464.97
(percentage points)
Quartiles (percent)
Upper
9. 62
13.35
35. 49
8.19
Median
1. 65
1. 78
1.88
1. 23
Lower
0.30
0.35
0 .14
0.06
Reg Alt 4
Number with costs
92
73
73
92
Number >5%
35
33
33
31
Mean (percent)
160.11
571.51
288.54
107.20
Standard deviation
936.81
4,049.95
2,118.54
561.53
(percentage points)
Quartiles (percent)
Upper
12 . 60
19.74
35.26
8.20
Median
2 .18
2.56
2 .29
0. 96
Lower
0.52
0 . 42
0.25
0.07
(continued)
6-109
-------
TABLE 6-20. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
BASELINE WASTE TREATMENT COSTS (continued)
J? _lJim size ±n d.iiiiud.1 mceipLs
($106/year)
Regulatory Alternative $60 to Over
and statistic $0 to $6 $6 to $60 $1,000 $1,000
Reg Alt 5
Number with costs 92 73 73 92
Number >5% 35 34 34 33
Mean (percent) 160.13 571.68 288.71 107.79
Standard deviation 936.81 4,049.99 2,118.51 561.43
(percentage points)
Quartiles (percent)
Upper 12.62 19.74 35.26 12.39
Median 2.24 2.73 2.72 1.35
Lower 0 . 52 0.64 0 . 35 0.08
Notes:
1. Companies that are not projected to incur compliance costs
are excluded from the impact. Three single-facility firms
projected to incur a plant closure are also excluded.
2. Annual compliance costs are the sum of capital costs
annualized over a 20-year time horizon at an estimated
company-specific cost of capital and annual operating
costs.
3. Baseline waste treatment costs were estimated using
facility-level data.
4. The large difference between the estimated mean and median
values indicate the presence of "outlier" observations.
Thus, the median values are the preferred measure of
central tendency.
6-110
-------
reports annual compliance costs as a percentage of baseline
waste treatment production costs. In reporting the
distribution of impacts, this analysis excluded the three
single-facility companies for which plant closure is
projected. Furthermore, companies that are not projected to
incur any compliance costs were also excluded. Consequently,
the number of observations differs by regulatory alternative
depending on the number of firms actually affected. Average
impacts range from less than 4 percent under RA1 to more than
100 percent under RA5. The greatest impacts are incurred by
firms in the two middle size categories ($6 million to $1
billion in annual revenues). Under RA1, only two companies
are projected to incur compliance costs that will increase
their baseline waste treatment costs by more than 5 percent.
This number jumps to over 100 under the other regulatory
alternatives.
Table 6-21
6-111
-------
TABLE 6-21. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
BASELINE PRODUCTION COSTS
i _ljliil size
±n annual
±ece±pLa
iHu v year >
Regulatory Alternative
$60 to
Over
and statistic
$0 to $6
$6 to $60
$1,000
$1,000
Reg Alt 1
Number with costs
3
7
4
1
Number >5%
1
0
0
0
Mean (percent)
3.40
0.16
0.01
0.01
Standard deviation
5.86
0.29
0.01
N/A
(percentage points)
Quartiles (percent)
Upper
10 .17
0.23
0.01
N/A
Median
0.03
0.00
0.01
0.01
Lower
0.00
0.00
0.01
N/A
Reg Alt 2
Number with costs
85
66
66
84
Number >5%
18
0
1
0
Mean (percent)
37 .69
0 . 22
0.32
0.00
Standard deviation
192.97
0.50
2.03
0.01
(percentage points)
Quartiles (percent)
Upper
2 .87
0 .24
0.03
0.00
Median
0.59
0.10
0.01
0.00
Lower
0.13
0.01
0.00
0.00
Reg Alt 3
Number with costs
87
70
69
88
Number >5%
24
1
1
0
Mean (percent)
207.97
0 . 42
0.34
0.00
Standard deviation
1,110.02
1.13
1. 99
0.01
(percentage points)
Quartiles (percent)
Upper
8 .17
0.37
0.07
0.01
Median
0.52
0.16
0.03
0.00
Lower
0.13
0.01
0.00
0.00
Reg Alt 4
Number with costs
92
73
73
92
Number >5%
27
1
1
0
Mean (percent)
268.34
0 . 55
0.87
0.01
Standard deviation
1,474.83
1.49
6.39
0.02
(percentage points)
Quartiles (percent)
Upper
8.13
0 . 51
0.08
0.01
Median
0.67
0 .21
0.03
0.00
Lower
0.26
0.02
0.01
0.00
(continued)
6-112
-------
TABLE 6-21. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
BASELINE PRODUCTION COSTS (continued)
J? _l Jim size ±n d.iiiiud.1 leueipLa $ I u : / y ecu )
Regulatory Alternative $60 to Over
and statistic $0 to $6 $6 to $60 $1, 000 $1,000
Reg Alt 5
Number with costs 92 73 73 92
Number >5% 27 1 1 0
Mean (percent) 268.35 0.60 0.88 0.01
Standard deviation 1,474.83 1.71 6.39 0.02
(percentage points)
Quartiles (percent)
Upper 8.13 0.58 0.08 0.01
Median 0.67 0.22 0.03 0.00
Lower 0.26 0.03 0.01 0.00
Notes:
1. Companies that are not projected to incur compliance costs
are excluded from the impact. Three single-facility firms
projected to incur a plant closure are also excluded.
2. Annual compliance costs are the sum of capital costs
(annualized over a 20-year time horizon at an estimated
company-specific cost of capital) and annual operating
costs.
3. Baseline production costs are the sum of costs of goods
sold and general operating expenses as reported in or as
estimated for the company-level financial statements.
6-113
-------
reports annual compliance costs as a percentage of total
baseline production costs. If the relevant measure of
baseline costs is total costs of production rather than waste
treatment costs, the numbers are significantly lower. Impacts
average less than 1 percent for large firms identified for
this analysis. This percentage compares to impacts for small
firms that range from approximately 4 percent under RA1 to
nearly 270 percent under RA4 and RA5. Virtually all of the
firms projected to incur annual compliance costs totaling more
than 5 percent of their
6-114
-------
6-115
-------
6-116
-------
6-117
-------
baseline production costs are small firms. Under RA1, only
one small firm has estimated annual compliance costs greater
than 5 percent of baseline total production costs. Under the
more stringent regulatory alternatives, this number jumps to
between 20 and 30. Only two large firms are projected to
incur compliance costs greater than 5 percent of baseline
production costs.
The second measure identified above is a relative measure
designed to compare the impacts for small entities to those
for larger entities. To facilitate the comparison of impacts
at large versus small firms, all firms contained in the three
largest size categories were grouped into one category of
firms with annual sales over $6 million. As for the previous
measure, relative impacts were evaluated using two methods.
First, annual compliance costs were computed as a percentage
of sales excluding firms that are not projected to incur
compliance costs. Annual compliance costs were then computed
as a percentage of annual sales for all firms regardless of
whether they incur costs.
Table 6-22
6-118
-------
TABLE 6-22. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
SALES: EXCLUDING FIRMS WITH ZERO COMPLIANCE COSTS
i±±m size ±n d.iiiiud.1 leceipLs
($106/year)
Regulatory Alternative and
statistic
$0 to $6
Over $6
Reg Alt 1
Facilities with costs
Mean (percent)
Standard Deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 2
Facilities with Costs
Mean (percent)
Standard Deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 3
Facilities with Costs
Mean (percent)
Standard Deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
Reg Alt 4
Facilities with Costs
Mean (percent)
Standard Deviation
(percentage points)
Quartiles (percent)
Upper
Median
Lower
3
2 .07
3.57
6.20
0.02
0.00
85
24.59
135.18
1.56
0.37
0.08
87
135.77
774.02
4 .40
0.37
0.08
92
175.06
1,028.03
4.66
0.48
0 .15
12
0.07
0.16
0.03
0.00
0.00
216
0 .11
0.00
0.04
0.00
0 .72
227
0.16
0.80
0.06
0.01
0.00
238
0.28
2.23
0.09
0.01
0.00
(continued)
6-119
-------
TABLE 6-22. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
SALES: EXCLUDING FIRMS WITH ZERO COMPLIANCE COSTS
(continued)
i±±m size ±n d.iiiiud.1 leceipLs
($106/year)
Regulatory Alternative and
statistic
$0 to $6
Over $6
Reg Alt 5
Facilities with costs 92 238
Mean (percent) 175.07 0.30
Standard Deviation 1,028.03 2.26
(percentage points)
Quartiles (percent)
Upper 4.66 0.10
Median 0.4 8 0.01
Lower 0.15 0.00
6-120
-------
reports the distribution of impacts for only those firms that
are projected to incur compliance costs. Table 6-23
6-121
-------
TABLE 6-23. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
SALES: INCLUDING FIRMS WITH ZERO COMPLIANCE COSTS
J? _lJim size ±n d.iiiiud.1 leueipLa
($106/year)
Regulatory Alternative and
statistic $0 to $6 Over $6
Reg Alt 1
Facilities with costs
107
278
Mean (percent)
0.06
0.003
Standard deviation
0.00
0.04
(percentage points)
Quartiles (percent)
Upper
0
0
Median
0
0
Lower
0
0
Reg Alt 2
Facilities with costs
107
278
Mean (percent)
19.53
0.08
Standard deviation
120 . 75
0.06
(percentage points)
Quartiles (percent)
Upper
0 . 74
0.02
Median
0 .14
0
Lower
0
0
Reg Alt 3
Facilities with costs
107
278
Mean (percent)
110.40
0.13
Standard deviation
699.21
0 .72
(percentage points)
Quartiles (percent)
Upper
2.56
0.04
Median
0 .15
0
Lower
0.01
0
Reg Alt 4
Facilities with costs
107
278
Mean (percent)
150.51
0.24
Standard deviation
954 . 47
2 .07
(percentage points)
Quartiles (percent)
Upper
3.22
0.06
Median
0.35
0
Lower
0.05
0
(continued)
6-122
-------
TABLE 6-23. ANNUAL COMPLIANCE COSTS AS A PERCENTAGE OF
SALES: INCLUDING FIRMS WITH ZERO COMPLIANCE COSTS
(continued)
J? _lJim size ±n d.iiiiud.1 leueipLa
($106/year)
Regulatory Alternative and
statistic
$0 to $6
Over $6
Reg Alt 5
Facilities with costs
107
278
Mean (percent)
150.51
0.26
Standard deviation
954 . 47
2.09
(percentage points)
Quartiles (percent)
Upper
3.22
0.06
Median
0.35
0
Lower
0.05
0
Notes:
1. Three single-facility firms projected to incur a plant
closure are also excluded.
2. Annual compliance costs are the sum of annualized
capital costs (annualized over a 20-year time horizon at
an estimated company-specific cost of capital) and
annual operating costs.
6-123
-------
reports the impacts for all firms identified for this
analysis. Under both measurement methods, average annual
compliance costs as a percentage of sales are significantly
higher for small firms than for large firms. Annual costs as
a percentage of sales average less than 1 percent for large
firms. This percentage compares to impacts ranging from about
4 percent under RA1 to 175 percent under RA5 for small firms.
However, if median values are used to gauge impacts, the
absolute value of the impacts as well as the relative
differences in impacts for small versus large firms is not as
significant.
The criterion for significant impacts under the third
measure identified above is not as straightforward as the
criterion given for each of the first two measures. The
relevant measure of the "capital available" is not explicitly
stated in the guidance. Furthermore, no specific numerical
benchmark is provided to determine whether the capital costs
6-124
-------
6-125
-------
6-126
-------
6-127
-------
of regulation represent a "significant" portion of capital
available to the firm. One measure of the capital available
to companies is the retained earnings breakpoint described in
Section 6.5. Table 6-14 reports the number of companies with
capital compliance costs that exceed the retained earnings
breakpoint. Impacts reported in this table exclude firms that
do not incur any compliance capital costs. Between 20 and 50
percent of the firms with compliance capital costs have costs
that exceed the retained earnings breakpoint. However, these
firms represent less than 3 percent of all potentially
affected firms under RA1 and between 12 and 30 percent of all
potentially affected firms under the more stringent
alternatives. Small firms fare slightly worse than large
firms under all of the regulatory alternatives except RA1.
The final measure states that impacts are significant if
the proposed rule is likely to result in the closure of small
entities. In Section 6.4 of this report, EPA projects
facility closures in response to the requirements of the
regulation. A plant closure does not necessarily translate
into a financial failure for large, multi-facility companies.
However, for small, single-facility companies, plant closure
is likely to be synonymous with financial failure. No plants
are projected to close under RA1. However, 10 plants are
projected to close under each of the other regulatory
alternatives. Of these 10 plants, three are owned by small,
single-facility companies.
6.6.3 Mitigating Measures
The impacts reported in this section indicate that
businesses of all sizes will experience impacts because of the
regulation. However, the impacts on small businesses are
generally greater than the impacts on larger entities. The
EPA is particularly concerned about these impacts on small
entities. To address these concerns, measures designed to
mitigate the impacts on small entities are being considered.
First, the regulatory alternatives are based on emission
standards rather than design, equipment, work practice, or
operational standards. This reduces impacts by giving the OWR
facility owner/operator the freedom to use the least costly
6-128
-------
control equipment that will satisfy the requirements of the
regulation. Note that this measure potentially reduces
impacts at all potentially affected OWR facilities regardless
of the size of the facility.
In addition, EPA is considering exempting all area source
facilities from the emission requirements. Area sources are
facilities that emit less than 22.7 Mg (25 tons) of hazardous
air pollutants per year. Note that this measure would exempt
small facilities not small companies per se. Some small
facilities owned by large companies would be exempted.
However, company size is related to facility size. Although
some small facilities are owned by large companies, small
companies own small facilities without exception. If the EPA
exempts all area sources from the emission requirements, only
10 small business entities will incur costs beyond reporting
and recordkeeping costs. Furthermore, all of the small,
single-facility companies that are projected to close under
RA2 through RA5 would be exempt. Thus, this second measure
would effectively mitigate impacts at all but a few small
entities.
6-129
-------
REFERENCES
1. Altman, Edward I. 1983. Corporate Financial Distress:
A Complete Guide to Predicting, Avoiding, and Dealing
with Bankruptcy. New York. John Wiley & Sons.
2. U.S. Small Business Administration. Changes in Size
Standards. 13 CFR, Chapter 1, Section 121 (January 1,
1991 Edition).
3. Memorandum from Anne Gorsuch, Administrator, U.S.
Environmental Protection Agency, entitled "EPA
Implementation of the Regulatory Flexibility Act."
February 9, 1982.
4. EPA National Computation Center. National Survey of
Hazardous Waste Treatment, Storage, Disposal, and
Recycling Facilities. EPA computer database, Durham, NC.
1986.
5. EPA National Computation Center. National Survey of
Hazardous Waste Generators. EPA computer database,
Durham, NC. 1986.
6. EPA Office of Water, Office of Science and Technology.
Waste Treatment Industry Questionnaire. EPA Office of
Water computer database, Washington, DC. 1989.
7. Riley, G.J., J.L. Warren, and R.D. Baker. Assessment of
Changes in Reported TRI Releases and Transfers Between
1989 and 1990. Research Triangle Institute. Research
Triangle Park, NC. May 1993. 38 pp.
8. Motorola. No-Clean Solder Process. Distributed at the
U.S. Department of Energy Conference on Industrial Waste
Reduction Program Review Conference, Santa Fe, NM, May
17-20, 1993.
9. Dorfman, M.H., W.R. Muir, and C. G. Miller.
Environmental Dividends: Cutting More Chemical Wastes.
New York, INFORM, Inc. 1992. 263 pp.
10. Bailey, J. (1993, April 30). Environment: Managing
Waste. The Wall Street Journal.
R-l
-------
11. Allen, R.G.D. Mathematical Analysis for Economists. New
York, St. Martin's Press. 1962. 509 pp.
12. Hicks, J.R. Marshall's Third Rule: A Further Comment.
Oxford Economic Papers. JL3_:262-65. 1961.
13. Hicks, J.R. The Theory of Wages. 2nd Ed. New York, St.
Martin's Press. 1963. 247 pp.
14. Memorandum from Peterson, P. and J. Coburn, Research
Triangle Institute, to E. Crump, EPA/OAQPS/ESD/CPB.
March 24, 1993. p. 3.
15. Moody's Industrial Manual. New York, Moody's Investor
Service, Inc. 1992.
16. Dun & Bradstreet. Dun's Market Identifiers. New York,
Dun & Bradstreet 1993.
17. Ward's Business Directory of U.S. Private and Public
Companies. Detroit, Gale Research, Inc. 1993.
18. Business America Online. Omaha, NE, American Business
Information. 1993-94.
19. Re f. 6.
2 0. Re f. 17.
21. Re f. 15.
22. Re f. 17.
23. Ref 18.
24. Ref. 4.
25. Dun & Bradstreet. Who Owns Whom? New York, Dun &
Bradstreet, 1990.
26.
Ref.
4 .
27 .
Ref.
25.
28 .
Ref.
6.
29.
Ref.
19.
30 .
Ref.
15.
31.
Ref.
17 .
32 .
Ref.
23.
R-2
-------
33. Re f. 4 .
34. Re f. 25.
35. Re f. 6.
3 6 . Re f . 6 .
37. Re f. 16.
3 8. Re f. 15.
3 9. Re f. 17.
4 0. Re f. 23.
41. Dun & Bradstreet. Industry Norms and Key Business
Ratios. New York, Dun & Bradstreet. Desktop Edition.
1990-91.
42. Ref. 4.
4 3. Re f. 25.
44. Survey of Current Business, Vol. 71, No. 9. 1991.
4 5. Re f. 6.
4 6. Re f. 16.
4 7. Re f. 15.
4 8. Re f. 17.
4 9. Re f. 23.
5 0. Re f. 41.
51. Re f. 4.
52. Re f. 25.
53. Confidential business information submitted in memorandum
to U.S. Environmental Protection Agency project manager,
March 25, 1994.
54. Standard and Poor's. Creditweek. January 4, 1993.
55. Re f. 54.
5 6. Re f. 1.
57. Re f. 6.
R-3
-------
5 8. Re f.
5 9. Re f.
60. Re f.
61. Re f.
62. Ref.
63. Re f.
64. Re f.
65. Re f.
6 6. Re f.
67. Re f.
68. Re f.
6 9. Re f.
7 0. Re f.
71. Re f.
72. Re f.
7 3. Re f.
7 4. Re f.
7 5. Re f.
7 6. Re f.
7 7. Re f.
7 8. Re f.
7 9. Re f.
8 0. Re f.
81. Re f.
82. Re f.
8 3. Re f.
8 4. Re f.
16
15
17
23
4 .
41
25
6.
16
15
17
23
4 .
41
25
6.
16
15
17
23
4 .
41
25
6.
16
15
17
-------
8 5. Re f. 2 3.
8 6. Re f. 4.
87. Ref. 41.
8 8. Re f. 25.
89. Ref. 1.
90. Dun & Bradstreet. Business Failure Record. New York,
Dun & Bradstreet. 1989-1992.
91. Memorandum from Peterson, P., and J. Coburn, Research
Triangle Institute, to E. Crump, EPA/OAQPS/ESD/CPB.
April 23, 1993. Comparison of Impact Estimates for
Candidate Regulatory Alternatives to be Considered for
the SWTSDF MACT Standard.
92. Memorandum from Peterson, P., and J. Coburn, Research
Triangle Institute, to E. Crump, EPA/OAQPS/ESD/CPB. May
6, 1993. Selection of SWTSDF MACT Standard Regulatory
Alternatives for Nationwide Environmental and Economic
Impact Analyses.
93. Ref. 92.
94. Ref. 92.
95. Kimbell, Larry J., and Glenn W. Harrison. On the
Solution of General Equilibrium Models. Economic
Modelling. _3:197-212. 1986.
96. Pogue, Dr. Gerald A. Estimation of the Cost of Capital
for Major United States Industries with Application to
Pollution-Control Investments. November. 1975.
97. Brigham, Eugene F., and Louis C. Gapenski. 1991.
Financial Management: Theory and Practice. 6th Ed.
Orlando, FL: The Dryden Press.
98. Re f. 97.
9 9. Re f. 97.
10 0. Re f 6.
101. Ref. 16.
102. Ref. 15.
103. Ref. 17.
R-5
-------
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
Re f. 18.
Re f. 4 .
Ref. 41.
Re f. 2 5.
Re f. 6 .
Re f. 16.
Re f. 15.
Re f. 17.
Re f. 18.
Re f. 4 .
Ref. 41.
Re f. 2 5.
Re f. 6 .
Re f. 16.
Re f. 15.
Re f. 17.
Re f. 2 3.
Re f. 4 .
Ref. 41.
Re f. 2 5.
Re f. 2 .
R-6
-------
APPENDIX A
OF SIC CODES PROVIDED TO RESPONDENTS TO THE NATIONAL SURVEY
HAZARDOUS WASTE TREATMENT, STORAGE, DISPOSAL, AND RECYLCING
FACILITIES
-------
APPENDIX B
PROGRAM DEFINING WASTE FORMS
-------
B.l
PROGRAM DEFINING WASTE FORMS
-------
B.2
WASTE DESCRIPTION CODES
Source: U.S. EPA. National Survey of Hazardous Waste Generations
(Inside Cover). 1986.
-------
B. 3
RCRA AND OTHER WASTE CODES
Source: U.S. EPA. National Survey of Hazardous Waste Generations
(Appendix C). 1986.
-------
APPENDIX C
ELASTICITY OF DEMAND FOR OFF-SITE
WASTE AND RECOVERY OPERATIONS
-------
APPENDIX D
FINANCIAL ANALYSIS METHOD
-------
APPENDIX E
ESTIMATING COMPANIES' WEIGHTED AVERAGE
COST OF CAPITAL
-------
APPENDIX F
ESTIMATING FACILITIES' BASELINE WASTE
MANAGEMENT QUANTITIES
-------
APPENDIX G
TECHNIQUE FOR ESTIMATING FACILITIES'
AVERAGE VARIABLE COSTS
-------
APPENDIX H
DOCUMENTATION AND SUMMARY OF METHODS USED TO
IMPUTE MISSING FINANCIAL STATEMENT VALUES
-------
APPENDIX B
PROGRAM DEFINING WASTE FORMS
-------
APPENDIX B
PROGRAM DEFINING WASTE FORMS
The Agency used waste composition descriptions provided
by respondents to the GENSUR to map each of the thousands of
individual waste streams generated in 1989 into one of the six
waste forms presented in Section B.l. Specifically, GENSUR
respondants were asked in Questions 1 and 2 of GENSUR
Questionnaire GB, the hazardous waste characterization section
of the GENSUR, to provide the RCRA Waste Code, and the Waste
Description Code that best describe each hazardous waste
generated in 1986. Respondents were provided with lists of
Waste Description Codes and definitions (shown in Section B.2)
and RCRA Waste Codes and definitions (shown in Section B.3) to
assist them in responding to Questions 1 and 2.
The Agency then used the computer program presented in
Section B.l to consolidate wastes that are similar in
composition into the six waste forms described in Section 2 of
this report.
B-l
-------
APPENDIX C
ELASTICITY OF DEMAND FOR OFF-SITE
WASTE AND RECOVERY OPERATIONS
The price-elasticity of demand (which will be referred to
as the elasticity of demand from here on) measures the
responsiveness of demand for a service to changes in its
price. It is defined as the percentage change in the quantity
demanded of a service divided by the percentage change in its
price.
Economic theory states that the elasticity of the derived
demand for an input is a function of the following:
• demand elasticity for the final good it will be used
to produce,
• the cost share of the input in total production cost,
• the elasticity of substitution between this input and
other inputs in production, and
• the elasticity of supply of other inputs.1,2,3
Using Hicks' formula,
E _ s(n +e) + Ke(n -s)
n + e - K(n - s)
where
E = elasticity of demand for the OWR service,
s = elasticity of substitution between OWR services and
all other inputs,
n = elasticity of demand for final product,
e = elasticity of supply of other inputs, and
K = cost share of this input in total production cost.
C-l
-------
Hicks, in the Appendix to The Theory of Wages, shows
that, if n > s, the demand for the input is less elastic the
smaller its cost share.4 If the data were available, this
formula could be used to actually compute the elasticity of
demand for each OWR service. As noted above, however, nearly
every production activity generates some waste that is managed
off site. The number of final products whose elasticity of
demand (n) would need to be included is very large, and the
elasticities of demand for those products vary widely. Thus,
resources do not permit determination of a value for n. This
makes direct computation of the elasticity of demand, E,
impossible. In spite of this, the formula is useful because
it identifies factors that influence the magnitude of the
elasticity of derived demand. Knowledge of the general
magnitude of those factors makes it possible to make an
educated assumption about the magnitude of E.
The elasticity of substitution, s, between waste
management services and other inputs is low but not zero.
This means that waste generators do have some limited options
in the way they produce their final goods or services. Some
limited substitution is possible between management
technologies for a given waste form. Further, facilities may
substitute on site capital, labor, and/or materials for off
site waste management either by choosing to manage the waste
on site or by undertaking on site pollution prevention
activities. These options are very limited, however, so s is
expected to be small, and n is almost certain to be larger
than s.
Thus, the magnitude of E depends on the magnitude of K,
the cost share of OWR in final goods production.
REFERENCES
1. Allen, R.G.D. Mathematical Analysis for Economists. New
York, St. Martin's Press. 1938. 509 pp.
C-2
-------
2. Hicks, J.R. Marshall's Third Rule: A Further Comment.
Oxford Economic Papers. JL3_:262-65. 1961.
3. Hicks, J.R. The Theory of Wages (2nd ed.). New York,
St. Martin's Press. 1966. 247 pp.
4 . Re f. 3 .
C-3
-------
APPENDIX D
FINANCIAL ANALYSIS METHOD
This analysis uses data from Dun & Bradstreet's (D&B's)
Industry Norms and Key Business Ratios (1992) to construct
typical financial statements for the firms for which actual
financial statements are not available. Industry Norms and
Key Business Ratios reports data by Standard Industrial
Classification (SIC) code and aggregates financial data for
all firms within a SIC code rather than reporting data for any
individual firm. Two types of financial data are contained in
the D&B database: common-size financial statements and
financial ratios. Common-size financial statements include a
representative (or average) income statement where all values
are expressed as a percentage of total revenues and a
representative balance sheet where all values are expressed as
a percentage of total assets. Key financial ratios reported
as quartile values representing above-average (upper
quartile), average (median), and below-average (lower
quartile) performance are also reported for each SIC code.
Two options are available for constructing financial
statements using D&B profiles. Under the first approach,
financial statements are constructed using the common-size
financial data and company data on total sales and/or total
assets to generate financial statements. Financial statements
constructed in this manner represent firms in average
financial condition only. The second approach uses the upper
quartile, median, and lower quartile financial ratios to
derive financial profiles. Under this approach, the
constructed financial statements represent firms in above-
average, average, and below-average financial condition.
The regulation will potentially have a more adverse
D-l
-------
impact on firms that are in average or below-average financial
condition than on firms in above-average financial condition.
Consequently, the second approach (based on financial ratios)
was used to construct financial profiles for the potentially
affected firms for which actual financial statements are not
available from published sources. To construct financial
statements for these firms, each firm was assigned to a
financial health category based on the following protocol:
• Assign a random number to each firm.
• Sort the firms by SIC code then sort the firms within
each SIC code by random number.
• Assign financial health within each SIC code based on
the following pattern: average, below average,
average, above average. Repeat this pattern until all
firms are assigned to a financial health category.
Using this method to assign financial health ensures that
each SIC category with four or more firms has a representative
firm in average, below-average, and above-average financial
condition. Furthermore, firms are distributed roughly in the
proportion 25 percent below average, 50 percent average, and
25 percent above average for most of the SIC categories. This
distribution is consistent with the quartile financial ratios
used to construct financial statements. Note, however, that a
perfectly systematic distribution of 25 percent below average,
50 percent average, and 25 percent above average does not
result from this method because the number of firms in each
SIC code is not a multiple of four. Consequently, the
distribution is slightly skewed toward the average and below-
average financial health categories.
Data on total revenues or total assets are required (at a
minimum) to construct financial statements using financial
ratios reported in D&B. All other lines in the financial
statements are derived, directly or indirectly, from the
quartile financial ratios and the common size financial
statements reported in D&B (see Table H-5 in Appendix H).
Several examples will clarify how the statements are derived.
D-2
-------
D&B reports that the median waste treatment firm (SIC 4953) in
the D&B database has a net profit of 6.7 percent of total
revenues. This ratio multiplied by the total revenue value
yields the estimated net profit in the income statement. The
three other lines in the income statement are analogously
derived by applying D&B ratios multiplied by sales.
Balance sheet items are derived in a similar manner. D&B
reports that the median waste treatment firm had about $528 of
total assets for every $1,000 of revenues. This ratio
multiplied by the total revenue value yields an estimate of
total assets. D&B reports that the average waste treatment
firm has about $421 of current assets, $347 of fixed assets,
and $232 of other noncurrent assets per $1,000 of total
assets. These ratios multiplied by the total assets estimates
yield the estimates for those variables. In the liabilities
section of the balance sheet, "total liabilities and net
worth" must equal "total assets," and the component parts are
computed using D&B ratios multiplied by the total.
D-3
-------
APPENDIX E
ESTIMATING COMPANIES' WEIGHTED AVERAGE
COST OF CAPITAL
To estimate the WACC, first values for Kd and Ke were
estimated. Marginal costs of capital, not historical average
costs, are appropriate hurdle rates for new investments.1
However, data are available only for the historical values.
All else being equal, the cost of both debt and equity capital
is generally higher for firms in below-average financial
condition than for firms in above-average financial condition.
This higher cost of capital reflects a higher level of risk
associated with the returns for firms in below-average
financial condition. Consequently, EPA estimated the cost of
capital for firms in below-average, average, and above-average
financial condition.
This analysis estimated the cost of debt for firms in
above-average and average financial condition based on the
average bond yields reported by Standard and Poors (S&P).2
Bond ratings indicate potential default risk. Bonds rated AAA
are considered low risk and are generally associated with
firms in above-average financial condition. Yields for
corporate industrial bonds rated AAA averaged 7.89 to 8.69
percent in 1992.3 Bonds rated BBB are considered average risk
and are associated with firms in average financial condition.
Yields for corporate industrial bonds rated BBB averaged 8.82
to 9.5 percent in 1992.4 For this analysis, EPA uses the
midpoint of the range, or 8.29 percent, for AAA bonds and 9.16
percent for BBB bonds. Bonds rated CCC are considered to be
riskier than average. Standard and Poors does not report
yields for lower grade bonds (rated BB-C) because of the high
E-l
-------
variability in returns for these bonds. However, Anderson et
al. project a 14.5 percent yield for bonds rated CCC.5 The
1992 CCC bond yield was estimated using the 1987 S&P average
yield for grade BBB bonds (10.36 percent),6 the 1992 S&P yield
for grade BBB bonds (9.16 percent), Anderson's estimates of
the 1987 CCC bond yield (14.5 percent), and the following
formula:
CCC92 = (CCC87 / BBB87) • BBB92 (E-l)
or
12.91 = (14.5 / 10.36) • 9.16
Based on these assumptions and data, the cost of debt for
firms was projected in three financial conditions:
• above-average financial condition: 8.29 percent
• average financial condition: 9.16 percent
• below-average financial condition: 12.91 percent
Because debt interest is deductible for state and federal
income tax purposes, the cost of debt has to be adjusted
downward. The Tax Foundation estimates that the effective
marginal state and federal tax rate averaged 30.3 percent in
1992.7 Applying this rate to the real costs of debt computed
above derived an after-tax debt costs for firms in three
different financial conditions:
• above-average financial condition: 5.78 percent
• average financial condition: 6.38 percent
• below-average financial condition: 9.00 percent
Financial analysts use several methods to estimate the
cost of equity capital including the Capital Asset Pricing
Model (CAPM), the Dividend Growth Model, and a risk premium
model. These methods are discussed in Appendix A of the
Economic Impact of Air Pollutant Emission Guidelines for
E-2
-------
Existing Municipal Waste Combustors.8 This analysis used the
CAPM to estimate the cost of equity capital. The CAPM is
expressed in the following equation:
Ke = Rf + p(Rm - Rf) (E-2)
where
Ke = the cost of equity capital
Rf = the risk-free rate of return (long-term
treasury bonds)
3 = beta, a measure of the relative risk of the
equity asset
(Rm - Rf) = the market risk premium
Estimates of the risk-free rate, the market risk premium,
and firm-specific beta values are required to estimate the
cost of equity capital. This analysis used the 1992 average
rate of return on long-term treasury bonds to estimate the
risk-free rate. The Survey of Current Business reports that
long-term treasury bonds averaged 7.52 percent during 1992.9
Ibbotson Associates estimate that the market risk premium
(Rm - Rf) has averaged approximately 6 percent over the last 66
years.10 The risk-free rate and the market risk premium are
for the market as a whole and, thus, are the same for all
firms regardless of the firm's financial condition. Beta
values, however, are a measure of the relative riskiness of
E-3
-------
TABLE E-l. BETA VALUES BY BOND RATING GROUP FOR A SAMPLE
OF POTENTIALLY AFFECTED FIRMS11
Bond rating
Beta
1.1b
1.2
Bond group average £>eta
~KK
A
1.18
BBB+
BB
BB
BB
BB-
B+
B+
B+
1.2
1 . 1
1. 7
2.3
1.2
1.15
1.25
1.35
1. 41
CCC+
2.06
2.06
the firm and vary from firm to firm. Table E-l reports beta
values for a small sample of firms that perform hazardous
waste management services.
To estimate Ke values for firms in each of three
financial conditions, average beta values were computed for
firms in different bond rating groups. Beta values for firms
with a bond rating of AAA to A averaged 1.18. Similarly, beta
values for firms with bonds rated BBB to B averaged 1.41.
Only one firm in the small sample was rated below B. This
firm was rated CCC+ and had a beta value of 2.06. These beta
values by bond rating group were used as representative betas
to estimate the cost of equity for firms in each of three
financial conditions:
• above-average financial condition:
P = 1.18, Ke = 14.57;
• average financial condition:
3 = 1.41, Ke = 15.96; and
• below-average financial condition:
p = 2.06, Ke = 19.88.
Next, the weighting factors were estimated and used to
estimate the WACC equation. The theoretically correct weights
are the target weights rather than historical weights.
E-4
-------
Financial theory holds that each firm has an optimal capital
structure that maximizes the value of the firm by minimizing
its cost of capital. When the firm raises new capital, it
generally tries to maintain an actual capital structure that
is reasonably close to the target or optimal structure. As
seen in the WACC equation above, returns (interest payments)
to debtholders are a tax-deductible expense for the firm.
This tax benefit associated with debt effectively reduces the
cost of debt financing for the firm. However, increasing the
use of debt in a firm's capital structure increases the fixed
interest payments incurred by the firm. The greater the use
of debt financing, the larger the fixed interest charges, and
the greater the probability that a decline in earnings will
lead to financial distress. This tradeoff between the tax
advantages of using debt and the financial distress costs
associated with debt is shown in Figure E-l.
E-5
-------
The firm's optimal capital structure is the point where
the tax advantages of using debt are just offset by the
financial distress costs. Estimating the target capital
structure for each potentially affected firm is beyond the
scope of this analysis. It was assumed that the actual
capital structure employed by firms approximates their target
or optimal capital structure and that firms are minimizing
their cost of capital in the baseline. Furthermore, it was
assumed that book-value weights approximate market-value
weights where market-value weights are not available.12
Figure E-l. Optimal capital structure: tradeoff model.
E-6
-------
REFERENCES
1. Bowlin, 0. D., J. D. Martin, and D. F. Scott. Guide to
Financial Analysis. 2nd Ed. New York, McGraw-Hill.
1990 .
2. Standard & Poor's. Security Owner's Stock Guide. Vol.
47, No. 1. January 1993.
3 . Re f. 2 .
4 . Re f. 2 .
5. Anderson, D. W., H. H. Mims, and A. S. Ross. Industry
Supply, Cost, and Availability of Capital, and Closure
Analysis. Draft report prepared for the Environmental
Protection Agency. Research Triangle Park, NC, Research
Triangle Institute. September 1987.
6 . Re f. 5 .
7. The Tax Foundation. Special Report. No. 18. March
1993.
8. U. S. Environmental Protection Agency. Economic Impact
of Air Pollutant Emission Guidelines for Existing
Municipal Waste Combustors. Research Triangle Park, NC.
EPA-450/3-89-005. August 1989.
9. Survey of Current Business. 1993.
10. Ibbotson and Associates. SBBI 1993 Yearbook. Chapter 6.
11. Value Line Investment Survey. June 11, 1993.
12. Ref. 1.
E-7
-------
APPENDIX F
ESTIMATING FACILITIES' BASELINE WASTE
MANAGEMENT QUANTITIES
F.l ESTIMATING BASELINE QUANTITIES
The baseline quantity of individual waste types managed
at each of the affected off-site waste and recovery (OWR)
facilities was estimated by synthesizing data from the
National Survey of Hazardous Waste Treatment, Storage,
Disposal, and Recycling Facilities (TSDR Survey) and the
National Survey of Hazardous Waste Generators (GENSUR). As
described in Section 2 of this report, the TSDR Survey
provides the total quantity of waste managed commercially and
noncommercially in each treatment process at each facility,
but does not provide any information as to the characteristics
of specific waste streams handled in each process. The
GENSUR, on the other hand, offers a detailed characterization
of each waste generated in 1986 and identifies the quantity of
each waste sent off site for management. The GENSUR also asks
generators to identify the OWR facilities to which each waste
stream was sent as well as for the generators' best guess of
which treatment and disposal processes await each waste stream
at the destination OWR facility. When facilities associated
more than one destination OWR facility with a given waste
stream, the reported quantity was divided equally among all
OWR facilities mentioned.
The Agency is able to group the approximately 27,000
individual waste streams from the GENSUR database into six
broad waste "forms" by using the GENSUR's detailed constituent
information. Then, by identifying which one of 10 broad
F-l
-------
categories of treatment generators believed would first be
used at the OWR facilities to which wastes were sent, the
Agency can differentiate these six "waste forms" into 60
distinct types of waste for which off-site waste management is
demanded. Throughout this section, "waste type" means one of
the 60 unique waste form/waste management process
combinations. The analysis of impacts on the markets for
commercial OWR services treats management of each of the 60
waste types as a unique OWR service with its own market supply
and demand and its own price.
F.l.l Resolving Data Limitations
The estimated quantities of individual waste types (waste
form and treatment category combinations) managed at each OWR
facility at baseline that are discussed in this section are
the Agency's best estimate of baseline conditions given the
data available. The Agency attempted to account for trends in
the waste management industry that have evolved in the seven
years since the GENSUR and TSDR Survey were conducted. For
example, 19 off-site waste management categories of the GENSUR
have been streamlined to 10, primarily to reflect revised
practices in land-based waste treatment and disposal resulting
from the Land Disposal Restrictions described in Section 2.
Also, the Agency assumes that most wastes formerly managed
with land application, or treatment, storage, and disposal in
wastepiles and surface impoundments, are currently being
landfilled and that wastewater treatment in tanks has now
replaced wastewater treatment in surface impoundments.
F-2
-------
TABLE F-l. DEFINITIONS OF MANAGEMENT CODES USED IN THIS
ANALYSIS
GENSUR off-site management codes
M01 Incineration
M02 Reuse as fuel
M03 Fuel blending
M04 Solidification/stabilization-
M05 Solvent recovery
M06 Metals recovery
M07 Wastewater treatment in tank-
M08 Wastewater treatment in
surface impoundment
M09 Wastewater treatment in
unknown treatment type
Mil Storage/treatment in waste
pile
M12 Storage/disposal in
surface impoundment
M13 Landfill
M14 Land treatment
M15 Underground injection
M10 Other treatment/recovery
M18 Other
M16 Discharge to POTW
M17 Discharge under NPDES permit-
M19 Unknown
Management codes used T"n analysis
Q1
Inciner
Q2
Reuse a
Q3
Fuel bl
Q4
S olidi f
Q5
Solvent
Q6
Metals
Q7
Wa s tewa
Q7
Wa s tewa
Q7
Wa s tewa
Q8
Landfil
Q8
Landfil
Q8
Landfil
Q8
Landfil
Q9
Undergr
Q10
Other
Q10
Other
-
Not inc
-
Not inc
Q20
Unknown
other o
categor
Table F-l shows how the 19 1986 off-site management codes
from the GENSUR were used to map 1986 flows of wastes managed
off site into the 1991 baseline industry profile presented
here. Column 1 shows OWR codes associated with wastes in the
GENSUR. Column 2 shows the waste management operation in the
analysis to which each OWR code was assigned.
F.1.2 Combining Process Quantities from the TSDR Survey with
Waste Form Data from the GENSUR
There are discrepancies between the amount of waste from
off site that OWR facilities reported accepting for each
category of treatment (in the TSDR Survey) and the quantity
that generators claimed (in the GENSUR) to have shipped to
F-3
-------
each treatment category at each OWR facility. To resolve this
discrepancy, the Agency has chosen to control to the total
quantities reported in the TSDR Survey but use the
distribution of waste forms described by the GENSUR. This
decision is appropriate because the approximately 6,000 waste-
generating facilities included in the GENSUR comprise only a
sample, albeit a large one, of the total population of
hazardous waste generating facilities, while the TSDR Survey
was a census of all RCRA-regulated treatment and disposal
facilities operating in 1986. It is also the Agency's belief
that the most reliable information regarding how much waste
was treated in each category of treatment at each OWR facility
is the information each OWR facility provided in its responses
to the TSDR Survey. Unlike the GENSUR, the TSDR Survey
specifically requests that respondents omit "brokered wastes,"
from their tallies of waste quantities managed in each
treatment category. Brokered wastes are those accepted from
off-site generators and then shipped to other waste treaters
for management. Omitting these wastes means that quantities
of waste reported as being treated in a treatment category at
an OWR facility are actually treated at that site. These are
the waste quantities needed for this analysis.
At the same time, the most accurate information about
waste forms being sent to OWR facilities comes from the
generators' GENSUR responses. To fully characterize the
wastes being managed at OWR facilities, the analysis combines
the distribution of waste forms from the GENSUR with the
quantities of waste managed in each process from the TSDR
Survey. Figure F-l
F-4
-------
TheTSDR
Survey provicted
the quantity of
waste a facility
handed in each
of the 10
process
categories.
Q1
Q2
q:
Q4
Q5
Q6
Q7
Q 8
Q9 Q10
E$ Data from the
GENSUR
Survey gave a
biealctown into
the six waste
forms for a
portion of the
waste the facility
managed in
each process.
Q6
Q7
QS
O.Q Q10
Q The proportion
of each fomn
within each
piocess (from
step B) is usad
to assign the
TSDR Survey
quantity
managed in
each piocess to
individual waste
forms.
G1
Q2
Q3
Q4
Q5
Q6
Q7
QS
Q9 Q10
Figure F-l. Preferred methodology for combining TSDR-survey
quantities with GENSUR waste form distribution for each process.
F-5
-------
illustrates the general approach taken for a hypothetical
facility. Panel A shows the quantities of waste managed in
each of the ten waste management processes, based on data from
the TSDR Survey. In panel B, the shaded distribution of waste
forms sent by generators to the facility for management in the
various processes, according to data from the GENSUR. The
waste form distribution from the GENSUR is applied to the
quantities reported in the TSDR, giving the quantities managed
of 60 specific waste types shown in panel C.
F.1.3 Waste Brokerage and Unnamed OWR Facilities
Ideally, the level of detail requested of respondents to
the GENSUR about the source, character, quantity, destination,
F-6
-------
and subsequent treatment of each waste shipped off site would
allow for simple and accurate portrayal of baseline conditions
at OWR facilities. Unfortunately, only 464 facilities of the
universe of 725 affected OWR facilities were mentioned by name
(EPA ID#) in the GENSUR as the OWR facilities to which wastes
were sent for treatment. Moreover, not all facilities that
responded to the GENSUR associated a destination OWR facility
with each waste stream that they indicated that they
generated. Another problem is that some facilities did not
respond to the question of where wastes were sent for any of
the waste streams that they generated, and others only named a
destination for some of their waste streams. In some cases,
the type of treatment that the generator claimed would be
provided at the receiving OWR facility was not even offered by
that OWR facility according to the TSDR Survey. These
facilities are referred to from now on as "misnamed" OWR
facilities and the wastes are referred to as "brokered
wastes." For this analysis, the Agency assumed that the named
receiving facility brokers these wastes to OWR facilities that
do offer that type of treatment.
To remedy this situation, all unassigned waste streams
identified in the GENSUR, and the brokered wastes described
above, were combined as if they were all being sent to a
single OWR facility. These wastes were then disaggregated
into the 60 waste types based on waste characteristics and
management process reportedly awaiting each waste stream at
the 246 unnamed OWR facilities.
The quantities of each waste type (waste form and
treatment category combination) treated at each of the 246 OWR
facilities that were not named as destination OWR facilities
by waste generators responding to the GENSUR were estimated
using the following approach. The quantity of waste treated
in each process at each of the 246 OWR facilities is set at
the quantity the facility reported in the TSDR Survey. The
distribution of waste forms for the wastes reported in GENSUR
F-7
-------
to be sent to a given treatment category at unnamed and
misnamed OWR facilities was assumed to hold for all of the 246
facilities having that treatment category. For example, if
the overall distribution of waste forms sent to incineration
at unnamed and misnamed OWR facilities were 20 percent Form 1,
30 percent Form 2, and 50 percent Form 4, each of the 246
facilities that does incineration is assumed to incinerate 20
percent Form 1, 30 percent Form 2, and 50 percent Form 4.
The advantage of this depiction of the OWR industry at
baseline is that the total quantity of management services
supplied for each waste type accepted from off site is
consistent with what the sample of generators indicated was
demanded in 1986 and the quantities are consistent with the
quantities reported by the 246 facilities in the TDSR Survey.
It has the disadvantage, however, of assuming that each of the
246 unnamed facilities that offered a given category of
treatment treated the same proportions of the same specific
waste types. In other words, whereas in reality some of these
facilities may treat only one or two of the six waste forms in
a given category of treatment, with other facilities treating
other waste forms, this approach assumes a much more
homogeneous supply of treatment services for all waste types
for which no destination OWR facility was indicated in the
GENSUR. The approach results in a wider and more homogeneous
distribution of waste forms being managed in each treatment
process at the 246 OWR facilities than is probably true in
reality.
F-8
-------
Figure F-2
F-9
-------
oniHntM of-Waste Rums
HorntfceGEHSUR Samey
{aggregated tw all pfocese^
"ISDB Suvey OnMfes
by PTOce^ witt Sefccfed
Hbste Fdmie *omGQtSUR
3 BasefiM OnfltRS*s
crfEacft Vbste R*m
fagg legated Itiral pmcesses)
) 2 3 4-5 6
** -E4 lamed" ficBBes
9784005 Kg
24.432 waste steams
•F^ro^ ¦:
CH-C^S pflCEM]
Q? [43.0m]
m [22.35W]
OHO [4.CKW]
Q4-6,S [-E.++M-]
o? [sasow]
OS p&flWi]
qio [i-sasw]
1
T
*
*
1 £ £• i £
S
DHb q natty nr
> 164-Mired-taciBBes
j 2^mj2TBg
Okslte qvaittylbf
> 164 ->3ITE<|-fKiBt£S
13T$m2m ag
zi
*w246 liiamed- telks
5£83/14Bg
2.167 IBSfe StBIIE
en pseaM]C
Ql-Si S [4.SB4.]
ft
CHO [I.-5EW]
Qi-e, S [<£3&Si]
Q? P&-S®*]
Q8 paoew]
QiO [«£?«¦]
. Ofclteqaaatflyldf
>2€ "•¦¦anEd'lcKiHtfes
S.19D393 Bg
OisHe qmtlyltw
|>2« ~iiiarrG
-------
illustrates the assumptions made in profiling the types and
quantities of wastes treated in the OWR industry at baseline.
Constituent data about wastes treated in each treatment
category at each of the 464 named facilities were available
only for roughly two-thirds of the approximately 14,600,000 Mg
of wastes accepted from off site. The remaining third of the
off-site wastes are assumed to be similar to those for which
data are available. Because the OWR
F-ll
-------
regulation would only apply to wastes transported off site for
treatment, the Agency performed no detailed analysis of the
physical composition of the roughly 106,000,000 Mg of on site-
generated wastes processed at affected OWR facilities. The
Agency has assumed that the distribution of waste forms of on-
site generated wastes managed in each category of treatment at
these facilities is the same as the distribution of waste
forms for the corresponding treatment categories of the
approximately 10,000,000 Mg of wastes sent to these facilities
from off-site GENSUR respondents. This assumption is based on
the Agency's belief that OWR facilities are most likely to
accept wastes from off site that are chemically similar to
wastes generated on site for which they are already equipped
to treat and dispose.
Figure F-2 also shows that the total quantity of waste
generators sent off site for treatment at unnamed and misnamed
facilities (5,888,714 Mg) is greater than the total quantity
of waste from off site reportedly accepted by the 246 unnamed
facilities (5,118,691 Mg). Thus, at least 770,023 Mg,
assigned to the imaginary catch-all facility and then used to
allocate the 246 unnamed facilities' TSDR Survey quantities
for each treatment category to specific waste forms, were
actually treated by other facilities, such as the named
facilities or the 15 non-RCRA wastewater treatment facilities
discussed below.
For each facility, the off-site waste form distribution
is applied to on-site wastes also. This suggests that the
industry-wide pattern of on-site waste forms managed should
match the industry-wide pattern of off-site waste forms
managed. Studying the third panel of Figure F-2 shows that
this is not the case. Industry-wide, Form 3 has a greater
share of the waste from off site than from on site, while Form
6 has a greater share of on-site waste than off-site waste.
This occurs because the quantity of wastes managed on site is
much larger than the off-site quantity at some facilities
F-12
-------
managing a lot of Form 6 waste. Their waste form
distributions have a greater influence on the on-site
distribution of waste forms than they had on the off-site
distribution. Conversely, facilities managing a relatively
large share of Form 3 waste dominate the industry-wide off-
site waste form distribution. Aggregating across facilities,
the overall pattern of on-site waste forms managed thus
differs from the pattern of off-site waste forms managed.
Table F-2 presents the estimated baseline quantities of
each waste form managed in each process for off-site generated
wastes and on-site generated wastes aggregated separately for
the group of 464 named facilities and the 246 unnamed
facilities. Figure F-3
F-13
-------
TABLE F-2. ESTIMATED AGGREGATE QUANTITIES OF EACH WASTE FORM
FROM OFF SITE AND ON SITE PROCESSED IN EACH TREATMENT CATEGORY AT
NAMED AND UNNAMED FACILITIES (Mg)
Piuutiaa Fuiiil 1 Fu-liu z! Fuhil J> Ji 'u-liu 4 ^ uiin b ^ uiin u luLcil
Off-site
quantities for 464
named facilit
Q1
20,196
972
21,683
161,947
46,717
19,023
270,538
Q2
1
8,236
9, 552
201,784
98,151
8, 538
326,262
Q3
367
16,797
15,205
1,427,805
1,200,301
3, 307
2,663,782
Q4
39,299
88,958
78,275
20,775
139,912
69,746
436,965
Q5
3,718
4, 853
37,003
1,455,269
1,140,051
8,178
2,649,072
Q6
247,984
4,446
53,503
3, 654
8
109,780
419,375
Q7
13,797
103,463
5,731,355
145,908
64,939
4,544,871
10,604,333
Q8
1,043,190
728,810
523,232
128,639
636,525
2,334,566
5,394,962
Q9
75
2, 382
353,034
14,090
8, 105
11,702
389,388
Q10
3, 936
84,971
174,483
40,941
20,061
654,858
979,250
Total
1,372,563
1, 043, 888
6,997,325
3,600,812
3,354,770
7,764,569
24,133,927
On-site
quantities for 464
named faciliti
Q1
833,148
58,730
568,694
1,526,041
768,575
2,106,240
5,861,428
Q2
0
0
18,045
301,180
1,383,532
55,353
1,758,110
Q3
16
607
7, 912
37,422
7,073
8,036
61,066
Q4
62,963
147,409
68,593
146,940
162,745
69,125
657,775
Q5
1
93
1, 985
176,838
2,470
140,122
321,509
Q6
104,810
97,613
114,600
0
0
67,303
384,326
Q7
144,863
2,090,729
35,300,602
5,374,772
2,380,381
55,274,686
100,566,033
Q8
8,144,558
8,276,654
261,195
201,268
3,232,770
36,293,280
56,409,725
Q9
11
1, 852
1,296,720
4,158
3, 841
408,129
1,714,711
Q10
7, 312
124,897
115,075
53,288
6,681,568
23,231,446
30,213,586
Total
9,297,682
10,798,584
37,753,421
7,821,907
14,622,955
117,653,720
197,948,269
(continued)
-------
TABLE F-2. ESTIMATED AGGREGATE QUANTITIES OF EACH WASTE FORM FROM
OFF SITE AND ON SITE PROCESSED IN EACH TREATMENT CATEGORY AT
NAMED AND UNNAMED FACILITIES (Mg) (continued)
vvamnn =
Lam 1
l am z
l am 3 =
l am 4
Lam 5
Lam n
'ratm
Off-site
quantities for 246
unnamed faci^
Q1
49
19
359
360
204
24
1,015
Q2
494
576
120,885
1,144
658
514
124,271
Q3
26
0
188
2, 624
1, 498
990
5, 326
Q4
30
28
28
28
28
28
170
Q5
132
0
2,506
2, 934
780
44
6, 396
Q6
26,278
5, 712
712
1, 042
7, 033
17,655
58,432
Q7
2,011
21,466
4,422,228
2, 948
2, 010
14, 727
4,465,390
Q8
37,999
5, 112
849
5, 793
11,849
307,392
368,994
Q9
0
0
13,288
0
25,939
1, 818
41,045
Q10
3,263
14
44,187
722
50
31,718
79,954
Total
70,282
32,927
4,605,230
17,595
50,049
374,910
5,150,993
On-site
quantities for 246
unnamed facil:
Q1
848,808
847,904
858,437
858,455
853,641
848,040
5,115,285
Q2
12,053
12,075
44,541
12,228
12,097
12,058
105,052
Q3
27
0
421
6,309
3, 587
2, 359
12,703
Q4
7
0
1
0
0
0
8
Q5
653
0
886
928
716
2, 035
5, 218
Q6
34,584
22,857
20,006
20,194
23,610
29,667
150,918
Q7
36,641
85,106
11,047,877
38,977
36,639
68,319
11,313,559
Q8
528,293
430,760
418,118
432,780
450,739
1,327,235
3,587,925
Q9
0
0
231,596
0
279,809
187,886
699,291
Q10
343,512
1, 460
4,651,631
76,056
5, 231
13,513,675
18,591,565
Total
1,804,578
1,400,162
17,273,514
1,445,927
1,666,069
15,991,274
39,581,524
-------
Form 1
Form 2
Fomn 3
Form 4
Form 5
Form 6
Figure F-3. Treatment categories most commonly used to
manage each waste form.
F-16
-------
I
"QT"
Q2
Q3
Q4
Q5
Q6
Q7
Q10
Total
TABLE F-3. ESTIMATED AGGREGATE QUANTITIES OF EACH WASTE FORM
PROCESSED IN EACH TREATMENT CATEGORY BY THE 710 OWRS THAT
RESPONDED TO THE TSDR SURVEY (Mg)
u'uiiii ^F
u'uiiii ^F
^F
^F
1,702,201
12,548
436
102,299
4,504
413,656
197,312
9,754,040
86
358,023
12,545,105
907 , 625
20,887
17,404
236,395
4,946
130,628
2,300,764
9,441,337
4,234
211,342
13,275,561
1,449,
193,
23,
146,
42,
188,
56,502,
1,203,
1,894,
4,985,
66,629,
TTT
023
726
897
380
821
062
394
638
376
490
2,546,
516,
1,474,
167,
1,635,
24,
5,562,
7 68 ,
18,
171,
12,886,
MT
336
160
743
969
890
605
480
248
007
241
U'Ulill 5
7TTT
u'uiiii ^F
iuldl
1, 669
1,494
1,212
302
1,144
30
2,483
4,331
317
6,706
19,693
,438
,459
,685
,017
,651
,883
,694
,910
,843
2, 973,
76,
14,
138,
150,
224,
59,902,
40,262,
60 9,
37,431,
141,784,
TIT
463
692
379
405
603
473
535
697
473
11,248,266
2,313,695
2,742,877
1,094,918
2,982,195
1,013,051
126,949,315
65,761,606
2,844,435
49,864,355
266,814,713
Cu
3
&
i-3
CU
tr
i—1
(D
I
co
o
o
3
tr
H-
3
(D
r+
tr
(D
Cu
3
a
r+
tr
(D
hO
cu
3
a
co
tr
o
r+
tr
(D
-------
distribution of waste forms across all processes for all
wastes managed at all 710 OWR facilities that completed the
TSDR Survey.
F.1.4 Non-RCRA Wastewater Treatment Facilities
In addition to the 464 named facilities and the 246
unnamed facilities discussed above, 15 OWR facilities were
never mentioned in the GENSUR as destination OWR facilities
and also did not complete the TSDR Survey. All waste quantity
information about these facilities was obtained from the 1989
CWT Survey conducted by EPA's Office of Water. These
facilities manage an estimated 22,067,009 Mg of waste from
off-site annually. The Agency assumes that all of this waste
is Form 3 and managed in wastewater treatment.
F.1.5 Unrecognizable OWR Codes
Some of the waste management codes used to identify the
type of treatment awaiting the waste stream at the receiving
OWR facility were not taken from the list of off-site
management codes provided in the GENSUR instruction package.
For these wastes it was not possible to determine what waste
management process was used. These waste quantities were
distributed equally across all waste types treated at each of
the OWR facilities to which they were reportedly sent for
F-18
-------
F-19
-------
F-20
-------
F-21
-------
management. If no destination OWR facility was associated
with a waste stream for which the off-site management code was
ambiguous, the waste quantity was similarly distributed across
the waste types managed at the imaginary catch-all facility
before those wastes were allocated to the 246 unnamed
facilities that responded to the TSDR Survey.
F-22
-------
APPENDIX G
TECHNIQUE FOR ESTIMATING FACILITIES'
AVERAGE VARIABLE COSTS
G.l ESTIMATING BASELINE COSTS
This appendix offers a detailed description of how the
Agency estimated facility-specific variable costs (AVCs) of
waste treatment for each of the 60 OWR treatment services
affected by the regulatory alternatives.
Neither the National Survey of Hazardous Waste Treatment,
Storage, Disposal, and Recycling Facilities (TSDR Survey) nor
the National Survey of Hazardous Waste Generators (GENSUR)
provides any information about facilities' costs of providing
waste management services. Process-specific waste management
costs are estimated using production and cost functions
developed by Research Triangle Institute (RTI) and published
in A Profile of the Market for Hazardous Waste Management
Services for EPA's Office of Air Quality Planning and
Standards.1 The waste treatment categories for which
production and cost functions were developed include rotary
kiln/hearth incineration, chemical precipitation, chemical
stabilization/fixation, steam stripping, and landfills. Table
G-l
G-l
-------
TABLE G-l
MODEL PROCESSES USED TO ESTIMATE COSTS
uwn L-treg-cr
category treatment
incineration
Q2 Reuse as fuel
Q3 Fuel blending
Q4 Solidification
Q5 Solvent recovery
Q6 Metals recovery
Q7 Wastewater treatment
Q8 Landfills
Q9 Underground injection
Q10 Other
udcJ lui xiijjul lav.Lui
quantity and cost estimation
Kotary kiln/hearth incineration
Rotary kiln/hearth incineration
without fuel as a Required Inputa
Chemical precipitation without
chemicals as required inputsb
Chemical stabilization/fixation
Steam stripping
Chemical precipitation with doubled
lime and polymer requirements0
Chemical precipitation
Landfills
Underground injection
Average unit costs of all other
processes
a Fuel is omitted from the list of input factors because the
wastes managed in this process have a high enough Btu
content to fuel the kiln or furnace.
b A production function specifically for fuel blending was not
available. Fuel blending generally involves storage tanks
with mixing and transfer capabilities. If chemicals are not
included, the remaining input requirements of labor,
electricity, water, and indirect O&M are roughly comparable
to a chemical precipitation process.
c The greater the concentration of the waste stream processed,
the greater the chemical requirements for chemical
precipitation.
G-2
-------
shows the production and cost functions used to estimate
costs for each of the 10 OWR treatment categories. These
production functions were developed by comparing the quantity
of inputs required per megagram of waste over a range of
throughput volumes for 8 of the 10 categories of treatment.
The estimated costs of providing waste treatment services for
each waste type managed at each OWR facility are the product
of a methodical estimation process. First, the required
quantity of each input to each OWR service offered by an
G-3
-------
G-4
-------
affected facility was estimated using the RTI production
functions for the appropriate category of treatment to the
estimated waste quantities processed at the facility. Then,
by applying current factor prices to the estimated quantities
of each required input factor and summing costs across all
required input factors the Agency obtained the total cost of
managing the given waste quantity (see Equations G-l, G-2, and
G-3 for a detailed example of this cost estimation process
applied to landfill services). A more condensed overview of
the production and cost functions used for each of the eight
treatment categories for which AVCs are a function of
throughput is found in Tables G-2 through G-9.
G-5
-------
TABLE G-2. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE WITH INCINERATION
O
i
-------
TABLE G-3. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE IN REUSE AS FUEL
O
i
-j
-------
TABLE G-4. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE WITH FUEL BLENDING
O
i
CO
-------
TABLE G-5. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE WITH SOLIDIFICATION/STABILIZATION
O
i
-------
TABLE G-6. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE IN SOLVENT RECOVERY
O
i
-------
TABLE G-7. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE IN METALS RECOVERY
O
i
-------
TABLE G-8. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE WITH WASTEWATER TREATMENT
O
i
i—1
N)
-------
TABLE G-9. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE IN LANDFILLS
O
i
i—1
CO
-------
TABLE G-10. INPUT REQUIREMENTS AND ESTIMATION PROCESS USED TO CALCULATE AVERAGE VARIABLE
COSTS OF MANAGING 1 Mg OF WASTE WITH UNDERGROUND INJECTION
O
i
i—1
-------
Input costs were also estimated for a typical underground
injection facility, but data limitations prohibited
development of production and cost functions to reflect how
the average costs may change with varying levels of throughput
for an underground injection well. The AVCs of underground
injection are based on data from a single underground
injection facility. For this reason the underground injection
presented in Table G-10 is assumed to be the same at all
facilities offering this waste management service. Facility-
specific estimates of the AVCs of managing Q10 wastes, that
is: waste managed in other processes, were calculated by
averaging the estimated AVCs of all other treatment categories
offered at each facility.
G.l.l Estimating Facility-specific Input Requirements for
Each Waste Type Managed
Although the Agency acknowledges that different processes
may be used to manage different waste forms within a broad
management process category, data limitations regarding the
costs of managing different waste forms in each treatment
category require using a single production function to
represent the management of all six waste forms in each of the
10 treatment categories. The quantity of inputs required for
management of each waste type and their corresponding costs,
G-15
-------
G-16
-------
G-17
-------
G-18
-------
G-19
-------
G-20
-------
G-21
-------
G-22
-------
G-23
-------
G-24
-------
however, are estimated based on the volume of each specific
waste type (waste form and treatment category combination)
processed at each OWR facility.
The production functions used to estimate the quantity of
each input factor required for management of Form 1 wastes
(organic solids, incinerator ash and solidified treatment
residuals) in landfills are as follows:
QUANTITY OF INPUTS USED TO LANDFILL FORM 1 WASTES (G-l)
QLabor (hours) = (0.227052 • volume landfilled (Mg) + 7999.935)
QElectricity (kwh) = (0.672269 • volume landfilled + 29663.866)
QLeachate Treatment (gallons) = (32.773109 • volume landfilled
+ 33613.445)
QFuel (gallons) = (0.52521 • volume landfilled + 10154.062)
QHeating (small plants) = (0.000008 • volume landfilled + 0.996)
Qlndirect 0 & M (small plants) = (0.000118 • volume landfilled + 0.941)
These input quantities, as mentioned above, are estimated
separately for each waste form landfilled, based on the
quantity of each waste form thought to be landfilled at each
OWR facility. These same production function equations were
used to estimate the input requirements for each waste form
accepted at facilities offering landfill services, with the
variable for "volume landfilled" in each case reflecting the
estimated quantity of the given waste form landfilled.
To estimate the total variable cost (TVC) of providing
landfill services of Form 1 wastes in 1991 at each OWR
facility that offered such services, these estimated
quantities of each input factor must be multiplied by 1991
factor prices. The 1982 factor prices originally used in
these cost functions were updated to mid-year 1991 prices
using a variety of price indexes. Table G-ll
G-25
-------
TABLE G-ll. COST INDEXES USED TO ADJUST COSTS TO 1991 DOLLARS
Factor inputs
uemeni:
index used lcj: adj us>"c
prices
ivi&b irocess ma.-uemem:
Source of index
unemicai engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Statistical Abstract
of the United States
1992
Statistical Abstract
of the United States
1992
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Economic Report of the
President, January
1993
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemical Engineering
(1982-1992)
Chemicals
Electricity
Fuel
Heat recovery
Heating
Indirect O&M
Lab work
Labor
M&S Process Ind.-
Chemicals
BLS-PPI Elec. Power
BLS-PPI #2 Diesel Fuel
M&S Process Ind.-Steam
M&S Process Ind.-Avg.
M&S Process Ind.-Avg.
CE Plant-Engineering
BLS-Empl. Cost Index
Leachate Tx.
M&S Process
Ind.
-Avg.
Lime
M&S Process
Ind.
-
Chemicals
Maintenance
M&S Process
Ind.
-Avg.
Polymer
M&S Process
Ind.
-
Chemicals
Steam
M&S Process
Ind.
-Cement
Water
M&S Process
Ind.
-Avg.
Water/Util
M&S Process
Ind.
-Avg.
G-26
-------
presents each of the indexes used to adjust factor prices
from 1982 dollars to 1991 dollars, the adjustment factor
corresponding to each index, and the resulting 1991 factor
prices of all input
G-27
-------
G-28
-------
factors used in the production and cost functions employed in
this analysis. Costs were estimated as follows:
COSTS OF INPUTS USED TO LANDFILL FORM 1 WASTES (G-2)
TVC(Labor) = (QLabor • 21.928421)
TVC(Electricity) = (QElectricity • 0.672269)
TVC(Leachate Treatment) = (QLeachate Treatment • 0.122904)
TVC(Fuel) = (QFuel • 0.786)
TVC(Heating) = (QHeating • 2,458.081803)
TVC(Indirect 0 & M = (Qlndirect 0 & M • 7 3,373.741808)
The total variable cost of providing waste management for
all Form 1 wastes landfilled at a given OWR facility is then
computed by summing the total variable costs of the M inputs.
The total cost for facility k, therefore, is as follows:
TVC(Landfills) = J (TVC ) (G-3)
k m=1 m,k
Reference
1. Reslay, W.A., T.H. Bingham, R.V. Chandran, L.S.
Maclntyre, and J.H. Wood. A Profile of the Market for
Hazardous Waste Management Services. Research Triangle
Institute. Research Triangle Park, NC. May 1986. pp.
138 .
G-2 9
-------
TABLE H-l. LOWER QUARTILE INDUSTRY BENCHMARK FINANCIAL RATIOS
Total
Debt to
Return
Return
Fixed
Collec-
liabilities
SIC
Current
Assets
total
Return
on
on net
assets to
tion
to net
Code
ratio
to sales
assets
on sales
assets
equity
net worth
period
worth
181
1. 3
108.7
63%
0.80%
0.70%
1.70%
121.3
4 9.5
16 6.9
1311
l. 0
354.5
56%
-3.90%
-1.90%
-2.90%
117.0
111.7
125.8
1382
0 . 8
324.7
64%
-1.30%
-0.90%
-2.20%
142.1
111.0
176.1
1611
1 . 3
65.4
64%
0.60%
0.70%
1.70%
116.5
71.2
175.1
1629
1 . 2
78.0
64%
1.10%
1.60%
4.40%
117.6
74.8
175.0
1799
1 . 3
47.5
65%
1.40%
2.70%
6.60%
94.6
66.1
185.8
2082
1 . 1
64.4
54%
3.60%
5.00%
8.50%
122.1
30 . 3
116.3
2211
1 . 4
68.1
63%
0.60%
1.30%
4.70%
77.2
53 . 3
166.8
2295
1 . 6
62 . 4
63%
1.20%
1.50%
3.20%
90.6
56.1
168.1
24 91
1 . 2
63.6
65%
0.50%
0.80%
2.40%
105.2
40.5
189.6
2511
1 . 3
56.2
69%
1.10%
2.70%
6.30%
113.2
49.3
221.8
2522
1 . 3
61.9
67%
1.10%
2.30%
4.20%
89.7
65 . 7
203.3
2599
1 . 4
51.7
72%
1.10%
1.40%
6.20%
103.7
52 . 9
262.0
2621
1 . 3
118.1
65%
1.00%
1.00%
2.80%
154.4
46.9
185.9
2812
1 . 2
92 . 3
81%
-1.00%
-1.00%
-2.20%
812.3
60 . 3
422.0
2819
1 . 2
86.6
71%
1.60%
2.00%
5.80%
133.9
63 . 2
250.7
2821
1 . 2
73.7
70%
0.60%
1.20%
1.80%
121.2
54 . 1
236.7
2834
1 . 5
124.9
60%
-2.20%
-2.10%
-6.20%
76.0
69.6
152.4
2842
1 . 6
61.4
60%
0.80%
1.50%
3.20%
64.0
56.6
153.1
2844
1 . 4
106.3
69%
0.80%
0.90%
2.60%
56.0
73.4
219.6
2851
1 . 7
56.3
61%
0.70%
1.60%
2.10%
56.0
58 . 1
155.0
28 69
1 . 2
77.1
66%
2.00%
3.60%
9.80%
112.4
58 . 8
193.6
2874
1 . 3
81.6
50%
1.30%
2.60%
4.80%
86.6
43.4
102.0
2875
1 . 3
49.6
65%
1.20%
2.50%
3.60%
114.9
55 . 5
185.7
287 9
1 . 4
102.3
63%
-1.00%
-0.80%
-3.00%
123.8
61 . 5
172.9
28 92
1 . 8
71.8
60%
5.90%
2.70%
19.30%
110.0
69.9
151.6
28 99
1 . 3
59.5
67%
1.70%
2.70%
5.90%
77.9
60 . 3
203.6
2911
1 . 1
97.7
74%
1.40%
2.00%
6.70%
212.1
53 . 9
288.2
2951
1 . 1
66.5
65%
0.50%
0.80%
1.80%
138.9
67 . 1
188.7
2 992
1 . 5
47.4
61%
1.70%
2.40%
6.40%
79.5
55 . 5
155.8
30 69
1 . 2
71.0
64%
0.80%
0.80%
4.40%
88.0
59.1
174.6
3241
1 . 7
173.0
68%
-2.00%
-2.30%
-3.00%
127.8
64 . 8
210.1
3272
1 . 3
65.6
64%
1.30%
2.40%
4.10%
99.0
64 . 3
175.1
(continued)
TABLE
H-l .
LOWER
QUARTILE
INDUSTRY
BENCHMARK
FINANCIAL
RATIOS
(Continue
d)
Debt to
Return on
fixed
Collec-
Total
SIC
Current
Assets
total
Return
Return on
net
assets to
tion
liabilities
Code
ratio
to sales
assets
on sales
assets
equity
net worth
period
to net worth
3273
1. 1
69.8
61%
0.50%
0.80%
1.50%
140.5
49.7
155.4
3312
1.2
71. 9
70%
1. 90%
2.10%
7.10%
147.6
60 . 6
231. 4
3321
1. 7
54 . 7
59%
1. 60%
2. 60%
4.70%
74 . 8
56.8
142 .1
3356
1.5
94 .2
71%
1.50%
2.20%
8.80%
119.2
64 . 6
239.5
3523
1.6
71. 8
63%
1. 60%
2. 90%
5.90%
80.8
55.9
172 . 4
3724
1.3
96.1
70%
1. 60%
2.40%
4 . 90%
110.8
68.0
235.3
4226
0.7
159.6
72%
3.20%
3.00%
7.70%
174.8
61.3
258.7
5171
1.3
32 . 9
65%
0.40%
1.80%
3.90%
103.3
30.7
183.8
3339
1. 4
85.3
52%
-0.10%
-3.50%
-7 . 90%
70 . 4
63.4
110.4
3341
1.2
48 . 9
63%
-0.10%
-0.30%
-0 . 60%
92.5
56.7
171.2
3351
1.3
98 . 9
73%
-10.00%
-10.40%
-27.00%
165.2
51.5
267.3
H-l
-------
3357
1.5
74 . 3
65%
0.80%
0. 90%
3.70%
67.5
59.9
187. 6
3369
1.6
48 .1
57%
-0.50%
-1.80%
-1.80%
85.1
63.5
133.5
3412
1.0
48.2
74%
-2.50%
-5.70%
-23.10%
179.4
42 .1
283.3
3425
2.3
48.8
40%
1.20%
1. 70%
3.80%
41. 8
53.8
65.4
3429
1. 4
69.8
62%
1. 60%
1. 70%
3.30%
75.5
53.4
160.5
3452
1.5
68.3
61%
0.50%
1.30%
3.10%
95.1
55.9
154 . 4
3471
1.2
59.9
61%
1. 40%
2.20%
4.70%
103.8
56.6
156.9
3479
1.2
71. 7
65%
1. 90%
2.80%
6.70%
125 . 4
60.4
187.0
3499
1. 4
68.8
64%
1. 70%
2.70%
5.60%
75.3
59.0
175.0
3531
1. 4
77 . 5
66%
-1. 90%
-3.50%
-5.80%
97.0
60.1
197.1
3533
1. 4
90.8
63%
1.20%
1. 60%
3.60%
71. 7
73 . 7
168.4
3579
1.5
84.2
68%
0.50%
0.80%
2 . 90%
52.5
73.3
211.8
3585
1.3
75 . 7
69%
1. 40%
0.70%
2.40%
77 . 5
66.1
221. 7
3612
1.6
62 .2
65%
1.50%
3.10%
6.70%
77 .1
66.0
185.0
3643
1.5
79.2
64%
-0.10%
-0.20%
-0.20%
61. 9
59.4
181.0
3661
1.5
81. 4
62%
-0.50%
-2.20%
-4 . 60%
49.2
73 .1
163.1
3674
1.5
92.0
61%
-0.10%
-0.70%
-0.30%
74 . 4
68.4
154. 6
3678
1. 7
79.1
62%
1.20%
1.20%
2.10%
76.4
58.8
161. 6
3679
1. 4
70 . 7
67%
0.30%
0.50%
2.00%
69.7
62.8
200.8
3691
1. 4
83.3
71%
0.50%
-0.40%
2.10%
121. 5
62.1
249.8
3714
1.3
69.2
70%
0. 60%
0. 60%
2.00%
101.2
53.1
230.8
3721
1. 4
92.8
62%
1. 60%
4 .10%
10.30%
60.1
71. 9
166.6
(continued)T
ABLE H-l.
LOWER
QUARTILE
INDUSTRY
BENCHMARK
FINANCIAL
RATIOS
(Continue
d)
Debt to
Return on
fixed
Collec-
Total
SIC
Current
Assets
total
Return
Return on
net
assets to
tion
liabilities
Code
ratio
to sales
assets
on sales
assets
equity
net worth
period
to net worth
3728
1. 4
74 . 0
68%
1. 60%
2.00%
5.50%
103.7
63.6
216.4
3731
1.3
76.8
75%
1.50%
3.20%
7.20%
118 . 9
79.1
294.4
3751
1.2
50.5
64%
2.80%
5. 60%
15.50%
69.6
53.1
177.3
3842
1.6
80.8
61%
0.50%
0.80%
3.20%
59.9
77 . 6
155.9
3861
1.0
78.0
60%
-0.80%
-0.50%
-0 . 90%
76.0
58.0
152.0
3951
2.2
89.3
52%
1.30%
2.20%
3.50%
61.2
53.7
107.0
3999
1. 4
63.7
62%
0. 90%
0. 90%
4.70%
86.1
55.1
159.8
4011
0.8
291. 9
65%
2.50%
1. 40%
2 . 90%
185.0
106.6
184.5
4212
0.9
58.3
68%
0.10%
0.10%
0 . 90%
167 .2
47 . 8
212.5
4214
1.0
55.7
65%
0.20%
1.20%
137.0
58.8
188.5
4789
1.2
98 .2
66%
0.70%
0. 60%
2 . 60%
142 . 9
72.3
198.2
4911
1.1
263.3
69%
3.20%
1. 60%
5.00%
241. 6
44 . 5
224 . 4
4922
0.8
246.7
71%
1.10%
1.80%
4.50%
213.9
80.0
241.9
4923
0.9
168 .2
72%
2. 60%
2.50%
8.30%
206.4
84.2
257.5
4931
1.2
284 . 9
63%
5.00%
2.00%
3.20%
187 . 6
42 .2
172 . 0
4953
0.8
86.2
68%
2.10%
2.80%
7.30%
163.0
69.5
211.7
4959
0.9
90.4
70%
1.20%
1. 60%
3.60%
116.2
63.6
233.3
5093
1.3
46.1
62%
0. 90%
3.20%
6.80%
96.5
36.9
165.9
5169
1.3
45 . 7
70%
0.70%
1.80%
5.20%
62.4
59.1
230.7
5172
1.2
35.7
68%
0.40%
1. 70%
4.20%
98.0
36.1
214.9
7389
1.2
53.4
66%
1.30%
1. 40%
4.80%
95.1
54.8
191.8
7699
1. 4
58 . 6
62%
1. 40%
2.30%
6.30%
88.7
54 . 4
163.2
8071
1.0
76.5
70%
1. 70%
1. 60%
2.50%
143.7
88.8
230.7
8731
1.3
93.2
61%
-1.00%
-1.30%
-3.40%
82.8
86.5
154.0
8999
1 .?
73.0
59%
0. 90%
0.10%
94.0
85.?
146.1
Source: Dun & Bradstreet Key Financial Ratios.
H-2
-------
SIC
Code
181
1311
1382
1611
1629
1799
2082
2211
2295
2491
2511
2522
2599
2621
2812
2819
2821
2834
2842
2844
2851
2869
2874
2875
2879
2892
2899
2911
2951
2992
3069
3241
3272
3273
3312
SIC
Code
TTZT
3356
3523
3724
4226
5171
3339
3341
3351
3357
3369
3412
3425
3429
3452
3471
3479
3499
TABLE H-2. MEDIAN INDUSTRY BENCHMARK FINANCIAL RATIOS
Debt to
Return
Fixed
Collec-
Total
Current
Assets
total
Return
Return on
on net
assets to
tion
liabilities to
ratio
to sales
assets
on sales
assets
worth
net worth
period
net worth
2.3
57 . 4
42%
4.70%
5.00%
10 . 90%
76.3
27 . 4
73.6
1.6
201.5
31%
7. 90%
3.00%
5.20%
55.1
60. 6
44 . 8
1.3
159.0
40%
6. 90%
3. 50%
6.00%
61.1
59.9
67 . 6
1.8
46.0
47%
2. 90%
5.40%
11.20%
71. 0
47.5
88.2
1. 7
49.2
47%
3.80%
6. 60%
15.00%
67.1
47.8
88.5
1.9
31. 9
46%
4.30%
10.00%
22.40%
49.8
42.0
85.1
1.5
49.0
44%
6. 60%
25.50%
38.40%
79.7
19.4
77 . 6
2.2
47.1
41%
3.20%
5. 60%
12.20%
52.8
41.3
68.1
2.3
39.0
41%
2.80%
6.70%
13.80%
36.0
41.3
68.3
1. 7
40.2
48%
2.10%
4.30%
11.90%
68.4
26.7
93.8
2.0
37.5
49%
3.80%
7 .10%
16.50%
51.4
33.6
95.7
2.0
48.4
45%
2. 90%
5. 50%
12.10%
47 . 8
46.4
81.2
2.1
34.3
51%
4 .10%
7 . 40%
23.30%
48 . 6
39.1
103.1
1. 7
69.2
54%
3.70%
3.40%
6.80%
85.5
36.5
115.3
1.5
72.0
64%
3.20%
3.20%
8. 60%
126.0
58.4
178.1
1. 7
53.5
52%
4 . 40%
8.20%
15.60%
49.3
46.0
109.0
1.9
43.4
50%
4. 60%
9.00%
20.40%
53.9
43.2
99.9
2.4
90.2
43%
5.00%
6.10%
12. 60%
46.7
49.9
74 . 4
2.4
44.1
39%
3. 30%
6.40%
10.60%
24 . 5
41.3
63.8
2.2
57 . 4
52%
3.70%
5.80%
14. 60%
31.0
50.4
107.4
2.5
42 . 4
44%
2.40%
4.80%
11.00%
31. 4
44.9
78 .1
1.9
49.9
48%
5. 30%
7.80%
16.80%
58.0
42 . 7
92.4
2.3
48.5
39%
3.00%
7 .10%
12.30%
25.0
19.4
63.2
2.0
40.4
42%
3.10%
7.00%
16.10%
52.1
34 . 7
13. 4
1.9
55.6
50%
3. 50%
4 . 40%
9.00%
36.1
47.3
98.1
2.1
49.8
49%
6. 90%
15.00%
35.20%
53.3
45.6
97 .2
2.3
41.4
45%
4 .10%
7. 90%
14.30%
38.7
44.9
82.1
1. 4
53.6
59%
3.40%
4. 90%
10.90%
132.5
39.8
146.9
2.0
51. 6
41%
3.10%
4 . 70%
10.20%
79.0
32.0
70.0
2.3
35.3
47%
3.00%
6.00%
13. 50%
28.1
42.3
88.2
2.1
48.5
45%
3.40%
5.40%
12.10%
47 . 8
48.2
83.3
2.1
146.1
47%
4.80%
3. 30%
8.10%
77 . 8
55.5
89.3
2.1
49.9
42%
4.20%
7.30%
14.60%
58 . 9
45.5
73 .1
1.9
48.0
42%
2. 60%
4.50%
9. 50%
77 . 5
35.8
72 . 9
1.8
43.9
55%
4 . 40%
7.20%
17 . 40%
68.1
42 . 7
122.0
(continued) TA
BLE H-2.
MEDIAN
INDUSTRY
BENCHMARK
FINANCIAL
RATIOS
(Continued)
Debt to
Return
Fixed
Collec-
Total
Current
Assets
total
Return
Return on
on net
assets to
tion ;
ratio
to sales
assets
on sales
assets
worth
net worth
period
net wortl:
'2.1
4b. 1
3«%
3-/0%
7. llii
14 . lOi
4 y. 6
41/.y
62 . 4
1.8
43.8
52%
2.80%
5. 50%
9.70%
65.7
48.9
109.1
2.5
50.2
44%
4.30%
7.20%
14.80%
34.8
31. 4
77 . 0
2.1
66.2
49%
3.80%
5. 60%
12. 60%
60.8
50.0
95.1
1.8
73.3
47%
7 .10%
9.00%
16.90%
78 . 7
41.6
87 . 6
1.8
21.6
46%
1.20%
5.20%
10.00%
59.0
20.1
86.1
1. 7
43.3
42%
4. 90%
10.80%
16.40%
43.2
38.7
72.8
1.8
34.0
44%
1.80%
5. 30%
13.80%
55.4
39.5
78 . 4
1.8
60.0
71%
1.10%
-0.20%
-3.90%
156.0
48.2
245.5
1.9
40.3
46%
2.50%
5.20%
13.10%
28.2
53.1
86.9
2.9
38.2
34%
2. 90%
7. 90%
8.20%
45.2
43.8
51.1
1.6
40.5
65%
-0.10%
-2. 90%
-10.70%
132.1
34 . 4
182.0
3.2
42.2
36%
3.80%
8.10%
14 . 40%
25 . 4
49.9
55.4
2.5
46.6
42%
3. 50%
5. 50%
12 . 70%
37.0
42.0
72 . 4
2.5
46.2
39%
3.20%
5.70%
10.90%
41. 3
43.8
64 .1
2.0
42 .1
42%
4.50%
8.50%
17.50%
57.8
44.9
72 . 4
2.1
45.5
44%
5.70%
9.80%
22.00%
60.5
45.6
80.0
2.6
47.6
40%
3.80%
7.20%
15.20%
37 . 9
40.7
65.7
H-3
-------
3531
3533
3579
3585
3612
3643
3661
3674
3678
3679
3691
3714
3721
3728
3731
3751
SIC
Code
3842
3861
3951
3999
4011
4212
4214
4789
4911
4922
4923
4931
4953
4959
5093
5169
5172
7389
7699
8071
8731
8999
2.0
54 . 4
51%
2.10%
3. 60%
10.10%
44 . 3
46.0
2.2
58.4
46%
4.80%
6.00%
11.30%
40 . 9
54.8
2.3
68.0
51%
3.10%
5. 30%
10.10%
27.8
57.1
1.9
53.8
54%
4.30%
7.00%
16.00%
34.8
49.3
2.3
46.4
53%
3.20%
6.40%
16.50%
36.7
47.7
2.5
52.5
40%
1. 60%
3. 90%
9.10%
39.0
47.3
2.3
63.5
46%
2.10%
3.40%
6. 60%
24.8
52.0
2.4
66.6
41%
3.70%
5. 50%
10.80%
41.2
56.2
2.4
55.3
40%
3.10%
4.50%
7 . 70%
52 .2
45.6
2.2
46.9
46%
3.00%
5.20%
13.10%
30.8
47.8
2.0
57. 9
44%
2. 60%
1.00%
10.00%
68 . 9
51. 9
1.9
46.4
51%
3. 50%
5.80%
13.00%
51.4
38.0
1.5
59.0
55%
3. 50%
6.00%
13. 60%
48 .1
49.6
2.0
54.3
44%
5.10%
8.20%
17.30%
50.7
47.5
1.8
55.0
54%
3. 50%
6.00%
14.80%
64.5
56.1
2.0
36.5
50%
5.20%
7.80%
28.30%
53.2
35.8
Debt to
Return
Fixed
Collec-
Current
Assets
total
Return
Return on
on net
assets to
tion
ratio
to sales
assets
on sales
assets
worth
net worth
period
2.8
48.9
39%
3. 50%
6. 50%
13.60%
31.0
53.9
2.3
48.9
44%
3. 50%
5.70%
9.20%
36.1
45.6
3.1
70.2
27%
6.20%
4. 90%
8.10%
21. 6
47.1
2.4
39.6
42%
4 .10%
8.00%
16.40%
37.8
39.1
1.2
199.5
48%
7.00%
4.30%
11. 70%
116.6
62.8
1.5
36.9
46%
2.70%
6. 30%
13.40%
87 . 4
31.0
1. 7
35.1
48%
2.50%
5.70%
12.90%
73.3
37. 6
1.8
57 . 2
50%
4 . 40%
4.50%
9.20%
57.8
45.3
1. 7
209.3
61%
6. 50%
3.20%
8.70%
174.6
34 . 7
1.2
139.2
60%
3.80%
3.80%
10.70%
128.8
51.7
1.1
91.3
62%
4.50%
4 . 40%
12.20%
132.1
58.8
1.8
227. 6
57%
8.00%
3. 90%
8. 90%
120 . 4
33.6
1. 4
52.8
50%
6.70%
8. 90%
20.50%
93.4
42 . 4
1. 7
47.1
49%
8.30%
10.70%
22.80%
74 . 4
47.7
2.2
30. 6
40%
3.10%
8.40%
18.00%
44 . 7
22. 6
1.8
32.0
50%
2.30%
6.40%
15. 30%
29.1
43.1
1.8
23.1
48%
1. 40%
5.40%
11.00%
48.5
23.6
2.0
32.2
42%
5.70%
11.00%
24 .10%
45.2
32.1
2.4
37. 6
42%
5. 60%
10.50%
21.50%
42 . 5
35.0
1. 7
44.4
48%
6.00%
10.20%
22.50%
71 . 4
61.3
2.4
50.2
33%
3.20%
5. 50%
10.20%
37 . 6
56.5
2.3
39.8
34%
6.80%
7.70%
18.50%
44.7
50.1
Dun & Bradstreet Key Financial Ratios.
H-4
-------
SIC
Code
181
1311
1382
1611
1629
1799
2082
2211
2295
2491
2511
2522
2599
2621
2812
2819
2821
2834
2842
2844
2851
2869
2874
2875
2879
2892
2899
2911
2951
2992
SIC
Code
3241
3272
3273
3312
3321
3356
3523
3724
4226
5171
3339
3341
3351
3357
3369
3412
3425
3429
3452
TABLE H-3. UPPER QUARTILE INDUSTRY BENCHMARK FINANCIAL RATIOS
Debt to
Return
Fixed
Collec-
Total
Current
Assets
total
Return on Return on
on net
assets to
tion
ratio
to sales
assets
sales
assets
worth
net worth
period
to net wor
6.4
35.4
19%
10.90%
12.10%
23.00%
39.6
14.2
23.1
4.0
108.3
13%
22.40%
9. 30%
17.60%
18.8
31. 4
14.8
3.7
68.5
14%
19.90%
11.20%
23.90%
18 . 4
27 . 4
15.9
3.1
32 . 9
28%
7.50%
12 . 40%
24.90%
38.0
26.7
39.1
3.1
33.4
25%
9.40%
15. 50%
34.50%
29.6
27 . 7
33.0
3.7
21. 6
25%
12.50%
25.00%
57.70%
22.5
19.7
33.9
2 . 6
40 . 9
32%
14.20%
41. 60%
60.80%
38.3
12.8
47.5
3.2
30.1
22%
7.00%
15.50%
26.70%
20.5
24 .1
28.8
4.5
30.3
30%
7 . 40%
11. 40%
29.70%
16.2
35.6
43.6
3.7
29.3
27%
5. 50%
16.40%
24.30%
34 .1
14 .1
37 .1
3.8
24 . 5
27%
7. 90%
15.70%
37.30%
21. 4
15.3
36.4
3.9
32.7
18%
6. 30%
12 . 40%
29.60%
22.0
38 . 9
22.2
3.1
23.1
29%
9.20%
15.90%
41.60%
18.0
20.4
41.8
3.1
38 . 9
32%
8.70%
9. 60%
19.10%
39.9
28.5
46.3
1. 9
59.1
38%
4.20%
5.40%
18.90%
74 . 4
48 . 6
62.4
3.3
33.9
26%
12.00%
15.80%
34.00%
21. 6
37 .1
35.4
3.5
30.7
25%
13.40%
21.30%
46.50%
21.0
27 . 6
33.7
5.4
51.7
16%
14.80%
15.40%
25.30%
16.9
30.8
19.4
4 . 7
31.1
21%
8.30%
12 . 70%
25.90%
12 . 9
29.9
27.3
3.7
37 . 6
27%
10.60%
14.20%
27.70%
15.1
38.5
36.9
4 .1
33.0
25%
5. 90%
11. 40%
23.00%
12 . 4
31. 4
32. 6
3.5
32.3
23%
10.00%
15.10%
36.40%
28.3
31.8
30.5
3.2
35.7
19%
6.80%
9.40%
19.80%
11.1
10.8
24.2
4.0
32.0
22%
6.40%
15.00%
21.00%
26.2
21.5
27.7
3.0
37 . 7
32%
11.30%
16.60%
31.30%
16.9
29.8
47.4
2.4
42.0
25%
8.70%
17 . 70%
39.60%
28 . 9
12.1
32. 6
3.9
30.1
23%
8.40%
15.20%
36.70%
18.3
32 . 9
30.4
2.1
40 . 9
39%
5.80%
9. 90%
19.70%
64.8
26.2
65.2
3.6
42 .1
21%
8.00%
12.10%
23.60%
29.7
15.1
26.9
3.8
28.5
24%
6. 30%
10. 60%
23.80%
15.5
32.3
31.3
(continued) TA
BLE H-3.
UPPER
QUARTILE
INDUSTRY
BENCHMARK
FINANCIAL
RATIOS
(Continued
)
Debt to
Return
Fixed
Collec-
Total
Current
Assets
total
Return on Return on
on net
assets to
tion
liabilities
ratio
to sales
assets
sales
assets
worth
net worth
period
to net worth
4.1
34.3
'J.H
/. 50%
12.50%
19.0
3 / . 2
3i. y
2.7
103.1
25%
7.20%
6. 50%
13.50%
60.8
39.1
33.3
4.3
37 .2
20%
9.20%
14 . 40%
31.10%
29.3
26.7
24.9
3.7
35.8
20%
6.10%
11.10%
22.80%
43 . 4
25.3
24.4
2.8
31. 4
37%
8.70%
15.40%
44.20%
28 . 9
31. 4
58.4
3.7
35.6
21%
6.80%
14 . 40%
30.60%
24.3
36.5
26.4
2.7
38.7
38%
4 . 70%
7.30%
26.30%
45.3
32 . 9
61.3
5.1
38 .2
21%
9.70%
14 . 90%
31.50%
16.1
19.1
27.0
3.9
44.2
24%
7.20%
8. 60%
23.80%
41.1
41. 4
31.3
3.7
33.9
18%
16.40%
16.70%
38.30%
30.4
27.0
21.6
2.8
15.5
26%
2.70%
9.40%
20.20%
28.7
13.1
34. 9
4 . 4
19.3
24%
11.80%
26.90%
34.30%
19.3
29.8
32.1
3.3
21. 4
27%
7.00%
17.50%
45.90%
27.2
20 . 6
37. 6
2.3
47 . 4
54%
3.10%
5. 30%
23.90%
103.5
39.4
119.4
2 . 9
31.2
33%
5.40%
11.10%
28.40%
15.5
37 . 6
48.4
5.0
30 . 6
15%
7. 90%
19.10%
30.90%
21.2
33.2
17.8
3.3
33.4
50%
1.80%
7.20%
32.40%
48.8
24 . 6
101. 6
5.2
30.8
27%
12.00%
16.00%
23.50%
13.0
39.3
37.5
4.2
32.3
22%
9.80%
13.80%
24 . 90%
14.5
29.6
27.8
4 .1
35.1
20%
8.30%
12.00%
31.00%
16.6
38.7
24.9
H-5
-------
3471
3479
3499
3531
3533
3579
3585
3612
3643
3661
3674
3678
3679
SIC
Code
3691
3714
3721
3728
3731
3751
3842
3861
3951
3999
4011
4212
4214
4789
4911
4922
4923
4931
4953
4959
5093
5169
5172
7389
7699
8071
8731
8999
3.9
30.8
22%
10.30%
16.10%
34.10%
27 . 7
34.0
4 .1
31.5
20%
12.50%
20. 60%
50.00%
30.1
31. 6
5.0
33.2
22%
10.70%
17.30%
34.30%
16.9
23.4
3.1
35.4
27%
6.40%
9.40%
26.00%
18 . 9
29.6
4 . 6
37.5
25%
13.20%
11. 90%
29.40%
16.0
34.3
3.7
50 . 6
28%
8.00%
10. 90%
19.40%
11.5
42.0
3.2
32 . 6
33%
8. 90%
13.40%
38.40%
14 . 9
33.2
4.0
32 . 6
30%
6.00%
12.80%
31.80%
12.8
40 . 6
5.3
35.3
22%
6. 60%
9.70%
25.90%
15.4
40.0
4.5
38.0
19%
7 . 70%
11.00%
26.40%
12 .2
38.4
4.5
43.6
23%
11.50%
13.20%
29.40%
17 . 0
43.8
2.7
41. 7
31%
8.30%
9.00%
16.10%
37 . 4
39.4
3.8
32.8
24%
8.00%
14.80%
31.80%
15.0
31. 4
Debt to
Return
Fixed
Collec-
Current
Assets
total
Return on Return on
on net
assets to
tion
ratio
to sales
assets
sales
assets
worth
net worth
period
2 . 9
35.5
26%
5.70%
7. 90%
18.70%
21.0
40 . 9
3.7
33.9
27%
8.70%
14 . 40%
29.70%
20.0
23.4
3.6
45.8
49%
7 . 40%
7 . 70%
24.30%
19.9
20.1
3.6
38 .2
24%
11.00%
16.60%
41.60%
20.0
25 . 4
2 . 6
37 .2
33%
6.80%
11. 40%
38.60%
42.8
42 . 5
2.8
29.9
36%
8.30%
25.30%
53.50%
22 . 6
19.8
6.5
33.5
17%
11.30%
19.10%
31.80%
11.0
34 . 9
5.1
34 .1
21%
8.40%
15.60%
31.60%
15.9
32.3
4.2
51.0
20%
11.20%
19.50%
25.20%
16.4
37 .2
5.0
26.9
21%
10.00%
19.40%
41.30%
14.2
22.3
2.2
135.2
30%
18.00%
8.40%
18.30%
81. 4
31.0
3.6
23.5
23%
7 .10%
15.50%
33.70%
42 . 5
16.8
3.6
24 . 5
26%
6. 30%
14.00%
31.90%
37.3
23.1
4.2
25 . 4
17%
7. 90%
12.20%
23.20%
29.1
23.4
2 . 9
167 . 4
51%
10.00%
4.50%
12.20%
112.3
26.7
1. 7
56.0
44%
10.00%
6. 90%
17.30%
91. 9
36.0
1.3
47 . 5
53%
8. 60%
6. 60%
18.10%
77 . 8
34 . 7
2 . 9
178.8
33%
13.80%
6.00%
15.30%
89.2
27 .1
3.1
33.5
28%
14.20%
20.30%
50.50%
41.2
24 . 9
3.7
32 . 9
25%
16.00%
28. 60%
73.30%
49.7
25 . 7
5.3
19.7
19%
7 .10%
17 . 40%
36.80%
18.8
11.3
3.3
22.7
29%
8.30%
16.80%
36.80%
9.3
30.7
3.1
16.2
26%
3.20%
10.50%
23.40%
20.5
13.9
4.8
19.2
18%
13.80%
30.30%
68 .20%
17.2
16.1
5.1
24 . 4
21%
12.80%
25.00%
57 .20%
18.0
16.4
3.6
30 .2
28%
13.40%
22.70%
50.80%
37 . 4
43.0
5.7
34 .1
16%
11. 40%
18.80%
30.40%
14 . 6
36.9
7.0
19.1
1 0%
18. 60%
? 0 . 8 0 %
37 . ?0%
18.3
?8.1
Dun & Bradstreet Key Financial Ratios.
H-6
-------
TABLE H-4. DATA FROM THE COMMON SIZE
SET UP BASELINE FINANCIAL
FINANCIALS REQUIRED TO
STATEMENTS
lilUUiliy b Ld Linen L ± LeiLLb
Liaianue—siiee l
± Lexus
General and
Total
SIC
Cost of
Gross
administrative
Net
Accounts
current
Code
sales
profit
expenses
income
Cash receivable
assets
1311
1382
1611
1629
1799
2082
2211
2295
24 91
2511
2522
2599
2621
2812
2819
2821
2834
2842
2844
2851
28 69
2874
2875
287 9
28 92
28 99
2911
2951
2 992
30 69
3241
3272
3273
3312
3321
3356
3523
3724
4226
0.516
0.536
0.747
0.685
0.628
0.641
0.691
0.702
0.760
0.670
0.670
0.670
0.770
0.745
0.629
0.631
0.525
0.601
0.508
0.659
0.633
0.707
0.728
0.603
0.737
0.599
0.725
0.750
0.669
0.682
0.754
0.616
0.625
0.689
0.767
0.740
0.679
0.705
0.563
0.484
0.464
0.253
0.315
0.372
0.359
0.309
0.298
0.240
0.330
0.330
0.330
0.230
0.255
0.371
0.369
0.475
0.399
0.492
0.341
0.367
0.293
0.272
0.397
0.263
0.401
0.275
0.250
0.331
0.318
0.246
0.384
0.375
0.311
0.233
0.260
0.321
0.295
0.437
0.413
0.391
0.216
0.260
0.310
0.338
0.263
0.251
0.215
0.284
0.277
0.279
0.187
0.228
0.312
0.297
0.442
0.349
0.436
0.306
0.314
0.264
0.233
0.362
0.220
0.351
0.241
0.215
0.302
0.278
0.211
0.331
0.342
0.255
0.192
0.223
0.268
0.247
0.357
0.071
0.073
0.037
0.055
0.062
0.021
0.046
0.047
0.025
0.046
0.053
0.051
0.043
0.027
0.059
0.072
0.033
0.050
0.056
0.035
0.053
0.029
0.039
0.035
0.043
0.050
0.034
0.035
0.029
0.040
0.035
0.053
0.033
0.056
0.041
0.037
0.053
0.048
0.080
0.162
0.161
0.162
0.151
0.150
0.100
0.106
0.118
0.046
0.111
0.081
0.122
0.100
0.059
0.108
0.103
0.124
0.100
0.078
0.094
0.113
0.066
0.120
0.094
0.031
0.126
0.080
0.143
0.086
0.110
0.041
0.117
0.124
0.107
0.116
0.090
0.104
0.080
0.133
0.143
0.147
0.277
0.270
0.322
0.124
0.243
0.273
0.187
0.219
0.280
0.287
0.221
0.222
0.285
0.282
0.189
0.295
0.257
0.290
0.248
0.227
0.257
0.220
0.307
0.297
0.186
0.247
0.317
0.290
0.109
0.249
0.226
0.287
0.277
0.308
0.196
0.227
0.194
0.418
0.434
0.560
0.556
0.654
0.411
0.641
0.725
0.561
0.650
0.679
0.693
0.538
0.463
0.626
0.621
0.608
0.705
0.731
0.740
0.587
0.580
0.655
0.636
0.636
0.678
0.514
0.555
0.674
0.646
0.339
0.580
0.477
0.609
0.583
0.681
0.715
0.634
0.428
(continued) TABLE
H-4. DATA FROM
THE COMMON SIZE
FINANCIALS
REQUIRED TO
SET UP BASELINE
FINANCIAL
STATEMENTS
(Continued)
income—s La Linen L—± Lems
Liaiance—siiee l
_l Lexus
General and
Total
SIC
Cost of
Gross
administrative
Net
Accounts
current
Code
sales
profit
expenses
income
Cash receivable
assets
3339
3341
0.792
0.779
0.208
0.221
0.153
0.185
0.055
0.036
0.098
0.111
0.121
0.254
0.590
0.635
H-7
-------
3351
3357
3369
3412
3425
3429
3452
3471
347 9
34 99
3531
3533
3579
3585
3612
3643
3661
3674
3678
367 9
3691
3714
3721
3728
3731
3751
3842
38 61
3951
3999
4011
4212
4214
478 9
4911
4 922
4 923
SIC
Code
TT3T
4 953
4 959
50 93
5169
5172
738 9
7 699
8071
8731
8 999
0.834
0.667
0.669
0.603
0.602
0.660
0.696
0.574
0.591
0.611
0.695
0.641
0.615
0.683
0.661
0.686
0.616
0.629
0.668
0.650
0.684
0.679
0.670
0.671
0.731
0.626
0.553
0.610
0.642
0.595
0.554
0.608
0.581
0.631
0.670
0.702
0.764
0.166
0.333
0.331
0.397
0.398
0.340
0.304
0.426
0.409
0.389
0.305
0.359
0.385
0.317
0.339
0.314
0.384
0.371
0.332
0.350
0.316
0.321
0.330
0.329
0.269
0.374
0.447
0.390
0.358
0.405
0.446
0.392
0.419
0.369
0.330
0.298
0.236
0.181
0.293
0.302
0.389
0.348
0.284
0.250
0.367
0.337
-0.151
0.282
0.315
0.355
0.273
0.296
0.280
0.369
0.329
0.323
0.315
0.265
0.276
0.283
0.271
0.226
0.291
0.394
0.360
0.311
0.352
0.342
0.357
0.388
0.344
0.269
0.239
0.177
-0.015
0.040
0.029
0.008
0.050
0.056
0.054
0.059
0.072
0.540
0.023
0.044
0.030
0.044
0.043
0.034
0.015
0.042
0.009
0.035
0.051
0.045
0.047
0.058
0.043
0.083
0.053
0.030
0.047
0.053
0.104
0.035
0.031
0.025
0.061
0.059
0.059
0.026
0.114
0.112
0.053
0.066
0.096
0.087
0.131
0.126
0.124
0.090
0.110
0.160
0.106
0.102
0.121
0.146
0.152
0.088
0.125
0.075
0.098
0.066
0.102
0.148
0.076
0.145
0.130
0.163
0.134
0.120
0.143
0.139
0.180
0.039
0.089
0.053
0.212
0.320
0.314
0.294
0.279
0.255
0.286
0.287
0.284
0.260
0.255
0.280
0.229
0.290
0.323
0.270
0.285
0.246
0.238
0.289
0.285
0.240
0.171
0.250
0.312
0.180
0.278
0.240
0.198
0.252
0.135
0.237
0.297
0.263
0.060
0.197
0.247
0.495
0.741
0.672
0.540
0.692
0.679
0.694
0.545
0.560
0.686
0.694
0.648
0.749
0.720
0.759
0.715
0.755
0.671
0.592
0.721
0.649
0.658
0.702
0.654
0.619
0.673
0.710
0.730
0.718
0.704
0.354
0.458
0.524
0.558
0.186
0.392
0.389
(continued) TABLE
H-4. DATA FROM
THE COMMON SIZE
FINANCIALS
REQUIRED TO
SET UP BASELINE
FINANCIAL
STATEMENTS
(Continued)
J. n c. o lTi s s t ct. t lTi s n t its iti s>
£3 cl _L cTTTT
It ltS l'l'l s :
General and
expenses
Total
current
Cost of
sales
0 .697
0.614
0.495
0.705
0.697
0.837
0.612
0.553
0.503
0.599
0.538
Gross
profit
Net
income
0 .303
0.386
0.505
0.295
0.303
0.163
0.388
0.447
0.497
0.401
0.462
0.215
0.319
0.430
0.252
0.264
0.142
0.319
0.376
0.435
0.359
0.402
0 .088
0.067
0.075
0.043
0.039
0.021
0.069
0.071
0.062
0.042
0.060
Cash
0 . 062
0.113
0.149
0.152
0.139
0.126
0.200
0.139
0.145
0.215
0.187
Accounts
receivable
0.057
0.221
0.233
0.237
0.368
0.312
0.249
0.239
0.277
0 .262
0.268
0.219
0.421
0.481
0.628
0.763
0.645
0.647
0.660
0.501
0.628
0.617
H-8
-------
Source: Dun & Bradstreet Key Financial Ratios.
H-9
-------
TABLE H-5. CALCULATIONS REQUIRED TO SET UP BASELINE FINANCIAL STATEMENTS
Financial statement category
Income statement
Annual revenues
Cost of sales
Gross profit
Other expenses and taxes
Net income
Balance sheet
Cash
Accounts receivable
Cash + accounts receivable
Other current as;
Total current as;
Fixed assets
Other noncurrent
Debt to total ass
Accounts payable
Other current
Total current
Noncurrent
Total
Net worth
Total
equity
and owner's
Collected from data sources identified in Table
or (total assets) / (assets to sales benchmark)
Sales • (1-ROS benchmark) * [ (cost of sales share
from common size income statment) / (cost of sales
share plus general and administrative expenses share
from common size income statment)]
Annual revenues - cost of sales
Gross profit - net income
ROS benchmark • annual revenues
(Cash + accounts receivable) - accounts receivable
(Collection period benchmark / 365) • annual
revenues
Total assets • [ (cash share from the common size
balance sheet plus accounts receivable share from
the common size balance sheet) / (total current
assets share from the common size balance sheet)]
Total current assets - (cash + accounts receivable)
Total current liabilities • current ratio benchmark
Fixed assets to net worth benchmark ratio • net
worth
Total assets - fixed assets - current assets
Collected from data sources identified in Table
or (annual sales) • (assets to sales D&B benchmark
ratio)
Annual revenues
benchmark
Total current
Current
worth
Total
Debt to total as
Debt to total as
worth benchmark)
Total assets
accounts payable to sales
- accounts payable
to net worth benchmark • net
- total current liabilities
;ts - net worth
;ts / (1+total liabilities to net
Note: These calculations were used to set up financial statements for
potentially affected firms for which actual financial statements were not
available from published sources. Benchmark ratios are based on the Dun &
Key Financial Ratios contained in Table C-l.
H-10
-------
TABLE H-6.
CALCULATIONS REQUIRED TO SET UP WITH-REGULATION
FINANCIAL STATEMENTS
Financial statement
category
Income statement
Annual revenues
Cost of sales
Gross profit
Expenses due to regulation
Other expenses and taxes
Net income
Balance sheet
Cash
Accounts receivable
Cash + accounts receivable
Other current assets
Total current assets
Fixed assets
Other noncurrent assets
Debt to total assets
Accounts payable
Other current
Total current
Noncurrent
Total
Net worth
Total liablities and
owner's equity
Baseline annual revenues + the estimated change in
annual revenues
No change from baseline
Annual revenues - cost of sales
Interest: Projected share of capital costs;
financied through debt • debt interest rate;
Depreciation: 10% • compliance capital costs;
Operating: operating compliance costs
(Gross profit - estimated expense due to
regulation) • baseline ratio of other expenses and
taxes to gross profit
Gross profit - estimated expense due to regulation
- other expenses and taxes
No change from baseline
No change from baseline
No change from baseline
No change from baseline
No change from baseline
Baseline fixed assets + compliance capital cost
No change from baseline
Total current assets + fixed assets + other
noncurrent assets
No change from baseline
Baseline other current liabilities + amortized
compliance cost financied through debt - estimated
interest expense
Accounts payable + other current liabilities
Baseline noncurrent liabilities +(capital
compliance cost financed through debt - current
portion of debt)
Total current liabilities + noncurrent
Total assets - total
Total assets
expense Is based on the first year's allowable deduction
equipment under the modified accelerated cost recovery system.
H-ll
-------
United States Office of Air Quality EPA-452/R-96-011
Environmental Protection Planning and Standards June 1996
Agency Research Triangle Park, NC 27711
Air
Off-Site Waste and Recovery Operations
NESHAP: Economic Impact Analysis
DRAFT
-------
------- |