United States
Environmental Protection
Agency
Office of Water Regulations
and Standards
Washirtgton. DC 20460
EPA 440(2/87-307
September 1987
ECONOMIC IMPACT ANALYSIS OF
EFFLUENT LIMITATIONS
GUIDELINES
AND STANDARDS FOR THE
ORGANIC
CHEMICALS, PLASTICS AND
SYNTHETIC
FIBERS INDUSTRY
QUANTITY
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ECONOMIC IMPACT ANALYSIS OF
EFFLUENT LIMITATIONS AND STANDARDS
FOR THE
ORGANIC CHEMICALS, PLASTICS, AND
SYNTHETIC FIBERS INDUSTRY
Submitted to:
U.S. Environmental Protection Agency
Office of Water Regulation and Standards
Office of Analysis and Evaluation
Washington, D.C. 20460
Submitted by:
Abt Associates Inc.
55 Wheeler Street
Cambridge, Massachusetts 02138
September 1987
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Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
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PREFACE
This document is a contractor's study prepared for the Office of Water
Regulations and Standards of the Environmental.Protection Agency (EPA). The purpose
of the study is to analyze the economic impact which could result from the application
of effluent standards and limitations issued under Sections 301, 30
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TABLE OF CONTENTS
Pa^e
1.0 EXECUTIVE SUMMARY l-l
1.1 Industry Coverage 1-1
1.2 The Economic Impact Assessment Methodology l-l
1.3 Industry Profile ¦ 1-2
1.4 Impact Analysis Results 1-2
1.4.2 Firm Impacts 1-7
1.4.3 Community Impacts 1-7
1.4.4 Balance of Trade Impacts 1-7
1.4.5 New Sources Impacts 1-7
1.5 Limits of Analysis 1-7
1.6 Sensitivity Analysis 1-8
2.0 INDUSTRY PROFILE 2-1
2.1 Overview 2-1
2.1.1 Definition of Industry Scope 2-1
2.2 Product Characteristics 2-2
2.2.1 Basic and Intermediate Chemicals 2-4
2.2.2 Finished Chemicals 2-6
2.3 Market Structure : 2-11
2.3.1 Industry Concentration 2-11
2.3.2 Integration and Diversification 2-12
2.3.3 Product Differentiation and Competition 2-13
2.3.4 Product Substitution, Research and
Development, Demand Elasticity and
Profitability. 2-16
2.3.5 Barriers to Entry 2-16
2.4 Industry Performance and the Business Cycle 2-17
2.4.1 Historical Production and Comparison
with Total Manufacturing ' 2-17
2.4.2 Industry Performance Trends 2-25
2.4.3 Price, Capacity Utilization and
Capital Spending Trends 2-25
2.5 Employment and Productivity 2-31
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TABLE OF CONTENTS
(continued)
Page
2.6 Foreign Trade Prof ile 2-36
2.6.1 Importance from Balance of Payments
Perspective 2-36
2.6.2 Importance of Trade for the U.S.
OCPSF Industry 2-40
2.6.3 Importance of the U.S. in the World
OCPSF Market 2-42
2.7 Financial Profile 2-42
2.8 Firm and Plant Characteristics 2-52
2.3. L SIC Groups 2-52
2.8.2 Single Versus Multi-Plant Firms 2-52
2.8.3 Production Quantity and Value 2-55
2.8.4 Sales Quantity and Value 2-55
2.8.5 Production Costs 2-66
2.8.6 Employment 2-66
2.8.7 Labor Productivity 2-72
2.8.8 Capital Expenditures 2-72
2.8.9 Plant Age 2-77
2.8.10 Discharge Status 2-77
2.8.11 Plant Locations 2-77
2.8.12 Type of Firm Ownership 2-77
3.0 METHODOLOGY 3-1
3.1 Introduction and Overview 3-1
3.2 Data Sources 3-4
3.2.1 §308 Survey 3-7
3.2.2 Dun <5c Bradstreet Data 3-8
3.2.3 DRI Services 3-9
3.2.4 Company Data Base 3-14
3.3 Baseline Estimates 3-14
3.3.1 Macro Level 3-15
3.3.2 Industry Level 3-15
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TABLE OF CONTENTS
(continued)
Page
3.3.3 Firm Levels 3-15
3.3.4 Plant Level 3-19
3.3.5 Product Level 3-24
3.3.6 New Sources 3-24
3.3.7 Cost of Capital and Time Horizon 3-25
3.4 Plant Level Impacts 3-26 .
3.4.1 Closure Analysis 3-26
3.4.2 Profitability 3-28
3.4.3 Cost as a Percent of Sales 3-29
3.5 Firm Level Analysis 3-29
3.6 Industry-Wide Impacts 3-31
3.7 Employment Impacts 3-33
3.8 Community Impacts 3-33
3.9 Small Business Analysis 3-36
3.10 International Trade Impacts 3-36
3.10.1 Sensitivity to Foreign Competition 3-37
3.10.2 Balance of Trade Impacts 3-38
3.11 New Sources 3-40
3.11.1 Estimating the Cost of Constructing
New Plants, and Cost of Expansions 3-41
3.11.2 Estimating the Impacts for New Plant
Construction 3-42
3.12 National Social Costs 3-43
3.12.1 Social Cost vs. Private Cost 3-43
3.12.2 Methodology 3-44
Appendix 3A Summary of §308 Survey Economic Data 3A-1
Appendix 3B Replacement Estimates for Missing §308
Survey Data 3B-1
Appendix 3C OCPSF Industry Cost of Capital Estimation 3C-1
Appendix 3D Company Financial Ratios and COMPUSTAT
Data Use 3D-1
Appendix 3E Construction Data 3E-1
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TABLE OF CONTENTS
(continued)
Page
4.0 TREATMENT COSTS 4-1
4.1 Overview 4-1
4.2 Statutory Authority 4-1
4.3 Treatment Control Technologies 4-2
4.4 Subcategorization of Industry 4-2
4.5 Regulatory Options 4-4
4.5.1 BPT Options 4-4
4.5.2 BAT Options 4-4
4.5.3 PSES Options 4-7
4.5.4 NSPS and PSNS Options 4-7
4.6 Consideration of Other Environmental Regulations 4-9
4.7 Estimation of Treatment Costs 4-10
4.7.1 Treatment Costing 4-10
4.7.2 Plants Costed Versus Plants Analyzed 4-12
5.0 BASELINE 5-1
5.1 Summary and Overview 5-1
5.2 Macroeconomic Baseline 5-5
5.2.1 General Economic Environment 5-S
5.2.2 Industry Specific Demand Factors 5-9
5.2.3 Industry Specific Cost Factors 5-11
5.3 Industry Baseline 5-11
5.4 Plant Baseline 5-17
5.4.1 Baseline Sales and Employment 5-22
5.4.2 Baseline Plant Closure Analysis 5-22
5.5 Firm Baseline 5-26
5.6 Foreign Trade Baseline 5-31
5.6.1 General International Trade Factor
Forecasts 5-32
5.6.2 Product Group Foreign Trade Forecasts 5-34
5.6.3 Summary of Foreign Trade Sensitive
Products 5-39
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TABLE OF CONTENTS
(continued)
Pa^e
Appendix 5 A Detailed Product Group Baseline 5A-1
5A.1 Plastics and Resin Materials (SIC 2821) 5A-1
5A.2 Synthetic Fibers (SIC 2824) 5A-3
5A.3 Miscellaneous End-Use Chemicals and
Chemical Products (SIC 2S69-6) 5A-S
5A.4 Plasticizers (SIC 2869-3) 5A-L 3
5A.5 Celulosic Fibers (SIC 2823) 5A-13
5A.6 Dyes (SIC 2S65-2) .5A-13
5A.7 Organic Pigments (SIC 2865-3) 5A-13
5A.8 Rubber Processing Chemicals (SIC 2869-3) 5A-17
5A.9 Flavor and Perfume Materials (SIC 2869-3) 5A-17
5A.10 Miscellaneous Cyclic and Acyclic
Chemicals (SIC 2869-7) 5A-17
5A.il Cyclic Intermediates (SIC 2865-1) 5A-25
6.0 ECONOMIC IMPACT ASSESSMENT RESULTS 6-1
6.1 Introduction 6-1
6.2 Plant Level Impacts 6-1
6.2.1 Direct Dischargers 6-1
6.2.2 Indirect Dischargers 6-5
6.3 Firm-Level Impacts 6-8
6.4 . Community Impacts 6-10
6.4.1 BAT Impacts 6-12
6.4.2 PSES Impacts 6-13
6.5 Small Business Impacts 6-14
6.6 Foreign Trade Impacts 6-14
6.7 New Sources Analysis 6-20
6.7.1 Increase in Plant Construction Costs 6-22
6.7.2 New Present Value of Cash Flow 6-24
6.8 National Social Costs 6-26
Appendix 6A Summary of Plant Level Costs and Impacts Used
For Detailed Analyses 6A-1
Appendix 6B Foreign Trade Impacts for Chemical Groups
Not Covered by DRI 6B-1
Appendix 6C Detailed Tables for New Sources Analysis 6C-1
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TABLE OF CONTENTS
(continued)
Page
7.0 SENSITIVITY ANALYSIS 7-1
8.0 LIMITS OF THE ANALYSIS S-l
8.1 Plant Closure Analysis 3-2
3.2 New Sources Analysis S-5
8.3 Foreign Trade Analysis 3-6
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LIST OF FIGURES
Pa^e
Figure 2-1 OCPSF Industry Production Paths 2-5
Figure 2-2a Value of Shipments 2-19
Figure 2-2b SIC 2869 Value of Shipments 2-20
Figure 2-2c SIC 2821 Value of Shipments 2-21
Figure 2-2d SIC 2824 Value of Shipments 2-22
Figure 2-2e SIC 2865 Value of Shipments 2-23
Figure 2-2f SIC 2823 Value of Shipments 2-24
Figure 2-3 OCPSF Production and Economic Trends 2-27
Figure 2-4 OCPSF Price, Production, Investment 2-33
Figure 2-5 OCPSF Production Employment 2-37
Figure 2-6 Mean and Median of OCPSF and Total Production
for Plants and Firms 2-61
Figure 2-7 Total Value of Shipments by SIC Code 2-64
Figure 3-1 Economic Impact Analysis of Organic Chemicals,
Plastics, and Synthetic Fibers Industry Effluent
Limitations Guidelines: Analytic Components 3-2
Figure 3-2 Flowchart of Information Flow and Analysis 3-5
Figure 3-3 Comparison of Sales: FIN/STAT vs. §308
Data 3-11
Figure 3-4 Comparison of Sales: Single Location, Non-
Subsidiary DNB vs. §308 Data 3-12
Figure 3-5 Comparison of Sales: DNB vs. §308 Data 3-13
Figure 3-6 Comparison of Firm-Specific Current Ratio
and Interest Coverage Data Based on RMA
Industry Norms 3-32
Figure 3-7 Comparison of Firm-Specific Debt to Worth and
Return on Assets Data to RMA Industry Norms 3-32
Figure 3-8 Supply and Demand for OCPSF Products 3-45
Figure 3-9 Real Resource and Welfare Effects of Effluent
Guidelines 3-46
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LIST OF FIGURES
(continued)
Page
Figure 5-1 Macroeconomic Baseline 5-7
Figure 5-2 Chemical Industry Production Growth -
Total Percent Growth, 1982-1988 5-14
Figure 5-3 Chemical Industry Production Growth
Annual Percent Growth, 19S2-193S 5-15
Figure 5-4 Outlook for OCPSF Product Groups
(1982-1988) Total Production Volume 5-19
Figure 5-5 Outlook for OCPSF Product Groups (1982-1988)-
Production Growth 5-^20
Figure 5-6 Frequency of 308 Data Profitability According
to Deciles of DNB Data Baseline for All Plants
included in the Analysis (SIC3 = 282) 5-29
Figure 5-7 Frequency of 308 Data Profitability According
to Deciles of DNB Data Baseline for All Plants
Included in the Analysis (SIC3 = 286) 5-30
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LIST OF TABLES
Page
Table l-l Summary of Results 1-3
Table 1-2 Summary of Cumulative Results:
Direct Dischargers 1-5
Table 2-1 Assignment of OCPSF In-Scope SIC Codes to
4-Digit SIC Code and Product Tvpe 2-2
Table 2-2 U.S. Production, Sales Price and Uses oi OCPSF
Products - 1982 2-3
Table 2-3 End-Use of Flavors, Perfumes and Related
Products(1979) 2-8
Table 2-4 Consumption of Plastics by End Use - 1979 2-10
Table 2-5 Uses of Manmade Cellulosic and Synthetic
Fibers - 1982 2-11
Table 2-6 Industry Concentration Ratios Percent of
Value of Product Shipments 2-12
Table 2-7 Industry Coverage and Specialization Ratios 2-14
Table 2-8 Chemical Industry Market Characteristics 2-14
Table 2-9 Market Classes of OCPSF Product Groups 2-15
Table 2-10 Production Trends bv OCPSF Product Group,
1975-1982 ! 2-LS
Table 2-11 OCPSF Production and U.S. Economic Trends 2-26
Table 2-12 Profit on Sales Trends 2-28
Table 2-13 Percent on Net Worth Trends 2-29
Table 2-14 Price Trends by OCPSF Product Group 2-30
Table 2-15 OCPSF Price, Capacity Utilization and Capital
Spending Trends 2-32
Table 2-16 OCPSF Employment Trends 2-34
Table 2-17 OCPSF Employment Productivity Trends 2-35
Table 2-18 Production Employment as a Percentage of Total
Employment (1972-1982) 2-36
Table 2-19 OCPSF Import and Export Trends 2-38
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LIST OF TABLES
(continued)
Page
Table 2-l9a OCPSF Import and Export Trends 2-39
Table 2-20 OCPSF Import and Export Trends as a Percent
of Shipments 2-41
Table 2-21 World Petrochemical Production in 19S0 2-43
Table 2-22 World Petrochemical Imports and Exports 2-44
Table 2-23 Approximate Annual Production and Proven
Reserves of Hydrocarbons in Quadrillion BTU 2-45
Table 2-24a Financial Ratios for Direct Owner Corporations
Owning In-Scope Plants Calculated from COMPUSTAT
Data 2-47
Table 2-24b Financial Ratios for Direct Owner Corporations
Owning In-Scope Plants Calculated from COMPUSTAT
Data 2-48
Table 2-25 Financial Ratios for Parent Corporations by
SIC Group by Year 2-49
Table 2-26 Median Financial Ratios by SIC Groups Using RMA
Data 2-51
Table 2-27 Firm and Plant Categorization by OCPSF SIC
Group and Degree of Plant Specialization 2-53
Table 2-28 Breakdown of Multi-Plant and Single-Plant OCPSF
Firms 2-54
Table 2-29 Distribution of 1982 Firm Production Quantity by
OCPSF SIC Group 2-56
Table 2-30 Distribution of 1982 Plant Production Quantity
by OCPSF SIC Group 2-57
Table 2-31 Firm 1982 Production Quantities and Values
and Employment by OCPSF SIC Group 2-58
Table 2-32 Plant 1982 Product and Sales Quantities and Values
by OCPSF SIC Group 2-59
Table 2-33 Comparison of Mean, Median OCPSF and Total
Production Quantity by Plant and by Firm 2-6.0
Table 2-34 Distribution of 1982 Plant Sales Quantity by OCPSF
SIC Group 2-62
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LIST OF TABLES
(continued)
Page
Table 2-35 Distribution of 1982 Plant Sales Value by OCPSF
SIC Group 2-63
Table 2-36 Comparison of 1982 Plant Sales to Plant
Production 2-65
Table 2-37 Distribution of 1982 Plant Production Costs
by OCPSF SIC Croup 2-67
Table 2-38 Distribution of 1982 Plant Production Costs to
Sales Value Ratio by OCPSF SIC Group 2-68
Table 2-39 Plant 1982 Production Costs, Employment and
Productivity by SIC Group . 2-69
Table 2-40 Distribution of 1982 Firm Employment by
OCPSF SIC Group 2-70
Table 2-41 Distribution of 1982 Plant Employment by
OCPSF SIC Group 2-71
Table 2-42 Distribution of 1982 Plant Productivity by OCPSF
SIC Group 2-72
Table 2-43 Summary of 1982 Plant Labor Productivity 2-74
Table 2-44 Distribution of Capital Expenditures by
Major SIC Group 2-75
Table 2-45 Plant Age and Capital Expenditures by SIC Group 2-76
Table 2-46 Distribution of Plant Age by Major
OCPSF SIC Groups 2-78
Table 2-47 Distribution of Plant Discharge Status by Major
OCPSF SIC Groups 2-79
Table 2-48 Location of OCPSF Plants 2-80
Table 2-49 Distribution Among SIC Groups by Type of
Ownership Production Value 2-81
Table 2-50 Firm OCPSF Employment by Type of Ownership 2-83
Table 2-51 Firm OCPSF Value of Shipments by Type
of Ownership 2-83
Table 3-1 Comparison of FIN/STAT and Dun <5c Bradstreet
Ratios 3-10
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LIST OF TABLES
(continued)
Paoe
Table 3-2 Baseline for OCPSF Economic Impact Analysis 3-16
Table 3-3 Values Used in Estimation of 1988 Sales 3-21
Table 3-4 Equations Used to Estimate Plant Level Financial
Parameters 3-23
Table 3A-1 Summary of §308 Survey Economic Data for
OCPSF Plants In Scope 3A-2
Table 3B-1 List of Unit Prices Used for Data Replacement
Methodology . 3B-3
Table 3C-1 Nominal and Real Weighted Average Cost of Capital
for OCPSF Producers In Scope 3C-4
Table 3E-1 Production Quantity of In-Scope Plants 3E-3
Table 4-1 Treatment Technologies for Abatement of OCPSF
Pollutants 4-3
Table 4-2 BPT Technology Option 4-5
Table 4-3 BAT Technology Options 4-6
Table 4-4 PSES Technology Options 4-8
Table 4-5 Summary of OCPSF Treatment Costs
By Regulatory Option 4-11
Table 4-6 OCPSF Plant Count Comparison: Those Covered by
Regulations, Those Incurring Costs, and Those
Included in the Economic Impact Analysis 4-13
Table 5-1 Macroeconomic Baseline 5-6
Table 5-2 Growth of OCPSF Demand Factors, 1982-1988 5-10
Table 5-3 Changes in OCPSF Prices and Input Costs 5-12
Table 5-4 Baseline Interests Rates 5-12
Table 5-5 Growth of Chemical Industry Production and
End-Use Indices 5-13
Table 5-6 OCPSF Industry Growth Indicators 5-16
Table 5-7 Summary of 1982-1988 Outlook for OCPSF Product
Groups 5-18
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LIST OF TABLES
(continued)
Pa%e
Table 5-8 Production, Capacity and Capacity Utilization,
1982 and 1988 ! ! 5-21
Table 5-9 Distribution of 1988 Plant Sales Value by OCPSF
SIC Group 5-23
Table 5-10 Distribution of 1982 Plant Employment by OCPSF
SIC Group 5-24
Table 5-11 Values Used in Estimation of 1988 Sales 5-25'
Table 5-12 Median Financial Ratios 5-27
Table 5-13 Profit Margin by SIC and Size 5-28
Table 5-14 Petrochemical Exports and Imports for Selected
Products for 1981, 1985, and 1990 5-33
Table 5-15 Announced World Capacity Expansion 5-35
Table 5-16 U.S. Foreign Trade by Chemical Product for
Plastics and Resins (SIC 2821) and Synthetic
Fibers (SIC 2824) 1984 and 1988 5-37
Table 5-17 U.S. Foreign Trade Situation by Product for
Miscellaneous Cyclic and Acyclic Chemicals
(SIC 2869-7) 1984 and 1988 5-38
Table 5-18 U.S. Foreign Trade Situation by Product for
Cyclic Intermediates (SIC 2865-1) Fibers (SIC 2824)
1984 and 1988 5-40
Table 5A-1 Plastics and Resin Materials Baseline 5A-2
Table 5A-2 Price, Production, and Value of Production by
Product for Plastics and Resins (SIC 2821) and
Synthetic Fibers (SIC 2824) 1982 and 1988 5A-4
Table 5A-3 Production, Capacity and Capacity Utilization by
Chemical for Plastics and Resins (SIC 2821) and
Synthetic Fibers (SIC 2824) 1982 and 1988 5A-5
Table 5A-4 International Trade Situation by Chemical for
Plastics and Resins (SIC 2821) and Synthetic
Fibers (SIC 2824) 1982 and 1988 5A-6
Table 5A-5 Synthetic Fibers Baseline 5A-7
Table 5A-6 Major Subgroups of Miscellaneous End-Use Chemicals
and Chemical Products (2969-6) 5A-9
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LIST OF TABLES
(continued)
Page
Table 5A-7 Miscellaneous End-Use Chemicals Real Growth,
1982-1988 (2S69-6) 5A-10
Table 5A-8 Cellulose, Acetate Real Growth, 1982-1988
(2869-6) 3A-11
Table 5A-9 Plasticizers Real Growth, 1982-1988 (2869-3) 5A-12
Table 5A-10 Cellulosic Fibers Real Growth, 1982-1988
(SIC 2823) 5A-14
Table 5A-U Dyes Real Growth, 1982-1988 (2865-2) 5A-15
Table 5A-12 Organic Pigments Real Growth, 1982-1988
(2965-3) 5A-16
Table 5A-13 Rubber Processing Real Growth, 1982-1988
(2869-3) 5A-18
Table 5A-14 Flavor and Perfume Materials Real Growth,
1982-1988(2869-3) 5A-19
Table 5A-15 Miscellaneous Cyclic and Acyclic Chemicals
Baseline (2869-7) 5A-20
Table 5A-16 Price, Production and Value of Production by
Product for Miscellaneous Cvclic and Acylic
Chemicals (SIC 2869-7) 1982 and 1988 5A-20a
Table 5A-17 Low Growth Miscellaneous Cyclic and Acylic
Chemicals 5A-21
Table 5A-18 Capacity and Capacity Utilization for
Miscellaneous Cyclic and Acyclic Chemicals
(SIC 2869-7) 5A-23
Table 5A-19 Low Capacity Utilization Miscellaneous Cyclic
and Acyclic Chemicals (2869-7) 5A-24
Table 5A-20 International Trade Miscellaneous Cyclic and
Acyclic Chemicals (Millions of Lbs.) (2869-7) 5A-26
Table 5A-21 Cyclic Intermediates 5A-27
Table 5A-22 Price, Production and Value of Production by
Product for Cyclic Intermediates (SIC 2865-1)
1982 and 1988 5A-28
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LIST OF TABLES
(continued)
Page
Table 5A-23 Production, Capacity and Capacity Utilization
bv Product for Cvctic Intermediates (SIC 2865-1)
1982 and 1988 . 5A-30
Table 5A-24 Low-Capacity Utilization Cyclic Intermediates 5A-3L
Table 5A-25 International Trade Situation by Product tor
Cyclic Intermediates (SIC 2865-1) 1982 and 1988 5A-32
Table 6-1 Summary or Results: Direct Dischargers 6-2
Table 6-2 Summary of Cumulative Results: Direct
Dischargers 6-4
Table 6-3 Summary of Results: Indirect Dischargers 6-6
Table 6-4 Firm-Level Financial Impacts — Interest Coverage
and Liquidity 6-9
Table 6-5 Summary of Community Impacts 6-11
Table 6-6 Foreign Trade Sensitive Chemicals in SIC
Categories Covered by DRI 6-15
Table 6-7 Production of Loss Due to Plant and Product
Line Closures 6-16
Table 6-8 Trade Sensitive Chemicals as a Percent of
Total Production 6-18
Table 6-9 Foreign Trade Impacts Due to Plant and
Production Line Closures 6-19
Table 6-10 Dollar Loss in Exports Due to Plant and
Product Line Closures 6-21
Table 6-11 Compliance Capital Investment Costs as a
Percentage of Total Cost of Construction of
a "Typical" New Plant 6-23
Table 6-12 Total Social Cost 6-27
Table 6A-1 Summary of Cumulative Results: Direct
Dischargers 6A-2
Table 6A-2 Summary of Results: Indirect Dischargers 6A-3
Table 6B-1 Percent of Total Production Lost in Chemical
Groups Not Covered by DRI Import/Export
Projections 6B-2
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LIST OF TABLES
(continued)
Page
Table 6C-1 Decrease in NPV/Investment Due to Compliance
Costs: BAT I Using WACC 1 6C-2
Table 6C-2 Decrease in NPV/Investment Due to Compliance
Costs: BAT I Using Hurdle = WACC + 2% 6C-3
Table 6C-3 Decrease in NPV and NPV/Investment Due to
Compliance Costs: BAT IIA Using WACC 6C-4
Table 6C-
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•1.0 EXECUTIVE SUMMARY
This report identifies and analyzes the economic impacts that are likely to
result from water pollution control regulations on.the Organic Chemicals, Plastics and
Synthetic Fibers (OCPSF) Industry. The regulations include effluent limitations and
standards based on Best Practicable Technology Currently Available (BPT), Best
Available Technology Economically Achievable (BAT), New Source Performance
Standards (NSPS), and Pretreatment Standards for Existing and New Sources (PSES and
PSNS). The primary economic impact variables assessed in this study include the costs
of the contemplated regulations, and the potential for these regulations to cause plant
closures, unemployment, reductions in profitability, shifts in the balance of trade and
anticompetitive effects on small businesses and new facilities. This study does not
reflect the results of setting BAT equal to BPT for small plants. That issue is addressed
in the preamble to regulation and a separate Regulatory Flexibility Analysis included in
the rulemaking record.
I. I Industry Coverage
Five Standard Industrial Classification (SIC) groups are considered to comprise
the OCPSF industry: SIC 2821 (Plastics Materials and Resins), SIC 2823 (Cellulosic
Manmade Fibers), SIC 2824 Noncellulosic Organic Fibers, SIC 2865 (Cyclic Crudes and
Intermediates) and SIC 2869 (Industrial Organic Chemicals; not elsewhere classified). A
total of 940 plants have been identified as manufacturing within these groups.
1.2 The Economic Impact Assessment Methodology
The principal element of the assessment methodology is a plant-by-plant
impact analysis. The plant level analysis is important in its own right and also drives
the other components of the economic impact assessment. Plant and product line
closures are projected using a discounted cash flow approach. These closures result in
employment losses which serve as input to the community impact analysis and in
production losses which provide a basis to estimate shifts in the balance of trade.
Compliance costs at the plant level are also used to assess the impacts on firms'
financial viability and on potential OCPSF industry expansion.
The principal source of data at the plant level is the EPA survey of
manufacturers conducted in 1983-84 under Section 308 of the Clean Water Act. The
survey effort yielded data on plant production, shipments and employment. Other key
data sources used in the analysis include U.S. Government statistics on the industry
1-1
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(Department of Commerce, Bureau of Census, etc.), Data Resources, Inc. (DRD
macroeconomic and chemical industry forecasts, and financial data from Dun and
Bradstreet, Robert Morris Associates and Compustat Services.
The baseline year for the analysis is 1983. The industry's economic condition
is projected to 19SS using survey information from 1982 and forecasts from DRI. Other
financial parameters, drawn principally from Dun and Bradstreet, are also used to
establish the baseline conditions.
1.3 Industry Profile
The OCPSF industry produces thousands of products which range from crude
coal coking residues to highly refined synthetic fibers and resins. These products can be
divided into basic or intermediate chemicals and finished chemicals. Basic and
intermediate chemicals 4re used almost exclusively as feedstocks- for more refined
products while finished products undergo no further chemical processing. In some
cases, however, chemicals that are finished products in certain lines are intermediate
feedstocks for further processing in other lines.
Based on the §308 Survey data, 1982 OCPSF production totaled 185 billion
pounds with sales of just over $59 billion (1982 dollars). Some 181 thousand workers
were employed in the industry in 1982.
The industry includes both very large and relatively small plants. Plants with
over $50 million in annual sales account for 25 percent of the plants in the industry
while 29 percent of the plants have annual sales of less than $5 million. Smaller plants
tend to be concentrated in SICs 2821 and 2865 which have median plant-level
production values of less than $20 million while plants in SIC 2823 (cellulose fibers)
have a median plant level production value of over $120 million.
Plant ownership is equally split among public and private firms. The majority
of plants are in SIC 2821 or 2869 which together account for 80 percent of plants in the
industry and 88 percent of sales; SIC 2865 accounts for a further 11 percent of the
plants and 4 percent of OCPSF industry sales.
1A Impact Analysis Results
Economic impacts are estimated for those plants which will incur costs and for
which sufficient economic data are available. Out of the 940 plants estimated to be the
industry universe, 654 plants are expected to incur costs. Impacts are evaluated for 645
plants and six options. (See Table l-l.)
1-2
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As shown in Table l-l, key impact measures include plant and product line
closures, associated employment losses and profitability or sales impacts. Note that all
costs are presented in 1982 dollars and the BAT costs and impacts in Table l-l are
incremental to BPT. Cumulative (to BPT 1) costs and impacts are shown in Tabie 1-2.
Costs and impacts presented herein do not reflect reduced standards for small direct
discharging plants.
Under BPT I, some 2\k plants are expected to incur costs. Capital costs are
projected to total $193 million (19S2 dollars)/ while annual operating and maincenan.ee
costs are estimated at $39 million. Total annualized costs are expected to run
approximately $68.5 million. No plant or product line closures are projected under this
option. However, it is expected that 8 plants will sustain significant profit or sales
impacts.
Some 289 plants are expected to incur costs to meet priority pollutant
limitations under the BAT options. Compliance with BAT IIA will require an
incremental capital investment of about $333 million. Operating and maintenance costs
are estimated to be about $231 million, for an annualized compliance cost of
approximately $281 million. These costs are expected to result in 12 plant and 12
product line closures and a loss of 1,743 jobs. An additional 21 plants are expected to
sustain significant profit or sales impacts.
Costs are somewhat lower and impacts less severe under BAT IIB. Incremental
capital investment is expected to total $323 million — approximately $10 million less
than BAT IIA. Operating and maintenance costs are estimated at $157 million per year
-- $73 million, or almost 30 percent less than BAT IIA. As a result, the total annualized
compliance costs of $206 million for BAT IIB are about 26 percent lower than those
associated with BAT IIA. Eleven plant and nine product line closures are expected as a
result of compliance with BAT IIB. The associated employment loss is estimated at
1,359 jobs — about 22 percent fewer than BAT IIA. In addition to the closures, 17 more
plants are expected to incur significant profit or sales impacts.
*Note that costs included in the Preamble are presented in 1986 dollars. They
were converted from 1982 dollars using a multiplier of 1.118 derived from construction
cost indices published in the Engineering News Record.
-------
Table 1-2
SUM4ARY OF CIMULATIVE RESULTS: DIRECT DISCHARGERS*
(1982 Million Dollars)"
REGULATORY OPTION
BAT I IA BAT MB
NUMBER OF PLANTS ANALYZED 283 283
NUMBER Of PLANTS INCURRING COSTS 289 289
COSTS Of COMPLIANCE
CAPITAL INVESTMENT 526.24 515.77
OPERATING AND MAINTENANCE 269.90 196.77
TOTAL ANNUAL COMPLIANCE COST 349.38 274.61
PLANT CLOSURES 12 II
PRODUCT LINE CLOSURES 12 9
PROFIT OR SALES IMPACTS*** 29 25
EMPLOYMENT REDUCTION 1,743 1,359
•Cost and impacts do not reflect-the results of setting
BAT equal to BPT for small direct dischargers.
•"Note that costs included in the Preamble are presented
in 1986 dollars. They were converted frcm 1982 dollars
using a multiplier of I.I 18 derived from construction
cost indices published by the Engineering News Record.
Costs and Impacts are cumulative to BPT I.
***Non-closures only. A significant sales impact Is defined
as annualized treatment costs In excess of 5 percent of
sales. A significant profit Impact Is said to occur
when a plant's past tax profit to sales ratio falls Into
the lowest dec! le for a given SIC code and size category.
-------
Table 1-2 presents cumulative (to BPT I) costs and impacts for the BAT
options. Since there were no plant or product line closures under BPT I, the number of
projected closures and the resulting job losses are identical to the incremental
estimates presented in Table 1-1 and discussed above. Compliance cost estimates and
the number of non-closure plants expected to sustain sales or profit impacts are simply
the sum of the BPT [ figure and the relevant incremental BAT option estimate.
Some 365 plants are expected to incur costs associated with PSES options; 362
of these were included in the analysis. As with the BAT options, the costs, and
associated impacts of the various options vary — total annualized costs range from $ IS3
million under PSES IVB to $31*2 million under PSES IVA. Similarly, closures range from
52 (PSES IVB) to 67 (PSES IVA).
Under PSES IVA, capital investment is expected to total over $318 million,
while annual operating and maintenance costs are estimated at approximately $263
million. This results in a total annualized compliance cost of about $312 million.
Thirty-seven plants are projected to close completely; another 30 are expected to shut
down their organic chemicals and plastics product lines. The reduction in employment
associated with these closures is estimated at 3,736 jobs. An additional 86 plants are
expected to sustain profit or sales impacts, bringing the total number of significantly
impacted plants to 153, or 42 percent of the indirect discharging plants included in the
analysis.
Both costs and impacts are reduced considerably under PSES IVB. Capital
investment required to comply with this option is estimated at $261 million — almost 20
percent less than PSES IVA. Annual operating and maintenance costs, expected to total
$143 million, are close to 50 percent lower. Thus, total annualized compliance costs --
about $183 million per year — are 41 percent less than those associated with PSES
IVA. As would be expected, economic impacts are considerably less severe. Some 25
plant and 27 product line closures are projected, with a resultant employment loss of
2,190 jobs. This represents a reduction of about 40 percent, as compared with
employment impacts under PSES IVA.
Under PSES VII, capital and annual operating and maintenance costs are
estimated at $319 million and $152 million, respectively. Total annualized compliance
costs are expected to total $201 million per year — about $20 million more than PSES
IVB. Impacts are slightly greater than those associated with PSES IVB. Two additional
plants are projected to close, raising the employment loss to 2,561 jobs — 371 more
than PSES IVB.
1-6
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1.4.2 Firm Impacts
One firm may have difficulty in financing, pollution control expenditures
associated with either BAT ilA or BAT [IB. In addition, four to six companies may
experience liquidity problems due to the need to comply with PSES guidelines. It should
be noted that firm level impacts are not likely to increase plant closures since a
profitable plant belonging to an ailing firm would probably be sold as an operating
facility if its parent firm were unable to finance the pollution control expenditure.
1.4.3 Community Impacts
No significant community impacts are expected under BPT I. Under BAT IIA,
three communities are projected to experience impacts; this number falls to two for
BAT IIB. One community is likely to sustain a significant impact under each of the
three PSES options.
1.4.4 Balance of Trade Impacts
The total effect on the U.S. balance of trade rs expected to be relatively
small. Even the most significant effects, which would occur under PSES IVA, represent
less than a tenth of a percent of U.S. exports.
1.4.5 New Sources Impacts
The costs associated with the regulations are not expected to pose significant
barriers to entry or to expansion of existing plants. On average, compliance capital
costs are projected to increase plant construction costs by less than 3 percent. Costs of
this magnitude are unlikely to effect the decision to site a new OCPSF plant.
1.5 Limits of Analysis
The methodology, and hence, the analysis are necessary limited by the
available data. The three major methodological limitations are: I) ability to project
accurately the 1988 baseline; 2) the recognition that a decision to close a plant is a
complex decision process which can not be modeled fully; and 3) that the no cost pass
through assumption yields conservative impact measures.
1-7
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1.6 Sensitivity Analysis
The impact results are relatively insensitive to changes in the weighted
average cost of capital, treatment cost estimates, and the no-cost pass through
assumption. This is particularly true for direct dischargers; the number of closures
increases or decreases by — at most -- three plants in response to variation in the above
parameters. Impacts on indirect dischargers are somewhat more sensitive; the number
of closures changes by 7 to 28 percent, depending upon the option and parameter
considered.
1-8
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2.0 INDUSTRY PROFILE
2.1 Overview
The Organic Chemicals, Plastics and Synthetic Fibers (OCPSF) industry
produces a broad range of products for use in the U.S. and abroad. Comprising some
3,000 production plants, the OCPSF industry produces approximately 25,000 different
products with both manufacturing and end-use applications. Total production volume of
the OCPSF industry in 1982 was 191.7 billion pounds, while total industry sales amounted
to 45 billion dollars. This value represented 3.7 percent of the total value of shipments
of all U.S. manufacturing industries.
This profile examines both the structure of the OCPSF industry and prevailing
market conditions for its products. These market factors influence the ability of the
industry to afford additional capital outlays for pollution control equipment as well as
operation and maintenance expenses. Included in this industry description are
subsections on major product groups and their end-uses, competitive structure of the
industry including concentration and integration, historical price and production
performance, employment, foreign trade, financial performance, and firm and plant
characteristics.
2.1.1 Definition of Industry Scope
For the purposes of this study, the Organic Chemicals Plastics and Synthetic
Fibers (OCPSF) industry is defined as consisting of those plants that produce products
classified in the following SIC groups:
SIC CODE PRODUCT
2821 Plastics, Synthetic Resins, Nonvuicanizable Elastomers
2823 Cellulose Man-Made Fibers
2324- Synthetic Organic Fibers, Except Cellulosic
2865 Cyclic Crudes, Dyes, Organic Pigments <3c Intermediates
2869 Industrial Organic Chemicals Not Elsewhere Classified
£
Much of the information presented in this industry profile is based on 1982
data, due largely to the infrequency of collection of comprehensive data on the
industry. The Agency is aware of industry trends since 1982; these are discussed in other
sections of the report, and have been factored into regulatory decisions. See, in
particular, Chapter 5.0, Baseline.
2-1
-------
¦The above SIC codes are classified as plastics or organic chemicals. Groupings were
made on the basis of product similarity.
TabLe 2-1
Assignment of OCPSF In-Scope SIC
Codes to 4-digit SIC Code and Product Tjrpe
4-Digit SIC Code
2821
Product.Type
PLast ics
2823
Plasc ics
2824
Plast ics
2865
Organic Chemicals
2869
Organic Chemicals
Within these overall classes, plants that produce organic chemical compounds
solely through the extraction of organic substances from natural materials—such as
plants and animals—or by fermentation processes are not included in this definition of
OCPSF industry scope even if classified in one of the above SIC groups. Organic
chemical products which generate wastewaters that are treated in combination with
petroleum refinery or pharmaceutical manufacturing wastewaters specifically regulated
under the Petrochemical Subcategory of the Petroleum Refining Point Source Category
(40 CFR 419, Subpart C) or the Chemical Synthesis Products Subcategory of the
Pharmeceuticals Manufacturing Point Source Category (40 CFR 439, Subpart C) are
considered to be non-OCPSF products for the purposes of this study.
2.2 Product Characteristics
The OCPSF industry produces thousands of products which range from crude
coal coking residues to highly refined synthetic fibers and resins. These products can be
grouped into two product types: I) basic and intermediate chemicals; and 2) finished
products. Basic and intermediate chemicals are used exclusively as feedstocks for more
refined chemical products. Finished products undergo no further chemical processing.
Table 2-2 presents production, sales, price and end-uses for the 12 principal
product groups which make up the OCPSF industry. Product groups were chosen to
2-2
-------
Table 2-2. U.S. Production, Sales Price and Uses of OCPSF Products - 1982
OCPSF Product Groups
Production
Sales
(Bl11 ion
lbs.)
Quantity
(Bl1 lion
Value
(Bl11 Ion
Unit Value
($ per pound)
Final Products or end-Uses
BASIC AND INTERMEDIATE CHEMICALS
Tars and Tar Crudes*
(4.003)
(2.093)
,(0.278*
(10.13)
Cy c11c In termed 1ates
37.637
16.193
5.831
10.36
Cheaical Intermediate.
Miscellaneous Cyclic and
AcyclIc Chemicals
80.494
34.647
10.604
SO. 29
Ctieaical Intermediate and solvents.
FINISHED CHEMICALS:
Dyes
0.222
0.214
0.685
$3.20
Coloring of textiles, natural and synthetic fibers, fabrics and
other materials.
Organic Pigments
0.071
0.059
0.374
$6.38
Coloring of printing inks, paints and plastics.
Flavor and Perfume Materials
0.156
0.113
0.284
*2.51
Food and beverage flavors, perfumery, cosmetics and toiletries.
Plastics and Resin Materials
38.313
32.002
15.313
10.48
BuiIdlng Materials (pipes, siding. Insulation), packaging (wrap-
pings, bottles, cartons), automotive applications.
Rubber Processing Chemicals
0.232
0.154
0.264
$1.72
Used In manufacturing natural and synthetic rubber.
Plastlcizers
1.411
1.316
0.741
$0.56
Used in manufacturing plastic and synthetic rubber products to im-
prove workability during fabrication or alter properties of final
products.
Synthetic Fibers**
6.442
6.780
7.160
$1.06
Hooe furnishings, reinforced plastics and electrical products,
tires, and apparel.
Cellulosic Fibers •*
0.584
0.588
0.972
$1.65
Drapery and upholstery, medical and sanitary products, apparel,
and other consumer products.
Miscellaneous End-Use Chemi-
cals and Chemical Products
22.146"*
3.278
2.804
$0.86
Polyaers for synthetic and eellulosic fibers, gasoline and lube oil
additives, enzyaes, chelating agents, paint driers, photographic
chemicals, tanning materials, solvents, chemical Intermediates.
TOTAL OCPSF INDUSTRY
191.709
97.437
45.310
$0.47
Source: ITC, Synthetic Organic Chemicals: Prices and Production'for 1982. Publication No. 1422, except where noted.
• The data for tar crudes are not available for 1982. These figures represent only the data for coal tar.
** These data are from Text11e Organon, January 1984, and U.S. Department of Cotnnerce, 1983 U.S. Industrial Outlook.
*** Includes 12.7 billion pounds of miscellaneous unspecified chemicals of which only 0.1 billion were sold. This 1982 figure may be a reporting error
since in 1981 this miscellaneous group Mas about 10 billion pounds.
-------
[natch the United States International Trade Commission (ITC) classification system in
order that ITC price, production and sales data could be used. The twelve product groups
are: tar and tar crudes; cyclic intermediates; miscellaneous cyclic and acyclic
chemicals; dyes; organic pigments; flavor and perfume materials; plastics and resin
materials; rubber processing chemicals; plasticisers; synthetic fibers; cellulosic fibers;
and miscellaneous end-use chemicals and chemical products. In 1982, production levels
ranged from 71 million pounds for organic pigments to 80,
-------
0R1
CHEMICAL SERVICE
Figure 2-1. OCPST Industry Production Paths
Source: Data Resources Inc.,
Ctemical Service, 1984
2-5
-------
naphthalene and other aromatic chemical products. Basic chemicals derived from
petroleum and natural gas are grouped in SIC 2911 and are not covered by this regulation.
Intermediate chemicals covered by this regulation include cyclic intermediates
(SIC 28651) and miscellaneous cyclic and acyclic chemicals (SIC 2S697). Figure 2-1
identifies the major intermediate chemicals and shows their role in the production path
from basic chemicals to finished products. The six largest cyclic intermediates by
volume are styrene, ethylbenzene, cumene, p-xylene, aniline and phenol. The ten largest
acyclic intermediates by volume are acetic acid, acrylonitrile, dimethyl terephthalate,
ethylene oxide, ethylene glycol, ethylene dichloride, formaldehyde, methanol,
terephthalic acid and vinyl chloride. In 1982, over two billion pounds of each of these 16
chemicals were produced in the U.S.
Although intermediates are principally used in chemical synthesis, some of the
chemicals in the two intermediate product groups are used as both intermediates and as
finished products. For example, ethylene glycol is used both in the synthesis of polyester
fiber and film and as a'finished product in antifreeze compositions. Many solvents are
used as both finished products and in the synthesis of other chemicals.
2.2.2 Finished Chemicals
Finished products undergo no further chemical synthesis. The nine major groups
of OCPSF finished products are: organic dyes, pigments, plastics and synthetic resins,
flavor and fragrance chemicals, rubber processing chemicals, plasticisers, synthetic
fibers, cellulosic fibers, and other miscellaneous finished products.
Dyes, classified in SIC 28652, are organic chemicals used to impart color to
fabric or other materials. They are generally soluble in water or other solvents. There
are currently over 1500 dyes produced domestically. These dyes are primarily used in the
textile industry, which utilizes 76 percent of total production, and are commonly known
by the textile industry's classification system. The nine dye groups in the system are
acid, azoic, basic, direct, disperse, mordant,. reactive, sulfur and vat. The most
important of these are the vat dyes. Other uses for dyes are in the paper industry (20
percent), plastics, leather, food, gasoline, and in the production of organic pigments. The
major dyes employed in non-textile uses are optical brighteners, solvent dyes, and food,
drug and cosmetic colors.
Organic pigments, lakes and toners (SIC 28653) are derived from dyes or from
intermediate chemicals which resemble dyes. The most important groups are Benzidene
2-6
-------
yellows, which are related to the azo dyes, and phthalocyanines, which are available in
blue and green. Other important organic pigments are quinacridone oranges and reds, vat
pigments, dioxazines, and tetrachloroisoi'ndolinones. The primary end-uses for organic
pigments are in printing inks (^5 percent), paints (35 percent) and plastics (10 percent).
The flavors and perfumes industry (SIC 2S693) accounts for only a very small
part of the industry's total production (less than a tenth of a percent), but is extremely
profitable. The industry is involved in the production of flavors and fragrances, flavor
enhancers and synthetic sweeteners; flavors and fragrances account for the bulk of both
production and sales. Companies in this industry group may be involved in: (1) synthesis
of aroma or flavor chemicals; (2) production or purchase of natural oils and other pro-
ducts; and (3) blending the synthetic and the natural substances to achieve a desired
flavor or aroma.
The primary end-use for flavors is soft drinks, with 60 percent of the total
volume going to that market. About two thirds of the perfumes produced are used in
cosmetics and toiletries and the remaining third is used in scented candles, household
cleansers and industrial deodorizers. Monosodium glutamate (MSG) is the only flavor
enhancer of economic significance with sales of $33 million in 1979. Since cyclamates-
were removed from the market in 1969, the only commercially important synthetic
sweeteners have been Saccharin and Aspartame (Nutrasweet^). In 1979, sales of
saccharin were $27 million. The distribution of flavor and perfume materials by end-use
is shown in Table 2-3.
2-7
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Table 2-3
End-Use of Flavors, Perfumes and Related Products (1979)
Merchant Sales
Percent
End-Use Product
(miLLion 1979$)
Flavors and fragrances
830
93
Flavor enhancers (MSG)
33
A
Synthetic sweeteners
27
3
Total
890
100
Source: Kline Guide to the Chemical Industry, 1980.
Plastics materials and synthetic resins (SIC 2821) make up a large and profitable
part of the chemical industry. While the terms are often used interchangeably, plastics
can be formed into solid shapes with good mechanical properties while resins are used in
coatings, adhesives and other uses where binding properties are needed. The polymers
used to make plastics are similar to those used for fibers and several of them are used in
the manufacture of both finished products.
Plastics and resins have many potential end-uses because of their mechanical
versatility. The increased use of these products as replacements for natural materials
such as metals, glass, wood, and paper has contributed to the growth of the industry.
While there are about 40 different plastic materials with commercial applications, four
major types—polyethylenes, vinyls, styrenes, and polypropylene—accounted for 74
percent of total production in 1982.
Table 2-4 shows both the quantities and percentages of plastic consumption by
end-use and the quantity and percentage of plastic type utilized for a particular end-
use. For example,- of the 10.017 billion pounds of plastics consumed in 1979 for
packaging polyethylene comprised 50 percent, vinyl-5 percent, styrene-14 percent, and
2-8
-------
polvpropylene-6 percent. Table 2-4 also shows that of the 12.841 billion pounds of
polyethylene consumed, 39 percent was used for packaging, six percent for construction,
36 percent for housewares and other domestic uses, and 13 percent was exported.
Rubber-processing chemicals (SIC 2S693) are. used to facilitate rubber pro-
cessing, and improve the quality of finished rubber products. The major types of rubber
processing chemicals are antioxidants—which retard the deterioration of rubber by
oxygen—and accelerators, which are used to increase the rate of vulcanization. Tires
and related products consumed almost 65 percent of ail rubber processing chemical
production, followed by mechanical goods (IS.5 percent), footwear (six percent), latex
foam products (3.5 percent), and wire and cable (one percent).
Plasticizers (SIC 28693) are organic chemicals that are mixed with vinyl or
other polymers to alter the latter's qualities, mainly by increasing flexibility. The major
plasticizers are the phthalates (with over 50 percent of total plasticizer production) and
phosphate plasticizers (roughly eight percent of total production). Approximately 85
percent of all plasticizers are used in plastics. PVC alone accounts for about two-thirds
of U.S. plasticizer consumption. The remainder are utilized in rubber compounding and
in non-plasticizer applications.
Synthetic fibers (SIC 2823) are produced by extruding filiment from a polymer
melt or solution through small orifices. Fiber characteristics vary with the different
polymers used and with the size and shape of the filament. The major synthetic fibers are
polyester, nylon, acrylics and polypropylene.
In 1979, polyester made up almost 45 percent of total manmade fibers pro-
duction, while nylon made up 29 percent of production. Celluiosic fibers (SIC 2S24) are
fibers produced from regenerated cellulose derived from high purity wood pulp or cotton
linters. The major celluiosic fibers are rayon and acetate. U.S. production of manmade
celluiosic and synthetic fibers in 1982 was approximately 7 billion pounds. Table 2-5
presents 1982 U.S. consumption of fibers by major end-uses.
Miscellaneous end-use chemicals and chemical products (SIC 28696) include a
number of different finished products classified as chelating agents, chemical indicators,
chemical reagents, enzymes, gasoline additives, lubricating oil and grease additives,
paint driers, photographic chemicals, polymers for fibers, water-soluble polymers,
synthetic tanning materials and textile chemicals.
2-9
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Table 2-4. Consuaption of Plastics by End Use - 1979
(billions of pounds)
Packaging
Construction
Resources
Exports
Other Uses
Total
Plastic
Type
Quantity
Consuned
Percent
Consumed
For This
End-Use
Quanti ty
Consuned
Percent
Consumed
For This
End-Use
Quant 1ty
Consumed
Percent
Consuned
For This
End-Use
Quantity
Consumed
Percent
Consumed
For This
End-Use
Quant i ty
Consumed
Percent
Consumed
For This
End Use
Quant I ty
Consumed
Polyethylene
5,049
39
731
6
4,592
36
1,641
13
828
6
12,841
Vinyl
530
7
3,238
42
1,956
26
492
6
1,447
19
7,663
Styrene"
1,395
22
621
10
2.605
42
397
6
1,447
19
6,228
Polypropylene
625
16
24
1
1,893
48
802
20
638
16
3,982
Other Plastics
2,418
15
3,647
23
4,303
27
1,143
7
4,162
27
15,673
TOTAL
10,017
22
8,261
18
15,349
33
4,475
10
8,285
18
46,387
Source: Kline Guide to the Chealcal Industry. 1980.
* Figures for styrene include: AerylontItriIe-butadiene-styrene (ABS; styrene-acryIon 1trlle (SAN); straight polystyrene; and other styrenes.
-------
TabLe 2-5
Uses of Manmade CeLLulosic and Synthetic Fibers - 1982
Percent of 1982
U.S. Consumption
Industrial and Other Consumer Goods Ceiluiosic Synthetic':
Reinforced plastics and electrical 0.0 9.0
Tires 2.4 5.1
Medical, surgical and sanitary '20.1 1.8
- Other (e.g., rope, coated fabrics) 14.4 13.2
Home Furnishings
Carpet, rugs 0.1 23.6
Drapery and upholstery 13.9 2.4
Other (e.g., curtains, blankets) 5.6 6.6
Apparel
Bottom weight fabrics 5.5 11.4
Topweight fabrics 10.2 5.6
Fabrics for lining 13.4 0.4
Other apparel 10.8 13.1
Export 3.6 2.8
Source: Textile Organon, September/October 1983.
"'Includes glass fibers which are not separable from available data.
2.3 Market Structure
The market structure of the OCPSF industry is discussed according to:
1) industry concentration;
2) integration and diversification;
3) product differentiation and competition;
4) product substitution, demand elasticity and profitability; and
5) barriers to entry into the industry.
2.3.1 Industry Concentration
Sales of OCPSF products are generally concentrated among a small number of
firms. Concentration ratios associated with the twelve principle product groups are
2-11
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presented in Table 2-6. Concentration varies among the different product groups, with
the greatest levels found in fiber and tar crude manufacturers. The four largest
companies producing tar crudes account for 97 percent of the total value of shipments,
while the eight largest cellulosic fiber producers account for 100 percent of ceilulosic
fiber shipments. By contrast, plastics and resin materials have the lowest level of
concentration with the four and eight largest companies accounting for only and 3S
percent, respectively, of the total value of shipments.
Table 2-6
Industry Concentration Ratios
Percont of Value of Product Shipments
SIC Class Associated Product Groups(s)
4 Largest
Companies
8 Largest
Companies
20 Largest
Comoan i as
2821
2823
2824
28651
28652
28653
28655
28693
28696
28697
Plastics and Resin Materials 24
Cellulosic F ibers NA
Non-Cellulosic Synthetic
Fibers 76
Cyclic Intermediates 44
~yes 43
Organic Pigments 48
Tar Crudes 97
Plastici sers,
Rubber Processing Chemicals.
Flavor and Perfume
Materials 31
Miscellaneous End Use
Chemicals and Chemical
Products 41
Miscellaneous Cyclic and
Acyclic Chemicals 39
38
100
90
59
63
71
99
46
62
55
61
100
99
81
93
94
100
75
90
75
Source: U.S. Department of Commerce, Census of Manufacturers, 1977.
2.3.2 Integration and Diversification
Vertical integration and product diversification are both common in the OCPSF
industry. The wide use of chemicals and chemical products in U.S. manufacturing has
encouraged many different types of companies to integrate backward to the manufacture
of basic chemicals. Furthermore, since chemical industry feedstocks are typically made
from oil industry by-products, there is a strong incentive for these kinds of companies to
integrate forward to the manufacture of basic chemicals. By integrating vertically, a
2-12
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plant can reduce transport, marketing and handling costs. Indeed, virtually all producers
of basic chemicals either have backward integration to oil refining operations, or forward
integration to intermediate chemical manufacturing operations at the same site. Most
intermediate and finished product manufacturers also produce associated basic,
intermediate or end-use products on site. According to the 1980 Kline Guide to the
Chemical Industry, only 11 of the 100 leading U.S. chemical manufacturers produced
chemicals exclusively, and only 20 generated over 75 percent of their revenues from
chemical products.
The extent to which the OCPSF industry is vertically integrated and/or di-
versified is demonstrated by the relatively low coverage and specialization ratios
reported by the Census of Manufacturers for the five major 4-digit SIC groups affected
by this regulation. The coverage ratio is the proportion of the total primary product that
is produced by establishments classified in an SIC group to the total production of that
product by all SIC groups. The specialization ratio is the ratio of the primary production
at an establishment to the total production at that establishment. Coverage and
specialization ratios are shown in Table 2-7. It can be seen from the table, that SIC
group 2865—tar crudes, cyclic intermediates, dyes and organic pigments—had a lower
specialization ratio than the other four SIC groups indicating a higher level of integration
and diversification. By contrast, the establishments producing non-ceilulosic fibers (SIC
2824) and plastics and resins (SIC 2821) were less highly integrated and diversified than
the other SIC groups—as shown by their higher coverage and specialization ratios.
Coverage and specialization ratios were also computed from §308 Survey data
and are compared to the Census of Manufactures' ratios in Table 2-7. The chief
difference between the two sets of ratios is that the Census of Manufactures figures
were based on firm-level data whereas the §308 Survey values were based on plant-level
data.
2.3.3 Product Differentiation and Competition
The Kline Guide to the Chemical Industry divides the U.S. chemical industry
into four market classes: true commodities, pseudo commodities, fine chemicals and
specialty chemicals. These market classes are based on production volume and product
differentiation, as illustrated in Table 2-8.
Table 2-9 associates these market classes with each of the twelve OCPSF
product groups.
2-13
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Table 2-7
Industry Coverage and Specialization Ratios
Coverage Ratio
SIC Associated 1982 Census 1982
CLass Product Groups of Manufactures §308 Survey
Specialization Ratio
1982 Census 1982
of Manufactures §308 Survey
87
81
68
82
54
2821 Plastics and Resin 77 74
Materials
2823 Cellulosic Manmade - 73
Fibers
2824 Non-Cellulosic
Synthetic Fibers 85 93
2865 Tar Crudes, Cyclic
Intermediates, Dyes 76 75
and Organic Pigments
2869 Plasticisers, Rubber 74 91
Processing Chemicals,
Flavor and Perfume
Materials, Miscellaneous
End use Chemicals and
Chemical Products, and
Miscellaneous Cyclic and
Acyclic Chemicals
Source: U.S. Department of Commerce, Census of Manufactures, 1982, and §308 Survey.
31
81
51
62
Production Level
Table 2-8
Chemical Industry Market Characteristics
Undifferentiated
Product Type
Differentiated
High VoLume
Low Volume
Chemicals
True Commodities
Fine Chemicals
Pseudo Commodities
Speciality
Source: Kline Guide to the Chemical Industry, 1980.
2-14
-------
Table 2-9
Market Classes of OCPSF Product Croups
Product Groups
Market CLass(es)
1.
Tar and Tar Crudes
Commodity, Fine
2.
Cyclic Intermediates
Commodity, Fine
3.
Misc. Cyclic & Acyclic Chemicals
Commodity, Fine
4.
Dyes
Specialty
5.
Organic Pigments
Specialty
6.
Flavor and Perfume Materials
Fine
7.
Plastics and Resin Materials
Pseudo Commodity, Specialty
8.
Rubber Processing Chemicals
Speciality
9.
Plasticisers
Speciality
10.
Synthetic Fibers
Pseudo Commodity
11.
Cellulosic Fibers
Pseudo Commodity
12.
Miscellaneous End-Use
Chemicals and Chemicals Products
Fine, Speciality
Sources: Kline Guide to the Chemical Industry, 1980, and EPA estimates.
Most basic chemicals are commodity products. Produced in high volumes, com-
modities are undifferentiated products which compete based on price. By vertically
integrating production facilities, producers can reduce transportation and sales costs,
thereby enhancing their competitive position. For example, oil companies may find that
their captive source of petroleum feedstock gives them a competitive advantage in the
production of basic and intermediate organic chemicals.
Pseudo commodities are high volume products which have some degree of pro-
duct differentiation. This group includes plastics and resin products, as well as fibers and
some pigments. These products are price competitive, although competition is tempered
by the differential performance of products provided by different producers.
The opposite situation exists for specialty products. Speciality products are
produced in small volumes, usually by single producers and for a single application. While
they may compete with other specialty chemicals, the competition is based largely on
performance rather than price. This portion of the industry generally is not vertically
integrated.
2-15
-------
Fine chemicals are undifferentiated and produced in small quantities. This
group includes low volume intermediates and flavor and perfume materials. Like
commodities, these products compete primarily on the basis of price.
2.3.4 Product Substitution, Research and Development, Demand Elasticity
and Profitability
The highest degree of product substitution in the OCPSF industry is among
speciality chemicals. These substitutions are usually made to improve performance
rather than to reduce costs. Pseudo commodities have somewhat less substitution and
undifferentiated chemicals have less yet.
Research and development of both products and production processes plays an
important role in OCPSF industry growth. Products are developed to meet new markets
and to compete with existing products for established markets. Manufacturers of
undifferentiated products use research and development to refine production processes
and reduce costs.
The elasticity of demand for OCPSF products is a measure of consumer sensi-
tivity to price changes. Demand elasticity tends to be low for most OCPSF products
since they generally make up only a small part of overall final consumer product prices.
Products that compete on performance rather than on price show further insensitivity to
price change. Despite the low product-level elasticity of demand in some segments, the
industry is highly competitive. Increasing foreign competition, and increasing confidence
in outside sourcing means that increased costs cannot be easily passed on for many
undifferentiated chemicals. Elasticity of demand as seen by domestic plants is relatively
high.
Profitability tends to be highest for producers of differentiated chemicals.
Since sales of these products are influenced more by performance than by price, prices
can be set high enough to ensure healthy profit margins. Profits are lowest for
undifferentiated, high volume chemicals. Pseudo commodities exhibit characteristics of
both the true commodities and speciality products. Their profitability, consequently,'
tends to lie between these two classes.
2.3.5 Barriers to Entry
New companies may be barred from entering high volume sectors of the OCPSF
industries due to the large capital investments necessary. Scale economies and the
nature of price competition in these sectors make small plants unprofitable. For
2-16
-------
example, a plant seeking to produce vinyl chloride would need an annual capacity of '400
million pounds per year and require over 175 million dollars of fixed capital in order to be
competitive. In addition, the plant might be at a disadvantage if it lacked a captive
supply of ethylene or a captive use for the vinyl chloride.
Since the disincentive effect of these barriers is smaller than the advantages of
having access to inexpensive petroleum and natural gas feedstocks, these barriers have
not prevented several petroleum producing countries from constructing world scale
petrochemical facilities.- In the past few years OPEC countries and Mexico and Canada
have acted to enter the commodity chemicals business. Their access to capital and low
cost basic feedstocks (primarily natural gas) has allowed them to compete successfully.
Since fine chemicals and specialty chemicals both require smaller capital
investments and compete on product performance rather than price, these sectors
present fewer barriers to entry.
2A Industry Performance and the Business Cycle
2AA Historical Production and Comparison with Total Manufacturing
OCPSF production for 1975 to 1982 is shown in Table 2-10. Industrywide pro-
duction, which grew at an average annual rate of 3.7 percent over the entire period, rose
to a peak in 1979, falling thereafter. Prior to the mid-1970s, production grew more
rapidly than the U.S. economy. Oil price increases, international competition and a
major economic recession have since slowed this rate of growth. OCPSF industries have
grown recently at a rate closer to that of the U.S. economy. Flavor and perfume
chemicals and plastics and resins have shown the strongest growth over the 7-year
period; both having had an average annual production increase of about 6.4 percent. Coal
tar, rubber processing chemicals and cellulosic fibers showned the slowest growth. Coal
tar underwent an average annual production decrease of 6.6 percent, primarily because
of production decreases in the U.S. steel industry of which coal/tar is a by-product.
Rubber processing chemicals and cellulosic fibers also had average annual production
decreases.
Figures 2-2(a-f) present total value of shipments data from 1972 to 1982 for the
five OCPSF SIC groups. It can be seen from the figures that shipments increased for
each SIC group from 1972 to 1981, falling sharply in 1982.
2-17
-------
Table 2-10
Production Trends by OCPSF Product Group, 1975-1982
(Hill ions of Pounds)
Average
Annua I
Change
Product Group
| 1975
1 '976 |
'977
1978
1979
| 1980 |
1981 j
1982
(Dercenr)
1 . Tar and
Tar Crudes*
13,252
(6455)
13,546
(6364)
(5929)
(5405)
(5896)
(4366)
(4,290)
(4003)
(-6.50)
2. Cycl ic
1ntermed i ates
31 ,412
40,535
44,176
45,808
49,642
45,070
45,323
37,637
2.62
3. Miscellaneous
Cycl ic and
Acyc I i c Chem i ca1s
77,850**
82,739
86,302
90,804
97,583
93,326
93,922
?0 ,944
0.56
4. Dyes
206
2 56
264
251
266
245
230
222
I .59
5. Organic Pigments
50
68
69
77
88
69
76
71 ¦
5.14
6. Flavor and
Perfume Chemicals
101
129
150
189
195
175
165
156
6.41
7. Plastics and
Resi ns
24,868
29,680
34,623
38,878
41,871
38,186
10,601
38,313
5.37
8. Rubber Processing
Chemica1s
279
384
382
366
395
291
280
232
-2.60
9. Plasticisers
I ,352
1 ,587
1 ,792
2,096
2,133
1 ,784
1 ,866
1,411
0.61
10. Synthetic
F i bers***
5,875
6,615
7,312
7,768
8,418
7,874
7,982
6,442
1 .32
11. Ce11uIos i c
F i bers***
749
841
888
905
930
806
770
. 584
-3.49
12. Miscellaneous
End-Use Chemicals
and Chemical
Products
7,689
8,204
9,572
10,394
10,642
10,281
22,145
5.98****
Total***** |
149,197
176,887 |
190,091
202,119
217,811
CO
o
CM
205,736 |
191,709
| 3.65
Source: ITC, Synthetic Organic
Chemi cals
U.S. Production and Sales, except
as noted
* Data for the entire tar and tar crudes category are available only for 1975 and 1976. Data for
the tar portion of this category are available for other years and are shown in parentheses.
** This value includes miscellaneous end use chemicals and chemical products production.
*** From Texti le Orqanon, January 1984.
*•** This is the average annual percent change from 1976 to 1981. The 1982 production figure was not
used due to a possible reporting error.
total includes tar production bqt excludes production of tar crudes.
2=-18
-------
Figure. 2-2a
P
5
2S
10
VALUE UF SHIPMENTS
1573 5974 1975 1376 1377
VEAR
4 I « AAA « AA •
1 yy o iwtr ivou 1901
XSIC 2869
O SIC 2821
'O SIC 2824
^ SIC 2865
-TSIC 2823
Source: U.S. Department of Commerce, Census of Manufacturers.
2-19
-------
Fiaure 2-2b
SIC 2B69
VALUE OF SHIPMENTS
(billions of 1982 dollars)
/ l\
y ' \
J/
/
i y
i / i
T7 1
~7~
S
-r
A
—f t~
/
JA
IVU IV/J
IW/* IV/O
iy/Q iy//
ivo imu ivoi
YtAft
Source: U.S. Department of Commerce, Census of Manufacturers.
2-20
-------
Figure 2-2c
SIC 2821
VALUE OF SHIPMENTS
(billions of 1982 dollars)
1
1
.
! |
)
1
1
1 / 1 ""sii
1 / 1 T
1/ 1 1-
1
1
I !
1
1
1
/
/
/
1 1 1
1
1
/
/
1 1 1
1
1
1
A
/
y
1 1 1
i i i
1
1
A
/
J
i 1 1
1 1 1
1
1
1
<
/'
/
r
1 I 1
i i t
1
1
/
/
1 ! i
1 1 t
1
t
1
I
/
k.
/
/
u
1 1 (
1 I :
1 1 I
1
1
/
/
¦
1 1 1
1 1 1
1
1 Jk
/
B
1 ! 1
1 1 l
1
I 1 f
1 t 1
1 1 1
1372 1973 *974 1375 1376 5377 1378 1373 1330 1981 1382
yEAw
Source: U.S. Department of Commerce, Census of Manufacturers¦
2-21
-------
Figure 2-26.
SIC 2824
P
5
Id
?
/
/
/
df
VALUE UK SHIPMENTS
(billions of 1982 dollars)
/
/
/
-if-
/
/
/
JC
I
di
/
/
\
/
I W/9 l WO
I V/ W I vou
\
to
YkAH
Source: U.S. Department of Commerce. Census of Manufacturers.
2-22
-------
Figure 2-2e
SIC 2865
y»
5
2 -»*-
valuE Ok shipments
(billions of 1982 dollars)
A
J-
/
I /
1/
' I
1
/
/
A
/
/
/
I
•L""'
it
J 573
137 E
YEAR
Source: U.S. Department of Commerce, f>nms of Manufacturers.
2-23
-------
Figure 2-2f
SIC 2823
VALUK OF shipments
z
UJ
1.3
1.2
0.9
o.s
o.fi
4-
(billions of 1982 dollars)
I /
I /
I /
1/
*-r-
J/
/T
/ I
I /
I /
ML
I
Source: U.S. Department of Commerce, Census of Manufacturers.
2-24
-------
Table 2-11 and Figure 2-3 present trends in the GNP, the Manufacturing Pro-
duction Index (MPI) and recent OCPSF production. It can be seen that annual changes in
recent OCPSF production have paralleled changes in both the MPI and the GNP.
2.2 Industry Performance Trends
Overall performance of the OCPSF industry was measured in terms of profit on
sales and on net worth. Historical trends in these measures are presented in Tables 2-12
and 2-13. Since most manufacturing companies are diversified into several industries,
profit records do not clearly reflect the profitability of discrete lines of business.
Robert Morris Associates examined available lines of business records to determine
profitability for SIC groups 282 and SIC 286. These data are reported as before-tax
profits and are used in the impact analysis.
Citibank provided aggregate profitability data for both the chemicals industries
and for ail U.S. manufacturing industries. Since these are after-tax profits they are not
directly comparable with the Robert Morris data, but they are presented here to provide
a reference point for chemical industry performance.
Although profitability in the OCPSF SIC groups 282 and 286 has varied with
production from year to year, the overall trend has been downward. This downward trend
was not apparent for aggregate chemical industry profitability, which has paralled
overall U.S. manufacturing profitability. Prior to 1980, the profit on sales performance
of the chemical industries was consistently better than average for all U.S.
manufacturing, reflecting its higher capital intensity. Profits on net worth, however,
have fluctuated about the U.S. average.
2.4.3 Price, Capacity Utilization and Capital Spending Trends
Price trends for the twelve OCPSF product groups are presented for the period
1975 to 1982 in Table 2-14. These constant dollar prices generally remained stable
throughout the period. Most prices rose slightly in 1979 then fell from 1980 to 1982.
1982 prices were equal to or lower than 1975 prices for all product groups except
cellulosic fibers, rubber processing chemicals and coal tar—the three groups with the
smallest production growth over this period. The sharpest price reductions between 1975
and 1982 were for dyes, organic pigments, flavor and perfume chemicals and
miscellaneous end-use chemicals. Each of these groups had average price reductions in
excess of 1.8 percent per year over the period.
2-25
-------
Year
I960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
197J
1974
1975
1976
1977
1978
1979
1980
1981
1982
Tabi e 2-11
OCPSF Production and U.S. Economic Trends
OCPSF
Change
GNP
Change
Manufactur i ng
Change
Product i on
in OCPSF
(biI I ions of
in GNP
Product ion
i n'MP 1
(biI I ion
Product i on
1972 doiIars)
(percent)
Index (MPI)
(percent)
pounds)
(percent)
737
2.2
.554
2.2
757
2.6
.656
0.3
800
5.8
.713
8.8
833
4.0
.758
6.3
876
5.3
.310
6.9
929
6.0
.397
10.7
985
6.0
.979
9. 1
101 I
2.7
.999
2. 1
1058
4.6
1 .063
6.4
1088
2.8
1 .110
4.4
1086
-0.2
1 .064
-4.1
1 122
3.4
t .082
1.7
1 186
5.7
1.189
9.9
1254
5.8
1.298
9.2
1246
-0.6
'1.294
-6.3
170.2
1232
-1.2
1 .164
-10.1
149.2
-12.3
1298
5.4
1.302
1 1.9
176.9
18.6
1 370
5.5
1 .384
6.3
190.1
7.5
1439
5.0
1 .468
6.1.
202.1
6.3
1479
2.8
1 .536
4.6
217.8
7.8
1474
-0.4
1 .467
-4.5
202.8
-6.9
1503
1.9
1.503
2.4
205.8
1 .5
1485
-1.9
1 .375
-8.5
191 .7
-6.8
3RI and ITC,
Synthetic Organ ic
Chemicals: U
S. Production and Sales.
2-26
-------
Figure 2-3
:--"t i'"'; o cr u '-j © i"~'i r*', i i r_,-r i ri \ i a n. ! r*-i ?¦.,; r i >, ,11 ~r © •-
i I I I l_' '-W-' I I 'I "* f—. I -4 I I '4 I I I . I I \ I I "4 !_/
i i
74 75 76 77 78 79 80 81 82
YEAR
~ MPI 4- Gr* -S- CiC?3? Pr4ifeKrtfan
0 Manufacturing Production Index
"~ GNP in trillions of 1972 dollars
0 OCPSF Production in hundred billion dollars
Sources: DRI and ITC, Synthetic and Organic Chemicals: U.S. Production and Sales.
2-27
-------
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
Sourc
Table 2-12. Profit on Sales Trends (percent)
Before-Tax Profit on Sales After-Tax Profit on Sales
Chemical All
282 286 Manufacturing Manufacturing
6.1
8.2
8.1
8.6
6.0
7.8
3.2
4.8
3.7
3.6
3.6
2.5
4.6
5.5
4.8
6.0
8.3
9.8
9.1
9.9
6.5
5.7
5.7
5.3
5.3
2.6
4.1
3.8
5.3
5.3
5.9
6.9
7.2
6.6
6.7
6.0
6.0
6.2
NA
NA
NA
4.5
4.7
5.0
5.7
5.2
4.4
5.1
5.0
5.2
5.5
NA .
NA
NA
Before tax-profit data are from Robert Morris Associates. The 282
group covers SIC classes 2821, 2823 and 2824. The 286 group covers
SIC classes 2861, 2865 and 2869. After-tax profit data are from the
Citibank Monthly Economic Letter.
2-28
-------
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
Table 2-13. Profit on Net Worth Trends (percent)
Before-Tax Profit on Net Worth After-Tax Profit on Net Worth
Chemical All
282 286 Manufacturing Manufacturing
9.5
10.1
18.2
14.8
9.7
10.8
25.6
16.1
11.3
12.1
32.0
24.1
15.2
14.9
29.7
36.9
18.8
15.2
20.9
30.6
15.8
12.6
27.9
32.6
16.1
15.0
22.5
26.5
14.3
14.9
25.3
22.6
14.9
15.9
24.0
24.5
17.3
18.4
18.8
25.9
NA
NA
23.4
20.8
NA
NA
15.4
13.5
NA
NA
24.0
15.2
24.2
20.4
Before tax-profit data are from Robert Morris Associates. The 282
group covers SIC classes 2821, 2823 and 2824. The 286 group covers
SIC classes 2861, 2865 and 2869. After-tax profit data are from the
Citibank Monthly Economic Letter.
2-29
-------
Table 2-14
Price Trends by OCPSF Product Group
(1972 Dollars per Pound)
Average
Year Annua I
Product
Group
1975 |
1976 |
1977 |
1978 |
1979
I 1980 |
1981
| 1982
Change
(percent-)
I. Tar and Tar Crudes*
.041
(.028)
.039
(.025)
NA
NA
NA
NA
(.10)
(.06)
(,l 1 .50)
2. Cyclic Intermediates
. 17
.17
. 16
.15
. 19
.20
.20
. 17
0.00
3. Miscelaneous Cyclic
and Acyclic Chemicals
-
.15
.14
.15
. 16
.16
. 1 4
-1.14
4. Dyes
1.81
1.87
1 .94
2.09
2.02
1.95
1 .81
1 .55
-2.19
5. Organic Pigments
3.19
3.63
3.33
3.31
3.45
3.33
3.32
3.06
-1 .36
6. Flavor and Perfume
1 .38
1.33
1 .38
1 .00
1.07
1.10
1 .09
1 .21
-1 .86
7. Plastics and Resins
.26
.26
.26
.25
.26
.27
.24
.23
1 .74
8. Rubber Processing
.81
.83
.84
.75
.86
.84
.83
0.35
9. Plasticisers
.28
.29
.27
.27
.28
.31
.29
.27
-0.52
10. Synthetic Fibers
.52
.51
.54
.51
.49
.50
.51
.51
-0.2"
11. Cellulosic Fibers
.77
.71
.71
.65
.72
.80
.83
.80
0.55
12. Miscellaneous End-Use
Chemicals and Chemical
Products
-
.54
.48
.50
1
.46
I
.40
1
.43
.42
-4.10
1
Sources: ITC, Synthetic Organic Chemicals: U.S
Production and
SaIes:
(line Gu ide
to the
Chem i ca1
Industry, 1980; and U.S. Department of Commerce, U.S. Industrial Outlook.
* Data for the entire tar and tar crudes category are only available for 1975 and 1976. Price data
for tar alone are available for 1981 and 1982. These values are shown in parentheses.
2-30
-------
Table 2-15 compares price trends to production, annual capacity, capacity
utilization, and new capital expenditures for OCPSF product groups, while Figure 2-4
compares price trends to production, capacity and capital investment. It can be seen
from the figure that prices, production, capacity .and investment remained fairly
constant over the 7-year period for SIC groups 2824, 2865 and 2869. For SIC 2821, price,
production and capacity remained fairly constant, while capital investment increased
from 1975 to 1980, falling thereafter. Capacity gradually decreased over the period for
SIC 2823, while production decreased after 1979. By contrast, capital investment
increased fairly dramatically after 1977. These capital expenditures generally repre-
sented a shift from funding new capacity to automating and streamlining existing
facilities.
2.5 Employment and Productivity
The OCPSF industry employed about 267,00 persons in 1982, or roughly 1.5
percent of total U.S. manufacturing employment. Tables 2-16, 2-17 and Figure 2-5
present employment and productivity trends for the five OCPSF SIC groups over the
period 1972 to 1982.
Table 2-16 shows that overall OCPSF employment fell over the period 1972-
1982 by approximately 4 percent, while the total number of production employees fell by
about 12 percent. Indeed, both production and total employment dropped over the period
for every SIC group except 2869 (plasticizers, flavor and perfume materials, and other
miscellaneous chemicals). The largest employment decrease occurred in SIC groups 2824
(23 percent drop in total employment and a 26 percent drop in production employment)
and 2823 (17 percent drop in total employment and 25 percent drop in production employ-
ment). By contrast, total employment in SIC 2869 increased slightly.
Peak employment, both for the industry as a whole and for SIC groups 2821,
2865 and 2869 occurred during 1977-1979, falling thereafter. Peak employment for SIC
groups 2823, 2324 occurred in 1974 and 1973, respectively.
As presented in Table 2-17, employee productivity in SIC groups 2821 (Plastics
and Resins) and 2824 (Synthetic Fibers) showed a net increase over the decade. The
productivity of synthetic fibers producers more than doubled from $37,700 per employee
in 1972 to $83,000 per employee in 1982 (1972 dollars). SIC groups 2823, 2S65 and 2869
showed productivity reductions over the period. The largest reduction was in SIC 2865
(Cyclic Crudes and Intermediates), where productivity declined from $82,700 per
employee in 1972 to $54,700 (1972 dollars) in 1982.
2-31
-------
Table 2-15. OCPSF
Price, Capacity Utilization
and Capital Spend!
ng Trends
Capac i ty
Capital
YEAR
Average
Production
Capaci ty»
UtiI ization**
1nvestment
Price (1972
(lbs x I09)
(lbs x 109)
(percent)
(current
dol1ars/lb.)
OR 1
dollars x I06)
SIC 2821
1975
.26
24.9
NA
NA
637.8
1976
.26
29.7
40.2
73.9
746.4
1977
.26
34.6
45.5
76.1
895.2
1978
.25
38.9
50.6
76.9
972.4
1979
.26
41.9
50.9
82.3
1077.1
1980
.27
38.2
52.9
72.2
1377.3
1981
.24
40.6
55.5
73.2
904.2
1982
.23
38.3
NA
NA
899.2
SIC 2823
1975
.77
.75
1.24
60.5
69.9
1976
.71
.84
1.19
70.5
41.6
1977
.70
.89
1.06
83.5
29.3
1978
.65
.90
1.09
83.3
32.7
1979
.72
.93
1.11
88.9
83.7
1980
.80
.81
.91
83.7
83.2
1981
.83
.77
.90
85.7
111.8
1982
.80
.58
.89
65.2
88.4
SIC 2824
1975
.52
5.9
8.4
69.8
700.9
1976
.51
6.6
9.1
72.6
534.2
1977
.54
7.3
9.35
78.2
338.5
1978
.51
7.8
9.56
81.3
487.5
1979
.49
8.4
9.78
86.0
448.7
1980
.50
7.9
9.63
81.8
503.2
1981
.51
8.0
9.7
82.3
444.5
1982
.51
6.4
9.33
69.0
443.2
SIC 2865
and SIC 2869
1975
.17
117.7
NA
NA
2107.2
1976
.17
139.8
193
72.3
2652.4
1977
.16
147.3
204
72.2
3605.7
1978
.15
154.6
212
73.0
2792.8
1979
.19
166.6
212
78.4
2839.8
1980
.20
156.0
228
68.4
2907.6
1981
.20
156.4
230
68.1
3237.7
1982
.17
146.4
NA
NA
3035.2
Sources:
ITC, Synthetic Organic Chemicals:
U.S. Production and Sales; U.S.
Department of Com-
merce, Census of Manufacturers; Oft I; Textile Orqanon, January 1984; and EPA estimates.
•Capacity values for SIC 2821 and 2865/2869 are derived from production data and capacity
ut iIi zat ionaI est i mates.
"Capacity utilization estimates for SIC 281 and 2965/2869 are developed from DRI capacity
utilization data covering 80S of SIC 2821 and 60S of 2865/2869.
2-32
-------
Figure 2-4. OCPSF Price, Production, Investment
OCPsP PRICE. PRODUCTION. INVESTMENT
(SIC 2821)
OCPSF PRICE. PRODUCTION. INVESTMENT
78 79
>M (t»- )
(1972 S/U>) <**¦• *
10 )
life*, « 10 )
& C*. MMI
(current $ x 10^)
ThAM (i^- )
0 pu ~ PRGOUCTON • opwcmr
9 Q
(1972$/lb) (lb*, s 10 ) (lbe. x 10 )
A CMP. IMCST
4
(current S x 10 )
OCPsP PRICE. PRODUCTION. INVESTMENT
(SIC 2624)
~ **0Ducm*
;197JVlb.) (lba x Id9)
rM (i»- )
~ cmctrr
(lbs. x 108)
A C4P. INK8T
4
(currant 5 x 10 )
OCPsP PRICE. PRODUCTION. INVESTMENT
(SIC 2865 and 2969)
0 MOCK
(1972$/lb)
ruM p*- ;
Ci*x*cmr
(lbs. x
106)
(Lbs. x
106)
(current S x 10 )
Sources: ITCf Synthetic Organic Chemicals: U.S. Production and Sales; U.S.
Department of Commerce, Census of Manufacturers; DRI; Textile Organon,
January 1984; and EPA estimates.
2-33
-------
TABLE 2-16
OCPSF Employment Trends
(thousands of persons)
SIC
Employment Type
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
2821
Total Employees
Production Empl.
54.8
35.0
54.4
35.0
57.7
37.6
54.3
34.0
56.2
36.4
57.2
36.7
58.4
37.6
60.3
38.4
58.8
36.6
57.6
35.3
54.7
32.8
2823
Total Employees
Production Empl.
17.1
14.4
16.7
14.3
20.5
16.2
15.9
12.0
16.7
12.8
16.0
12.6
15.7
12.5
17.0
13.6
16.1
12.7
15.6
12.2
14.2
10.8
2823
Total Employees
Production Empl.
78.2
58.4
81.8
61.5
80.9
60.5
70.2
51.0
69.3
50.2
74.0
54.8
72.3
54.0
70.8
52.7
65.3
47.7
58.0
39.1
60.4
43.3
2823
Total Employees
Production Empl.
28.2
18.7
29.5
19.0
27.6
18.4
27.8
17.9
27.8
17.9
35.7
23.4
35.5
22.0
32.4
21.1
33.7
21.4
33.2
21.4
27.3
16.0
2823
Total Employees
Production Empl.
102.4
64.5
102.8
66.1
102.5
65.6
104.9
64.8
109.3
68.7
112.3
70.7
128.6
62.8
115.9
71.8
117.2
70.8
116.7
70.1
111.8
65.0
2823
Total Employees
Production Empl.
280.7
191.0
285.2
195.9
289.2
198.3
273.1
179.7
279.3
186.0
295.2
198.2
310.5
188.9
296.4
197.6
291.1
189.2
281.1
177.8
268.4
167.9
Source: U.S. Department of Commerce, Census of Manufacturers.
-------
Table 2-17 OCPSF Employment Productivity Treads
(value of shipment per employee, in thousands of 1972 dollars)
SIC Group
1972
1977
1979
1980
1981
1982*
2821
81.9
97.0
107.6
99.4
106.8
94.0
2823
40.0
39.1
41.4
40.5
39.8
31.7
2824
37.7
69.4
80.8
82.0
91.0
83.0
2865
82.7.
66.3
73.3
58.8
60.7
54.7
2869
72.9
77.0
76.9
67.9
69.2
65.0
Source: U.S. Department of Commerce, 1983 U.S. Industrial Outlook.
The 1982 data are estimates.
2-35
-------
Table 2-18 and Figure 2-5 show OCPSF production employment as a percentage
of total plant employment over the 10-year period 1972-1982. SIC group 2823 (Cellulosic
Fibers) had the highest percentage of employment in OSPSF production (79 percent),
while SIC 2869 (Plasticisers, miscellaneous organic chemicals) had the lowest percentage
of employment in OCPSF production (61 percent).
Table 2-18
Production Employment
as a Percentage of Total Employment (1972-1982).
SIC Mean (Z) Scd. Dev. (%)
2821 63.3 1.6
2823 79.3 3.1
2824 73.2 2.2
2865 64.1 2.2
2869 60.8 4.4
TOTAL OCPSF INDUSTRY 66.0 2.1
Source: U.S. Department of Commerce, Census of Manufactures, 1982.
2.6 Foreign Trade Profile
Three aspects of the OCPSF industry are important from a foreign trade
perspective: 1) the effect of industry activity on the U.S. trade balance; 2) the relative
weights of trade in the output and consumption of OCPSF products; and 3) the role of the
U.S. industry within the world OCPSF market. The factors influencing the U.S. position
include feedstock prices and availablity here and abroad, other factor prices, global
capacity expansions and U.S. and international demands for OCPSF products.
2.6.1 Importance from Balance of Payments Perspective
The OCPSF industry is one of the largest exporting industries in the U.S. In
1984, the five major SIC groups which are included in the OCPSF industry exported
$10.26 billion, or 4.896 of total U.S. exports of goods (of $212 billion). OCPSF imports in
1984 totalled $4.22 billion or 1.3% of total imports of goods (of $325 billion).
Tables 2-19 and 2-l9a shows the import and export trends of the industry com-
ponents by SIC over the twelve years 1972-1984.. Current dollar values of OCPSF
2-36
-------
Figure 2-5
JiO
TO
«n —
3C
/ /
' .-'l
f A
/1
Y
Y'..
. y
•40
/I
J50 -/
™ -
ym' / / / ..'1
'/:///.)
V//A
V///A
Y / / / ,-i
V././ y" ,-'1
V///A
r' / /' I
/
''////}
U' .. 1 •
;, * ' , ,• /' .0
! ,*¦' /*" .>"t
r' /"/" / 1
/// / \
K/V
L-J ///,.
f//
y y
Y/s
.-I i
VA Y
/- .."i
vvi
?—I
/ / /
// ..'1
1 L.
f
2821
2823
2824 2865
2!C CSC'L?
2869
TOTAL
Source: U.S. Department of Conmerce, Census of Manufacturers
2-37
-------
Table 2-19
OCPSF Import and Export Trends
VaI ue (Smi I I ion)
SIC
1972
1977
1979
1980
1981
1982
1983
1984
Average
Com-
pounded
Annua 1
Growth
(J)
2821 Import
Export
56.4
438.9
106.3
1057.2
246.4
2183.3
263.4
2703.4
288.4
2554.5
267.8
2471 .7
468.7
2509.5
677.6
2655.4
23.0
16.2
2823 Import
Export
25.7
29.2
51 .0
61 .6
25.0
92.4
23.3
81.6
28.5
72.5
21.4
70.4
22.9
47.7
26.9
51.3
1.5
4.3
2824 Import
Export
138.1
177.6
89.3
388.3
65.0
938.8
69.5
1236.5
99.0
1518.0
91.7
1083.0
169.0
860.0
234.0
985.0
4.9
15.3
2865 Import
Export
281.5
305.6
551 .7
885.8
789.1
1605.2
818.9
1849.9
998.1
1807.1
924.3
1505.4
1272.7
1570.4
1507.2
1842.7
15.0
16.2
2869 Import
Export
167.1
767.5
543.1
1993.6
995.0
3888.7
1190.0
4442.7
1352.0
4560.0
1055.0
4386.6
1345.0
4250.6
1779.0
4723.8
21 .8
16.
Total OCPSF
Import
Export
668.8
1718.8
1498.7
4386.5
2120.9
8708.4
2365.1
10314.1
2765.7
10512.1
2360.2
9517.1
3278.8
9238.2
4224.8
10258.2
16.6
16.1
Total U.S.
of Goods
Import
Export
55,600
48,400
150,400
118,900
209,500
178,600
244,900
216,500
261,000
228,900
244,000
207,100
258,000
196,000
325,700
212,100
15.9
13.1
OCPSF i
Total U.S.
Import
Export
1.20
3.55
1.00
3.69
1.01
4.88
0.97
4.76'
1.06
4.59
0.97
4.60
1.27
4.71
1.30
4.84
0.6
2.6
Source: US Industrial Outlook 1986, 1984, 1983.
U.S. Bureau of The Census: Highlights of U.S. Exports and Imports Trade, Report 990.
2-38
-------
Table 2-19a
OCPSF Import and.Export Trends
Value (SmiI I ion)
Constant S (1982)
SIC
1972
1977
1979
1980
1981
1982
1983
1984
Average
Com-
pounded
Annua 1
Growth
(1)
2821 Import
Export
131.1
1012.7
169.3
1683.9
327.7
2903.4
308.5
3166.7
306.1
2711.1
267.8
2471.7
454.1
2431.3
629.1
2467.6
14.0
7.7
2823 Import
Export
59.3
67.4
81.2
98.1
33.2
122.9
27.3
95.6
30.2
76.9
21.4
70.4
22.2
46.2
25.0
47.7
-6.9
-2.8
2824 Import
Export
318.6
409.8
142.2
618.5
86.4
1248.4
81.4
1448.4
105.1
1611.1
91.7
1083.0
163.7
833.2
217.5
915.3
-3.1
6.9
2865 Import
Export
649.5
705.1
878.8
1410.9
1049.4
2134.6
959.3
2167.0
1059.3
1917.9
924.3
1505.4
1233.0
1521.5
1400.6
1712.4
6.6
7.7
2869 Import
Export
385.5
1770.8
865.1
3175.5
1323.2
5171.2
1394.0
5204.2
1434.9
4839.6
1055.0
4386.6
1303.1
4118.1
1653.2
4389.7
12.9
7.9
Total OCPSF
Import
Export
1543.1
3965.7
2387.2
6987.0
2820.4
11580.5
2770.5
12081.9
2935.3
11156.5
2360.2
9517.1
3176.6
8950.3
3926.0
9532.6
8.1
7.6
Total U.S.
of Goods
1mport
Export
128,283.8
111,671.5
239,562.8
189,338.4
278,594.5
237,503.5
286,874.4
253,606.8
277.001.1
242.933.2
244,000
207,100
249,959.1
189,891.4
302,667.5
197,101.0
7.4
4.8
OCPSF *
Total U.S.
Import
Export
1.20
3.55
1.00
3.69
1.01
4.88
0.97
4.76
1 .06
4.59
0.97
4.60
1.27
4.71
1.30
4.84
0.6
2.6
Source: US Industrial Outlook 1986, 1984, 1983.
U.S. Bureau of the Census: Highlights of U.S. Exports and Imports Trade, Report 990.
CPI (for Constant $ Values) from Statistical Abstract of the U.S. 1986.
2-39
-------
imports and exports are shown in Table 2-19 and constant L982 dollar values in Table 2-
19a. Table 2-19a shows that real imports and exports of OCPSF products have risen
during the past decade. The only exception is synthetic fibers where in SIC 2S23 both
real imports and exports declined. These groups, particularly 2S23, are small trade
products, so, in spite of the decline, total OCPSF trade volumes rose. The relative
shares of OCPSF in both total exports and imports of goods have grown since 1977; 3.S%
and 4% per year respectively, making the industry increasingly important in terms of the
Balance of Trade. Since 1972 the compounded average growth rates were 0.6% for
imports and 2.6 % for exports.
SIC group 2869, Industrial Organic Chemicals, is both the largest exporter and
importer in the industry accounting for 46% of exports and 42% of. imports in 1984. For
this group and for Plastics, SIC 2821, the value of imports has been increasing faster than
exports, while for the others exports have been increasing faster than imports. Since
these are large importers, the total effect is OCPSF imports increasing faster than
exports during the period from 1972-1984.
2.6.2 Importance of Trade for the U.S. OCPSF Industry
*
Table 2-20 shows that both imports as a percent of new supply and exports as a
percent of shipments have grown over the period 1972-1984 meaning that trade has
become increasingly important to the OCPSF industry. Total OCPSF imports have grown
at a slightly faster pace than exports: 3.5% per year versus a compounded average
annual growth in exports of 2.7%. During the decade 1972-1982 exports grew at an
average rat£ of 15%, while imports grew at a rate of 0.5% per year. However, during
1983 and 1984 total exports remained constant while import as a percent of new supply
grew relatively quickly.
Exports as a percent of shipments grew for all categories except Cellulosic
Fibers, SIC 2823 over the period 1972 to 1984. For both Fiber groups, imports actually
decreased as a percent of new supply through 1984.
Relative to shipments, SIC 2865, Cyclic Crudes and Intermediates, is the largest'
exporter — 18.9% of shipments were exported in 1984. The export market is important
for all SIC groups except 2823, which exported only 4.3% of shipments in 1984. The only
*
New supply equals sum of imports and domestic production.
2-40
-------
Table 2-20
OCPSF Import & Export Trends
As Percent of Shipments*
SIC
1972
1977
1979
1980
1981
1982
1983
1984
Average
Com-
pounded
Annua i
Gro»th
(1)
2821 Import
1.0
0.7
1.2
1.3
1.8
1.5
2.2
2.8
9.0 j
Export
9.3
3.1
12.0
11.8
13.6
14.0
11.9
11 .6
1 .9 !
2823 Import
3.6
5.7
2.3
2.3
2.3
1.9
1.9
2.2
-4.0
Export
4.3
7.2
8.5
7.1
5.9
6.3
4.0 ¦
4.3
0.0
2824 l«port
4.5
1.9
1.1
1.1
1.4
1.3
2.0
2.7
-4.2
Export
3.8
3.6
11.2
13.8
15.0
15.1
10.4
11.8
9.9
I
2865 Import
10.7
9.1
9.7
9.6
10.4
10.7
12.6
13.4
1.9 |
Export
13.1
16.1
21.7
23.9
21.1
19.6
17.8
18.9
„ j
2869 Import
2.3
2.9
3.3
3.5
3.4
4.1
4.8
5.3
7.2 ^
Export
10.2
10.3
15.5
16.4
14.5
16.4
14.9
14.9
3.2 !
i
Total
i
Import
3.7
3.5
3.7
3.9
4.0
3.9
4.8
5.6
3.5 ,
Export
9.6
10.1
15.2
16.8
15.1
15.7
13.2
13.3
;
Source: U.S. Industrial Outlook 1986, 1984, 1983, U.S. Bureau of the Census.
•Imports as percent of import and shipments (i.e., new supply).
Highlights of U.S. Exports and imports. Trade Report 990.
2-41
-------
SIC which imports a significant percent of new supply is SIC 2865. However in both
Organic Chemicals, 2869 and Plastics, 2821 the relative importance of imports has been
rising over the period.
2.6.3 Importance of the U.S. in the World OCPSF Market
*
In 1980 the U.S. accounted for 32% of free world petrochemical production.
Table 2-21 shows the amounts of U.S. and total free world production in the basic
petrochemical product groups.
The growth in U.S. exports through the early 1980's reflected an overall growth
in the world, demand for petrochemicals. Table 2-22 shows growth in the U.S. share of
world imports and exports through 1981. Since 1981 the U.S. share in world exports has
decreased, while its share in imports has continued to rise.
This shift reflects both a more expensive dollar and expanded production
capacity abroad. From about 1981 to 1985, the strong dollar caused both U.S. and
foreign users to prefer less costly foreign goods. In addition, petroleum rich countries
have been increasing their petrochemical capacities causing a deterioration in the com-
petitive position of U.S. firms in recent years. Table 2-23 describes the 1980 world
distribution of hydrocarbon reserves and production.
Natural gas is an important feedstock for petrochemical production and its
distribution illustrates the potential for foreign capacity increase. The table shows that
U.S. production equalled 10% of reserves, whereas in the Middle East production
amounted to 0.001% of reserves. This data suggests that the pattern of expansion in
foreign petrochemical production capacity will continue.
2.7 Financial Profile
Four financial ratios, Debt to Met Worth, Return on Assets, Current and
Interest Coverage were estimated for OCPSF firms as an indication of their financial
health, as part of the firm level analysis described in Chapter 3. These ratios are
The petrochemical industry includes SICs: 2821, 2822, 2824, 2843, 2865, 2869,
2873 and 2895, thus only partially overlapping with OCPSF which includes SIC 2823 and
does not include 2822, 2843, 2873 and 2895. Exports of petrochemicals in 1980 were
$11,797 million and OCPSF without 2823 were $10,431 million so that petrochemicals
include $1366 million not covered by OCPSF. OCPSF included $82 million covered by
petrochemicals.
2-42
-------
Table 2-21
World Petrochemical Production in 1980 (Billions 1982 $)
U.S. Free World
Commodities 47 (30Z) 155
Pseudo-commodities 45 (30Z) 150
Fine chemicals 23 (33Z) 77
Specialty chemicals 28 (41Z) 69
143 (32Z) 445
Source: A Competitive Assessment of the U.S. Petrochemical Industry, U.S.
Department of Commerce, 1982, p.4.
2-4 3
-------
Table 2-22
World Petrochemical Imports and Exports
(Billions 1982 $)
U.S. Exports
U.S. Imports
V World Exports
Source: A Competitive Assessment of the U.S. Petrochemical Industry, U.S. Department of Commerce, 1982,. p. App III.3.
and Chemical and Engineering News 6/10/85, p.22.
1979
1980
1981
1982
1983
1984
23,014 (13.7%) 24,295 (14.91) 22,486 (14.8%) 19,900 (14.6%) 19,183 (14.1%) 20,723 (13.4%)
9,954 (6.0Z) 10,067 (6.2%) 10,025 (6.61) 9,500 (7.0%) 10,463 (7.7%) 12,731 (8.6%)
167,056 162,941 151,767 135,900 135,637 148,685
-------
Table 2-23
Approximate Annual Production and Proven Reserves of Hydrocarbons
in Quadri11 ion BTU
1979 - 1980 DATA
NATURAL GAS
PETROLEUM
COAL
LIQUID GASES
Product ion
Reserves
Production
Reserves
Product ion
Reserves
Annual Production
1961
United States
20.1
o
-------
calculated for 102 publiclv-owned OCPSF parent companies* owning plants in scope for
which data are available from Standard and Poor's COMPUSTAT service.
Five to six years of data are available for most firms in the Compustat data
base. Ninety-nine firms are direct owners of plants in scope. (One hundred nineteen are
parent firms). All ninety-nine firms are included for the years 1979 to 1982. Seventy-
nine are included for 1978, twenty for 1983, seventy-seven for 1984 and 15 fo4 1985.
Financial values from this database were used to calculate the following financial
ratios: current, interest coverage, debt to worth, and return on assets. For the purposes
of the firm levei portion of the plant closure analysis, the year of data with the median
* *
return on assets was chosen for a given company. The ratio formulas used are listed in
Appendix 3E of Chapter 3.0.
Tables 2-24A and 2-24B illustrate the mean and quartile values for the financial
ratios for direct owners and parent firms, respectively. The tables show the general
worsening of conditions for the chemical industry from about 1980 through 1983 with
some recovery thereafter. Companies took on slightly more debt realtive to equity, on
average; interest coverage decreased and return on assets decreased. Very little
difference is seen between direct owners and parent firms overall.
The financial ratios have also been calcualted for parent companies by four-
digit OCPSF SIC code. SIC codes were assigned by summing organic shipments of plants
owned by a firm, by SIC, and choosing the SIC code with the greatest firm-wide value.
(Note: many firms do not produce principally OCPSF products, and thus would not be
considered to fall under these assigned SIC codes; however, the Compustat database
contains SIC codes only for 1984 and 1985, whereas the data begin with 1978.) See Table
2-25.
For comparative purposes, these financial' ratios were also calculated from
Robert Morris Associates (RMA) data for SIC groups 282 (includes 2821, 2823, 2824) and
286 (includes 2861, 2865 and 2869). (See Table 2-26)
£
Parent companies are the highest level of ownership for OCPSF database
plants. Other ownership level aggregations, such as direct owners, are used in other
sections of this report. However, the availability of data necessitates the use of parent
companies here.
**This is to avoid using different years of data for different ratios for a single
company.
2-46
-------
Table 2-24A
Financial Ratios tor Oirect Owner Corporations Owning »n-Scope
Pteof* Calculated tram COAJSTAT Data
Number of
Direct
Owner Ma an of Standard Percentilas
Tear Coooanies Ratios Deviation 231 Median 791
Oebt to Met North
1978
79
1.03
39
.83
1.01
1.22
1979
98
¦ 1.11
.63
.81
1.05
1.27
1960
96
1.13
.82
.78
1.04
1.26
1981
98
1.23
.78
.78
1.01
1.23
1962
99
1.04
.42
.77
1.02
1.24
1963
20
.91
35
.63
.86
1.13
1984
77
1.09
.33
.78
1.02
1.36
1985
15
1.22
.88
.74
.96
1.23
Ai I rears
383
1.09
.83
.78
1.02
1.25
Interest Coverage
1978
76
ft*
4.63
6.11
10.90
1979
97
MC
W
4.26
6.46
9.97
I960
97
W*
Itf
3.31
4.72
8.4J
1961
98
m
Mf
3.44
3.06
9.03
1982
98
If
2.18
3.93
8.33
1965
20
6.40
6.60
2.13
«.32
7.99
1984
77
Kf
3.06
4.79
7.18
1985
15
3.34
3.61
1.15
4.32
6.33
A11 rain
380
WF
IMF
3.39
3.13
8.82
Currant Ratio
1976
79
2.20
.71
1.74
2.08
2.48
1979
98
2.10
.36
1.63
2.04
2.47
1960'
96
2.1
.66
1.36
2.03
2.37
1981
99
2.07
.86
1.68
2.01
2.39
1962
99
2.07
.74
1.36
1.96
2.46
1963
20
2.32
.77
1.38
2.40
2.94
>964
77
1.93
.72
1.31
1.90
2.27
1963
15
2.2*
.86
1.63
2.11
2.53
A11 rmtrt
365
2.10
.<9
1.83
2.01
2.42
Raturn on Assert
(before taxes)
1978
79
.13
.07
.09
.11
.16
1979
96
.13
.07
• 08
.12
.16
I960
96
.11
.06
.07
.11
.15
198t
99
.11
.07
.07
.11
.15
1962
99
.07
.08
.03
.07
.12
1963
20
.08
.07
.03
.06
.15
1964
77
.14
.34
.07
.11
.14
1984
77
.14
.34
.07
.11
. 14
1963
13
.07
.07
.00
.06
.14
AM Tears
369
.11
.14
.06
.10
.15
*Mo aeanlngtul figure.
Source: Standard and Pocr's CCNPllSTAT Service*
2-47
-------
Tat id 2-248
Financial Ratios for Parent Coroorations Owning in-Scope
Plants Calculated fro* CONSTAT Data
Mwnoer of
, Parent Mean of Standard °erce"t:ias
Companies Ratios deviation 251 Median 751
Oeot to Met Worth
1978
1979
1980
1961
1982
1983
1984
1985
95
M7
117
118
118
23
91
18
1.06
I .16
1 .18
I .18
1.12
t .08
1.24
1.27
.45
.69
.31
.81
.58
.55
.73
.86
.8}
.80
.77
.78
.78
.66
.79
.73
1.02
¦ .09
! .08
i .06
1.06
1..09
1.11
1.18
1.29
1 .37
1 .37
I .38
l .35
1 .34
1 .42
I .53
697
1.16
.69
.78
1 .07
1 .37
interest Coverage
1978
1979
1980
1981
1982
1983
1984
1985
94
116
116
117
117
23
91
18
692
t**
5.95
**
6.71
NMf
m
mf
6.77
Mf
8.39
M4F
4.67
4.02
3.42
3.48
2.17
t .81
2.91
1.99
3.31
5.81
5.98
4.38
4.99
4.00
3.92
4.62
4.28
4.99
10.78
9.35
8.37
8.91
6.16
10.71
6.91
6.53
Current Ratio
1978
1979
1980
1981
1982
1983
1984
1985
95
117
117
118
118
23
91
18
2.20
2.12
2.11
2.06
2.09
2.37
1.93
2.37
.73
.61
.68
.68
.82
.86
.80
l .00
1.73
1.65
1.57
1.39
1.56
1.52
1.50
1.61
2.08
2.08
2.07
2.00
1.96
2.57
i .83
2.05
2.48
2.52
2.37
2.40
2.42
3.01
2.24
2.99
Ail rears
Return on Astats
(before tamee
1978
1979
1980
1981
1982
1983
1984
1984
1985
697
95
117
117
118
118
23
91
91
18
697
2.11
.129
.124
.112
.114
.078
.070
.103
.103
.076
.107
.74
.067
.072
.079
.072
.082
.083
.074
.074
.068
.076
1.60
.085
.082
.067
.073
.035
.033
.067
.067
.030
.066
2.01
.1 >4
.121
.107
.113
.075
.073
.103
.103
.071
.105
2.43
.153
.153
.148
.150
.127
.131
.136
.136
.137
.145
Source: Standard and Poor's CONSTAT Service.
2-48
-------
Taoio 2-»
Financial Ratio* Par*«r Cor&or«r>on* ov SlC Grow» Cy r«*r
*Mjo^ OCPSF S*C Crowes and S*i*ct«0 Stat'tric*
raar
fiHinti «l
Ratio
Nunar or
2021 7023 2924
ttaan v«8
040r to •eirtn
.83
.10 - .10
1.4 - 1.34
9.71 - 18.??
2.41 - 2.03
.14 - ,14
¦ 979
D#ot re *orrn
mraraar Co^vafa
Currant
BT Atturn on A>MM
43 0 4
42 0 4
43 0 4
4} 0 4
i.JS - 1.19
8.6 - 4.39
2.0? - 2.31
.11 - .12
.93 - .65
3.21 - -.62
t.Jl - 1.54
.07 - -.03
1.09 - 1.13
3.22 3.47
1.97 - 2.57
.10 - .12
1.33 - 1.79
8.*6 8.J4
2.39 - 2.SI
.14 - .28
i960
Qaot to aorrn
iif»r«ir Cov«raga
Currant
07 ftatwrn on Mmti
4 J 0 4
42 0 4
43 0 4
43 0 4
1.33 - 1.02
J.9 - 7.33
2.09 - 2.3!
.09 * .19
.95 - .31
2.66 - 2.49
1.32 - 1.3ft
.04 • .04
1.10 - 1.01
4.13 - 6.95
I.W - 2.33
.09 - . .19
1.61 - 1.34
7.23 • 12.33
2.3 - 2.43
.13 - .14
IMI
Qaot to «yt»
mriritr Cov*raga
Currant
BT (Utwrn on *««ar«
43 0 4
42 0 4
4) 0 4
43 0 4
i.JS - .93
3.3 • 10.3
1.99 - 2.64
.09 - .20
.92 - .54
2.37 - 5.39
1.34 - 1.71
.05 - .13
1.07 • .86
4.36 - 10.31
1.M - 3.74
.06 - .18
1.32 - 1.16
7.27 - 14.96
2.» - l.li
.13 • .26
>962
Oaot to worm
inr«fMt Covarag*
Currant
Bt fcatyrn on A«»*ti
43 0 *
42 0 4
43 0 4
43 0 4
».K - .97
3.J - 9.82
1.99 - 2.24
.0*7 - .13
.90 - .63
1.66 - 3.re
.31 « 1.33
.02 - .07
1.09 • .69
3.39 - 6.66
1.90 - 2.36
.06 • .14
1.30 - 1.26
3.11 • 17.63
2.46 - 2.62
.09 .17
¦ >>65
0#6t re aor'ft
intarait Covaraga
Currant
BT Raturn on Miati
9 0 1
9 0 1
9 0 J
9 0 1
.96 - .34
9.35 - 10.91
2.43 - 2.95
.96 - .17
.32 - .34
2.23 - 10.91
1.99 - 2.65
.03 - .17
1.09 • .34
4.11 - 10.91
2.90 • 2.95
.07 - .17
1.27 - .34
14.96 - >0.91
3.06 - 2.93
.12 -
•«4
0#or ro aorrn
Co*»f«9a
Cur ran*
gr R*twrn on HMTt
34 0 3
33 0 3
34 0 3
34 0 3
1.53 - 1.23
4.1 - 2.94
1.76 - 1.91
.06 - .07
.94 .69
1.95 - .63
1.24 - 1.20
.06 - -.01
i.26 • 1.37
4.19, - 2.93
1.62 - 2.13
.05 - .09
1.80 - 1.12
6.56 - 3.10
2.ro - 2.«i
.09 - .14
>993
Daor ro Horrrt
idtarwr Co»araga
Currodt
BT a»r*>A ON AtMTI
9 0 1
9 0 1
9 0 1
1 0 1
I.J* - .49
6.91 - 17.95
2.17 - 2.96
.07 - .13
.96 -¦ .49
1.01 - <7.95
1.53 * 2.96
-0 - .13
1.19 - .49
3.25 - 17.95
2.12 - 2.96
.05 - .13
2.11 - .49
9.21 - 17.83
2.32 - 2.86
.14 - .13
»»#rag®
or AM
raar*
Oaot re norm
inrarMt Ce^«9»
Currant
ST Ratwrn on >tt«fi
297 0 24
21T 0 24
257 0 24
' 257 0 34
i.3l • 1.00
1.9 - 9.03
2.03 - 2.34
0,09 - O. 4
.94 - 0.33
2.67 - 3.96
1.52 ¦ 1.33
0.05 • 0.09
i.lO • 0.92
4.41 • 6.24
1.96 • 2.3?
0.09 - O.H
1.30 - 1.41
7.24 - 11.00
2.16 - 2.67
0.12 • 0.17
2-49
-------
Financial Ratios for Parent Corporation* dv SiC Qrouo &> i**r
(contingad)
Major OCPSF SIC Groups ana Saiactao Statistics
Taar
Financial
Ratio
Nuoir of
Firvs fttortsonta*
Al 1
2663 2669 F\rm%
M»«n Vaiuo
Al 1
2663 7669 Firvs
23 Paresnriia
Al 1
2663 2869 Fir*«
Maeian
Al 1
2663 2669 Fir*«
73 Parcantiia
«i i
2663 2869 f,rm%
1976
Oaor to North
mtaratt Covoraga
Currant
Br R*twrn on AsMts
10 46 93
10 49 94
10 46 93
10 46 99
I.JO .93 1.06
6.63 9.42 6.77
2.09 2.29 2.20
.U .14 .13
.93 .67 .93
4.13 4.77 4.67
1.73 1.91 1.73
.10 .09 .09
1.29 i.OO 1.02
8.02 6.13 3.81
2.27 2.22 1.7)
.13 .Jl .09
1.73 t.16 1.29
12.03 12. )2 10./8
2.37 2.34 2.46
.17 .}7 .a
1979
Oaor ro Nortn
inttrnt Co««r*9a
Current ,
ar Rarurn on AaMts
13 3? 117
12 30 lift
13 97 117
13 37 If?
1.23 1.02 1.16
6.76 9.73 6.94
2.24 2.12 2.12
.If .14 .12
.66 .72 .60
3.63 4.71 4.02
1.64 >.72 1.69
.09 .'0 .06
1.16 - 1.01 1.09
9.92 6.96 9.96
2.30 2.06 1.69
.It .13 .06
1.97 1.28 1.37
11.32 M.39 9.39
2.63 ?.<9 2.92
.15 .16 .13
i960
Oaor to North
irtt#r«tt Covoraga
Currant
8T ftaturn on AimTi
13 37 117
12 30 114
13 37 117
!3 37 117
1.19 1.06 1.16
6.69 7.30 3.73
2.30 2.09 2.H
.12 .12 .11
.93 .70 .77
3.64 3.36 3.42
1.78 1.64 1.37
.09 .06 .07
1.09 1.07 1.06
4.37 3.46 4.36
2.11 2.07 1.37
.12 .12 .07
1.62 1.29 1.37
11.78 11.00 6.37
2.36 2.57 2.37
.16 .16 .13
196»
Oaot to North
int*r*«t Covsraga
Currant
8T Ratgrn on Ass«rs
13 30 117
13 30 116
13 36 116
13 36 116
1.19 1.06 1.16
6.T2 7.17 3.7J
2.14 2.04 2.06
.13 .12 .11
.66 .70 .76
1.73 3.66 3.46
1.33 1.70 1.39
.10 .09 .07
1.13 1.03 1.00
4.66 3.34 4.99
2.11 2.00 1.39
.12 .12 .07
1.34 1.30 1.36
9.36 >0.63 8.91
2.32 2.36 2.40
.13 .16 .13
'962
OoOt to Norm
intarast Co*oraga
Cwrr#nf
0T Return on Assart
13 36 116
13 30 117
IJ 36 >16
13 36 116
1.17 1.03 1.12
4.64 4.68 4.47
2.24 2.12 2.09
.09 .09 .06
.64 .73 .76
2.31 2.34 2.17
1.33 '.71 1.96
.03 .04 .04
1.12 1.03 1.06
3.76 4.12 «.00
2.04 2.00 '.36
.10 .09 .04
1.60 1.23 1.33
6.63 6.62 6.16
2.72 2.39 2.4?
.14 .13 .13
>963
Oaor to North
mtarasr Covoraga
Currant
6T Rat urn on AiMti
3 10 23
3 10 23
3 10 23
3 10 23
.96 1.23 1.06
4.20 3.63 3.93
2.32 2.26 2.37
.09 . 09 . 07
.06 .84 .66
2.06 .63 1.81
1.27 1.49 1.92
-.07 -.01 .03
.79 1.13 1.09
3.44 3.67 3.92
2.32 2.10 1.92
.07 .07 .03
1.49 1.69 1.34
11.29 6.23 10.71
5.36 2.94 5.01
.14 .12 .13
1964
OoOt to North
mtaraar Cowraga
Currant
0T ft*turn on Aiun
6 46 91
6 36 91
6 46 91
6 46 91
1.04 1.06 1.24
4.06 3.66 3.42
1.97 2.04 1.93
.09 .12 .10
.69 .73 .79
2.47 3.21 2.96
1.33 1.63 1.30
.04 .06 .07
.94 1.01 1.11
4.93 9.29 4.62
1.76 1.91 1.30
.11 .11 .07
1.33 1.34 1.42
6.22 8.30 6.91
2.63 2.32 2.24
.16 .17 .14
1963 .
Oaor to North
'nr«ra«f Cowrago
Currant
8T Raturn on Assort
2 7 10
2 7 16
2 7 16
2 7 16
.66 1.21 1.27
10.96 3.66 6.71
2.43 2.52 2.37
.11 .07 .06
0.34 .79 .73
3.30 2.«3 1.99
1.49 1.63 1.61
0.06 .04 .03
.66 1.2) 1.16
10.96 4.37 4.20
2.43 1.97 1.61
.11 .06 .03
1.19 1.73 1.33
9.62 3.45 6.53
3.36 4.20 2.99
.17 .10 .14
Av*r»ga
0# All
Taar*
Oaor to aorrn
mtarast Covoraga
Currant
BT Return on Assort
73 341 697
73 300 6a
73 341 697
73 341 697
1.16 1.09 l .16
6.37 6.76 9.73
2.19 2.13 Ml
0.11 0.12 .M
.66 0.71 0.76
3.34 3.64 3.3t
1.99 1.71 1.60
0.06 0.06 . 07
1.13 1.03 1.07
4.62 J.JJ 4.99
2.16 2.04 1.60
0.21 .11 .07
>.36 1.26 1.37
9.23 9.74 8.21
2.37 2.47 2.43
0.19 0.16 .13
2-50
-------
TabLe 2-26
Median Financial Ratios by SIC Croups Using RMA Data
Number of
Firms
Current
Coverage
Debt Co
Worth
Before
Tax Return
on Assecs
SIC 282
1980
127
1.5
2.9 (103)
1.4
8.0
1981
116
1.6
2.8 (101)
1.8
7.3
1982
126
1.5
2.4 (108)
1.6
6.5
1983
116
1.5
4.4 (102)
1.5
9.0
1984
103
1.5
3.6 (88)
1.6
8.7
1985
128
1.5
2.7 (110)
1.7
7.6
Mean of
All Years*
1.5
3.10
1.6
7.8
. SIC 286
1980
109
1.7
4.1 (82)
1.2
11.3
1981
77
1.6
3.1 (62)
1.3
10.7
1982
115
1.7
2.3 (95)
1.1
5.9
1983
108
1.6
3.4 (90)
1.3
7.2
1984
144
1.6
3.2 (114)
1.4
8.5
1985
131
1.5
3.0 (108)
1.6
6.6
Mean of
1.6
3.2
. 1.3
8.2
All Years*
Source: Robert Morris Associates, Annual Statement Studies, for 1980-1985.
-Weighed by number of firms.
2-51
-------
While the numbers are similar, the cross-section of firms covered in the two
databases are different. RMA polls firms with less than $50 million in assets, while the
Compustat database contains numerous large publicly held firms.
2.S Firm and Plant Characteristics
OCPSF firm and plant characteristics are based on §308 Survey data. Infor-
mation presented includes: firm and plant data classified by SIC product group, including
the numbers of plants per firm, production quantity and value; plant data, including sales
quantity and value, employment, productivity capital expenditures, discharge status and
location; and firm ownership data.
2.3.1 SIC Groups
To facilitate presentation of the data in this section, both plants and firms were
classified by four-digit SIC product group. This was done by assigning plants and firms to
the OCPSF SIC group with the largest production value for that plant or firm. In
addition to classification by SIC group, plants were also categorized as either primary or
secondary OCPSF producers. Primary producers are those with at least 50 percent of
their total production value in OCPSF products, while secondary producers produce less
than 50 percent of their total production in OCPSF products.
Table 2-27 presents the classification of firms and plants by SIC group and the
degree of plant specialization in each group. SIC groups 2821 (plastics and resin
materials) and 2869 (industrial organic chemicals) each accounted for about 40 percent of
both firms and plants in the industry; together, they include over 80 percent of the plants
and of the firms. Approximately 70 percent of the plants in these two SIC groups were
primary producers. SIC groups 2823 (cellulosic fibers) and 2824 (synthetic fibers) each
accounted for a very small percentage of the OCPSF plants and firms, but almost all of
these plants were primary producers. Twelve percent of the firms and thirteen percent
of the plants in the OCPSF industry were classified in the 2865 SIC group (cyclic crudes
and intermediates); 88 percent of these plants were primary producers.
2.8.2 Single Versus Multi-Plant Firms
More than 70 percent of the firms in the OCPSF industry were single-plant
firms in 1982, as shown in Table 2-28. Very few firms (29) owned more than five plants.
The mean plant size of plants owned by multi-plant firms was larger than the mean size
of plants owned by single-plant firms.
2-52
-------
Table 2-27
Firm and Plant Categorization by
OCPSF SIC
Group and Degree
of Plant Specialization
Firms
Plants
SIC Croup4
Total
Number
Percent of
Total Number
Total
Number
Percent of
Total Number
Number of
Primary ^
Producers
Percent
of SI£..
Croup
Number of
Secondary
Producers
2821
164
38.1
383
40.8
280
73.1
103
2823
4
0.9
6
0.6
6
100
0
282A
15
3.5
41
4.4
40
97.6
1
2865
52
12.1
111
11.8
98
88.3
13
2869
195
45.3
398
42.4
313
78.6
85
ft A "it "it
No SIC
25
—
39
—
—
—
—
TOTAL
455
100.0
978
100.0
737
NA
202
Source: §308 Survey
* Based on OCPSF SIC group with largest production value for the firm or plant.
Over 50 percent of production value is in the OCPSF industry. The numbers in this column and in the last column are based on a
total plant count of 1047; the rest of the analysis uses a total OCPSF industry plant count of 997.
• ¦ t
Percent primary producers of all plants in each SIC group.
in
Not included in percent computations.
-------
Table 2-28
BREAKDOWN OF MULTI-PLANT AND SINGLE PLANT OCPSF FIRMS
Primary Producers
Number of Plants
Per Firm
1
2-5
more Chan 5
Number of Firms
247
69
29
345
Mean Sales'
25.4
265.0
1494.0
Tocal Sales'
6,271
18,281
43,335
Secondary Producers
Number of Plants
Per Firm
1
2-5
more than 5
Number of Firms
81
25
4
110
Mean Sales
57.5
240.0
640.0
Total Sales'
4,654
6,003
2,561
Source: §308 Survey and EPA Company Database.
Based on Sales Value. Sales In millions of 1982 dollars.
2-54
-------
2.8.3 Production Quantity and Value
Tables 2-29 and 2-30 present, respectively, the distribution of total and OCP5F
production quantity by OCPSF SIC group for firms and plants. Tables 2-31 and 2-32 show
mean, median and total OCPSF and overall production quantities by SIC group for firms
and plants.
Annual OCPSF production was greater than 20,000 million pounds for about 40
percent of all firms and 50 percent of all plants. About 50 percent of the firms and over
60 percent of the plants produced more than 20,000 million pounds of total (OCPSF and
non-OCPSF) production.
Table 2-33 and Figure 2-6 show mean and median OCPSF and total production in
thousand tons for plants and firms. Median OCPSF plant production in 1982 was 21.93
million pounds, while mean OCPSF plant production was 191.35 million pounds. Median
OCPSF firm production was 10.91 million pounds, and mean OCPSF firm production was
412.52 million pounds. The large difference between median and mean production
quantities reflects the existence of a few very large plants, whereas the majority of
plants are small and medium sized. Similarly, the large difference between plant and
firm median and mean values reflects the fact that most firms consist of a single plant;
those plants owned by multi-plant firms tend to be large producers.
Median total plant production was 38.8 million pounds in 1982, while mean total
plant production was 302.75 million pounds. Median firm total production was 19.S8
million pounds, and mean firm total production was 652.69 million pounds.
2.8.4 Sales Quantity and Value
Tables 2-34 and 2-35 present the distribution of plant sales quantity and value
by SIC group for both OCPSF and total plant sales, while Figure 2-7 presents the
breakdown of value of shipments by 4-digit SIC code. Summary data on mean, median
and total sales quantity and value for plants by SIC group are presented in Table 2-32.
These tables show results similar to the ones discussed above for plant production
quantity and value. This is due to a high correlation between production and sales (as
shown in Table 2-36.) These correlations do not vary significantly among the different
SIC groups.
2-55
-------
TABLE 2-29: DISTRIBUTION OF
NO SIC 2821
I NO. OF I HO. OF
I FIRMS PERCENT | FIRMS PERCENT
OCPSF
PRODUCTION
(MILLION
LBS.)
HISSING
6
24.0
#
*
ZERO
19
76.0
1
0.6
0-.2
*
•
6
3.7
.2-1
•
•
14
8.5
1-2
*
•
12
7.3
2-10
*
*
37
22.6
10-20
•
•
23
14.0
20-100
»
•
36
22.0
100 PLUS
*
»
35
21.3
ALL
25
100.0
164
100.0
TOTAL
PROOUCTION
(MILLION
LBS. >
MISSING
6
24.0
*
«
ZERO
1
4.0
1
0.6
0- .2
2
8.0
6
3.7
.2-1
1
4.0
11
6.7
1-2
1
4.0
9
5.5
2-10
a
32.0
25
15.2
10-20
2
8.0
20
12.2
20-100
2
8.0
47
28.7
100 PLUS
2
8.0
45
27.4
ALL
25
100.0
164
100.0
982 FIR.M PRODUCTION QUANTITY** BY OCPSF SIC CROUP.
MAJOR SIC GROUP
2823
2824
NO. OF
NO. OF
2865
HO. OF
2869
FIRHS PERCENT FIRMS PERCENT FIRMS PERCEHT FIRMS PERCENT FIRHS
NO. OF
ALL
HO. OF
ALL
PERCEHT
1 25.0
3 75.0
4 100.0
13.3
*
6.7
*
33.3
13.3
13.3
20.0
100.0
10
10
7.7
26.9
7.7
19.2
7.7
11.5
19.2
2
25
18
13
33
21
29
54
1.0
12.8
9.2
6.7
16.9
10.8
14.9
27.7
52 100.0
195 100.0
6
24
35
47
29
85
50
74
105
4?5
1.3
5.3
7.7
10.3
6.4
18.7
11.0
16.3
23.1
100.0
1 25.0
3 75.0
4 10
13.3
*
6.7
*
33.3
13.3
13.3
20.0
100.0
2
11
6
10
5
6
12
3.8
21.2
11.5
19.2
9.6
11.5
23.1
2
19
11
10
33
19
34
1.0
9.7
5.6
5.1
16.9
9.7
17.4
52 100.0
67 34.4
195 100.0
6
6
29
35
26
SI
48
92
132
455
1.3
1.3
6.4
7.7
5.7
17.8
10.5
20.?
29.0
101
-------
N>
I
U1
-J
TABLE 2-30: DISTRIBUTION OF 1982 PLANT PRODUCTION QUANTITY BY OCPSF SIC CROUP
4 DIGIT MAJOR OCPSF SIC GROUP
NO SIC
| HO. OF
j PLANTS PERCENT
2821
NO. OF
PLANTS PERCENT
2823
| NO. OF
j PLANTS PERCENT
OCPSF
PRODUCT ION
(MILLION
LBS.)
MISSING
10
25.6
•
•
ZERO
29
74.4
3
0.8
0-.2
•
*
10
2.6
•2-1
•
•
22
5.7
1-2
*
*
18
4.7
2-10
*
*
67
17.5
10-20
*
*
60
15.7
20-100
*
*
120
31.3
100 PLUS
*
*
83
21.7
ALL
39
100.0
383
100.0
TOTAL
PRODUCTION
(MILLION
LBS.)
MISSING
10
25.6
*
ft
ZERO
2
5.1
3
0.8
0- .2
2
5.1
6
1.6
.2-1
2
5.1
12
3.1
1-2
1
2.6
12
3.1
2-10
12
30.8
40
10.4
10-20
5
12.8
50
13.1
20-100
3
7.7
151
39.4
100 PLUS
2
5.1
109
28.5
ALL
39
100.0
383
100.0
2824
2865
NO. OF
PLANTS PERCENT PLANTS PERCENT
NO. OF
2869
HO. OF
PLANTS PERCENT
ALL
NO. OF
PLANTS
ALL
PERCENT
•
•
•
*
*
ft
•
10
1.0
*
2
4.9
•
•
3
0.8
37
3.8
•
•
•
6
5.4
29
7.3
45
4.6
*
1
2.4
17
15.3
22
5.5
62
6.3
*
•
*
5
4.5
19
4.8
42
4.3
16.7
6
14.6
25
22.5
75
18.8
174
17.8
•
2
4.9
10
9.0
37
9.3
109
11.1
16.7
12
29.3
14
12.6
109
27.4
256
26.2
66.7
18
43.9
34
30.6
104
26.1
243
24.8
100.0
41
100.0
111
100.0
398
100.0
978
100.0
*
*
•
*
•
*
•
10
1.0
2
4.9
•
•
3
0.8
10
1.0
•
•
*
3
2.7
22
5.5
33
3.4
*
1
2.4
14
12.6
12
3.0
41
4.2
*
*
*
7
6.3
11
2.8
31
3.2
16.7
6
14.6
23
20.7
65
16.3
147
15.0
*
2
4.9
11
9.9
33
8.3
101
10.3
16.7
11
26.8
14
12.6
107
26.9
28 7
29.3
66.7
19
46.3
39
35.1
145
36.4
318
32.5
100.0
41
100.0
111
100.0
398
100.0
978
100.0
-------
Tab I 9 2-3 1
Firm 1982 Production Quantities and Vjlues
and Employment by OCPSF SIC Group
Major OCPSF Group
No SIC
2821
2823
2824
2865
2869
ALL
OCPSF Prod. Quantity
(Mill ion 1 bs)
• Mean
• Median
• Total
*
t
t
188.16
14.34
30,867.44
266.56
150.70
1,066.22
509.75
8.60
7,646.25
167.12
4.02
8,690.47
702.37
11.75
136,961.58
412.52
10.91
185,221.96
OCPSF Prod. Value
(Mi 11 ion S)
• Mean
• Med i an
• Total
»
»
•
70.49
8.89
11,278.30
256.39
118.89
1,025.55
290.80
27.93
3,780.34
71.96
14.08
3,742.00
265.96
13.72
51,064.60
168.39
12.00
70,890.80
Total Prod. Quantity
(Ml 11 ion lbs.)
• Mean
• Median
• Total
30.40
6.52
577.60
290.14
28.90
4,759.67
322.49
238.21
1,289.96
770.92
8.62
11,563.82
417.72
7.31
21,721.42
1,078.58
22.37
2\0,322.52
652.69
19.88
29,305.90
Total Prod. Value
(Mi 11 ion S)
• Mean
• Median
• Total
16.91
4.31
304.38
157.30
18.81
25,480.90
255.55
123.33
1,022.18
319.98
27.93
4,159.74
99.32
17.98
5,164.54
326.90
21.67
63,091.90
224.49
18.84
99,223.70
OCPSF Employment
• Mean
• Median
• Total
55.33
13.00
1,162.00
150.26
28.25
24,643.20
2,116.00
1,105.00
8,464.00
903.15
192.00
13,547.30
201.38
46.50
10,471.70
645.55
38.00
124,592.00
407.31
35.00
182,880.00
Total Employment
• Mean
• Median
• Total
113.91
23.00
2,734.00
324.05
56.00
52,820.80
2,120.25
1,110.00
8,481.00
1,138.22
222.00
17,073.20
454.18
55.50
23,617.50
946.63
76.50
183,645.00
637.99
67.00
288,372.00
Source: §308 Survey
2-58
-------
Table 2-32
Plant 1982 Product and Sates Quantities and Values
by OCPSF SIC Group
Major OCPSF Group.
Mo SIC
2821
2823
2824
2865
2869
ALL
OCPSF Prod. Quantity
(Million lbs)
• Mean
• Median
• Total
ft
~
ft
103.67
22.94
39,705.01
220.02
0.00
1,320.15
170.48
90.63
6,989.68
131.26
13.30
14,569.58
308.13
25.32
122,637.43
191.35
21 .93
185,221 .96
OCPSF Prod. Value
(Million})
• Mean
• Median
• Total
ft
ft
ft
48.14
13.83
17,812.50
161.99
118.89
971.96
183.75
142.72
7,166.31
55.45
20.00
6,154.65
99.19
19.91
38,785.40
77.31
17.66
70,890.80
OCPSF Sales Quantity
(Mi 11 ion lbs)
• Mean
• Median
• Total
•
ft
ft
95.09
20.00
36,421.01
164.90
151.86
989.38
148.55
89.86
6,090.43
117.83
1 1.65
13,079.36
238.40
23.21
94,882.03
156.47
19.45
151,462.39
OCPSF Sales Value
(Mi 11 ion S)
• Mean
• Median
• Total
ft
ft
ft
41.86
12.00
16,033.00
124.33
119.88
745.97
159.56
116.00
6,542.10
48.12
18.43
5,341.60
77.07
17.80
30,672.00
61.30
14.90
59,335.00
Total Prod. Quantity
(Mi 11 ion lbs)
• Mean
• Median
• Tota1
24.46
6.52
709.93
92,830.80
38.89
711,084.00
257.23
238.21
1 ,543.38
1,730.05
92.00
7,094.94
260.92
18.39
28,961.61
461.41
48.84
183,640.74
302.75
38.80
29,305.90
Total Prod. Value
(Mi l I ion S)
• Mean
• Median
• Total
19.66
5.97
530.93
89.68
23.79
33,721.20
160.99
123.33
965.93
189.80
142.72
7,402.34
66.89
25.52
7,425.02
125.14
29.39
49,178.30
104.23
26.21
99,223.70
Total Sales Quantity
(Miilion lbs)
• Mean
• Median
• Total
21.81
6.51
632.46
142.93
36.67
54,741.77
202.15
239.36
1,212.94
151.12
92.87
6,195.96
241.09
15.12
26,761.13
370.27
41.27
147,366.38
244.74
35.18
236,910.06
Total Sales Value
(Mi 11 ion S)
• Mean
• Median
• Total
0.03
0.01
477.78
69.23
21.69
26,512.30
126.07
123.90
756.43
165.31
116.00
6,777.60
58.59
23.00
6,503.90
100.70
26.00
40,075.00
83.79
24.00
81 ,104.40
Source: §309 Survey
2-59
-------
Table 2-33
Comparison of Mean, Median OCPSF and Total
Production Quantity by Plant and by Firm (million lbs.)
OCPSF
PRODUCTION
Median
Mean
PLANT
21.93
191.35
FIRM
10.91
412.52
TOTAL
(OCPSF and N0N-0CPSF) PRODUCTION
PLANT
38.80
302.75
FIRM
19.88
652.69
2-60
-------
Figure 2-6: Mean and Median of OCPSF and Total Production for Plants and Firms
lJ- • f^i T's! I | j |\ |
I l I \ I i t
j'ljflW A,*."* ^CTMlkl',
aco -(
32C
- JOO -I
2S5 -i
Z
c
D
£
C
2C0
INNN^vCxS
k\\\\XN!
S.W
\\1
|\W\\\\!
\\WS\\1
v/mm
'/a:\
F77777>t
' . T-
^;i
'OCT / N I r'"*i N. 1 r'"i »•"• u>Cr C"
•I wM /' I '< « < S-' ' I «w> I
JMSAN AN2 «S2!X-.'J
D(
i I r "i
600
£00
= *oo
£ yo
0
1
"Z 20C
c.
fSSS\\^i
k\\\\\V1
VvVxVj
//AWWxXt
' . \WN
< // // / / A S \ \ \ W1
K / / / / / / X \W \ \ \ N
V / / / / / 1 \\ \ \ \ \ N
v / /// y/\\\v\\s!
1CO -I,' / //'/'-'VNV-A \ \\i
r/z/Z/AXW v-.x i
"• ' ' ' ' ¦' - A \ V \ \\ \
iXV .
i\\\\
y /
' s////y\V\ , .
y > v •- s \ \ ~ ,|
V//////-
FIR'.
Source: S308 Survey.
2-61
-------
TABUS 2-34: DISTRIBUTION OF 1982 PLANT SALES QUANTITY BY OCPSF SIC GROUP
4 DIGIT HAJOR OCPSF SIC GROUP
HO SIC
2821
2S23
2824
2865
2869
ALL
NJ
I
tr>
N>
ALL
NO. OF
PLANTS
PERCENT
NO. OF
PLANTS
PERCENT
NO. OF
PLANTS
PERCENT
NO. OF
PLANTS
PERCENT
HO. OF
PLANTS PERCENT
NO. OF
PLANTS
PERCENT
NO. OF
PLANTS
PERCENT
OCPSF SALES
QUANTITY
(MILLION
LBS.)
HISSING
10
25.6
*
•
•
•
*
*
*
*
*
•
10
1.0
ZERO
29
74.4
11
2.9
*
*
2
4.9
•
*
7
1.8
49
5.0
0-.2
•
*
1&
4.2
*
*
•
6
5.4
30
7.5
52
5.3
.2-1
•
•
20
5.2
*
*
1
2.4
17
15.3
26
6.5
64
6.5
1-2
•
*
20
5.2
*
*
*
•
6
5.4
15
3.8
41
4.2
2-10
*
*
66
17.2
1
16.7
7
17.1
24
21.6
77
19.3
175
17.9
10-20
*
*
59
15.4
*
*
2
4.9
14
12.6
35
8.8
110
11.2
20-100
*
*
114
29.8
16.7
11
26.8
10
9.0
116
29.1
252
25.8
100 PLUS
*
*
77
20.1
4
66.7
18
43.9
34
30.6
92
23.1
225
23.0
ALL
39
100.0
383
100.0
6
100.0
41
100.0
111
100.0
398
100.0
978
100.0
TOTAL SALES
QUANTITY
(MILLION
LBS.)
HISSING
10
25.6
*
*
*
*
*
*
•
*
*
*
10
1.0
ZERO
2
5.1
5
1.3
*
*
2
4.9
*
5
1.3
14
1.4
0-.2
2
5.1
8
2.1
*
*
*
*
3
2.7
23
5.8
36
3.7
.2-1
2
5.1
12
3.1
*
*
1
2.4
15
13.5
13
3.3
43
4.4
1-2
1
2.6
12
3.1
*
*
*
*
6
5.4
11
2.8
30
3.1
2-10
12
30.8
42
11.0
1
16.7
6
14.6
23
20.7
68
17.1
152
15.5
10-20
5
12.8
48
12.5
*
*
2
4.9
16
14.4
35
8.8
106
10.8
20-100
10.3
152
39.7
1
16.7
11
26.8
9
8.1
109
27.4
286
29.2
100 PLUS
1
2.6
104
27.2
4
66.7
19
46.3
39
35.1
134
33.7
301
30.8
ALL
59
100.0
383
100.0
6
100.0
41
100.0
111
100.0
398
100.0
978
100.0
-------
TABLE 2-35: DISTRIBUTION OF 1982 PLANT SALES VALUE BY OCPSF SIC GROUP
4 DIGIT MAJOR OCPSF SIC GROUP
NO SIC
2S21
2823
2824
2865
2869
ALL
ALL
NO. OF
NO. OF
NO. OF
HO. OF
NO. OF
NO. OF
NO. OF
PLANTS
PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS
PERCENT
OCPSF SALES
VALUE
(MILLION t)
MISSING
10
25.6
•
•
* •
*
*
•
•
*
•
10
1.0
ZERO
29
74.4
11
2.9
* *
2
4.9
*
*
8
2.0
50
5.1
0 1
•
•
34
8.9
* *
*
*
5
4.5
39
9.8
78
8.0
1-5
*
*
76
19.8
• »
2
4.9
23
20.7
56
14.1
157
16.1
5-10
*
*
61
15.9
1 16.7
3
7.3
11
9.9
47
11.8
123
12.6
10-50
*
*
128
33.4
1 16.7
8
19.5
45
40.5
132
33.2
314
32.1
50-100
*
*
33
8.6
* *
5
12.2
10
9.0
43
10.8
91
9.3
100-500
•
*
38
9.9
4 66.7
20
48.8
17
15.3
57
14.3
136
13.9
500 PLUS
*
*
2
0.5
• *
1
2.4
•
*
16
4.0
19
1.9
ALL
39
100.0
383
100.0
6 100.0
41
100.0
111
100.0
398
100.0
978
100.0
TOTAL SALES
VALUE
(MILLION $)
MISSING
10
25.6
*
•
• •
*
•
*
•
10
1.0
ZERO
J
7.7
5
1.3
• *
2
4.9
•
A
6
1.5
16
1.6
0-1
2
5.1
15
3.9
* •
*
•
5
4.5
26
6.5
48
4.9
1-5
9
23.1
32
8.4
* *
1
2.4
15
13.5
45
11.3
102
10.4
5-10
3
7.7
56
14.6
1 16.7
3
7.3
13
11.7
33
8.3
109
11.1
10-50
9
23.1
157
41.0
1 16.7
9
22.0
47
42.3
143
35.9
366
37.4
50-100
2
5.1
58
15.1
• *
5
12.2
13
11.7
46
11.6
124
12.7
100-500
1
2.6
50
13.1
4 66.7
20
48.8
18
16.2
82
20.6
175
17.9
500 PLUS
*
*
10
2.6
• »
1
2.4
«
•
17
4.3
2B
2.9
ALL
39
100.0
383
100.0
6 mc.o
41
100.0
111
100.0
398
100.0
978
100.0
-------
Figure 2-7
)>t it i (>i i i _ . , •;. > (j - », .J"-- \
r"1, L /-», Li -3: 11 i ;V{ i \ n i _!'• iZT'
5? !
jtc.
' —¦
T
£.
-r1 .TO -i
CD
2821 2823 2824 2865 2869
2869 (49.7%)
OF !9B2 TOTAL':
\ 2821 (32.9%)
2823 (0.9%)
2824 (8.4%)
2865 (8.1%)
2-64
-------
Table 2-36: Comparison of 1982 Plant Sales to Plant Production*
Percent of ALL PLants
Sales/Production Ratio
Less than 0.8
Greater than 0.8
Source: §308 Survey.
*Data in this tabLe are based on an OCPSF industry total pLant count of
1047 plants; the total plant count used in the rest of the analysis is 997.
OCPSF Sales Total Plant Sales
Quantity Value Quantity Value
18 16 16 15
82 84 84 85
2-65
-------
Median plant sales quantities were 19.45 million pounds for OCPSF sales and
35.18 million pounds for total sales. Mean plant sales quantities were 156.47 million
pounds for OCPSF sales and 244.74 million pounds for total sales. These sales generally
represented about 80 percent of production.
The median OCPSF value of shipments was $14.9 million, while the median total
plant value of shipments was $24.0 million. These median shipment values represented
about 90 percent of median plant production. Mean value of shipments were $61.3
million for OCPSF sales and $83.79 million for total plant sales, representing 80 percent
of mean plant production. In general, larger plants had lower sales to production ratios
because of the greater degree to which they are vertically integrated.
2.8.5 Production Costs
Total plant production costs (which include all expenses except capital-related
£
ones) were calculated from §308 Survey data and labor cost data. Table 2-37 shows the
distribution of plant production costs by SIC group as well as the ratio of these costs to
total plant sales value (Table 2-38). Mean, median and total values for production costs,
employment, and productivity are shown in Table 2-39.
The median total production cost level was $14.66 million, while the mean level
was $57.96 million. Comparable figures for total plant sales median and mean values
were $24.0 and $83.79 million, respectively. About 56 percent of the plants had
* *
production cost to sales ratios of greater than 0.6.
2.8.6 Employment
Tables 2-40 and 2-41 present the distribution of both OCPSF-related and overall
firm and plant employment, while mean, median and total employment values are shown
in Table 2-39. Median plant OCPSF employment in 1982 was 39 (about one-half of the
median total plant employment of 82). Mean OCPSF employment was 192, and mean
total plant employment was 297. The highest percentage (31 percent) of plants employed
between 10 and 50 persons in OCPSF-related work. The distribution of total plant
&
Labor cost was calculated using employment data from the §308 Survey and
the hourly wage rates (including all benefits) from Chemical Week.
Plants with cost/sales ratios greater than one represent either reporting
errors or plants that increased inventory.
2-66
-------
TABLE 2-37:
DISTRIBUTION OF 1982 PLANT PRODUCTION COSTS BY OCPSF SIC CROUP
4 DIGIT MAJOR OCPSF SIC GROUP
NO SIC
2821
-O
NO. OF
NO. OF
PLANTS PERCENT PLANTS PERCENT
PRODUCTION
COSTS
(MILLION S)
HISSING
0-1
1-5
5-10
10-50
50-100
100-500
OVER 500
ALL
2
8
11
5
11
1
5.1
20.5
28.2
12.8
28.2
2.6
1 2.6
39 100.'
15
34
52
67
151
30
33
1
383
2823
NO. OF
PLANTS PERCENT
2824
2865
3.9
8.9
13.6
17.5
39.4
7.8
8.6
0.3
100.0
NO. OF
PLANTS PERCENT I PLANTS PERCENT
NO. OF
33.3
33.3
33.3
*
100.0
6
1
13
3
17
2.4
*
14.6
2.4
31.7
7.3
41.5
41 100.0
2
10
23
12
46
4
12
2
111
2869
NO. OF
PLANTS PERCENT
1.8
9.0
20.7
10.8
41.4
3.6
10.8
1.8
100.0
13
38
59
52
126
40
58
12
398
3.3
9.5
14.8
13.1
31.7
10.1
14.6
3.0
100.0
ALL
NO. OF
PLANTS PERCENT
33
90
151
137
349
80
122
16
978
3.4
9.2
15.4
14.0
35.7
8.2
12.5
1.6
100.0
-------
TABLE 2-38:
DISTRIBUTION OF 1982 PLANT PRODUCTION COSTS TO SALES VALUE RATIO
NO SIC
MO. OF
PLANTS PERCENT
2821
NO. OF
PLANTS PERCENT
BY OCPSF SIC GROUP
4 DIGIT HAJOR OCPSF SIC GROUP
2823
NO. OF
PLANTS PERCENT
2824
NO. OF
PLANTS PERCENT
2865
NO. OF
PUNTS PERCENT
2669
HO. OF
PLANTS PERCENT
ALL
NO. OF
PLANTS PERCENT
RATIO OF
PROO. COSTS
TO SALES
VALUE
to
I
00
HISSING
13
33.3
17
4.4
*
*
3
7.3
2 .
1.8
17
4.3
52
5.3
0-0:2
2
5.1
2S
7.3
*
*
1
2.4
3
2.7
28
7.0
62
6.3
0.2-0.A
3
7.7
25
6.5
•
•
2
4.9
9
6.1
35
8.8
74
7.6
0.4-0.6
7
17.9
89
23.2
3
50.0
17
41.5
29
26.1
92
23.1
237
24.2
0.6-0.8
8
20.5
117
30.5
2
33.3
14
34.1
41
36.9
116
29.1
298
30.5
0.8-1.0
2
5.1
72
18.8
*
*
3
7.3
18
16.2
53
13.3
148
15.1
OVER 1.0
4
10.3
35
9.1
1
16.7
1
2.4
9
8.1
57
14.3
107
10.9
ALL
39
100.0
383
100.fi
6
100.0
41
100.0
111
100.0
393
100.0
978
100.0
-------
Table 2-39
Plant 1982 Production Costs, Empleyment and Productivity
by SIC Group
Major OCPSF Group
No SIC
2821
2823
2824
2865
2869
ALL
OCPSF Prod. Costs
(Mi 11 ion 1bs)
• Mean
• Median
• Total
»
»
•
25.63
8.48
9,407.80
66.84
56.14
401 .06
99.84
66.51
3,793.88
39.. 10
10.38
4,261.77
53.75
9.19
20,640.00
41 .36
9.15
38,510.00
Total Prod. Costs
(Mi 11 ion S)
• Mean
• Median
• Total
113.32
4.44
4,192.67
33.58
13.56
12,360.00
80.32
85.25
481.90
99.08
49.81
3,963.20
53.10
15.42
5,784.62
72.70
15.65
27,990.00
57.96
14.66
54,770.00
OCPSF Employment
• Mean
• Median
• Total
61 .17
36.00
2,141.00
97.45
29.25
37,030.50
1,301.17
1,105.00
7,807.00
1,064.02
559.00
42,560.80
160.83
49.00
17,851.70
193.56
42.86
75,488.70
190.10
39.00
182,880.00
Total Employment
• Mean
• Median
• Total
128.61
47.50
4,887.00
230.62
59.00
77,578.60
1,330.50
1,110.00
7,983.00
1,151.09
713.00
46,043.70
160.83
91.98
31,431.50
303.39
91 .00
120,448.00
296.37
84.00
288,372.00
OCPSF Productivity
(t/Emp.)
• Mean
• Median
t
*
604,500.00
440,408.00
102,295.00
113,071.00
227,323.15
142,163.00
569,320.00
280,355.00
322,240.00
412,222.00
461,867.00
382,683.00
Total Productivity
(S/Emp.)
• Mean
• Median
223,513.00
152,116.00
4,652,422
352,017.00
99,994.60
117,048.00
214,424.00
132,782.00
459,869.00
240,765.00
471 ,517.00
308,245.00
2,101,843.
301,564.00
2-69
-------
TABLE 2-40:
EMPLOYMENT-
ORGAN ICS
HISSING
ZERO
0 TO 1
1 TO 5
5 TO 10
10 TO 50
50 TO 100
100 TO 500
500 PLUS
ALL
EMPLOYMENT-
TOTAL
HISSING
ZERO
0 TO 1
1 TO 5
5 TO 10
10 TO 50
50 TO 100
100 TO 500
500 PLUS
ALL
NO SIC
NO. OF
FIRMS PERCENT
4 16.0
1 4.0
• *
5 20.0
3 12.0
7 28.0
3 12.0
1 4.0
1 4.0
25 100.0
1 4.0
1 4.0
* *
1 4.0
3 12.0
10 40.0
4 16.0
3 12.0
2 8.0
25 100.0
2821
I NO. OF
| FIRMS PERCENT
2 1.2
6 3.7
26 15.9
18 11.0
57 34.8
20 12.2
21 12.8
14 8.5
164 100.0
1 0.6
* *
2 1.2
10 6.1
12 7.3
52 31.7
25 15.2
37 22.6
25 15.2
164 100.0
DISTRIBUTION OF 1982 FIRM EMPLOYMENT BY OCPSF SIC CROUP
MAJOR SIC GROUP
2823 2824 2865 2869 ALL
ALL
NO. OF I NO. OF I NO. OF I NO. OF I NO. OF
FIRMS PERCENT FIRMS PERCENT FIRMS PERCENT FIRMS PERCENT FIRMS PERCENT
*
•
•
*
*
2
1.0
6
*
•
•
•
•
2
1.0
5
*
*
*
1
1.9
6
3.1
13
•
•
•
*
•
23
11.8
54
*
1
6.7
4
7.7
12
6.2
38
*
1
6.7
24
46.2
63
32.3
152
*
4
26.7
5
9.6
24
12.3
56
*
5
33.3
12
23.1
32
16.4
71
100.0
4
26.7
6
11.5
31
15.9
60
100.0
15
100.0
52
100.0
195
100.0
455
*
*
•
*
•
1
0.5
3
*
*
*
*
*
*
*
1
*
*
*
1
1.9
•
*
3
*
*
*
*
*
11
5.6
22
*
1
6.7
3
5.8
9
4.6
28
*
1
6.7
21
40.4
57
29.2
141
*
4
26.7
5
9.6
29
14.9
67
*
5
33.3
16
30.8
44
22.6
105
100.0
4
26.7
6
11.5
44
22.6
85
100.
15
100.0
52
100.0
195
100.0
455
1.3
1.1
2.9
11.9
8.4
33.4
12.3
15.6
13.2
100.0
0.7
0.2
0.7
4.8
6.2
31.0
14.7
23.1
18.7
100.0
-------
TABLE 2-41: DISTRIBUTION OF 1982 PLANT EMPLOYMENT BY OCPSF SIC CROUP
4 DIGIT MAJOR OCPSF SIC GROUP
NO SIC
2821
2823
2824
2865
2869
ALL
ALL
1 NO. OF
NO. OF
NO. OF
NO. OF
NO. OF
NO. OF
NO. OF
| PLANTS
PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS
PERCENT
OCPSF
EMPLOYMENT
HISSING
10.3
3
0.8
* *
1
2.4
*
*
9
2.3
17
1.7
ZERO
1
2.6
2
0.5
• »
•
*
*
4
1.0
7
0.7
0-1
*
m
8
2.1
* •
*
*
1
0.9
10
2.5
19
1.9
1-5
6
15.4
39
10.2
• *
*
•
3
2.7
34
8.5
82
8.4
5-10
3
7.7
38
9.9
• *
1
2.4
6
5.4
26
6.5
74
7.6
10-50
12
30.8
170
44.4
• •
1
2.4
49
44.1
140
35.2
372
38.0
50-100
8
20.5
51
13.3
• »
6
14.6
15
13.5
57
14.3
137
14.0
100-500
5
12.8
56
14.6
1 16.7
11
26.8
29
26.1
86
21.6
188
19.2
500 PLUS
«
*
16
4.2
5 83.3
21
51.2
8
7.2
32
8.0
82
8.4
ALL
39
100.0
383
100.0
6 100.0
41
100.0
111
100.0
398
100.0
978
100.0
TOTAL
EMPLOYMENT
MISSING
1
2.6
2
0.5
* *
1
2.4
-*
*
1
0.3
5
0.5
ZERO
1
2:6
*
*
• *
•
*
•
*
*
•
1
0.1
0-1
*
•
2
0.5
* *
*
*
1
0.9
*
*
3
0.3
1-5
1
2.6
10
2.6
* *
*
*
1
0.9
12
3.0
24
2.5
5-10
3
7.7
17
4.4
* *
1
2.4
4
3.6
13
3.3
38
3.9
10-50
15
38.5
143
37.3
* *
1
2.4
37
33.3
117
29.4
313
32.0
50-100
5
12.8
58
15.1
# *
4
9.8
18
16.2
66
16.6
151
15.4
100-500
11
28.2
112
29.2
1 16.7
12
29.3
37
33.3
130
32.7
303
31.0
500 PLUS
2
5.1
39
10.2
5 83.3
22
53.7
13
11.7
59
14.8
140
14.3
ALL
39
100.0
383
100.0
6 100.0
41
100.0
111
100.0
398
100.0
978
100.0
-------
.employment, however, was bimodal; the most frequent employment levels were 10 to 50
and 100 to 500 persons. This bimodality reflects the size differential between diversified
and non-diversified plants and firms.
Fiber-related firms and plants—both ceiluiosic (SIC 2323) and synthetic (SIC
2S24)— had significantly higher than average employment, while plastics plants (SIC 2S21)
had slightly lower than average OCPSF plant employment.
2.8.7 Labor Productivity
Table 2-42 presents the distribution of plant productivity by 4-digit SIC group.
Productivity was calculated in terms of dollars of production value per employee for both
OCPSF and total production (mean, median and total values are presented in Table 2-
40). The largest percentage of plants had productivity values between $100,000 and
$500,000 per employee for both OCPSF and total production (46 and 59 percent,
respectively). The median total plant productivity was $301,564, while the median plant
OCPSF productivity was $382,683 per employee.
Fiber production (both ceiluiosic and non-cellulosic) was more labor intensive
(i.e. less productive) than either intermediate chemical or plastics production. Median
fiber productivity was $113,071 for SIC 2823 and $142,163 for SIC 2824. A summary of
the plant productivity values in Table 2-42 is shown in Table 2-43.
2.8.8 Capital Expenditures
Table 2-44 presents the distribution of capital expenditures on new and used
equipment by plants in 1982 by SIC group. Mean, median and total vaiues for capital
expenditures are shown in Table 2-45. Over 50 percent of the plants spent less than one
million dollars for capital expenditures, while about 20 percent spent over 5 million
dollars. Of all expenditures, the vast majority were for new equipment; only about 20
percent of the plants purchased any used equipment. Average annual expenditures
amounted to 6.5 million dollars for new equipment and 0.1 million dollars for used
equipment.
Synthetic fiber plants (SIC 2824) and industrial organic chemicals plants (SIC
2869) showed significantly higher than average capital expenditures, whereas producers
of plastics and resins (SIC 2821) had lower than average capital expenditures.
2-72
-------
TABLE 2 42: DISTRIBUTION OF 1982 PLANT PRODUCTIVITY BY OCPSF SIC CROUP
4 DIGIT MAJOR OCPSF SIC CROUP
HO SIC 2021 2823 2624 2865 2869 ALL
I NO. OF I MO. OF I NO. OF I NO. OF I NO. OF I NO. OF I NO. OF
I PLANTS PERCENT | PLANTS PERCENT j PLANTS PERCENT ) PLANTS PERCENT ] PLANTS PERCENT j PLANTS PERCENT j PLANTS PERCENT
OCPSF
PRODUCTIVI•
TT (S/EHPl)
HISSING
39
100.0
18
4.7
•
*
3
7.3
*
*
20
5.0
80
8.2
0-10,000
«
*
1
0.3
•
•
•
•
1
0.9
9
2.3
11
1.1
10,000-
50,000
*
*
6
1.6
2
33,3
1
2.4
4
3.6
12
3.0
25
2.6
50,000
100,000
*
*
IS
4.7
*
•
9
22.0
8
7.2
15
3.8
50
5.1
100,000-
500,000
*
*
177
46.2
4
66.7
25
61.0
71
64.0
178
44.7
455
46.5
500,000-
1,000,000
4
*
118
30.8
*
•
2
4.9
14
12.6
91
22.9
225
23.0
1,000,000
PLUS
*
*
45
11.7
•
*
1
2.4
13
11.7
73
18.3
132
13.5
ALL
19
100.0
383
100.0
6
100.0
M
100.0
111
100.0
398
100.0
978
100.0
TOTAL
PRODUCTIVI-
TY (S/EHPL)
HISSING
13
33.3
9
2.3
*
*
3
7.3
-*
*
6
1.5
31
3.2
ZERO
1
2.6
*
»
#
•
*
*
*
*
1
0.3
2
0.2
0-10,000
1
2.6
#
•
«
•
•
*
1
0.9
9
2.3
11
1.1
10,000-
50,000
3
7.7
a
2.1
2
33,3
i
2.4
4
3.6
11
2.8
29
3.0
50,000-
100,000
5
12.8
22
r>.7
*
*
9
22.0
6
5.4
20
5.0
62
6.3
100,000-
500,000
13
33.3
226
59.0
4
66.7
26
63.4
78
70.3
230
57.8
577
59.0
500,000-
1,000,000
3
7.7
93
24.3
*
*
1
2.4
10
9.0
85
21.4
192
19.6
1,000,000
PLUS
*
*
25
6.5
«
•
1
2.4
12
10.8
36
9.0
74
7.6
ALL
39
100.0
383
100.0
6
100.0
41
100.0
111
100.0
398 "
100.0
978
100.0
-------
Table 2-43
Summary of 1982 Plant Labor Productivity
Plant Productivity
($/employee)
Percent of All Plants1
OCPSF-production Total production
$ 0 - 100,000
$100,000 - 500,000
$500,000 and above
9.6
50.7
39.8
11.0
60.9
28.1
100.0
100.0
Source: §308 Survey
if
Excludes plants with missing data.
2-74
-------
TABLE 2-44: DISTRIBUTION OF CAPITAL EXPENDITURES BY MAJOR SIC GROl'P
NO SIC 2821
| HO. OF | MO. OF
| PLANTS PERCENT j PUNTS PERCENT
MAJOR QCPSf SIC GROUP
2823 2824
2B65
2&69
NO. OF I HO. OF I NO. OF f *0- OF | NO, OF
PLANTS PERCENT | PLANTS PERCENT | PLANTS PERCENT j PLANTS PE3CENT | PLANTS
ALL
PERCENT
CAP. EXPENO
ON NEW
EQUIP.
(MILLION 1)
MISSING
7
17.9
27
7.0
• •
2
4.9
3
2.7
16
4.0
55
5.4
IERO
1
2.6
1ft
4.7
• «
3
7.3
3
2.7
16
4.0
41
4.2
0-1
25
64.1
231
60.3
2 J3.3
8
19.5
64
57.7
174
43-7
504
51.5
1-5
3
7.7
68
17.8
• *
7
17.1
21
18.9
97
24.4
196
20.0
5-10
0
«
19
S.O
3 50.0
8
19.5
10
9.0
28
7.0
66
7.0
10-50
2
5.1
18
t. 7
1 16.7
12
29.3
9
8.1
54
13.6
96
9.8
50-100
•
•
2
0.5
• •
•
'•
•
•
3
0.8
5
0.5
100-500
1
2.6
•
•
* •
1
2.4
1
0.9
9
2.3
12
1.2
OVER 500
«
•
•
•
• •
•
*
•
•
1
0.3
1
0.1
ALL
39
100.0
383
100.0
6 100.0
41
100.0
111
100.0
398
100.0
97B
100.0
CAP. EXPEND
ON USED
EQUIP.
(MILLION t)
MISSING
. 18
(6.2
107
27.9
1 16.7
¦14
34.1
22
19.8
96
24,1
258
26.4
ZERO
14
35.9 .
2t2
55.4
t (6.7
21
51.2
67
60.4
228
57.3
543
55.5
0-1
5
12.8
61
15.9
3 50.0
5
12.2
21
18.9
67
16.a
162
16.6
1-5
1
2.6
J
o.a
1 16.7
•
•
1
0.9
5
1.3
11
1.1
5-\0
*
•
•
•
» •
1
2.4
•
•
2
C.5
J
10-50
1
2.6
•
•
» •
•
•
•
•
•
1
ALL
TOTAL
CAPITAL
EXPEND*
I TUBES
(MILLION 1)
39
100.0
303
100.0
6 100.0
41
100.0 '
111
100.0
398
100.0
9-3
KISSING
5
12.8
20
5.2
• •
1
2.4
1
0.9
10
2.5
37
3.8
ZERO
2
5.1
14
3.7
• •
•
•
1
0.9
16
4.0
33
0-1
25
64.1
239
62.4
2 33.3
11
26.8
68
61.5
179
45.0
524
1-5
2
5.1
71
18.5
• «
6
19.5
20
18.0
95
23.9
196
20.0
5-10
1
2.6
19
5.0
3 50.0
6
19.5
11
9.9
29
7.3
71
10-50
3
7.7
18
4,7
1 16.7
12
29,3
9
8.1
56
14.1
99
.50-100
•
*
2
0.5
• •
•
•
•
•
3
o.a
5
0.5
100-500
1
2.6
•
•
• •
1
2.4
1
0.9 "
9
2.3
2 1
OVER 500
•
•
•
•
• •
•
•
-
-
1
0.3
1
0.1
ALL
39
100.0
533
100.0
6 100.0
61
100.0
hi
too.o
393
100.0
973
100.0
2-75
-------
TaDle 2-45
Plant Age and Capital Expenditures by SIC Group
Major OCPSF Group
No SIC
2821
2823
2824
2865
2869
ALL
Plant Age
~ Mean
• Median
16.18
13.00
20.84
19.00
40.50
38.00
18.41
17.00
27.83
24.00
21 .54
20.00
21 .76
20.00
Capital Expenditure
on New Equipment
• Mean
• Median
• Tota1
5.53
0.18
176.85
2.56
0.31
910.47
7.12
7.62
42.64
11.36
5.96
443.22
4.19
0.50
452.92
10.38
1 .04
3,965.43
6.49
0.57
5,991.53
Capital Expenditure
on Used Equipment
• Mean
• Median
• Total
0.70
0.00
14.61
0.04
0.00
12.37
0.42
0.07
2.09
0.31
0.00
8.48
0.07
0.00
5.87
0.08
0.00
24.15
0.09
0.00
67.58
Total Capital
Expenditures
• Mean
• Med i an
• Total
9.84
0.39
187.01
2.46
0.23
660.42
7.57
8.53
37.86
9.61
7.13
249.91
3.76
0.53
327.54
1 1 .52
0.99
3,411.29
6.94
0.59
4,874.04
Source: §308 Survey
By Millions of 1982 dollars.
2-76
-------
2.5.9 Plant Age
Table 2-46 presents the distribution of plant age by four-digit SIC group.
Means, medians and totals are given in Table 2-47. Age was defined as the age of the
plant site, and does not necessarily correspond to the age of a particular production
line. Therefore, "Plant Age" can be misleading, since plants tend to have major
replacements every 10 to 15 years. The majority (about 85 percent) of the plants that
responded to the §308 Survey were over 10 years old in 1982, while about 35 percent
were over 30 years old. The median age was 24 years. Plants in SIC 2865 and 2823
tended to be older, with 50 and 83 percent of these plants, respectively, being over 30
years old. By contrast, plants in SIC 2824 tended to be younger, reflecting the recent
growth of the non-cellulose synthetic fibers industry as compared to plastics.
2.3.10 Discharge Status
Table 2-47 presents the distribution of discharge status by SIC code. Indirect
dischargers were the most common, involving about one-third of .the plants. Direct
discharge was the second most common status, involving about one-quarter of the
plants. Other forms of disposal (deep well, contract hauling and private systems) were
used exclusively by about 10 percent of the plants, although nearly one-quarter of the
plants employed these methods to some degree. Fibers plants (both SIC 2823 and 2824)
were more likely to be direct dischargers than other plants.
2.8.11 Plant Locations
Plants in the OCPSF industry are concentrated in the North Central,.Mid-
Atlantic, Southeastern, and Southwestern states. EPA Regions II, III, IV, V and VI
contained 82.5 percent of the 980 plants. Regions I, VII, VIII, IX, and X—which include
the northeastern and western states, Hawaii and Alaska— only accounted for 17.5
percent of the plants. New Jersey and Texas alone accounted for 23 percent of the
plants, with 119 and 109 plants, respectively. Table 2-48 presents plant distribution by
state and by region.
2.8.12 Type of Firm Ownership
Table 2-49 presents the distribution of firms by SIC group and by type of
ownership. Of firms for which the ownership was known, private and public ownership
each accounted for about 91 percent of total firm ownership, while foreign ownership
accounted for 9 percent. This distribution did not vary significantly by SIC group.
2-77
-------
Table 2-46
Distribution of Plant Age by Major OCPSF SIC Groups
MAJOR OCPSF SIC GROUP
NO SIC
2821
2823
2824
2865
2869
ALL
ALL
NO. OF
NO. OF
NO. OF
NO. OF
NO. OF
NO. OF
NO. OF
PLANTS
PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLANTS
PERCENT
AGE OF
PLANT IN
1982(YEARS)
HISSING
1
2.6
3
0.8
# *
*
•
*
#
2
0.5
6
0.6
NEW
*
*
2
0.5
* *
*
*
•
*
4
1.0
6
0.6
1 OR LESS
1
2.6
5
1.3
* *
•
*
1
0.9
6
1.5
13
1.3
1 TO 5
5
12.B
12
3.1
* *
3
7.3
10
9.0
21
5.3
51
5.2
5 TO 10
3
7.7
40
10.4
* *
5
12.2
6
5.4
27
6.8
81
8.3
10 TO 20
15
38.5
109
28.5
• •
14
34.1
22
19.8
95
23.9
255
26.1
20 TO 30
9
23.1
92
24.0
1 16.7
12
29.3
15
13.5
103
25.9
232
23.7
30 PLUS
5
12.8
120
31.3
5 83.3
7
17.1
57
51.4
140
35.2
334
34.2
ALL
39
100.0
383
100.0
6 100.0
41
100.0
111
100.0
398
100.0
978
100.0
-------
Table 2-47
Distribution of Plant Discharge Status by Major OCPSF SIC Groups
MAJOR OCPSF SIC CROUP
HO SIC
2821
2823
2824
2865
2869
ALL
ALL
1 NO. OF
1
1 NO. OF
I NO. OF
I NO. OF
1 NO. OF
I NO. OF
1 NO. OF
| PLANTS
PERCENT
| PLANTS PERCENT |
| PLANTS PERCENT
| PLANTS PERCENT j
| PLANTS PERCENT |
| PLANTS
PERCENT
| PLANTS
PERCENT
DISCHARGE
STATUS
DIRECT &
INDIR
2
5.1
5
1.3
•
*
1
2.4
3
2.7
6
1.5
17
1.7
DIRECT &
OTHER
*
•
•
*
•
*
*
*
*
*
1
0.3
1
0.1
DIRECT ONLY
1
2.6
90
23.5
6
100.0
23
56.1
34
30.6
135
33.9
289
29.6
INDIRECT &
OTH
*
•
2
0.5
*
*
•
*
*
•
2
0.5
4
0.4
INDIRECT
ONLY
12
30.S
162
42.3
•
*
8
19.5
63
56.8
156
39.2
401
41.0
UMKNOUM
2
5.1
5
1.3
*
*
*
*
*
*
5
1.3
12
1.2
ZERO
22
56.4
119
31.1
*
*
9
22.0
11
9.9
93
23.4
254
26.0
ALL
39
100.0
383
100.0
6
100.0
41
100.0
111
100.0
398
100.0
978
100.0
-------
Table 2-48
Location of OCPSF Plants
Number of Percent of
PI ants All PI ants
Region I 54 5.5
Maine 2 0.2
New Hampshire 4 0.4
Vermont 0 0.0
Massachusetts 22 2.2
Connect i cut 17 1.7
Rhode Island 9 0.9
Region 2 161 16.4
New York 45 4.6
New Jersey 114 11.9
Puerto Rico 2 0.2
Virgin Islands 0 0.0
Reg I on 3 86 11.3
Pennsylvania 45 4.6
West Virginia 22 2.2
V i rg i n i a 24 2.4
DeI aware 9 0.9
Mary I and 10 1.0
Region 4 185 18.9
Kentucky 21 2.1
Tennessee 19 1.9
North Carolina 41 4.2
South Carol ina 39 4.0
Mississippi 12 1.2
Alabama 23 2.3
Georgia 18 1.8
Florida 12 1.2
Region 5 184 18.8
Minnesota 4 0.4
Wisconsin 13 1.3
lilt noi s 56 5.7
Michigan 23 2.3
Indlana 13 1.3
Ohio 75 7.7
Number of Percent of
PI ants All Pi ants
Region 6 166 16.9
New Mexico 0 0.0
Texas 108 11.0
Oklahoma 2 0.2
Arkansas 8 0.8
Louisiana 48 4.9
Region 7 27 2.8
Nebraska 1 0.1
lowa 7 0.7
Kansas 4 0.4
Missouri 15 1.5
Region 8 7 0.7
Montana 1 0.1
North Dakota 0 0.0
South Dakota 0 0.0
Wyoming 0 0.0
Utah 2 0.2
Colorado 4 0.4
Region 9 68 6.9
CaIi forn i a 68 6.8
Nevada 0 0.0
Ari*ona 0 0.0
Hawaii 0 0.0
Reg i on 10 18 1.8
Washington 8 0.8
Oregon 10 1.0
Idaho 0 0.0
Alaska 0 0.0
TOTAL 980 100.0
Source: §308 Survey Mailing List. Percents may not total due to rounding
2-80
-------
Table 2-49
Distribution Aaong SIC Groups by Type
Of Ownership Production Value
Number of Firms by Major SIC
Hissing
2821
2823
2824
2865
2869
Al 1
Ownersh i p
N
N .
N
N
N
N
N
FOREIGN
•
14.00
1.00
1.00
5.00
15.00
36.00
PRIVATE
11.00
58.00
2.00
6.00
22.00
71.00
170.00
PUBLIC
6.00
62.00
1.00
7.00
18.00
05.00
179.00
UNKNOWN
8.00
30.00
•
1.00
7.00
24.00
70.00
ALL
25.00
164.00
4.00
15.00
52.00
195.00
455.00
2-81
-------
Tables 2-50 and 2-51 present the distribution of firms OCPSF employment and
production values by type of ownership. Foreign and publicly owned firms tended to be
larger, while private firms were generally significantly smaller.
2-82
-------
Table 2-50
Firm OCPSF Employment by Type of Ownership
Type of Firm Ownership and Percent of
EmpIoymen t Firms at Each Employment Level
Levels (persons) Pub Ii c Pr i vate Fore i qn Unknown AlI Types
0-5 19 0 13 6
5-10 18 3 16 6
10-50 19 46 8 37 31
50-100 14 14 19 16 15
100-500 29 20 39 15 23
over 500 37 3 31 3 19
100 100 100 100 100
Number of Firms* 179 169 36 68 452
Source: §308 Survey
Excludes Firms missing employment values. Percentages nay not total due to rounding.
Table 2-51
Fira OCPSF Value of Shi patents by Type of Ownership
OCPSF value of Shipaents
(mi 11 ion do!lars)
Types
0-5
5-10
10-50
50-100
100-500
over 500
Pub Iic
10
8
30
13
22
17
100
Type of Firm Ownership and Percent of
Firms at Each Level of Shipments
Private
52
3
31
6
6
1^
100
Foreign
6
6
25
19
19
14
100
Unknown
46
21
21
6
6
0
100
Al I
30
8
29
10
10
9
100
Number of Firms*
Source: §308 Survey
178
151
* Excludes firms missing value of shipments data.
Percentages may not total due to rounding.
36
68
433
2-83
-------
3.0 METHODOLOGY
3.1 Introduction and Overview
The economic analysis is designed to evaluate the economic achievability of
the regulations as defined by the Clean Water Act and to examine their' impacts on
small businesses as required by the Regulatory Flexibility Act. These measures of
achievability or impact include:
• The total national cost of the regulations
• Employment losses and associated community effects
International trade competitive effects
• Impacts on existing plants (closures, profitability and sales
impacts)
• Effects on new plants planned for construction after promulgation
of the regulations.
• Effects on small plants
This chapter describes the methodology used to measure the economic effects of the
regulation. The overall structure of the analysis is summarized in Figure 3-1.
Inputs to the analysis consist of a description of industry baseline financial and
operating conditions, costs of compliance with effluent guidelines and cost of
compliance with other regulatory programs. The industry baseline description is
derived, on the one hand, from the Agency's §308 survey of the 997 plants in the
industry and, on the other hand, from financial profiles of the industry compiled by Dun
<5c Bradstreet, COMPUSTAT and Robert Morris Associates. Plant-specific compliance
costs developed by the Agency serve as inputs to the analyses. These costs are broken
down into capital, land and operating costs and reflect costs for wastewater treatment
and monitoring and sludge treatment and disposal. The analysis also incorporates
RCRA and Superfund requirements into the baseline estimates of costs for industry.
As shown in Figure 3-1 the key analytical building blocks for the analysis are
the plant, firm and national level analyses. These analyses differ in both the entities
being examined and the kinds of questions being asked. Generally speaking, the
analyses are performed from the following perspectives:
• The plant level analysis is the central component of the economic
impact assessment methodology. Compliance costs are incurred at
the plant level. These costs, together with baseline conditions, are
3-1
-------
Figure 3-1
Economic Impact Analysis of Organic Chemicals, Plastics,
and Synthetic Fibers Industry Effluent Limitations Guidelines:
Analytic Components
/////////////////
/// Basel ine ////
////Condition////
// (including ///
/// RCRA and ////
// Superfund ////
//// Costs) /////
/////////////////
/////////////////
// CompIi ance ///
/ Capital, Land /
/ and Operating /
/ Costs, inclu- /
/ding sludge ///
/ treatment and /
// disposal /////
/////////////////
WNWWWWWWW
National Social
\\\\\ Costs XXXXX
WNWWWWWWW
\w\wwwwww\
\ww\wwww\w
\www\w\www
\\wwwww\ww
\w\wwwww\w
\www\www\w
WNWWWWWWW
WW\ Plant \ww
\WW Level WW\
WW Analysis \W
WWWWWWWXW
\ww\wwwww\
\w\wwwwww\
\\w\wwwwww
\ww\wwww\w
\ww\wwww\w
WWWWWWWXW
WWWWWWWXW
wwxwwwwwxx
wwxxxxwxxwwx
wwwwwxwxwx
wwwxwxwwxw
WWWWWWWXW
WWWWWWWXW
wwwwwxxwxxx
wwwwwxwww
National Social
Costs
PI ant
Impacts
Employment
Impacts
—>
Smaii Plant
Impacts
Production
Commun i ty
Impacts
ReguIatory
FlexibiIi ty
Ana Iysi s
Foreign Trade
impacts
New Source¦
Impacts
WWWWWWWXW
W Firm Level XXX
XXX Analysis WW
WW\X\XW\XXWXX
WWWWWWWWX
impacts
|///| = Data Inputs
| W\| = Analytical Outputs
Key Analytical Components
3-2
-------
used to conduct the plant closure analysis. In the plant closure
analysis, plant level costs are examined initially from the
perspective of corporate management to determine whether the
corporation would be better off keeping a plant in operation or
closing the plant and selling it at its liquidation value.
• The firm level analysis is performed from the perspective of
stockholders and lending institutions who will be sources of new
equity or debt capital in order to assess its financial viability.
Assuming that, at a corporate level a decision is made to keep a
plant in operation, lending institutions will be concerned with the
extent to which a firm is already committed to debt obligations
and with its ability to meet its fixed interest obligations.
Stockholders will be concerned with decreases in firm profitability
which makes stocks less attractive by reducing either dividends or
retained earnings.
• The national analysis derives from the plant-level analysis and
examines the cost to society of the regulations. This analysis
differs in certain important respects from the plant and firm level
analyses. First, unlike the firm and plant level analyses it does not
account for tax benefits (interest deductions or depreciation)
because these benefits are regulatory costs borne by the
government rather than by the firm. Second, future costs are
discounted not at the costs of capital to the firm (which accounts
for risk and tax components) but at society's opportunity costs of
capital.
The outputs of the analysis are estimates of the measures of economic achievability and
impact specified by the Clean Water Act and the Regulatory Flexibility Act. The
direct outputs of the plant and national analyses are the national cost of the
regulations, expressed in terms of 1982 dollars which, in turn, ire used to develop
estimates of effects on new plants and on expansion of existing plants. The outputs of
the plant closure analysis are estimates of the production and employment losses
associated with plant closures, balance of trade impacts due to production losses, and of
community impacts resulting from employment losses.
The plant closure analysis is also the primary basis for the small plant analysis
which is required by the Regulatory Flexibility Act. This analysis is designed to
determine whether the regulation will have disproportionately greater effects on small
plants and the extent to which these effects can be mitigated by modifications in the
design of the regulation.
The remainder of this chapter describes the data and methodology used to
estimate these impacts. After a description of the data sources in Section 3.2, Section
3.3 presents the methods used to derive baseline estimates of national, industry, firm
3-3
-------
and plant level parameters. Section 3A describes the assumptions and procedures used
to estimate the firm and plant level impacts. This is followed by discussions of the
methodology employed to estimate industry-wide impacts (Section 3.6), employment
impacts (Section" 3,7) and community impacts (Section 3.8). Procedures for assessing
the impacts on small businesses and implications for use in the regulatory flexibility
analysis are summarized in Section 3.9. A more complete description is contained in
the Regulatory Flexibility Analysis Report. Methods for estimating international trade
effects are described in Section 3.10, followed by a discussion of procedures used to
estimate the impact of the regulation of new effluent sources (Section 3.11). The
chapter culminates in a section which describes the methodology used to estimate
national social costs.
3.2 Data Sources
The economic impact analysis employs data from many sources at differing
levels of aggregation. Survey data collected under Section 308 of the Clean Water Act
include plant-specific information on OCPSF production, value of shipments,
employment and wastewater flows. Plant level' financial data are derived from firms in
Dun <5c Bradstreet's Financial Profile (D<3cB> data base and Robert Morris Associates
(RMA), while firm level financial information is obtained from COMPUSTAT. The Data
Resources, Inc. (DRD data base and forecasting models provide product-specific
economic information, OCPSF industry statistics and U.S. macroeconomic data. Data
from the Bureau of Economic Analysis (BEA) and the Bureau of Labor Statistics (BLS)
supplement the DRI macroeconomic information; the International Trade Commission
(ITC) and the Bureau of the Census provide additional OCPSF industry data.
Figure 3-2 shows how these data sources are integrated into the impact assess-
ment. The important analytical components are presented in the center of the figure.
These are projected for the baseline year (1988) as discussed in Section 3.3 and then,
with the addition of treatment costs provided by EPA, are used in the impact analysis
which is described in Sections 3.4 through 3.11. Data sources, databases and models are
shown on the left-hand side of the figure.
Wherever possible and appropriate in the analysis, data drawn directly from
the regulated plants or firms are used. However, in cases where the required
information is not directly available or suitable, aggregate or publicly available data
are used. Of the various data sources, only the data from COMPUSTAT (which are
taken directly from Form 10-K reports submitted by companies to the Securities and
3-4
-------
Figure 3-2
Flowchart of Information Flow and Analysis
The U.S. Economy Forecasting
Real GNP
Industrial Production Index
OR I Database,
Housing Starts
Macromodel 4
Sales of U.S. Made Cars
iNPUT-OUTPUT >
Unemployment Rate
Model
Consumer Price
I ndex
Interest Rates
Household Formation
BEA >
Public and Private Investment
BLS
Community Earnings and Employment
Other Demand Indicators
The Chemical Industry Projection
OR 1 Chemical
Values of Shipments
Services and >
Average Capacity Utilization Rate
Kline Guide
Chemical Price
indices
Capital Spending
Quantity of Production
ire,
Employment and Productivity
Bureau of >
Workers Earnings (i/hour)
Census
Export and Import Business
Firm Level Analys
s
Primary Producers:
COMPUSTAT,
Capitalization
Dun's Financial
Size Distribution
Prof i1e, >
Financial and Operating Ratios
Robert Morris
Secondary Producers:
Annual Studies
Capi tal izat
on
Size Distribution
Financial and Operating Ratios
Small Business
3-5
-------
Figure 3-2 continued
Dun's Financial
Prof ile,
Robert Morr i s
Annual Studies,
§308 Survey
Plant Level Analysis
Financial A Operating Performance
Employment
Capital Expenditure
Production Quantity S, Values by
Product
Process Capacity
Wastewater Information
Di scharge Status
Volume
Pol Iutants
Treatment in Place
Products Level Assessment
DRI Chemical
Production Levels
Services A >
Pr i ce
§308 Survey
Values of Shipment
Processes
Demand Factors
OR 1 Chemical
Serv i ces
New Sources Analysis
§308 Survey >
Capacity Expansion
Chemical Industry
Production Value
Periodicals
Financial and Operating Ratio
3-6
-------
Exchange Commission) and from the §308 Survey are provided directly by the plants or
firms covered. While there is some overlap between the D&B data and the §308 plants,
there is no key that can be used to merge the two data bases. Therefore, the D&B data
were referenced to the §308 plant-specific data based on 4 digit SIC codes and OCPSF
sales. The financial information provided by Robert Morris Associates is drawn from
company financial statements submitted by commercial banks, but it is aggregated by
line of business. Like the D&B data, the Robert Morris data were referenced to plants
in the data base on the basis of sales and SIC codes.
The sources of data used in each step of the methodology are described in the
sections which follow, but as four of them (§308 Survey, Dun's Financial Profile, DRI
and COMPUSTAT) are of major importance, they are also discussed in more detail here.
3.2.1 §308 Survey
A survey of the entire organic chemicals, plastics and resin manufacturing
industry was conducted by EPA in 1983 and 1984 in order to collect data on
manufacturing and wastewater discharges and treatment. This survey was authorized
by §308 of the Clean Water Act, and was carried out to obtain the data necessary to
establish wastewater effluent limitations for the OCPSF industry.
The §308 Survey provides selected economic and operating information at the
plant level. The economic data in the §308 Survey includes product types, production
quantities and values (sales), operating capacities, employment, capital expenditures,
and some production costs. Appendix 3A summarizes the economic data included in the
§308 Survey.
An actual or estimated organic chemicals sales value is required for each plant
included in the plant level impact and closure analyses. Where available, actual plant
sales values are used. Estimates are made for plants missing these and other necessary
§308 Survey data as described in Appendix 3B. Plants for which a sales estimate cannot
be made, due to insufficient §308 Survey data, cannot be included in the plant level
analysis. (Out of 940 in scope plants, 22 could not be included in the analysis due to an
absence of sufficient data.)
3-7
-------
3.2.2 Dun & Bradstreet Data
The Financial Profile data file, compiled by Dun and Bradstreet (D&B),
contains balance sheet information (assets and liabilities) as well as several items from
standard income statements (e.g., sales, profit after tax). The data are collected by
D&B reporters in making routine field visits to update information or to service credit
inquiries on new or existing firms. As discussed in Section 3.3, these data are used to
estimate plant level cash flow, liquidation value, and profits.
The data are comparable to the Financial Statistics (FIN/STAT) data available
through the Small Business Administration (SBA). SBA's FIN/STAT data represent an
edited and internally consistent subset of the Dun's Financial Profile data base. How-
ever, the available FIN/STAT data had two major shortcomings which limit their useful-
ness for this analysis: I) the data cover 1976 to 1981 and are, therefore, outdated, par-
ticularly in light of recent structural changes in the U.S. chemical industry; and 2) the
edited data base contains a total of 61 observations across all firms and years and
almost two thirds (66 percent) apply to plants with less than $2.5 million in annual
sales. Due to the sparse data for firms with larger sales values, valid statistics could
not be developed using the FIN/STAT data even when aggregated to the 3 digit SIC code
level.
For these reasons, EPA obtained additional more current data from Dun and
Bradstreet. Originally the data were limited to non-modeled, single location, non-
subsidiary firms with primary SIC codes of 2821, 2823, 2824, 2865, and.2869. These
data were subjected to edit and consistency checks identical to those used by the SBA
in constructing the FIN/STAT file. Specifically, the following checks were made:
1. Only fiscal, individual fiscal or combination fiscal financial
statements are included.
2. Only firms (observations) with net sales, total assets, total
liabilities and capital, fixed assets, and net profits after tax
greater than zero are utilized.
3. Sum of current asset components must be within two percent of
total current assets.
Sum of non-current asset components and total current assets
must be within two percent of total assets.
5. Sum of current liability components must be within two percent
of total current liabilities.
3-8
-------
6. Sum of non-current liability components and total current
liabilities must be within two percent of total liabilities and
capital less net worth.
However, this selection process still yielded too few data points for the larger
size facilities for use in the analyses. EPA, therefore, obtained additional financial
data from D&B, this time relaxing the criteria pertaining to single plant and single
location. Data searches included multi-plant subsidiary operations provided those
facilities complied with all other editing criteria first esablished by the SBA. The
number of observations obtained from this process is shown in Table 3-1. This table
also shows the number of observations in SBA's FIN/STAT data base and the yield from
the first Dun and Bradstreet request focused on single plant, single location non-
subsidiary firms. Histograms contrasting the various data bases with the plants in the
§308 Survey are shown in Figures 3-3 through 3-5. These figures indicate that, of the
available data bases, the DdcB data used by EPA (Figure 3-5) provide the best coverage
in terms of financial data in both SIC codes and across plant size ranges.
EPA used the Dun and Bradstreet multi-plant data base because: (a) the
number and distribution of observations is more representative of the §308 Survey
plants than alternative data bases; (b) the median financial ratios for the D<5cB multi-
plant data fairly closely approximate the FIN/STAT data base; and (c) the data are
more current and, thus, will more accurately predict economic impacts.
3.2.3 DRI Services
Historical data and 1988 forecasts from DRI Services are closely integrated
into the economic impact analysis. The DRI Services and data sources used in the
analysis include:
specification of the baseline for the macro environment;
specification of the baseline for the industry;
product data;
foreign trade data.
The DRI macro model forecasts are the main sources of data used to establish
a U.S. economic baseline against which impacts can be examined. (See Chapter 5.) The
macro model forecasts the GNP and its components, industrial production and price
indices. Demand indicators such as housing starts, automobile sales, employment rates,
household formation and private investment are also forecast.
3-9
-------
Table 3-1
COMPARISON Of FI N/STAT AND DUN & BRADSTREET RATIOS
(Median Values)
SIC/SIZE
N
FlN/STAT SINGLE
LOCATION, NON-
SUBSIDIARY ('76-'8l)
N
DAB SINGLE-
NON-SUBSIDIARY
LOCATION
cai-'ea)"
N
D4B--ALL
('81-'
FIRMS
86)'
CASH FLOW/
SALES
LIQUIDATION
VALUE/SALES
CASH FLOW/
SALES
LIQUIDATION
VALUE/SALES
CASH FLOW/
SALES
LIQUIDATION
VALUE/SALES
282
$10M
3
0.123
0.061
8
0.092
0.122
47
0.095
0.230
286
<»2.5M
19
0.074
0. 152
29
0.082
0.136
38 .
0.061
0.138
i2.5-IOM
5
0.044
0. 134
8
0.055
0. 126
15
0.058
0.118.
>110M
1
0. 101
0.199
0
N/A
N/A
26
0.086
0.260
"Principally 1984-1986.
-------
Figure 3-3
COMPARISON OF SALES: FIN/STAT VS. §308 DATA
percentage
50
30
20
SJC_CODE«282
PERCENTAGE BAR CHAT
<$2.5m J2.5-10* 110-25M S2S-80H >M0M
j 308 OATA |
M0m _saiES
f FINSTAT | SOURCE
PERCENTAGE
70
40
30
20
SIC_OSE-2S6
PERCENTAGE BAR CHART
• ••••
S8» <»2.5H 12.5-10W 110-25* J25-8W >MO" .SALES
| | F1NSTAI I SOWCE
3-11
-------
°E RCEMT AGE
50
40
30
20
10
Figure 3-4
COMPARISON OF SALES: SINGLE LOCATION, NON-SUBSIDIARY
D£B VS. §308 DATA
SIC_COOE«282
PERCENTAGE BAR CHART
U(M 180N _ SALES
| 308 DATA | | UNITED OU I SOLS a
PERCENTAGE
S[C_a»E-286
PERCENTAL BAR CHANT
<$2.5N S2.5* ION $10-25* S25-80* >MO*
| 308 DATA - |
<*2.5N M.5-10M S10-25A *25 • SOW 'WON _SALES
| LIMITED 048 I .SOURCE
3-12
-------
Figure 3-5
COMPARISON OF SALES: DSB VS, §308 DATA
StC_CCD€*2A2
PERCENTAGE MR CHART
iiih
«»««> ••••• t*«M
•••••
>ll«»
*•••• •••«•
>«M • *•«*
•m ••••• »*••<
<*2.5* 12.5-10" 110-25* *25-MM >S60N
| 308 DATA |
<12.S« S2.5-10A U0-Z5N *25-80* >S60M .SALES
• | AIL 046 I SOURCE
tCENTAGE
SIC_CGDC«286
PCRCENTAGI BM OURT
10
W
•••••
•••••
UQt
1 308 OATA I
M» SALES
I AIL DM I SOU»CE
3-13
-------
DRI's simulation models of the chemical industry determine the baseline
conditions for the industry. The baseline ties explicitly to the macroeconomic
conditions which are forecast for the baseline year. The demand indicators developed
by the macro model are used as inputs to forecast industrial production for different
sectors of the economy including the chemical industry. Estimates of price, production,
domestic consumption and foreign trade are developed from these models.
These same models provide information at the product level. Price,
production and value of production for specific chemicals or groups of chemicals can be
obtained.
DRI's foreign trad€ data base includes data on the volume and location of
international trade of chemical products. Using these data in conjunction with
information obtained from the Department of Commerce, markets which are important
for foreign trade (e.g., declining exports or increasing imports) are identified.
3.2.4 Company Data Base
The company database covers 997 plants and their parent companies. The
information in the database includes the identification of public, private and foreign
firm ownership, financial data such as stock prices and various financial ratios based on
company income statements and balance sheets, and general industry financial data.
The main source of financial information for the database is the Standard and Poor's
Compustat Status Report for public firms, which is supplemented by data from the
State Industrial Guides and other directories and guides for firms not included in
COMPUSTAT. These data are used to compute and assign the Weighted Average Cost
of Capital (WACC) (see Section 3.3.4) and to estimate firm level impacts. (See Section
3.5.)
3.3 Baseline Estimates
In order to analyze the impacts of the regulation, it is necessary to have an
analytic baseline to which compliance costs can be compared. That is, what would the
U.S. economy, in general, and the OCPSF industry, in particular, look like in the
absence of the effluent guidelines? For purposes of this analysis, 1988 is used as the
baseline year. This year was chosen for two reasons: I) based on DRI and other
projections it is anticipated that it will be a typical year for the OCPSF industry, i.e.,
will represent neither a peak nor a trough in OCPSF production; and 2) plants and firms
will plan for compliance with these regulations around that time.
3-14
-------
The baseline for the economic impact analysis is composed of six levels of
data, from the U.S. economy to plant-specific information. Table 3-2 shows the six
levels included in the baseline and representative types of data for each. The data are
both historical and projected to the end of the baseline period. The following
paragraphs describe the types of data specified at each level and the data sources.
3.3.1 Macro Level. Data at the macro level include broad measures of
overall U.S. economic activity such as real GNP and industrial production, as well as
demand indicators associated with economic growth, such as housing starts and
automobile sales. The economic data base and macro-economic forecasts of Data
Resources, Inc. (DRI) provide the necessary information. They include both historical
data showing trends over the past decade as well as projections from the benchmark
year (1982) to the baseline period (1988).
3.3.2 Industry Level. The demand indicators specified at the macro level
are used to estimate production requirements for the chemical industry sector.
Historical data on the chemical industry are obtained from DRI, the International Trade
Commission (ITC), the Kline Guide and The Census of Manufactures for 1982. Data at
this level include such items as value of shipments, operating rates, and production.
3.3.3 Firm Level. Firm level data, including financial and operating ratios
and capitalization information for publicly owned firms, come primarily from
COMPUSTAT. These data are historical and are analyzed to determine trends that are
likely to continue through the baseline period. Where firm level analysis is necessary
for non-public firms, estimates are generated from Robert Morris Associates and Dun's
Financial Profiles data.
Firm level sales data for 1982 were compiled from a number of sources,
including COMPUSTAT, the Million Dollar Director and the State Insurance Guides.
These data cover 858 of the 939 in-scope plants. Where 1982 firm level sales data were
available, they were used as a basis for projecting 1988 sales. In cases where company
sales were not available, they were approximated as the sum of 1988 sales for all plants
belonging to that firm.
3-15
-------
Table 3-2 Baseline for OCPSF Economic Impact Analysis
THE U.S. ECONOMY (Sources: DR1, Bureau of Census, OMB, BEA, BL5)
Real GNP
Industrial Production Index
Housing Starts
Sales of U.S. Made Cars
Unemployment Rate
Consumer Price Index
Interest Rates
Household Formation
Public and Private Investment
Community Earnings and Employment
Other Demand Indicators
THE CHEMICAL INDUSTRY (Sources: DRI, ITC, Kline Guide, Bureau of. Census)
Values of Production
Average Capacity Utilization Rate by Product Group
Chemical Price Indices
Capital Spending
Quantity of Production
Concentration
Employment
Workers Earnings ($/hour)
Export and Import Business
FIRMS (Sources: COMPUSTAT, Dun's Financial Profile, Robert Morris Associates)
Primary Producers:
Capitalization
Size Distribution
Financial <5c Operating Ratios
Secondary Producers:
Capitalization
Size Distribution
Financial 6c Operating Ratios
3-16
-------
Table 3-2 Baseline for OCPSF Economic Impact Analysis
(Continued)
PLANTS (Sources: §308 Survey, Dun's Financial Profile, Robert Morris Associates)
Financial 3c Operating Ratios
Employment
Costs of Materials and Services
Capital Expenditure
Production Quantity by Product Group
Production Values by Product Group
Process Capacity
Wastewater Information:
Discharge 5tatus
Volume
Pollutants
Treatment in Place
RCRA and Superfund Costs
PRODUCT GROUPS (Sources: §308 Survey, DRI)
Production Levels
Price
Value of Production
Processes
Demand Determinants
NEW SOURCES (Sources: §308 Survey, Dun's Financial Profile, Robert Morris
Associates, Chemical Industry Periodicals)
Production Value
Financial and Operating Ratios
Capacity Expansion'
3-17
-------
The procedure used to project 1988 firm sales based on 1982 sales is as
follows:
Saiesf(1988)
m
SUM Sales (1988) + SalesQ(1988)
p=l P
(1)
Salesf (1988)
Sales-t (1988)
SalesQ (1988)
m
and
Sales0 (1988)
where:
SalesQ (1982)
PRM198X)
WPIM (198X)
IPD (198X)
1988 firm sales
Total 1988 sales for plant p belonging to firm f (see
Section 3.3.4)
1988 firm sales from non-OCPSF plants
number of plants belonging to firm f
Sales0(l982) x PRI(i988)/PRI(1982) x
WP1M(1988)/WPIM( 1982) x
IPD( 1982)/IPD( 1988)
(2)
1982 firm sales from non-OCPSF plants
Overall manufacturing production index in year 198X
Wholesale Price Index for all manufacturing in year 198X
Implicit Price Deflator in year 198X
Equation (1) represents total sale for a given firm as the sum of sales of in-
scope plants plus sales from other parts of the company. Procedures for projecting
OCPSF plant sales are described in Section 3.3.^, below. The method used to estimate
other 1988 sales (for non-OCPSF activities) is shown in Equation (2). Since these non-
OCPSF activities are generally unknown, but are thought to cover a wide spectrum,
production and price indices for total manufacturing are used. The ratio of production
indices projects relative production changes. Price level changes are estimated by the
ratio of the wholesale price indices and the purely inflationary component is removed
by the IPD ratio. The result is 1988 firm sales of non-OCPSF plants in real 1982
dollars.
3-18
-------
3.3A Plant Level. Plant-specific information including plant level sales,
cash flow, liquidation value, profits, and employment serve as the baseline measures
against which the impacts from regulatory action are examined. The estimation
methodology for each is described below.
Sales
Individual plant sales are projected for the 1988 baseline target year using the
following methodology:
SaleSp (1988)
= SUM Sales, (1988)
i=l
(3)
where:
Salesp (1988)
Salesj(1988)
n
and
Salesj(1988)
where,
PROD (198X)
CPI (198X)
IPD (L98X)
Sales: (1982)
= 1988 plant level OCPSF sales
= 1988 OCPSF product level sales for product i*
= number of OCPSF products in plant p
= Salesj (1982) x PROD(1988)/PROD(1982) x
CPI( 1988)/CPI( 1982) x IPD( 1982)/IPD( 1988)
(f)
Aggregate 4-digit SIC group production rate in year
198X
Chemical price index in year 198X
Implicit price deflator in year 198X
Value of shipments from the §308 survey by 8-digit SIC
group
Equation (4) adjusts sales for product i for three factors, expected to change
from 1982 to 1988. The production ratio adjusts production for each plant to projected
1988 levels. The CPI ratio inflates the price levels for those products to levels
expected in 1988, while the IPD ratio removes the expected inflation component; thus
leaving prices to reflect 1988 conditions, but stated in 1982 dollars. Therefore,
Equation (<0 predicts sales for product i for the plant operating at a higher production
*OCPSF products are defined as 8-digit SIC product groups as reported in the
§308 survey.
3-19
-------
level in 19S8 and adjusts for the expected change in real price levels between 1982 and
1988 (see Table 3-3). This relationship is first calculated for each OCPSF product
manufactured by a plant, and then, 1988 plant level sales is computed as the sum of the
1988 product level sales. Thus, equation (4) assumes a constant value of production to
sales ratio for the plant. (Inventories are neither built up nor depleted.)
Sales (i.e., value of shipments) for 1982 by OCPSF 8-digit SIC product group
are contained in the §308 survey. Production for 1982 and 1988 were obtained from
DRI for four of the five SIC product groups. However, DRI does not cover Synthetic
Cellulosic Fibers (SIC 2823). For this group, 1982 production was taken from 1TC
figures; 1988 production was estimated using the 1982-198^ growth rate. Historical
(1982) price indices are those published by the Department of Commerce; 1988 values
are based on DRI's January 1987 forecast.
Financial Parameters
Baseline profitability, cash flow, and liquidation value are estimated based on
1988 projected sales and regression equations derived from the D<5cB data by four digit
SIC. Specific items which are not available in DicB (interest, depreciation) are obtained
from RMA. For example, cash flow and liquidation value are estimated as:
CFO = NI + INT x U-CT) + DEP (5)
where:
CFO = Cash flow
NI = Net income (estimated by profit after taxes/sales from D<5cB
INT = Interest expense estimated (from RMA) as
Profit Before Taxes x Total Assets / EBIT -I
Total Assets Sales Interest
CT = Corporate income tax rate (assumed to be 34 percent)
DEP = Depreciation expenses (estimated as Depreciation/Sales from
RMA). 1.
and .
LV = f(^2\ FA + RE + WC (6)
where: \_y
LV = Liquidation value
FA = Fixed Assets (estimated as Fixtures and Equipment <5c Other
Fixed Assets from DdcB)
RE = Real Estate (from DicB)
3-20
-------
taoie 3-3
Values Used
in Estimation of
1988 Sales3
SIC
1982
Production
(10^ Pounds)
1988
Product i on
(10^ Pounds)
1938 Production
1982 Production
i 988 CPI
1982 CPI
1982 IPO
1988 IPD
1988 Sales
1982 Sales
2821
35.6
49.7
1 .396
1 .075
0.822
1 .234
2823
0.6b
0.8C
1 .250
1 .075
0.822
1 .105
2824
5.7
6.7
1 .175
1 .075
0.322
1 .038
2865
31.1
42.5
1 .366
1 .075
0.822
1 .207
2869
47.8
56.4
1 .180
1 .075
0.822
1 .043
aAI I data from DRI (May 1986 and January 1987), unless otherwise indicated.
''Synthetic Organic Chemicals, ITC, 1982.
cBased on ITC growth rates, 1982-1984,
3-21
-------
WC = Working Capital (estimated as Total Current Assets - Total
Current Liabilities from D&B)
Profits and the computed values of cash flow-and liquidation value were then
regressed against sales to develop equations that could be applied to the §308 data.
Specification of the final equations involved several steps, including:
• Screening runs — Test of alternative model specifications for each
SIC and dependent variable. Based on summary statistics, several
models were chosen for further examination, i.e., diagnostic runs.
• Diagnostic runs — Residuals analysis for candidate specifications
identified by the screening analysis. This included examination
plots of studentized residuals vs. the dependent variable and
predicted vs. actual values as well as examination of influential
outliers based on Cook's D.* In only one case was an observation
removed due to extreme influences.
The resulting equations are presented in Table 3-4.**
In order to estimate financial parameters for plants in the §308 data base,
1988 OCPSF sales (in 1982 dollars) were substituted for the SALES variable(s) in the
equations. This resulted in plant level estimates of cash flow, liquidation, value and
profits.
Employment
Employment is assumed to be the same as that reported for 1982. This
assumption is reasonable because in recent years, chemical companies have been
putting a high priority on cost reductions and on making operations more efficient.
Furthermore, due to the nature of the chemical industry, as production increases
following the 1982 recession, employment will not rise nearly as much as the industry's
output. Thus, with the emphasis of the industry on accelerating productivity, it can be
safely assumed that productivity increases during the baseline period take the place of
employment increases. (This assumption is supported by DRI forecasts).
*Cook's distance (i.e., Cook's D) is a measure of the change in the vector of
estimated regression coefficients when a single case is deleted and can be used to
detect outliers or possible data errors. See Sanford Weisburg, Applied Linear
Regression, New York: John Wiley and Sons, pp. 106-113.
**A detailed presentation of the runs is contained ip the rulemaking record.
3-22
-------
Table 3-4
Equations Used to Esimate Plant Level Financial Parameters*
Cash Flow
SIC 2S21
CFO
0.5
SIC 2823 and 2824
CFO'
SIC 2865
CFO
SIC 2869
CFO
0.5
0.2908 SALES
(0.0076)
0.5
0.038S +
(0.0506)
0.3060 SALES0,5
(0.0117)
0.0795 SALES
(0.0026
1.1826 +(0.5439 E-3) SALES2
(0.7588) (0.1414 E-3)
R' = 0.9513
F(2,75) = 1463.69
R2 = 0.9785
F(l,15) = 682.90
R2 = 0.9861
F(1,13) = 923.35
R2 = 0.9642
F(2,55) = 1480.31
Liquidation Value
SIC 2821
SVO
SIC 2823 and 2824
SVO
SIC 2865
SVO
SIC 2869
SVO
0.2405 SALES
(0.0074)
0.2773 SALES
(0.0101)
-0.3214 +
(0.2025)
2.8744 +
(2.0048)
0.2585 SALES
(0.0019)
0.0012 SALES
(0.0004)
R2 = 0.9322
F(l,76) = 1045.41
R2 = 0.9804
F(lf 15) = 750.48
R2.= 0.9994
F(2,12) = 18603.91
R2 = 0.9478
F(2,55) = 998.35
Profits (Net Income)
SIC 2821
0.5
NI
SIC 2823 and 2824
NI0,5
SIC 2865
NI0*5
SIC 2869
NI
where:
CFO =
SALES =
SVO
Ml
0.2054 SALES0*5
(0.0070)
0.2261 SALES0,5
(0.0139)
0.1774 SALES0,3
(0.0071)
0.4883 +(0.2918 E-3) SALES2
(0.4184) (0.0078 E-5)
R2 = 0.9199
F( 1,76) = 872.58
R2 = 0.9462
F(l, 15) = 263.75
R2 = 0.9796
F( 1,13) = 625.80
R2 = 0.9622
F(2,55) = 1401.20
Cash flow (in millions of 1982 $)
Sales (in millions of 1982 $)
Liquidation Value (in millions of 1982 $)
Net Income or Profit After Tax (in millions of 1982 $)
*The standard of error of each coefficient is shown in parentheses below it.
3-23
-------
RCRA and Superfund Costs
Baseline conditions for the economic impact analysis involved estimating the
compliance costs of the Resource Conservation and Recovery Act (RCRA) Amendments
of 1984 (related to restricting land disposal of hazardous wastes) which were expected
to be in place prior to the 1988 baseline year. Only 47 of the 313 OCPSF plants
contained in the "1986 National Screening Survey of Hazardous Waste Treatment,
Storage and Disposal Facilities" were both active treatment, storage, disposal or
recycling facilities under RCRA and also nonzero dischargers subject to compliance
costs under Clean Water Act effluent limitation guidelines. In total, RCRA compliance
costs were developed for 42 facilities because five of the facilities lacked the necessary
information to develop costs.
It was assumed that OCPSF plants would incur two types of capital costs in
complying with the 1984 RCRA Amendments: a capital cost of retrofitting wastewater
treatment impoundments with double line'rs, and a capital cost of installing groundwater
monitoring equipment. The liner cost estimates were based on plant^specific flow data
in conjunction with technical assumptions regarding average impoundment retention
time. The monitoring costs were estimated as a function of the size (in terms of flow)
of the regulated impoundment or lagoon. Ail costs were reported in 1982 dollars.
Other RCRA-related costs, e.g. administrative costs and others associated
with the listing of various substances are incorporated in the baseline through the
financial ratios. That is, since cash flow and profitability are based principally on 1984
to 1986 dat^, costs associated with in-place RCRA regulations are already reflected in
the cost-of-doing-business.
Similarly, firms have been paying Superfund taxes since 1981. From June,
1981 to December 1985, $1.1 billion were collected. Extrapolating this to 5 years gives
$1.4 billion—the goal of the recently passed Superfund bill. Hence, these costs are also
already incorporated in the cost-of-doing-business and reflected in the financial ratios.
3.3.5 Product Level. Product or product group data come from the DRl
Chemical Service, the §308 Survey and ITC. They include information on production
and price. Historical data and projections for the baseline period developed by DRI are
used.
3.3.6 New Sources. In order to determine whether treatment capital costs
represent significant barriers to OCPSF manufacture entry, estimates of the capital
3-24
-------
costs of constructing and equipping new model plants are developed. Treatment capital
costs are later compared to these initial costs to estimate construction costs increases
attributable to the regulation.
3.3.7 Cost of Capital and Time Horizon
The cost of capital is required for two purposes: I) to discount future cash
flows for the closure and analysis; and 2) to annualize wastewater treatment capital
costs. The analysis calculates a weighted average cost of capital in real terms. The
method is briefly described below. A more detailed presentation of the method, related
concepts, and theory is found" in Appendix 3C.
The real weighted average cost of capital, Real WACC, is defined as:
Real WACC = [(1 + Nominal WACO/O + g)] -1 (7)
where:
Real WACC = weighted average cost of capital
g = inflation rate
and
Nominal WACC = r(e/a) + y(l - tXd/a) (8)
where:
r = after tax return on equity
e = firm equity
d = firm long-term debt
a = e + d = value of the firm
y = before-tax interest rate on debt
t = corporate marginal income tax rate
In order to account for the higher perceived risk of smaller firms and the more
limited sources of funds available to them, the WACC is assumed to vary with firm
size. Based on a 1986 paper prepared by the Board of Governors of the Federal Reserve
3-25
-------
System, three size categories based on sales are defined: 1) less than $17.5 million;
$17.5 to $131 million; and $131 million and over.*
The WACC for the largest firms is derived as described in Equation (5) using
the 1988 prime rate (from DRI) and debt to equity ratios derived from COMPUSTAT.
(See Appendix 3C.) For mid-size ($17.5 to $131 million) firms, 1.5 percentage points
are added to the nominal WACC; for small firms (less than $17.5 million), 2.5
percentage points are added. This results in WACC values of 8.11, 9.55 and 10.51 for
large, medium and small firms, respectively.
3A Plant Level Impacts
The analysis of plant level economic impacts uses three measures: 1) plant or
product line closure; 2) change in profitability; and 3) annualized costs as a percent of
sales. Plant and product line closures are the key impact measures. They serve as both
the bottom line impact and as a building block for other analyses. The profit and sales-
based impacts provide descriptive information on the relative magnitudes of the effects
of alternative options. In addition, they are indicative of potentially significant long
run impacts, short of closure.
All measures are based on the OCPSF portion of the plant and assume no cost
pass through. While this is a conservative assumption, it is not unreasonable given
competition from foreign suppliers in many industry segments.** The derivation and
interpretation of each impact measure is described below.
3.4.1 Closure Analysis
The principal component of the plant level analysis is the estimation of plant
and product line closures. The purpose of this analysis is to determine the number and
type of plants and product lines that are likely to close as a result of the regulations.
*The Federal Reserve Bank defined the middle market as firms with sales of
$20 to $150 million 1986 dollars for the purpose of this study. These boundaries were
converted to 1982 dollars using the IPD, to result in a middle market definition of $17.5
to $131 million in 1982 dollars. See August 1986 Senior Loan Officer Opinion Survey on
Bank Lending Practices, Board of Governors, Federal Reserve System, September, 1986.
**An analysis of the sensitivity of the impacts to changes in this assumption is
presented in Chapter 7.0.
3-26
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A decision to close a plant is extremely complex and involves numerous
factors. Some of the more important ones are:
Present and expected profitability of the plant;
Current market or salvage value of the plant, i.e., the opportunity
costs of keeping the plant open;
• Required pollution control investment;
• Expected increase in annual costs due to pollution control
requirements;
• Expected product price, production costs, and profitability of the
plant after pollution control equipment is installed and operating;
and
• Other major economic developments expected for the plant {i.e.,
change in the competitive position, increase/decrease in market
growth).
In general, a plant owner faced with pollution control requirements must
decide whether to make the additional investment in pollution control or to liquidate
the plant. A rational owner would, in the majority of cases, decide to continue
operations if the post-control cash flows are greater than the current liquidation value
of the plant. If the expected cash flows are less than the current liquidation value of
the plant, the owner would be better off selling the plant. Since the plant will remain
open for many years if the investment is made in pollution control, the analysis takes
into account the cash flow expected over the life of the plant and equipment. The
present value of future cash flow is calculated by discounting the expected income
stream by the weighted average cost of capital. It is assumed that the plant will
remain open if the present value of the expected cash flows less the costs of investing
in pollution control exceeds the expected current liquidation value. If the expected
cash flows are less, the owner will presumably sell the plant.
As described in Section 3.3A, liquidation value is estimated as 20 percent of a
plant's net fixed assets plus its working capital. Cash flow is calculated as net income
plus after tax interest plus depreciation. Both cash flow and liquidation value are
calculated from Dun's Financial Profile and RMA (for interest and depreciation) data
using regression equations. The equations are applied to each plant's 1988 OCPSF sales
projections to arrive at plant-specific estimates of cash flow and liquidation value.
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The present value (PV) of cash flow is then calculated as:
n
PV (CF) = SUM CF - CI - L
i = l (l+r)'
(9)
where:
n
life of the investment
year of the investment
CF = cash flow of the plant with treatment
CI = treatment costs capital investment
L = land costs for additional treatment facility
r = real rate of return on total assets (Real WACC)
The life of the investment, n, is estimated to be ten years. The real weighted average
cost of capital, Real WACC as defined in Subsection 3.3.7 above, is used for r. The
cash flow with treatment is approximated as:
where:
NI = net income (see definition of tax rate, t, below)
I = interest expense
D = depreciation (adjusted by a factor to represent measurement in real
terms)
t = corporate marginal income tax rate, 34 percent
OM = operation and maintenance costs of treatment
Each closure candidate identified by the above analysis is further examined to
determine whether the entire plant or only the OCPSF product 'line(s) is likely to
close. The decision rule is based on plant employment: if 80 percent or more of the
plant's production workers are engaged in OCPSF manufacture, it is expected that the
entire plant will close. Otherwise, only the OCPSF product line(s) are projected to shut
down.
3.4.2 Profitability
A profitability impact is termed significant when a plant's profit to sales ratio
falls into the lowest decile for that SIC and size category. Post treatment (after tax)
profits are caclulated by subtracting annualized capital and land costs and post-tax
CF = NI + 1(1 - t) + D - (1 - t) (OM)
(10)
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operating and maintenance costs from baseline profits. Post treatment profit to sales
ratios are then compared to industry norms, based on the D&B data using 3-dLgit SIC
codes and three size categories for plants based on sales (< $2.5 million, $2.5-10 million,
> $10 million).
As noted above, a substantial decline in profitability may signal a significant,
but less immediate impact. For example, a firm may decide to keep a plant in
operation over the next few years, but may cease to reinvest in the plant's building and
equipment, eventually closing it.
3A.3 Cost as a Percent of Sales
Annualized treatment cost as a percent of sales is another indicator of the
relative magnitude of economic impact. Although the analysis assumes zero cost pass
through, cost as a percent of sales represents a rought approximation of the percentage
price increase that would result from 100 percent cost pass through, i.e., the
percentage increase in price needed to cover treatment costs. Cost-to-sales ratios in
excess of 5 percent are assumed to represent a significant impact.
3.5 Firm Level Analysis
The firm level analysis focuses on financial viability. The perspective in the
analysis is that of lending institutions and investors who would provide the capital to
finance treatment capital costs, and the key consideration in the analysis is whether the
firm has the financial strength to raise capital. It focuses on the firm because it is the
firm,- not the plant, that would raise debt or equity capital. Two factors are examined
in the firm-level financial viability analysis: the ability of the firm to meet its fixed
cost obligations and its attractiveness to financial institutions and investors.. Each is
described below.
Ability to meet fixed cost obligations — measured by a firm's current ratio and
its interest coverage ratio. This analysis is performed from the perspective of lending
institutions who would examine a firm's balance sheet and income statement data to
assess its ability to incur additional debt. A firm's current ratio or quick ratio (a more
conservative measure that assumes inventories cannot readily be converted into cash)
indicates its ability to meet its current obligations out of its existing current assets. It
does not consider the firm's earning potential. Taken alone, however, neither the
current nor the quick ratio is a good indicator of a firm's ability to meet additional debt
3-29
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pbligations. There are numerous reasons—including efficient cash management—why a
firm may have a low current or quick ratio.
A more comprehensive measure of a firm's ability to meet its fixed obligations
is its interest coverage ratio. Interest coverage can be measured either by the ratio of
earnings before interest and taxes (EB1T) to interest or by the so-called Beaver's ratio
of cash flow to total debt. Both of these ratios compare the firm's earnings to its debt
obligations to determine whether the firm will be able to generate enough cash to meet
these obligations. For purposes of this analysis, the EBIT/interest ratio is selected
because industry norms are published by Robert Morris Associates for this measure.
The effect of treatment costs on the current and interest coverage ratios is
examined on the basis of annualized compliance costs. This portion of the analysis
assumes that the operating and maintenance compliance costs would require additional
cash (and short-term, noninterest-bearing liabilities) on the balance sheet, and that the
capital and land costs would be financed by a combination of debt and equity, such that
the capital structure of the firms would change little, if at all. (Note: the mean 5 year
average capital structure for 100 firms in the chemical industry covered in the
COMPUSTAT database was used in this calculation.) Thus, current obligations and
assets in the current ratio are increased by the amount of operating and maintenance
and interest expenses in the current ratio is changed to reflect the decrease in profits
before tax and increases in interest expense.
Attractiveness to lending institutions and investors. In determining whether to
make a loan or an investment, lending institutions and investors will examine the degree
to which a firm has already been financed out of debt (leverage, measured by the ratio
of the firm's debt to its worth) and its return on net assets. Lending institutions will be
concerned about making additional loans to a highly leveraged firm which may have
difficulty meeting its fixed interest obligations or repaying principal in the event of
bankruptcy. Investors will be most interested in a firm with a high return on net worth
that can be expected either to pay substantial dividends or to increase its stock value
through retained earnings.
Leverage and return on net worth need to be considered jointly in examining a
firm's financial attractiveness. A highly leveraged firm would be expected to have a
higher return on net worth than a less leveraged firm with an equivalent return on total
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assets, because the net worth of the leveraged firm would be lower. Consequently, the
firms that would be most vulnerable to closure would be those with a high ratio of debt
to equity and a low return on assets.
The analysis of the effect of treatment costs on the financial attractiveness of
firms assumes that capital costs would be financed out of a combination of debt and
equity and that additional costs would not be passed through to customers. Thus, the
firms' debt/worth ratio is changed by the capital and land costs incurred by all its
plants. The total debt is also increased by the amount of operating and maintenance
liabilities and new interest expense. The firm's return on assets is reduced as a result
of its annualized cost of compliance with the regulation, and its increase in asset base
(capital, land and liquid assets).
Using these measures, a baseline profile of firms is developed for liquidity and
interest coverage and for debt/worth and return on assets. This step is an effort to
duplicate the process that would be utilized by a lending institution in making a decision
concerning a loan application from a chemical industry plant—the financial data
presented by the company would be compared to RMA industry data for the appropriate
SIC group.
As shown in Figures 3-6 and 3-7, baseline industry data for liquidity and
interest coverage and for debt/worth and return on assets are examined jointly. In
Figure 3.5.1, firms in the upper left corner are flagged as highly vulnerable in terms of
their ability to meet their fixed cost obligations—they fall below the industry lower
quartile in terms of both their ability to meet their current obligationss out of current
assets and in terms of their ability to meet their fixed interest payments out of
earnings. Conversely, firms in the lower right corner exceed the industry upper quartile
in terms of both liquidity and interest coverage. Similarly, in Figure 3.5.2, firms in the
upper left corner fall below the industry average in both debt/worth and return on
assets. These firms are financially vulnerable in that they are more heavily in debt
than most firms in the industry, and despite their relatively high debt, they realize a
low return on assets.
3.6 Industry-Wide Impacts
Industry-wide impacts are the sum total of the .plant level impacts, aggregated
across regulated plants. Industry-wide impacts are assumed to be proportional to the
impacts calculated for the individual plants.
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Figure 3-6
Comparison of Firm-Specific Current Ratio and Interest Coverage Data
Based on RMA industry Norms
EBIT/INTEREST
CURRENT RATIO
Lower
Quart i1e
Med i an
Upper
Quarti le
lower Quart i1e
H i gh1y
VuInerable
Med ian
Upper Quart i1e
Figure 3-7
Comparison of Firm-Specific Dabt to tJorth and Return on Assets
Data to F&tA I ndustry Norms
RETURN ON ASSETS
DEBT/WORTH
Lower
Quartile
Med i an
Upper
Quarti le
Lower Quart iIe
Highly
VuInerabie
Medi an
Upper Quarti le
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Treatment costs capital investment aggregated for all plants in the industry is
compared to total annual plant investment aggregated industry-wide. It is calculated as
the ratio of capital treatment costs to annual investment for all plants and summarized
by option, subcategory and discharge status.
3.7 Employment Impacts
Unemployment resulting from plant and product line closures is estimated
directly from the plant closure analysis, based on plant level employment data from the
§308 Survey. In the case of plant closures, this is represented by total employment
(OCPSF and non-OCPSF), including both production and other employees. For product
line closures, only OCPSF-related jobs are expected to be lost.
3.8 Community Impacts
Community impacts result primarily from employment and earnings losses.
Direct impacts from pollution control regulations such as plant closures or output
reductions can be expected to have direct and indirect effects. These direct and
indirect impacts are defined as community impacts. Community impacts are analyzed
in two stages. The first stage analyzes the economic data for a geographic area in
which the proposed regulation is expected to close an OCPSF plant, to determine: 1)
the population of the community or metropolitan area and the accessibility of other
populous areas; 2) the percentage of a community's population that would be affected
by the closure; and 3) the unemployment rate in the community.
The significance of community impacts are determined by the ratio of
employment lost from plant or product line closures to the population of the
community. Communities in which this ratio is .44 percent or greater are considered to
be significantly impacted, according to the following reasoning:
1. U.S. Department of Labor Statistics show that 99.3 million
Americans were employed in 1980. The U.S. Bureau of the
Census reported the population at 226.5 million that year.
Threfore, 43.8 percent of the population was employed.
2. It is assumed that a decline in employment of one percent would
be considered significant.
3. Therefore, a ratio of employment lost to community population of
0.44 percent or greater would be considered significant, as
follows:
(0.01) (43.8 percent) = 0.44 percent
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•The unemployment rate in the community and the accessibility of other populous areas
are also considered in determining the significance of the impacts.
For purposes of this analysis, community is defined in terms of easy
commuting distance. Therefore, if the plant is located within a Metropolitan Statistical
Area (MSA), as defined by the U.S. Office of Management and Budget, then the MSA
population is used.* If a community is not located in an MSA, but is in a township
(mostly eastern states), then the township population is used. Population information is
from the 1980 U.S. Census of Population.
If impacts on a particular community are estimated to be significant, then
secondary effects are assessed by multiplier analysis, the second stage of the analysis
discussed below. As mentioned earlier, direct impacts from pollution control
regulations such as plant closures, output reductions, employment losses and earnings
losses have indirect effects, arising from the reduction in demand for inputs by the
affected plant and induced impacts attributable to reductions in consumption because
of both direct and indirect losses in earnings. Input/output analysis provides a
straightforward framework for accounting for these secondary effects as long as the
direct effects are small and a number of other important limitations (e.g. constant
returns to scale, fixed input ratios) are recognized.**
Given a change in final demand in a certain industry, an input-output table can
be used to determine the changes in demand (gross output) in other industries that
would arise from this change as well as the total effect of changes in household
consumption due to changes in income. The number obtained is the "gross output
multiplier." However, the change in gross output is not a useful measure of impact
because it results in substantial double-counting. Only the change in value-added should
be counted. The measure of net impact used by the U.S. Department of Commerce,
*lf it is part of a PMSA (Primary Metropolitan Statistical Area), then the
PMSA population is used.
**See U.S. Water Resources Council, Guideline 5: Regional Multipliers
(Industry Specific Gross Output Multipliers for BEA Economic Areas) prepared by
Regional Economic Analysis Division, Bureau of Economic Analysis, U.S. Department of
Commerce, Washington, D.C., January 1977 and Regional Multipliers, A User Handbook
for the Regional Input-Output Modelling System (RIMS II), U.S. Department of
Commerce, May 1986.
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Bureau of Economic Analysis (BEA) (and that adopted here) is earnings. The impact on
earnings can be calculated by multiplying the demand change in each sector by the ratio
of earnings to gross output in that sector and then summing earnings changes over
sectors.
This procedure is used by BEA to calculate an earnings muitipler for change in
total earnings to changes in final demand for the organic chemicals indsutry, as follows:
M = Change in Total Earnings (11)
Change in Organic Chemicals Industry Demand
This number includes direct and indirect earnings changes and represents a national
average. It is not feasible to use state-specific gross output multipliers to obtain
similar earnings/final demand multipliers for each state because of their serious
limitations. The total impact of a plant closure or output reduction is just:
Change in Total Earnings = M x Change in Revenues (12)
where
Change in Revenues = Change in Sales
and M is a BEA Earnings Multiplier. The BEA multipliers are estimated via the
Regional Industrial Multiplier System (RIMS) developed by the Regional Economic
Analysis Division of BEA. The five digit SIC groups in the OCPSF industry correspond
to four of the RIMS "column industry" groups. Each plant analyzed is matched to the
appropriate RIMS column industry, which determines the specific multiplier, to use.
Since the analysis is focused on the total community impact, the total multiplier for
that industry group is used. The most recent multipliers available are based on 1977
input/output relationships. It is assumed that the basic relationships remain unchanged
in 1988.
The direct impact on earnings at a plant can be estimated from §308 Survey
employment data plus industry average hourly earnings information. The indirect
imapct or community earnings impact is the change in total earnings minus the direct
earnings change.
Community employment impacts can be calculated from state average wage
rates applied to the indirect earnings changes estimated as described above. Therefore:
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Change in Indirect Employment =
Change in Indirect Earnings/(Earnings/Employment-l)
(13)
where Earnings/Employment^ is the average wage rate for state i. This allows the use
of available state average wage rates.
3.9 Small Business Analysis
Public Law 96-354, the Regulatory Flexibility Act, requires EPA to determine
if a significant impact on a substantial number of small businesses occurs as a result of
the proposed regulation. If there is a significant impact, the act requires that
alternative regulatory approaches that mitigate or eliminate economic impacts on small
businesses be examined. To address these objectives, an analysis is performed to
identify whether or not small businsses in the OCPSF industry are significantly
impacted by the proposed regulation and to assess the effects of regulatory
alternatives. The methodology used to perform this analysis is described in detail in the
Regulatory Flexibility Analysis report, but is summarized briefly below.
The analysis involves several steps, including:
1. Definition of a small business
2. Determination of disproportionate impacts
3. Development and assessment of mitigation alternatives.
For purposes of this analysis, steps 1 and 2 are considered jointly. That is, the
definition of a small business is based on the relative severity of impacts. Definitions
examined consider annual plant production (solely) and annual plant production coupled
with firm sales size. Given a small business definition and a determination that
disproportionate impacts will occur, alternative mitigation strategies are assessed
considering the number of significantly affected plants covered, the number of plants
included that are not significantly affected and the relative amount and toxicity of
pollutants which would remain uncontrolled.
3.10 International Trade Impacts
Most OCPSF products, as described in Chapter 2, are traded in a highly
competitive international market, with producers and consumers located all over the
world. In fact, the market extends into the less developed nations of the world
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particulary where newly discovered oil supplies are providing the feedstock base for
petrochemical production industries. Because of the international nature of the
market, foreign trade considerations affect the analysis in two ways. First, foreign
supply competition may limit the ability of U.S. producers to pass through abatement
costs to consumers in the form of price increases. In other words, the price elasticity
of demand for some U.S. products may be very high. Second, for those OCPSF products
that are an important part of U.S. imports or exports, a significant change in U.S.
production capacity will affect the macroeconomic balance of trade. These effects
would include changes in the current accounts balance (goods and services) and in the
capital accounts balance (investment).
3.10.1 Sensitivity to Foreign Competition
The analysis of foreign competition draws upon the basic closure analysis
described in Section 3A. That analysis was based on a "worst case" assumption that no
plants would be able to pass through abatement costs to customers by increasing
prices. This assumption is accurate only to the extent that demand for the domestic
product is very elastic. That is, customers would respond to price increases by reducing
their purchases significantly. A major determinant of customer price sensitivity is
whether or not there are alternative sources of supply of close substitutes where prices
have not increased.
In the case of internationally traded OCPSF products, U.S. producers will be
less able to raise their prices whenever there are foreign producers able to sell identical
products or good substitutes at unchanged prices. If the U.S. share of the world market
for the concerned product is very small, and the product is homogeneous, then a drop in
its production is not likely to effect the international price. In cases where substitutes
from abroad aire not available in the needed quantities, then U.S. producers will be able
to raise their prices without much effect on demand.
This sensitivity of customers to price change operates both in the import and
export markets. If alternative foreign supplies are available, then domestic price
increases will cause exports to decline (foreign consumers switch to foreign suppliers)
and imports will rise (domestic consumers switch to foreign suppliers). Both of these
effects, however, depend on the availability of alternative foreign supplies.
To identify the markets which are susceptible to these forces, we use the DRI
foreign trade data base and the Department of Commerce petrochemical international
market assessment analysis are used. The following criteria are used to identify trade
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sensitive products:
1. Significant foreign production capacity is available or under
construction in sufficient size to supply new U.S. customers
(excess foreign production capacity of at least 10% of U.S.
production).
and
2. Transport costs are low enough to allow international trade at
modest price differentials (exports plus imports exceed 15% of
production in 19S8).
or
3. A significant decline in net exports is expected between 1985 and
1988.
Products that meet these criteria are defined to.be trade sensitive, and plants
producing these products are properly analyzed by the basic closure procedure. Product
markets that are found to be not trade sensitive should be able to absorb some price
increases. For these non-sensitive parts of the industry, plant closures are probably
overstated in the basic analysis.
3.10.2 Balance of Trade Impacts
Despite recent declines in net exports, the petrochemical industry is an
important component of U.S. international trade. In this section, we assess the impact
that plant closures may have on OCPSF contributions to the U.S. balance of trade.
To estimate trade impacts, we assume that total world demand will remain as
projected for 1988, then trace the effects of predicted plant closures on imports and
exports. Assuming that the international prices will not change as a result of the
projected loss of production related to compliance, several scenarios might occur, alone
or in combination for various products. One such scenario is described below, with the
assumption that the same scenario will apply to all products concerned. We assume
that domestic consumers are favored in the sense that foreign customers are the first
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group to be foreclosed Erom U.S. supplies. The analysis is performed only for products
that are important sources of trade as defined by the following criteria:*
1. exports or imports are more than ten percent of production in
1988
or
2. exports plus imports are more than fifteen percent of production
in 1988.
The products identified by these criteria are assigned the appropriate eight-
digit SIC code. These products are matched by SIC with the appropriate plants and
product lines that are closure candidates. In this way, we determine the percentage of
production that will be lost in each of the eight-digit SIC codes, under each regulatory
option.**
Exports are reduced by the full amount of lost production so long as the
change in production is less than or equal to baseline exports. If exports can absorb all
lost production, then imports remain unaffected, but if the change in production
exceeds exports, then any residual production loss is taken from domestic customers to
be displaced by new imports. This scenario may be viewed as a worst case impact from
the industry perspective. The resulting effect of loss of production on balance of
payments will be negative to the extent of the value of net exports lost.***
~Ideally, the level of exports as a percent of production is not as important as
the price sensitivity in foreign markets; however, the available data will not support the
identification of trade sensitive chemicals based on foreign production and foreign
prices sensitivity.
**Identfication of trade sensitive chemicals is limited to those chemicals
covered by DRI. Product level production on a plant-by-plant basis is not available.
Therefore, matching trade sensitive chemicals by SIC assumes that the production loss
in trade sensitive chemicals is proportional to the trade sensitive chemical's share of
production in the eight-digit SIC product group.
***In reality, the effect may be somewhat larger because of the
macroeconomic effect on income, through a "trade-multiplier" effect. That is, the loss
in value of net exports alone does not account for the decreased demand for inputs,
e.g., raw materials, which may further affect balance of payments.
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3.11 New Sources
The purpose of this analysis is to determine the extent to which the proposed
regulations will increase barriers to entry of new plants .into the OCPSF industry, and to
expansion of existing plants. The analysis consists of two components, including
estimation of:
• The increase in construction costs due to the need to comply with
the regulation. That is, what is the percentage increase in new
plant capital costs attributable to treatment capital costs?
• The decrease in the net present value (NPV) of cash flow and
decrease in the profitability index (NPV/Investment) due to
treatment capital and operating costs. In other words, to what
extent would the rate of return be affected by treatment capital
and operating costs for a new investment?
Each component is estimated separately for typical new plants and for typical
expansions.
Briefly, the first impact measure can be estimated as the capital treatment
costs (including land) divided by the cost to construct and equip a new plant, or expand
and equip an existing facility or plant.
The second measure, although somewhat more complicated, is a cash flow
calculation similar to that used in the plant closure analysis. The cash flow is
calculated as After Tax Profits plus Depreciation plus Interest times (l-tax rate).
Present va-lue of cash flow less the initial investment provides the net present value.
The rational firm would not construct a plant, or undertake an expansion under baseline
conditions if the net present value of the investment were negative, since that would
indicate a lower than required rate of return. The net present value of cash flow
divided by the initial investment yields the profitability index, which is typically used in
capital budgeting to rank non-interdependent, non-mutually exclusive investments.
Theoretically, a capital planner would choose the investment with the higher index, as
that should yield a higher return per dollar of investment.
Post-baseline conditions includes the addition of capital and operating
compliance costs to the net present value calculation. The capital costs are added to
the initial investment, and the operating costs times (l-tax rate) are subtracted from
annual profits. The capital structure is assumed to remain the same as the industry
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norm used in the plant closure analysis, i.e., 26 percent of the investment is assumed to
be financed by debt (requiring interest payments) with the remainder financed via
equity.
3.11.1 Estimating the Cost of Constructing New Plants, and Cost of
Expansions
The methodology described above requires estimating the cost to construct
new "typical" plants of different types. The reality of the marketplace makes this type
of information difficult to collect. First, it is not readily available for a majority of
new plants. Second, as discussed in previous sections, the OCPSF market is an
international one in which competition from foreign sources with ready access to
feedstocks is becoming increasingly important. Many U.S. firms are planning to build
new plants offshore to service foreign markets. Also, fewer new plants are being
constructed in the U.S. than in other parts of the world, especially in developing
countries.
Estimations of the costs of constructing small and large plants in SIC 2821
(plastics), and large plants in SIC 2865 (cyclic intermediates) and SIC 2869
(miscellaneous cyclic and acyclic compounds) were made based on three years of
available data from the trade publication Hydrocarbon Processing and Chemical
Engineering. (No data were available for SICs 2823 or 282^, synthetic fibers.)
Hydrocarbon Processing lists, three times annually, active hydrocarbon-related plant
construction, renovation, treatment and expansion projects worldwide. In a number of
cases, the capacity of the plant, or the capacity added, as well as the planned project
cost are included with an individual listing. Chemical Engineering similarly compiles
construction data, once annually.
In 1986, there were over 900 active petrochemical construction projects
worldwide (about 2000 active projects total, including refining and gas). About 75 of
these were projects in the U.S. Within the U.S., approximately 50 percent of the
projects appear to be treatment facility projects, including desulfurization, hydrogen
treatment, wastewater treatment, jet fuel treatment, etc. Roughly another quarter of
the projects were for plants not in the scope of the study, e.g. natural gas plants,
cogeneration, coal gasification, and nitrogen compounds. The remaining projects
involved plants of interest, e.g. methanol, fuel alcohol, plastics, resins, a few
intermediate cyclics and miscellaneous compounds.
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Approximately 4.8 percent of currently announced capacity expansion
worldwide from 1986 through 1991 represents planned capacity in the U.S. Thus, the
U.S. fraction of world capacity expansion in millions of pounds annually is smaller than
the U.S. fraction of total projects, suggesting that U.S. projects will, on average, be
smaller in terms of capacity. Inspection of the available construction data available
supports this.* The available data suggest that foreign competition is, and will
continue to be, a major barrier to entry into the industry.
3.1 L.2 Estimating the Impacts for New Plant Construction
The data necessary to calculate the impacts on the "typical" new plants
described above were derived from a subset of actual plants in scope with
characteristics resembling those "typical" plants in size (capacity) and SIC. In essence,
the new construction cost was "assigned" to those plants which fit the following
criteria:
SIC 2821 Small plastics plants described in Hydrocarbon Processing
and Chemical Engineering tended to be polymer or resins
plants costing in the range of $6 to $15 million, with
capacities in the range of 6 to 22 million pounds per
year. Therefore $10 million was chosen as an average
cost for constructing such a plant. Plants in scope in this
SIC with capacities (assuming the 1982 percent capacity
utilization for that SIC) in the 0 to 20 million lb. range (§
308 data) were assigned a new cost of construction of $10
million.
Large plants in the range of 100 to 200 million lbs.
capacity (actual plants) were similarly assigned a cost of
$85 million, based on the observation that costs for
several new large plastics plants were somewhat less than
$1 million per 1 million Ibs./year of capacity.
SIC 2865 Large plants in scope with greater than 500 lbs. capacity
were assigned a new cost of construction of $150 million,
based again on observations from Hydrocarbon Processing
and Chemical Engineering.
*A significant number of small polymer plants (e.g., engineering resins) are
planned for the U.S., while fewer large commodity chemical plant construction plans
are evident. In contrast, developing and newly industrialized countries are pursuing
large construction projects, for intermediate and basic chemicals. (Source:
Hydrocarbon Processing, June 1986.)
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SIC 2869 Large plants in scope with capacity of 100 to 200 million
lbs. were similarly assigned a new cost of construction of
$50 million, again, based on available data.
This subset of actual plants in scope was used in calculating the estimates of
impact described earlier. Thus, the calculation of percent of total cost of construction
represented by compliance capital costs was calculated for each plant in the subset, by
size and SIC, using each plant's projected capital compliance costs (land and capital).
The mean and standard deviation for this impact are reported in the results'section.
Sensitivity analyses results for these estimations are reported as well in the results
section.
The cash flow calculations required in the NPV determination, before and
after compliance costs, are calculated for this same subset of plants in scope. The
profits calculated for plants in the plant closure analysis are used here as well. Upper
and lower quartiles and medians for NPV of investment and the associated Profitability
Index, for baseline and post-compliance conditions, are reported in the results section.
3.12 National Social Costs
Executive Order 12291, released in February 1981, is intended to ensure that
regulatory agencies evaluate the need for taking regulatory action, consider available
alternative actions, and design their programs on the basis of the costs and benefits of
the various alternatives. In particular, the Order establishes a set of regulatory reform
and review procedures, including a requirement that regulations be analyzed in terms of
their total cost to society.
This section describes the methodology for estimating the total social costs of
compliance with the proposed effluent regulations. Social costs can be defined- as the
value of goods and services lost by society resulting from the use of resources to
comply with a regulation, the use of resources to implement a regulation and reductions
in output due to compliance.
3.12.1 Social Cost vs. Private Cost
In order to estimate the economic impact of the proposed rules on the OCPSF
industry, it is appropriate to measure only the costs of compliance that would be
incurred by the affected firms. The private compliance cost in most industries,
however, would understate the total social cost for a variety of reasons. For example,
tax deductions which defray the firms' cost of compliance merely represent a shifting
3-43
-------
of cost from the private sector to the government. Social cost estimates add back any
tax benefits received by firms.
In addition, there may be indirect costs borne by other sectors of the economy
as well as the administrative costs of the regulatory agencies. A further issue involves
the choice of a discount rate for aggregating expenditures over time.
The total social costs of regulation can be classified into the following four
groups:
• R6al resource costs; total expenditures on abatement and
compliance in the private sector
° Deadweight welfare loss: decreases in consumer and producer
surplus resulting from a decrease in production
° Adjustment costs for unemployed resources: lost wages of laid-off
workers while searching for new employment
• Government administrative cost: the incremental effort needed to
monitor and enforce the regulations
To the extent that production of pollution control equipment increases, the
deadweight welfare loss and worker adjustment costs may be overstated.
3.12.2 Methodology
Real resource costs and deadweight welfare losses can be illustrated by use of
a simple supply and demand graph for the industry. In Figure 3-8, the pre-regulation
equilibrium price is Pe, and quantity sold is Qe. Total consumer and producer surplus is
represented as the shaded area OAB.
When effluent regulations are imposed, the cost of production rises, and the
effect can be shown as an upward shift of the supply curve, as shown in Figure 3-9. the
post-regulation price is increased to Pr, while sales decline to Qr. The area marked
OCDE is the real resource cost of compliance, and the area DEB is the welfare loss
associated with a decrease in the quantity of goods produced.
Real resource costs are nearly identical to the direct expenditures made by
plants for pollution control. Two adjustments to plant cost estimate need to be made in
order to arrive at a social resource cost estimate. First, firms receive tax benefits
when they invest in and operate abatement facilities. Since these tax subsidies to the
firms are costs to society, they should be added back in the firms' actual outlays.
-------
-------
Figure 3-9
Real Resource and Welfare Effects
of Effluent Guidelines
A
Pr
Pt
C
0
Quant Ity
3-46
-------
Second, the estimation method incorporates a discount rate used for
annualizing capital costs or for calculating the present value of streams of expenditures
made over time. When assessing the economic impact on the firm, it is appropriate to
use the firm's cost of capital as a discount rate. For social cost analysis, however, we
should use a discount rate reflecting the cost of capital to the government or a
politically determined social discount rate. This analysis will be carried with two
alternative rates: 1) 10 percent, since EPA has recently used 10 percent as a social
discount rate in its "Cost of Clean" report and other analyses, and 2) the current yield
on long-term government securities, since this reflects the current opportunity cost of
capital to the government.
Under these assumptions, a simple formula for the resource costs of
compliance is:
Annual Resource Costs = (r x CI) + O + M (IV)
where
r = capital recovery factor for a given real perpetual return
CI = capital investment (with tax benefits added back in)
O+M = operating and maintenance costs (with tax benefits added back in)
The deadweight welfare loss can be estimated by measuring the economic
profits that would have been earned by plants that were forced to close as a result of
the guidelines. Economic profit is defined as the difference between the actual return
earned by the firm and the "normal" return earned in the long run by the average firm
in the industry. In the case of the OCPSF industry, closure candidates are usually
operating under low profit margins even before regulation, so the lost economic profits
can be expected to be very small. However, assuming that all plants in given SIC face
the same risks and therefore demand the same profit margins, they can be estimated by
comparing profit rates of closure plants to industry averages.
The major adjustment cost incurred by unemployed workers is the loss of
wages during the time spent searching for a new job. This cost can be estimated by
multiplying the daily wage times the number of days of average duration of
unemployment times the number of workers laid off at closed plants.
3-47
-------
The government administrative cost of monitoring and enforcement is likely to
be insignificant compared with other social costs. This is because the administrative
system and staff are already in place. Therefore, the proposed regulations require a
minor incremental effort.
Total national social costs, then, are equal to the sum of these four
components: 1) real resource costs; 2) deadweight welfare loss; 3) worker adjustment
costs; 4) government administrative costs.
3-^a
-------
APPENDIX 3A
Summary of §308 Survey Economic Data
There are 978 plants in the OCPSF §308 Survey database. Of these, 939 plants
list at least one OCPSF SIC code being produced at the plant in the year requested by the
Survey (1982) (i.e., are in-scope); 39 plants do not list any SIC codes that are categorized
as OCPSF; and 35 plants give no sales or production data.
Table 3A-1 summarizes employment, production and shipments data from the
plants in-scope in the OCPSF §308 Survey database.
Number
of
Plants in §308 database
978
Number
of
Plants in scope
939
Number
of
Plants out of scope
39
3A-1
-------
Table 3A-1. Suamary of §308 Survey Economic Data for OCPSF Planes
In Scope*
Variable
# of Plants
with Data
# of Plants
missing Data
or Zero Values
Mean Value
Sum
o£ Values
Plant Employment
935
4
303
283,485
OCPSF Employment
927
12
195
180,739
OCPSF Production
931
8
99,474.
92,610,981
Quantity (tons)
Non-OCPSF Production
431
508
108,2142
46,640,270
Quantity (tons)
OCPSF Shipments
919
20
32,406.1
75,731,198
Quantity (tons)
Value (M$)
918
21
64.6
59,334.8
Non-OCPSF Shipments
433
506
83,062.52
35,966,051
Quantity (tons)
Value (M$)
433
506
46.7
20,242
Note: 1 ton = 2000 Lbs
M$ = million doLlars
'"These plants list at least one OCPSF SIC product group as produced at
the plant at the time of the §308 Survey.
^These values exclude plane production for which no SIC category was
indicated.
3 A—2
-------
Appendix 3B
Replacement Estimates for Hissing §308 Survey Data
For planes missing §308 Survey production and sales data, che following
methods were used to estimate replacement values. Missing production/saLes
data feLl into 7 distinct categories:
1) Total quantity produced (all purposes) missing only.
2) Quantity shipped missing only.
3) Value of shipments missing only.
4) Both total quantity and quantity of shipments missing.
5) Both quantity and value of shipments missing.
6) Both total quantity produced and value of shipments missing.
7) TotaL quantity, quantity shipped, value of shipments missing.
Replacement values were estimated for categories 1-6 only.
Missing data were filled using two ratios:
1) product ion/shipment ratio, and
2) unit price, equal to the quantity of shipments divided by the
value of shipments.
For both of these ratios, median values for individual SIC codes were
used. Median values were used because mean statistics had extremeLy large
variances—resulting from a few extreme values (e.g., high-priced, low-volume
specialty products). In determining production/shipment ratios, it was found
that a 1:1 relationship generally existed between total production and quan-
tity of shipments. For the purposes of the data replacement methodology,
total production and quantity of shipments were assumed to be equal. Median
unit price values were calcualted for 8-digit SIC codes. If median unit
prices could not be fixed for 8-digit SIC codes, 4-digit codes were used. In
the event that unit prices for 4-digit codes could not be fixed, 3-digit SIC
codes were used. In cases where unit prices for 3-digit SIC codes could not
be determined, unit prices were not used. Unit prices by 8-digit SIC code are
shown in Table 3C-1.
Missing data were estimated as follows:
1) Total quantity missing only: total quantity set equal to quantity of
shipments.
2) Quantity shipped missing only: quantity skipped set equal to total
quantity produced.
3) Value of shipment tnisging only: value of shipments set equal to quantity
shipped multiplied by unit price.
4) Both total quantity and quantity of shipments missing: quantity of ship-
ments set equal to value of shipments divided by unit price. Total
quantity set equal to quantity of shipments.
3B-1
-------
5) Both quantity and value of shipments missing: quantity shipped equal to
total quantity, value o£ shipments equal'to quantity shipped muLtipLied by
nit price.
6) Both total quantity produced and vaLue.of shipments missing: total
quantity set equal to quantity shipped multiplied by unit price.
Replacement data were not estimated if: 1) data were missing for total
quantity of production and quantity shipped and value of shipments, or 2)
insufficient data were available to determine unit price (and unit price was
needed. Co estimate the replacement value), or 3) SIC code was missing.
3B-2
-------
Table 3B-1
LIST OF UNIT PRICES USED FOR OATA REPLACEMENT METHODOLOGY
SIC
UNITPRICE
SIC
UNITPRICE
(S/lb.)
(J/lb.)
IOOOO
.72
28342004
(283)
4.2
20000
NA
28343002
(283)
4.2
30000
NA
28344000
(283)
4.2
18286120
NA
28345007
(283)
4.2
20481000
NA
28346005
(283)
4.2
20874715
NA
28347003
(283)
4.2
22971250
NA
28348001
(283)
4.2
227971352
NA
28349009
(283)
4.2
26112813
NA
28410130
(284)
.68
26112854
NA
2841100 (284)
.68
26289926
(262)*
.39
28412000
(284)
.68
26414000
NA
28423000
(284)
.68
26452003
NA
28424000
(284)
.68
28121002
(28T2)
.07
28430007
(2843)
.675
28123008
(2812)
.07
28430858
.63
28132009
(281)
.14
28441376
(284)
.68
28135002
(281)
.14
28443158
(284)
.68
28136000
(281)
.14
2851000 (2851)
.97
28137008
(281)
.14
28511000
(2851)
.97
28163000
(281)
.14
28511210
(2851)
.97
28163103
(281)
.14
28511228
(2851)
.97
28163319
(281)
.14
28511244
(2851)
.97
28190000
(2819)
.19
28511251
(2851)
.97
28190190
(2819)
.19
28511350
(2851)
.97
28193001
(2819)
.19
28511376
(2851)
.97
28194009
.04
28511384
(2851)
.97
28197002
.23
28511434
(2851)
.97
28198000
(2819)
.19
28511459
(2851)
.97
28199008
.35
28511475
(2851)
.97
28212000
(2821)
.58
28511491
(2851)
.97
28213007
.54
28511533
(2851)
.97
28214005
.62
28511574
(2851)
.97
28219005
(2821)
.58
28511590
(2851)
.97
28220000
(2822)
1.09
28511632
(2851)
.97
28220002
(2822)
1.09
28511657
(2851)
.97
28233419
(282)
.70
28511699
(2851)
.97
28241438
(2824)
1.05
28511715
(2851)
.97
28274005
(282)
.70
28511731
(2851)
.97
28331000
(2833)
4.00
28511756
(2851)
.97
28331205
(2833)
4.00
28511772
(2851)
.97
28332458
(2833)
4.00
28511814
(2851)
.97
28333185
(2833)
4.00
28511830
(2851)
.97
28341006
(283)
4.2
28511855
(2851)
.97
28511897
(2851)
.97
28797819
(2879)'
2.34
28511939
(2851)
.97
28798007
(2879)
2.34
28512000
(2851)
.97
28914000
.77
28512515
(285T)
.97
2891433T
(289T)
.64
28512531
(2851)
.97
28914414
(2891)
.64
( ) denotes SIC group used for unit price If 8-digit SIC not
used.
3B-3
-------
SIC
UNITP9ICE
SIC GROUP
UNITPRICE
(S/lb.)
(S/lb.)
28512614
(2851)
.97
28914430
(2891)
.64~
28513000
(2851)
.97
28914539
(2891)
.64
28513018
(285D
.97
28918610'
(2891)
.64
28513075
(2851)
.97
28992923
(2899)
.62
28513117
(2851)
.97
28992949
(2899)
.62
28513133
(285D
.97
28995314
(2899)
.62
28513299
(2851)
.97
28995595
(2899)
.62
28514000
(285D
.97
28995611
(2899)
.62
28516000
(285D
.97
28995686
(2899)
.62
28518213
(285D
.97
28995819
(2899)
.62
28519000
(285D
.97
28995835
(2899)
.62
28519114
(2851)
.97
28995959
(2899)
.62
28519783
(2851)
.97
28995975
(2899)
.62
28611135
(286) -
.96
28995983
(2899)
.62
28611234
(286)
.96
28999000
(2899)
.62
28611317
(286)
.96
29110582
(291t)
.18
28612968
(286)
.96
29110590
(2911)
.18
28612984
(286)
.96
29111317
(291t)
.18
28651008
.54
29115110
(2911)
.18
28652000
(2865)
1.34
29116324
(2911)
.18
28652006
(2865)
4.02
29123008
(291)
.18
28653004
4.60
29920212
NA
28653005
(2869)
4.60
30200000
NA
28653500
1.34
30790000
(3079)
1.28
28655009
1.34
30790208
(3079)
1.28
28693133
3.47
30790406
(3079)
1.28
28693158
.93
30790422
(3079)
1.28
28693315
1.23
30790448
(3079)
1.28
28693513
.65
30790455
(3079)
1.28
28694008
(2869)
3.47
30790463
(3079)
1.28
28695310
(2869)
.93
30790471
(3079)
1.28
28695334
.93
30790604
(3079)
1.28
28695377
7.22
30790612
(3079)
1.28
28695534
(2869)
.93
30790992
(3079)
1.28
28645559
(2869)
.93
30791000
(3079)
1.28
28695989
.93
30791107
(3079)
1.28
28696003
1.02
32990980
NA
28696258
(2869)
.93
34121004
NA
28697000
(2869)
.93
34122002
NA
38697001
.70
34123190
NA
28731008
.07
34286930
NA
28795318
(2879)
2.34
35555640
NA
28795417
(2879)
2.34
35690000
NA
28796001
(2879)
2.34
35756000
NA
28796415
(2879)
2.34
36293980
NA
28796613
(2879)
2.34
36627982
NA
28796712
(2879)
2.34
36790905
NA
28796811
(2879)
2.34
38610000
NA
38611210
NA
3861400a
NA
38618138
NA
42289959
NA
87280000
NA
93000008
.88
99980138
(9998)
.74
99980518
(9998)
.74
99980989
(9998)
.74
99989006 .79
3B-4
-------
APPENDIX 3C
OCPSF Industry Cost of Capital Estimation
There are many ways that industry cost of capital can be estimated. This
appendix discusses some of the concepts important for estimating cost of capital,
highlights some of the problematical areas in developing such estimates, notes the
alternatives considered for this analysis, and describes the method used in the economic
impact analysis.
The cost of capital is used in this analysis in two ways: 1) to annualize
wastewater treament capital investment costs; and 2) to discount cash flows for the
closure analysis. Investment in wastewater treatment is new investment and so the rate
used must be incremental for new funds rather than based on the firm's historical
financing costs. The cost of capital for wastewater treatment depends on how the
investment is financed, but fundamentally, it is an opportunity cost reflecting the best
alternative rate of return that can be obtained by the firm including purchase of its own
stocks.
To discount cash flow and the terminal salvage value of the plant over the
planning period for closure analysis, a discount rate is required. Because the bulk of
fixed costs is already sunk in plant and equipment in place, an average historical rate of
return based on total assets is appropriate for this type of analysis. This rate is also an
opportunity cost based on the best return that is obtained by the firm from its
investment.
To finance business enterprise, a company may issue stock to obtain funds which
is called equity financing. A company also has the option of buying back its own stock on
the open market and if it should do so, the resulting increase in stock value would be the
highest rate of return available on the equity portion of its assets. Debt is a second
source of funds which includes bonds, notes and short-term commercial paper. These are
usually the cheapest forms of funding, but as a firm expands its debt holdings, its cost of
debt increases, forcing it to reach an equilibrium with its return on equity. In addition to
these two major financing mechanisms, a company can issue preferred stock. These
latter sources of capital are minor in comparison to common stock and corporate debt
issues.
Some of the difficulties and necessary assumptions involved in estimating cost
of capital are summarized below:
1. The marginal rate of return on debt, equity or total assets is
the appropriate rate to use to estimate cost of capital since
the estimation is of the return to (or cost of) an additional
dollar spent. Unfortunately, however, data to estimate the
marginal rate are not available; company income statement
data provide only historical information on the average rate
of return, which reflects past Investors* perceptions of the
firm's financial position. Therefore, it was necessary to
accept this limitation in order to estimate cost of capital
from company financial statements.
2.. There is some question as to whether to estimate cost of
capital using return on equity or return on capital as a
3C-1
-------
whole. Pollution control equipment can be financed using
new stock issues, debt instrument issues or retained
earnings. In addition, a company's equity position can change
through buy-outs or mergers or additional loans. Also, in a
period of inflation, the value of debt decreases relative to the
value of equity. It, therefore, appears preferable to estimate
the cost of capital based on cost of both debt and equity, i.e.,
the weighted average cost of capital.
3. It is generally agreed that real rate of return calcualtions are
preferable to nominal rate calculations for discounted cash
flow analyses because they allow the use of constant annual
cash flows instead of projecting future cash flows. However,
such a choice does limit the data available for the calculation
since information on inflation adjustments is only available
for a few years from large public companies which are
required to include this information on the IQ-K reports.
Furthermore, if the real rate of return is used to estimate
cost of capital, the other items in the analysis such as
depreciation and inventory must also be adjusted for inflation
effects. Despite these limitations, a real rate of return is
estimated for the closure analysis cost of capital, and other
appropriate adjustments are made so that annual cash flows
can be assumed to remain constant over the planning period.
4. Stock prices are sometimes used to calculate return on
equity. This assumes that the stock price represents the
value of the firm, but may not be an appropriate assumption
since the stock price is affected by many other factors which
create optimistic or pessimistic markets. Investor dividends
are also sometimes used for cost of capital estimations, but
the future growth rate of dividends is not easy to predict. In
addition, if earnings data are used along with stock prices,
they may not be reported for the same time periods.
Therefore, neither of these measures were used. Rather, the
Capital Asset Pricing Model (CAPM) equation was used to
estimate cost of equity.
Both nominal and real weighted average costs ot capital have been developed
for those OCPSF parent corporations in the Standard and Poor's COMPUSTAT Database
and for which the Value Line Investment Survey reports a Beta (B) or risk premium. This
is done only for those plants with no missing values for debt or equity on COMPUSTAT.
Therefore, the weighted average costs of capital were developed for 84 companies with
plants in scope. The following equations are used for the calculations:
r = i + (Rm - 1)B,
(1)
Nominal WACC = Ke/a) +- y
-------
Definitions and Sources of Variable Values
r = After tax return on company equity estimated using
CAPM. Presented in percents.
i = 7.90% = Risk free rate ofreturn (from the DRI Macromodel
rate on Long Term Government Bonds).
(Rm - i) = 8.3% = Risk Premium = Rate of return of market portfolio
less the rate on risk free investments. Developed from 56
years of data.
B = Beta = A measure of the risk of an individual firm
compared with the market. An average of four years of
company Beta values taken from Value Line Investment
Survey, Part 1 Summaries
-------
TABLE 3C-1. NOMINAL AND REAL WEIGHTED AVERACE COST
OF CAPITAL FOR OCPSF PRODUCERS IN SCOPE
Standard
N Mean Deviation
After Tax Return 84 16.08 .16
on Equity when
i = 7.90 (percent)
Ratio of Long- 84 .28 .08
Term Debt to
Total Assets
(d/a)
Nominal Weighted 84 14.02 1.22
Average Cost of
Capital when
i = 7.90 and
y=7.43
Real Weighted 84 8.11 1.17
Average Cost of
Capital when
inflation=4.5
percent
3C-4
-------
APPENDIX 3D
Company Financial Ratios and COMPUSTAT Data Use
The firm level analysis portion of the full plant closure analyis utilized financial
ratios calculated from COMPUSTAT data for those firms for which such data were
available. (102 firms owning approximately one half of the plants in scope).
The four baseline ratios calculated are shown below:
Current ratio = Total Current Assets
Total Current Liabilities
Coverage ratio = Profit Before Tax & Interest
(times interest Interest
earned)
Return on
Total Assets = Profit Before Tax
Total Assets
Debt to Worth = Total Liabilities
(Total Assets - Total Liabilities)
Ratios were recalculated after adding compliance capital, O&M costs, and new
interest in order to estimate the financial condition of firms under post-baseline
conditions.
Note: For firms without available COMPUSTAT data, median financial ratios
based on Dun and Bradstreet data were calculated under baseline conditions, for size and
two 3-digit SIC codes. The baseline ratio values were perturbed using individual firm
level estimates of changes in current assets, total debt, etc.
3D-1
-------
APPENDIX 3E
Construction Data
1986 Data
For U.S. plants only (including those in engineering stage or with estimated
dates of completion into 1987), the following information on new plant construction was
available. (NOTE: MM = million, M = thousand, t = metric tons, b = barrels, cf = cubic
feet, d = day.) (1986 data.)
Product Number of Plants Capacity Range
Natural Gas Plant 4 15-65 MM cf/d
Isomerizer C5-C6 6 .5-7A M b/d
Fuel Alcohols 8 .2-2.3 M b/d
Resins 2 80-240 t/d
("40-120 mil lb/yr)
The following are also under construction but have no cost information available:
Dinitrotoluene 1 260 t/d
("130 mil lb/yr)
Polymerizer 1 5.5 M b/d
Additives 1 25 MM b/d
Propylene Oxide 1 (expansion) add 220 MM lb/day
Glycol Ether I (expansion) add 60 MM lb/yr
Acrylic Acid 1 120 MM lb/yr
Acetic Acid 1 (expansion) add 160 MM lb/yr
Alpha Olefins 1 (expansion) add 50 MM lb/yr
MBTE 1 2.1 M b/d
Vinyl Copolymers 1 22 MM lb/yr
In addition, two polymer plants are planned, but no capacities were given.
Based on estimated cost, both are small plants. The last group is included to provide a
feel for what other types of plants are being built, and for the nature of planned
expansions, even though there is no cost data.
Because the baseline analysis year is 1988, the most recent data (1986) would
preferredly have been used, as these projects include some planned into 1987. In order to
improve (expand) the cost data somewhat, those plants listed in 1984 and 1985—but not in
1986—were included as well. A resultant summary of estimated capacity and estimated
cost by SIC for various types of plants is presented below. (Ideally, this analysis should
be based on small and large model plants for each subcategory. However, the data will
not support estimates across ail subcategories. Hence, use of SIC codes appears to be
the best alternative.)
^Hydrocarbon Processing, Boxscore Section, June 1986.
3E-1
-------
SIC Project
2821
2823
2824
2865
2869
Resins
Polyners
Resins
Polystyrene
Vinyl Copolymer
ABS Resins
Summary Data
Estimated Capacity
22
Small (not given)
80 MM lb/vr
50 MM lb/yr
22 MM lb/yr
60 MM lb/yr
Estimated Cost
No cost given
$4 Mil, $6 Mil
$80 Mil
$10 Mil
No cost given
$60 Mil
No information available from this source.
No information available from this source.
Dinitrotoluene
Benzene
Acrylic Acid
Ethylene Glycol
Ethylene Oxide
Fuel Alcohol,
(e.g. Ethanol)
Propylene Oxide
Acetic Acid
Butanediol
260 td/Cl30 MM lb/yr)
327 Mt/y (654 MM lb/yr)
75 MM lb/yr
378 MM lb/yr
300 MM lb/yr
1 M b/d
add 220 MM lb/yr
300 MM lb/yr
100 MM b/yr
No cost given
$135 Mil
$75 Mil
No cost given
No cost given
$40 Mil
No cost given
$100 Mil
$16 Mil
Note:
Data for a few of the chemicals above are average figures based on data for
more than I plant being constructed..
These estimates are rough because there are not many new plants being built in
the U.S. and because some of those which are being built have no cost data associated
with them. It is still possible to get some feeling for what might constitute a small plant
vs. a large plant for the different SIC categories. In general, the plastics plants now
being constructed tend to be small relative to the miscellaneous cyclics and acyclics,
excluding the fuel alcohols. Within the plastics and resins, 'polymers' appear to be small
relative to resins and polystyrene (although the types of polymers were not specified and
polystyrene is also a polymer, it is assumed these are specialty polymers). Within SIC
2865, benzene production is much larger than DNT production.
Based on the data described above, it was determined that small plastics plants
tended to be polymer or resins plants costing in the range of $6-15 million dollars, with
capacities of approximately 6 to 22 million pounds a year. There were no data for small
This observation is supported by summary data from April 1984, 1985, and 1986
Chemical Engineering construction data which suggest that about 40% of capacity
addition in plastics and resins is resulting from new plant construction compared with
about 65% in organics. Note: While we do not believe that this information source is
presenting all expansion construction, the relationship is relevant. Large plastics plants
are being expanded, while small plastics plants are being built from scratch.
3E-2
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TabLe 3E-1
PRODUCTION QUAMTTTY OF IN-SCOPE PLAMTS
(millions of pounds/year)
Size 1
Size 2
Size 3
Size 4
Size 5
LT 20
20-50
50-100
100-200
GE 200
MO SIC #
23
3
1
1
1
Mean
SD
2821
# of Plants
102
91
60
53
77
Mean
7.7
32.7
70.4
140.3
954.1
SD
6.2
8.1
14.7
28.4
1943.7
Range
(205-16,482)
2823
# of Plants
1
1
4
Mean
7.65
28.2
—
—
473.4
SD
••
209.0
2824
# of Plants
11
3
5
7
15
Mean
5.5
37.6
82.1
151.5
481.6
SD
5.4
8.1
10.0
35.4
264.9
2865
# of Plants
54
11
6
5
35
Mean
5.6
31.7
78.3
158.6
979.7
SD
5.5
10.1
16.0
27.3
2140.8
Range
(215-13,001)
2869
# of Plants
133
56
47
40
122
Mean
6.1
32.8
75.7
134.7
1786.6
SD
5.5
8.6
14.8
25.8
2604.7
Range
(201-19,296)
3E-3
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SIC 2365 or SIC 2869 plants. Medium co large plants in these SICs have capacities of
about 30-300 million pounds per year, and cost aLout $30-135 million. As a result, $L0
million was chosen for small plants in SIC 2821 and $ 100- L10 for large plants in SIC 2821,
2S65 and 2869. These 'typical' construction costs were then linked to plants in scope
having similar characteristics.
A frequency distribution of production quantity of §308 plants showed that a
large percentage of existing plants fell either into the small category or a larger one.
(See following page.) Therefore, 0-20 million pounds/year capacity plants from the §308
database were assumed to have characteristics similar to a new plant costing $10
million. Plants in the range 100-200 million pounds per year (SIC 2821) or 200-500 (SIC
2865 and 2869) were considered to have similar characteristics to a new one costing $100
(SIC 2861, 2865) or $110 (SIC 2869) million. (Based on the appearance that large plastics
plants are somewhat smaller and cost in the same range as large SIC 2869 plants.) These
estimaxes are very rough, at best. (Capacity Utilization was assumed to be 80 percent.)
3E-4
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».0 TREATMENT COSTS
4.1 Overview
This impact analysis addresses the effects on manufacturers of organic
chemicals, plastics and synthetic fibers of cost increases due to wastewater pollution
control. This section provides a brief description of treatment technologies and their
costs. It also discusses the statutory mandate for developing effluent guidelines
limitations and standards regulations, a summary of the regulatory options, the
regulatory subcategorization scheme, the effects of other environmental regulations,
and a discussion of the treatment costs used in this analysis. A detailed discussion of
the production processes, effluent wastewater sources, pollutant loadings, existing
treatment practices, available treatment technologies, and the costing methodology is
given in the technical support documents (Costing Documentation and Notice of New
Information Report).
4.2 Statutory Authority
EPA, under Section 301 of the Clean Water Act, is mandated to establish
regulations for the following categories.*
Best Practicable Control Technology Currently Available (BPT).
These rules apply to . existing industrial direct dischargers, and
generally cover control of conventional pollutant discharge.
Best Available Technology Economically Achievable (BAT). These
rules apply to existing industrial direct dischargers and control of pri-
ority non-conventional pollutant discharges more stringent than
BPT.
New Source Performance Standards (NSPS). These rules apply to new
industrial direct dischargers and cover ail pollutant categories.
*
U.S.C. et seq. as amended by Public law 95-217.
* Conventional pollutants are defined as biochemical oxygen demand (BOD)
total suspended solids (TSS), oil and grease, and pH. Other pollutants may also be
regulated at the BPT level.
Priority pollutants are defined as the 126 pollutants listed in the Clean
Water Act. Non-conventional pollutants are those parameters not defined as
conventional or priority pollutants.
4-1
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Pretreatment Standards for Existing Sources (PSES). These rules
apply to existing indirect dischargers (whose discharges enter
POTWs). They generally cover the control of toxic and non-
conventional pollutant discharges that pass through the POTW or
interfere with its operation. They are analogous to the BAT controls.
Pretreatment Standards for New Sources (PSNS). These rules apply to
new indirect dischargers and generally cover the control of toxic and
non-conventional pollutant discharges that pass through the POTW or
interfere with its operation.
4.3 Treatment Control Technologies
The OCPSF industry has a diversity of effluent wastewater characteristics
among the segments of the industry. Even within some plants, wastewaters contain a
variety of pollutants that require several treatment technologies to control both
conventional and priority poilutant discharges. The technologies described here, alone
or in combination with others, are expected to enable manufacturing facilities to
achieve the effluent limitations presented in this notice. Table 4-1 summarizes the
relevant treatment technologies and the classes of pollutant parameters they typically
treat.
4.4 Subcategorization of Industry
Seven production subcategories were developed by the Agency to classify
production lines, characterize pollutant discharges, and estimate the costs of BPT
control technologies. The compliance cost estimation is based on the determination of
long-term average effluent target concentrations of BOD and TS5 using the same
regression analysis used to determine subcategory limitations. This method determines
plant target limits for costing purposes by taking into account the production in each of
these subcategories rather than assigning plants to a single production subcategory.
They are generally defined as follows:
(1) Rayon Fiber (Viscose process only)
(2) Other Fibers (SIC 2823, except rayon, and 2824)
(3) Thermoplastics (SIC 28213)
*Both PSES and PSNS control non-conventional pollutants, but may also cover
conventional pollutants.
4-2
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Table 4—1. Treatment Technologies Available
for Abatement of OCPSF Pollutants
Treatment Process
Class of Pollutant Parameters Treated
In-Plant Controls
Solvent Recovery
Activated Carbon Adsorption
Steam Stripping
Oxidation
Precipitation/Coagulation/
Flocculation
In-pLanc Biological Treatment
End-of-Pipe Controls
Equalization
Neutralizat ion
Clarification
Flotation
Biological Treatment
Polishing Technologies after
Secondary Treatment
(polishing ponds, filtration,
etc.)
solvents (benzene, toluene, methylene
chloride, etc.)
BOD, COD, TOC, all priority organic
pollutants
voLatile organic chemicals(VOCs)
cyanide, sulfide, ammonia, most organic
compounds
suspended solidsr suspended metals
polynuclear aromatic compounds (PNAs-),
phthalate esters, acrylonitrile, phenol,
and 2,4-dimethylphenol
no direct removal — increases
effectiveness of subsequent creatment
processes
pH
suspended solids and other suspended
pollutants
suspended solids, oil and grease, other
suspended pollutants
BOD, TSS, COD, TOC, all priority
pollutants
BOD, TSS, COD, TOC, all priority
pollutants
Zero or Alternative Discharge entire discharge diverted
Deep well disposal
Contract Hauling
Offsite treatment
Incineration
Evaporation
Impoundment
Land Disposal
Source: Industrial Technology Division, U.S. EPA
4-3
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(4) Thermosets (SIC 28214)
(5) Commodity Organics — organic chemical products produced
nationally in amounts greater than or equal to one billion pounds
per year (generally SIC 2865 and 2869)
(6) Bulk Organics ~ organic chemical products produced nationally
in amounts less than 1 billion but more than 40 million pounds
per year (generally SIC 2865 and 2869)
(7) Specialty Organics — organic chemical products produced
nationally in amounts less than or equal to 40 million pounds per
year (generally SIC 2865 and 2869)
4.5 Regulatory Options
Unlike other industries for which EPA has established el£luent guidelines, the
OCPSF industry is not amenable to the specification of a single mode! technology.
Instead, effluent limitations will be achieved using some combination of in-plant
controls, treatment of specific wastestreams by any of a variety of physical/chemical
methods, biological treatment of combined wastestreams, and posc-oiological
treatment. Several options were considered in a preliminary analysis, but were not
retained because they were not technically viable. The final analysis focused on BPT
Option I, BAT Options IIA and LIB, and PSES Options IVA, IVB, and VII.
4.5.1 BPT Options
Effluent limitations for BPT are developed by analyzing effluent data from
biological treatment facilities that perform well. Three technology bases were initially
considered for purposes of setting effluent limitations. BPT Option I is based on
biological treatment without post^biological controls. BPT Option II is based on
biological .treatment systems with polishing ponds. BPT Option III is based on BPT
Option I technology with the addition of multimedia filtration to reduce solids in the
effluent wastewater. The rationale for considering these technologies is included in the
technical support documents. BPT control options II and III were not retained in the
final analysis. BPT Option I is described in Table 4-2.
4.5.2 BAT Options
BAT options are developed to control priority pollutants. Non-conventional
pollutants are not directly controlled by these regulations, though they will be treated
incidentally. Table 4-3 summarizes these options. BAT Option [ is based on biological
4-4
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TabLe 4-2. BPT Technology Option
BPT Options Description
BPT Option I End-of-pipe biological treatment for BOD, TSS and pH. The
bioLogicaL treatment unit operation, typicaLly activated
sludge or aerated Lagoons, is followed by clarification and
may be preceded by appropriate process controls and in-
plant treatment to assure that the biological system may be
operated optimally. BPT Option I technologies generally
include one or more of the foLlowing items: chemically-
assisted clarification, improved bioLogicaL treatment
operating procedures, or second—stage bioLogicaL
treatment.*
-Contract Hauling is used for flows of less than 500 gpd.
-------
Table 4-3. 8AT Technology Options
3AT Options
Descri pc ion
BAT Option I
BioLogicaL treatment (based on BPT Option I) or
in-pLant controLs for pLants with physical/chemi-
cal treatment in pLace.*
BAT Option IIA
End-of-pipe bioLogicaL treatment plus in-plant
physical/chemical controls for priority
po11utants.
For waste streams
containing:
— poLynuclear aromatic
priority pollutants
(PNAs)
— activated carbon adsorption-
— metals
— chemicaL precipitation
— volatiLe compounds
— steam stripping
— base/neutral or acid
— activated carbon adsorption (with the
combination of steam stripping and activated
carbon for one poLLutant)
priority poLLucants
— cyanide
— aLkaline chLorination
BAT Option IIB
End-of-pipe biological treatment plus in-plant
biological and physical/chemical controLs for
priority pollutants.
For waste streams
containing:
— PNAs
— in-pLant bioLogicaL treatment
— metals
— chemicaL precipitation
— volatiLe compounds
— steam stripping
--¦ base/neutral or acid
priority polLu.Lan.ta
— activated carbon adsorption (with the
combination of. steam stripping and
activated carbon for one poLLutant)
— cyanide
— aLkaLine chLorination
BAT Option V
BAT Option IIA and end-of-pipe activated carbon
adsorption.*
-Contract HauLing is used for flows o£ less than 500 gpd.
4-6
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treatment equivalent to BPT Option I. This level of control can be achieved using
either biological or physical/chemical treatment. BAT Option IIA is based on biological
treatment plus a variety of in-olant controls for waste streams containing metals,
volatile organic compounds, base-neutral or acid priority pollutants, and cyanide. BAT
Option 1IB is equivalent to BAT Option IIA controls except that in-plant biological
treatment is used rather than activated carbon for removal of certain priority
pollutants such as polynuclear aromatics, phthalate esters, phenol, acrylonitrile, and
2,^-dimethvlphenol. BAT Option V is based on BAT Option IIA plus end-of-pipe carbon
adsorption for greater control of certain organic pollutants.
4.5.3 PSES Options
PSES options control priority and non-conventional pollutants discharged from
indirect dischargers. Table 4-4 summarizes these options. The Agency is considering
the full range of technology options for indirect discharges that are under consideration
for BAT. PSES options control those pollutants that pass through, or interfere with, a
well-operated POTW to the levels calculated for BAT Options IIA or (IB.
PSES Option IVA is based on a variety of in-plant control technologies and
treatments comparable to those considered under BAT Option IIA. In-plant controls
under PSES Option IVB are equivalent to BAT Option IIB in-plant controls including in-
plant biological treatment as described above. PSES Option VII is the same as PSES
Option IVB controls plus end-of-pipe biological treatment for the additional removal of
selected priority pollutants. All of these options are based on a variety of in-plant
physical/chemical controls, and where necessary, in-plant biological treatment.
4.5.4 NSPS and PSNS Options
The regulatory options for control of emissions of priority and non-
conventional pollutants from new sources (NSPS and PSNS) are identical to those
considered for existing dischargers.
NSPS Options
The options for controlling conventional poLLutants for NSPS are the same as
for BPT Option I. No new combinations of technologies have been identified.
For priority pollutants, the technology options for NSPS are the four BAT
options. Again, no new technologies have been identified.
4-7
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Table 4-4. PSES Technology Options
PSES Options
Description
PSES Option IVA
For waste streams containing:
~ PNAs
— metals
— volatile compounds
— base/neutral or acid priority
pollutants
— cyanide
Equivalent to 3AT IIA Ln-plant
controls for priority poLLutants.
— activated carbon adsorption
— chemical precipitation
— steam stripping
— activated, carbon adsorption
(t*ith the combination of
steam stripping and activated
carbon for one poLLutant)
— alkaline chLorination
PSES Option IVB
For waste streams containing:
— PNAs
— metals
— volatiLe compounds
— base/neutral or acid priority
pollutants
— cyanide
Equivalent to BAT IIB in-plant
controls for priority pollutants,
— in-plant biological treatment
— chemical precipitation
— steam stripping
— activated carbon adsorption
(with the combination of
steam stripping and activated
carbon for one pollutant)
— alkaline chlorination
PSES Option VII
End-of-pipe biologicaL treatment
for selected priority polLutancs
plus in-plant physical/chemicaL
controls analogous to BAT 11(B).
"Contract Hauling is used for flows of less than 500 gpd.
4-B
-------
PSNS Options
PSNS are intended to prevent the discharge of pollutants which pass through,
interfere with, or are otherwise incompatible with POTWs. As with existing indirect
dischargers, only priority pollutants will be regulated under PSNS. The technology
options for PSNS are the three PSES options.
-------
The nature, extent and cost of such monitoring and lagoon-lining have been estimated
by the Agency for the OCPSF industry.
The total capital costs of installing monitoring wells and lagoon liners for 41
OCPSF facilities is estimated to total $22.6 million (1982 dollars). In addition, the
annual operational costs of groundwater monitoring and other administrative costs total
$4.5 million for the 41 plants incurring RCRA costs.
4.7 Estimation of Treatment Costs
4.7.1 Treatment Costing
The Industrial Technology Division of EPA developed engineering cost
estimates for various components of pollution control. The major categories of costs
that are estimated for the treatment technologies discussed in Section 4.4 are:
capital equipment
• land
operation and maintenance, or haulage
sludge treatment and disposal (capital and 0<5cM)
compliance monitoring
Annual compliance costs include operation and maintenance for wastewater
treatment (contract hauling is employed for flows of less than 500 gpd), operation and
maintenance for sludge treatment, and disposal and compliance monitoring costs.
Capital investment includes capital equipment costs for wastewater treat-
ment, land costs, and capital costs for sludge treatment and disposal. The capital
investment costs'are annualized over 10 years using a capital recovery factor based on
the weighted average cost of capital. For plants belonging to small firms, the rate is
10.51 percent, for medium sized firms the rate is 9.55 percent, and for large firms, it is
8.11 percent. (See Chapter 3.0.)
All costs are estimated on a plant-by-plant basis. The treatment costs are
incremental over the cost of treatment in-place at the plants. In addition, BAT costs
are incremental to the costs of complying with BPT. Table 4-5 presents the total
estimated capital, operation and maintenance and total annualized costs for each of the
major options.
4-10
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Table 4-5. Summity of OCPSF Treatoent Costs by ReguLatory Option
(1982 ^millions)
Treatment Coses"-'
Regulatory
Opt ion
Number of Planes
Incurring Costs
Capical
Investment
Operacion &
Maintenance
Tocal
Annualized
BPT Option I
214
193.0
39.4
68.6
BAT Option I**
289
162.6
115.5
139.9
BAT Option IIA**
289
333.2
230.5
280.9
BAT Option IIB**
289
322.7
157.4
206.L
3AT Option V**
289
1100.8
578.1
744.1
PSES Option IVA
365
318.9
262.8
311.7
PSES Option IVB
365
260.7
142.8
182.7
PSES Option VII
365
319.4
152.4
201.3
-For che BPT arid PSES options, costs are incremental CO current treatment in
place. For che BAT.options, costs are incremental to BPT Option I.
•'•"^Plants with both direct and indirect discharges are included in BAT
options. All BAT costs are incremental to BPT I costs.
Source: EPA Estimates
4-11
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4.72 Plants Costed Versus Plants Analyzed
Table 4-6 presents the number of plants that are subject to this regulation, the
number of plants that are expected to incur costs, and the number o; plants for which
economic impacts are estimated. A total of 940 plants are expected to be covered by
the regulations. Of this total, EPA estimates that 657 plants (70 percent) vv ill actually
incur costs as a result of the regulations. Of the 283 plants that are not costed, 42
plants did not provide sufficient information to estimate compliance costs. The
remaining 240 plants are zero dischargers and would therefore not incur compliance
costs under the regulations. Nine of the 657 plants incurring compliance costs have
been excluded from the economic impact analysis for a number of reasons, including the
fact that the plant may have failed to report its production and sales by 4-digit SIC
code or that the plant did not report any production or sales within the OCPSF industry,
according to SIC codes.
All compliance cost estimates in this report are based on the total 657 plants
that were costed. The economic analysis impacts are reported based on the 648 plants
analyzed.
4-12
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Table 4-6. OCPSF Plane Count Comparison:
Those Covered by Regulations, Those Incurring Costs, and
Those Included in the Economic Impact Analysis
Direct
Dischargers*
Indirect
Dischargers
Zero
Dischargers
or Missing
Di scharge
Daca
TocaL
PLants
Covered by Regulations
292
365
233
940
Plants
Incurring Costs
292
365
0
657
PLants Included in
Economic Impact Analysis
286
362
0
648
••'Counts for direct dischargers incLude three plants which incurred costs under
BPT, but not under BAT because toxic pollutant Loadings information was not
available.
Source: EPA Estimates
4-13
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5.0 BASELINE
In order to assess the impacts of pollution control costs on the OCPSF
industry, it is necessary to understand its current and likely future economic and
financial condition. Since, as described in Chapter 3.0 (Methodology), the analysis is
driven by the plant level impacts, baseline plant economic and financial parameters are
of key importance. However, the plant level baseline estimates incorporate
assumptions and forecasts ol general macro-economic trends, as well as factors
associated with overall industry health and behavior. For example, much of the OCPSF
industry is in the process of restructuring. This restructuring has come about, to a
large extent, in response to increased competition from developing countries with
direct access to petroleum feedstocks and has implications for plant level capacity,
production and sales, as well as for foreign trade and new sources impacts.
The baseline year is assumed to be 1988. This year was selected because it is
expected to be a typical year for the economy in general, and for the OCPSF industry,
in particular. In addition, it is thought that firms will plan for compliance around that
time. This chapter summarizes conditions expected in 1988 and compares them to
those of 1982, the year reflected by the Section 308 data base. Section 5.1 presents an
overview of key baseline indicators. Relevant macroeconomic trends are described in
Section 5.2. The industry baseline is presented in Section 5.3, followed by the plant and
firm level baselines in Sections 5A and 5.5, respectively. The Foreign Trade baseline is
described in Section 5.6.
5.1 Summary and Overview
Overall economic performance through 1988 is expected to remain
moderately good. This, in turn, should lead to continued relatively
high consumption demand for the OCPSF industry products in the U.S.
Average GNP growth is projected to be about 3.5 percent through 1988.
Actual growth in 1983 and 198<* was substantially higher. Fixed investment is
anticipated to be especially high for the 6 year period, again, largely because of high
growth from 1983 to 1985. Inflation has been moderate from 1982. through the present
time, and is expected to remain so through 1988-. Housing starts picked up
tremendously from 1982 to 1983 as the economy recovered, leveling somewhat
thereafter. A slight cooling is expected after 1986. The unemployment rate has
dropped from 9.7 percent in 1982 to about 7 percent currently and is expected to drop
further. Interest rates have fallen substantially since 1982 when the prime rate was
5-1
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14.9 percent. DRI has projected that it will decrease to 7A percent by 198S.
Manufacturing capacity utilization increased to about SO percent after the recession,
where it has remained since 1983. Similar levels are expected through 1988.
On the negative side, the Federal deficit should stay high through 1988, and
the merchandise trade balance is projected to remain large and negative through 1988
£
as well. Slight improvement from the 1985 level of -$117 billion is anticipated.
General economic performance affects the OCPSF industry through industry
specific demand factors. Personal consumption, housing starts and automobile sales are
important domestic demand factors for the OCPSF industry. Marry of the miscellaneous
end products of the industry, such as dyes, perfumes and flavors, gasoline additives and
so on, go into such consumer products as food and beverages* cosmetics, detergents,
textiles and printed matter. Plastics and resins are used to a great extent in housing
construction and furnishings, and in automobiles. About 70 percent of intermediate
chemicals in the scope of study are used in finished chemicals in scope; about 10-20
percent of finished chemicals are used as intermediates in the production of plastics
and fibers.
Personal consumption is expected to parallel GNP growth, at about 3.5 percent
annually. As mentioned above, housing starts grew significantly from 1982 to the
present, but will grow little, if at all, from the present through 1988. Automobile sales
are expected to grow most rapidly over the period. In addition, automobile
manufacturers are moving towards increased use of plastics and resins in automobile
ft #
production, which may increase demand for plastics further.
Strength of the dollar is an important demand factor for the foreign
market.
A weakening dollar aids in improving the U.S. export position. DRI forecasts
that the dollar will fall nearly 9 percent relative to major trading partners in the period
from 1982 to 1988.
* Based on 1987 DRI projections for . 1982 through 1988, and Wall Street Journal,
October 1986.
**High Technology, October 1986.
5-2
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Input costs in OCPSF production will decrease relative to wholesale
prices.
While wages are projected to increase slightly faster than producer wholesale
chemical prices, other input costs are very favorable. Interest rates have fallen
dramatically since 1982, and are expected to stay fairly low through 1988. Feedstock
prices have also fallen a great deal since 1982, with crude petroleum and petroleum
products prices forecast to fall the most (51 and 57 percent, respectively, over the
period 1982 to 1988). Finally, electric power, a major input in the production of many
chemicals, is expected to increase in price slightly less than wholesale chemical
prices. Most of that increase has already occurred.
International competition, especially in commodity chemicals, is a
major factor driving a restructuring of the chemical industry.
For most chemical product groups in the OCPSF industry, a drop in exports
and increase in imports is expected between 19&2 and 1988. For instance, in plastics
and resins, the single largest OCPSF product group, exports will drop about 26% over
the period, while imports will increase almost 300%; at the same time, domestic
consumption will grow about ^7 percent, and prices will drop slightly. The pattern is
similar for miscellaneous cyclic' and acyclic chemicals. Cyclic intermediates exports
are expected to increase about 12 percent over the 6 years, but imports should increase
about 180 percent, while domestic consumption increases 37 percent.
Tempering these numbers somewhat is the fact that overall net exports
accounted for only about 9-10 percent of production in 1982. Net exports will drop to
about 3 percent of production in 1988 as a result of increased imports and lower export
growth.*
Most available information (trade press, Department of Commerce, personal
communications) strongly suggests that in general, U.S. plastics and organic chemical
capacity will expand more slowly than world (especially developing country) capacity
over the forseeable future. In plastics, at least, the U.S. Department of Commerce
indicates that "U.S. firms will be preparing for the longer term prospects of keen
competition with foreign producers of commodity and speciality plastics, and will
* Based on 1987 DRI projections for 1982-1988.
5-3
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increasingly use facilities in other countries as bases for production for servicing
foreign markets."
The U.S. chemical industry is in a period of restructuring as U.S. firms
acknowledge that more and more commodity products will be produced in developing
countries with access to hydrocarbon feedstocks. This U.S. restructuring is based on
two major themes. First, producers are becoming less dependent on revenues from
production of commodities, and are continuing to move toward specialty products (e.g.,
pesticides, fertilizers and low-volume, higher value-added specialty chemicals). There
is potential for some of these low-volume products to become'medium- or possibly high-
volume products over time, However, as demand increases. Second, they are making
great strides in productivity improvement (e.g.,. by using cogeneration and replacing
production workers with technology). Furthermore, some hope to reap the benefits of
biotechnology in the relatively near future.
Announced capacity expansion world-wide through 1990-1991 is massive. Most
of this expansion will take place in developing countries, especially, Mexico, Brazil and
China. U.S. expansion is expected to comprise only about 4.8% of the total. The table
on the following page shows a breakdown of this announced expansion.by region. These
figures bury the product mix of planned production in each region, but in general,
commodity cyclic intermediates and crudes and commodity miscellaneous cyclic and
acyclic compounds, and some plastics, e.g., PVC, plants will be constructed primarily in
the developing countries, while smaller polymers and resins plants, and fuel alcohol and
additives plants {e.g., MTBE), will be constructed in the U.S. and other developed
& &
countries. (Some developing countries, especially in Latin America, also plan on
constructing fuel alcohol and MTBE plants).
Some 307 of 2,071 active projects in all stages of construction in the refining
and petrochemical industries are U.S. projects. However, the majority of U.S. projects
do not involve construction of new OCPSF plants, as they do in many developing
countries. U.S. capital expenditures for the chemical industry are up in 1986, but only
about a third of the money will be used to expand capacity.
Twenty percent of the new announced. U.S. projects are for cogenerating
plants, and the Chemical Manufacturers' Association estimates that expenditures for
U.S. Department of Commerce, U.S. Industrial Outlook, 1985, p. 14-2.
Construction Boxscore," Hydrocarbon Processing, Section 2, June 1986.
5-4
-------
environmental controls (air and water quality and solid waste management) and
occupational health will comprise about 13% of capital expenditures in the chemical
*
industry in 1986. Such large volume chemical plants as those for polypropylene,
ethylene, acetylene, styrene are more likely to be renovated, debottlenecked, and in
some cases, expanded, in the U.S. New plant construction is more likely to be for
specialty plastics or resins, fuel additives, or fuel alcohol.
Between 1980 and 1985, employment dropped 6.5 percent in the chemical
industry. Production workers' employment during that period dropped 8 percent.
Analysts expect further drops in production workers, as automation increases, and as
the need for increased customer service employees in speciality chemicals increases. In
* *
1985 and the first part of 1986, unit labor costs declined, and. productivity increased.
The majority of plants in the OCPSF industry have less than 500
employees, and less than 50 million in sales annually.
This is not true for fibers plants (cellulosics or synthetic fibers), which tend to
be significantly larger, although fewer in number. The baseline year employment in this
study has been assumed to remain at 1982 levels. Sales have been projected forward to
1988 based on DRI data. (See section 3.3.1.4).
We now turn to a more detailed description of the 1988 baseline projections
for the OCPSF industry.
5.2 Macroeconomic Baseline
The macroeconomic baseline defines the general economic environment in
which the OCPSF industry is projected to operate. It is based on DRI trend forecasts
for the U.S. economy. In addition, while many of the macroeconomic indicators
described in this section are not used directly in the analysis, they are implicit in the
industry-specific variables that are used to estimate plant production and sales, and
foreign trade impacts.
*Ted Wett, "Petrochemical Report," Oil and Gas Journal Report,
April 7, 1986, p. <*3.
Chemical Industry in Midst of Major Restructuring," Chemical and
Engineering News, April 7, 1986.
5-5
-------
Table 5-1
MACROECONOMIC BASELINE
Real Growth 1982-1988
Economic Indicators
Real GNP
GNP Expenditure Components:
Personal Consumption
Fixed Investment
Non-res ident ial
Residential
Final Sales
Inventory Investment
Federal Deficit
Prime Rate (change in prime rate)
Industrial Production
Manufacturing Capacity Utilization
Unemployment Rate
Total Employment
Consumer Price Index (all urban consumers)
Producer Price Index (finished goods)
Annual
Percent
3.5
3.5
4.4
11.1
3.3
2.0
-2.5
-10.9
4.2
2.4
-6.5
2.3
3.5
1.7
Total
Percent
23
23
29
88
21
13
-14
-50
28
15
-33
15
23
11
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1988
Forecast Results, May 7, 1986.
5-6
-------
Figure 5~1
MACROECONOMIC BASELINE
PERCENT GROWTH 1962-88
M
«
I
N
CO
Op
X
$
o
a.
o
5
u
s
ui
a
90
ao -
70 -
60
30 "
40 -
30 "
20 -
10
O
-10
-20
-30 H
-40
-SO
\
\
\
JZlS
\
\
K
\
JZ^
m
I
m
T~
6
T
7
\
s
\
\
R
n
n
\
\
\
\
s
N
\
\
\
\
J
-i 1 1 1 r
10 11 12 13 14
ECONOMIC IhOICCTORS
[7"7T AMMUAL IVnI TDWL
Key to Economic Indicators
1. Real GNP
2. Personal Consumption
3. Non-residential Fixed Investment
4. Residential Fixed Investment
5. Final Sales
6. Inventory Investment
7. Federal Deficit
8. Prime Rate
9. Industrial Production
10. Manufacturing Capacity Utilization
11. Unemploymen t
12. Total Employment
13. Consumer Price Indes (all urban consumers)
14. Consumer Price Indes (finished goods)
5-7
-------
As described above, 1988 was chosen as the baseline year based on
expectations that it will be a typical year for the OCPSF industry, and that wastewater
treatment regulations will be planned about this time. This section presents projected
changes in the general economic environment between" 1982, the year the §308 Survey
of the OCPSF industry was conducted, and 198S, the baseline year, and then examines
specific OCPSF industry demand and cost factors, as mentioned in the introduction.
3.2.1 General Economic Environment
DRI projects that the overall economy, in terms of real GNP, should grow at a
moderate annual rate of 3.5 percent between L982 and 1988, or by a total of about 23
percent. The growth of GNP expenditure components and other economic indicators is
shown in Table 5-1 and Figure 5-1.
As shown in Table 5-1, fixed investment, in particular residential fixed
investment, is expected to exhibit the greatest growth. Non-residential fixed
investment will also exhibit good growth, and inventory investment will grow a modest
two percent annually. The inventory-to-saies ratio is not expected to decrease
radically.
The federal government deficit is forecasted to remain high at $125 billion in
1988 (in 1982 dollars). However, this represents a decrease of about 14 percent from its
1982 level. These deficits are not expected to significantly limit investment funds nor
exert significant upward pressure on interest rates. The prime rate is expected to fall
from nearly 15 percent in 1982 to about 7A percent in 1988, according to DRI
projections as of January, 1987.
On the production side, industrial output is projected to increase at about 4.2
percent annually. Manufacturing capacity utilization will increase from 71 percent in
1982 to about 8L percent in 1988.
The unemployment rate is expected to fall from its 1982 level of 9.6 percent
to 6.5 percent in 1988. During this period, total employment is expected to increase by
about 15 percent or 2.3 percent annually.
Inflation is expected to be moderate^ with the consumer price index increasing
at about three to four percent annually between 1984 and 1988. The producer price
index is expected to increase at an even lower annual rate of one to two percent over
those years.
5-8
-------
5.2.2 Industry Specific Demand Factors
The most important demand factors for the OCPSF industry are: personal
consumption, housing starts, and automobile sales for strength of the U.S. market, and
strength of the U.S. dollar for foreign economic growth and growth of foreign OCPSF
producers. Available data on the baseline growth of these factors are shown in Table 5-
2. DRI data through L985 are actual, whereas those for 1986-1988 are projected.
Total personal consumption is projected to grow by average 3.5 percent
*
annually. This growth is partly due to a gradual downward trend in unemployment
coupled with a gradual increase in real wages.
Housing starts are an important demand indicator far the OCPSF industry
because OCPSF materials are used both in the construction and in the furnishing of
houses. Housing starts grew at 61 percent from 1982 to 1983; however, between 1983
and 1988 this rate of growth is expected to slow considerably to about 2 percent
annually (average annual growth rate = 8.6%). The value of residential construction
follows a similar trend with a high growth rate from 1982 to 1983 with a radical
subsequent slowing. The increase in housing starts over 1982-1983 is partially due to a
large decrease in housing starts the previous year, as well as a decrease in mortgage
interest rates from 16.6 to I3.
-------
Table 5-1
GROWTH OF OCPSF DEMAND FACTORS, 1982 TO 1988
Real Growth 1982-1988
Demand Factors
Domestic
Personal. Consumption
Housing Starts
Retail Unit Car Sales
International:
U.S. Dollar Strength
(Trade Weighted Exchange Race)
Average Annual
Percent Change
3.5
8.6
5.5
¦1.5
Total
Percent Change
23
64
38
Source: Data Resources Inc., Review of the U.S. Economy: Forecast Summary,
January 1987.
5-10
-------
5.2.3 Industry Specific Cost Factors
Input costs for the OCPSF industry during the 1982 to 1988 time period are
expected to remain favorable because interest rates have decreased dramatically since
1982, and are expected to stay low; wage increases are projected to grow only slightly,
faster than industry wholesale prices, and energy/feedstock prices have also decreased
dramatically. Projected prices and input costs changes for this period are shown in
Table 5-3. The interest rates used in the impact analysis and the cost of debt are
expected to decline over the period as shown in Table 5-4.
5.3 Industry Baseline
Between L982 and 1988, the OCPSF industry is expected to show an average
growth rate similar to that of all manufacturing industries. This is largely a result of
anticipated growth in U.S. consumption. The outlook for relevant production indices is
shown in Table 5-5 and Figures 5-2 and 5-3. Synthetic materials, the largest segment of
the OCPSF industry, are expected to show significantly higher than average growth, as
are rubber and plastic products. Moderate growth is expected for other OCPSF
products, with a decline in agricultural chemical production.
Growth in real prices and production between 1982 and 1988 is shown in Table
5-6. This growth is based on DRI chemical Model forecasts which cover approximately
75% of OCPSF production.
Overall nonagricultural employment in the U.S. is forecast to increase by 14
percent from 1982 to 1988, while the OCPSF sectors of the chemical industry are
projected to increase approximately 4 percent in the same period. Rubber and plastics
should grow a total of about 19 percent, while basic chemicals and petroleum product
employment will decrease at a .5 to 1.5 percent average rate annually.
Exports have been a significant market for chemical products, making up
about 10 percent of production in 1982. Foreign markets are projected to shrink to
comprise only 3 percent of production in 1988. This loss is primarily due to increasing
competition from foreign producers of commodity chemicals, particularly from plants
in energy-rich countries^
Note: Trade press articles indicate that some agricultural chemicals, e.g.,
pesticides, are expected to grow from 1986 on.
5-11
-------
Table 5-3
CHANCES IK OCPSF PRICES AND INPUT COSTS
Real Growth 1982-1983
Prices and Input Coses
Average
Annual
Percent
Total
Percent
Producer Price Index (Chemical and Allied Products)
1.2
7
Unit Labor Costs*"
3.7
26
Natural. Cas (Gas Fuels)
-4.7
-25
Crude Oil (Domescic and Foreign)
-11.1
-51
Pecroleum Products
-13.0
-57
Electricity
2.4
15
Source: Data Resources Inc., Review of Che U.S. Economyi Forecast Summary,
January 1987.
Table 5-4
BASELINE INTEREST RATES
Interest Races, Percent
Debt Instrument
1982
1988
Change
New AAA Bonds
13.79
8.79
-36.3
Risfcless Rate (T-bill)
10.61
7.90
-25.5
Prime Rate
14.86
7.43
-50.0
Source: Data Resources Inc.,
Review of the U.S. Economy:
Forecast
Summary
January 1987.
^Unit labor cost changes were calculated as the difference between changes in
the adjusted average hourly earnings for private non-farm production workers and
changes in output per hour for the non-farm business sector.
5-12
-------
TabLe 5-5
GROWTH OF CHEMICAL INDUSTRY PRODUCTION AND EHD-USE INDICES
Real Growth 1982-1988
Production Indices
Annual
Percent
Tota 1
Percent
Real GNP
3.5
23
AIL Manufacturing
4.0
28
Chemical End Products
5.6
39
Basic Chemicals
1.9
12
Synthetic Materials
8.8
66
Agricultural Chemicals
0.7
4
Rubber and Plastic Products
7.6
55
Textiles
5.4
37
Source: Data Resources Inc., Review of the U.S.
Economy: Forecast
Summary,
January 1987.
5-13
-------
Figure 5-2
CHEMICAL INDUSTRY PRODUCTION GROWTH
TOTAL PERCENT GROWTH 1962-1968
E£2
6
2
3
4
a
7
a
fTODUCTON INOCES
Key to Economic Indicators
1. Real GNP
2. Manufacturing
3. Chemical End Products
4. Basic Chemicals
5. Synthetic Materials
6. Rubber and Plastic Products.
7. Agricultraal Chenicals
8. Textiles
5-14
-------
Figure 5-3
CHEMICAL INDUSTRY PRODUCTION GROWTH
AWLW_ PERCENT GROWTH 1962-1988
S
7
6
a
2
4
R*CDLCTON INOCES
Key to Economic Indicators
1. Real GNP
2. Manufacturing
3. Chemical End Products
4. Basic Chemicals
5. Synthetic Materials
6. Rubber and Plastic Products
7. AgricuLtrual Cheaicals
8. Textiles
5-15
-------
TabLe 5-6
OCPSF INDUSTRY GROWTH INDICATORS
Industry Indicacors
Intermediate Organic Chemicals
Real Prices
Production (billion pounds)
Production Value (billion dollars)
Final Products (Plastics, Fibers, etc.)
Real Prices
Production (billion pounds)
Production Value (billion dollars)
OCPSF Employment (weighted ave)
Chemicals and Products
Petroleum Products
Rubber and Plastics
Total Employment (Nonagricultural)
Net Exports (Trade Balance, Goods and Se
ReaL Growth 1982-1988
Annual. TotaL
Percent Percent
.4 3
.4 3
.8 6
1.0 7
7.1 50
8.2 61
+.7 4.2
-.3 -2
-1.5 -10
2.9 19
2.0 14
ices) -5.3 -37
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1988
Forecast Results, May 7, 1986.
5-16
-------
While the outlook overall for the OCPSF industry is favorable, some segments
are expected to exhibit more growth than are others. As presented in Section 2, the
industry can be separated into two parts: I) intermediate (and basic) chemicals (3
product groups); and 2) finished chemicals (9 product groups). According to L982
production data, about 70 percent of the intermediate chemicals in the study scope are
used to produce finished chemicals in study scope. The remaining 30 percent are used
as solvents or to produce finished chemicals or other intermediate chemicals not in
scope. Further, about 10 percent of intermediate chemical production is used as
finished chemicals (e.g. solvents) and about 10 to 20 percent of the finished chemicals
are used as intermediate chemicals (e.g. polymer precursors for fibers and plasticizers).
The outlook for the overall OCPSF industry is primarily dependent on sales of
finished chemicals. The nine finished chemicals product groups are discussed as
intermediate and basic chemicals. Table 5-7 presents a summary of the results. Total
OCPSF industry production is projected to increase by about 30 percent between 1982
and 1988. Production growth by product group varies widely, but growth for most
groups ranges from 20 to 50 percent. These changes are shown graphically in total and
on an annual basis in Figures 5-4 and 5-5, respectively.
These production changes can be mapped into the five four-digit SIC codes
covered by the regulation. As shown in Table 5-8, plastics and resins (SIC 2821) and
cyclic crudes and intermendiates (SIC 2865) are expected to experience the greatest
production increases -- between 35 and 40 percent between 1982 and 1988. For SIC
2821, this increase in production is expected to be accompanied by an increase in
capacity of about 23 percent. Capacity in SIC 2865 is expected to decrease slightly
(about five percent). Both industry segments are projected to have capacity utilization
of 80 percent or greater.
5.4 Plant Baseline
In order to isolate and quantify the impacts of the proposed regulations on
plants and firms, it is necessary to perform baseline plant and firm level analyses
beforehand. Plant baseline data have been derived from the Section 308 survey on
£
. Those basic feedstock chemicals derived from coal about 5 percent of total
feedstock chemicals derived from petroleum or natural gas are not included.
*¦ * ...
This level serves only as a general guideline. Chemical specific capacities
can be misleading because equipment can be used to produce a variety of chemicals.
5-17
-------
Table 5-7
SUMMARY OF 1982-1988 OUTLOOK FOR OCPSF PRODUCT GROUPS
Production
Volume
Chemicals
Billion
1982
Pounds
1988
Real
1982
Annual %
Growth
-1988
Total %
FINISHED CHEMICALS
1.
Plastics and Resins
38.3
54.0
6.0
41
2.
Synthetic Fibers
6.4
7.5
2.7
18
3.
Miscellaneous End-Use
Chemicals and Chemical Products
22.1
28.7
4.5
30
4,
Plasticisers
1.4
2.0
6.0
43
5.
Cellulosic Fibers
0.6
0.8
3.8
25
6.
Dyes
0.2
0.25
4.8
25
7.
Organic Pigments
.07
.13
9.8
85
8.
Rubber Processing Chemicals
0.2
0.3
6.0
50
9.
Flavor and Perfume Materials
.2
.2
0
0
SUBTOTAL
UNFINISHED CHEMICALS
69.5
93.8
5
(avg.)
35
10.
Miscellaneous Cyclic
and Acylic
81.5
96.2
2.7
18
11.
Cyclic Intermediates
37.6
51.5
5.5
37
12.
Tars and Tar Crudes
4.0
NA
NA
—
SUBTOTAL
119.I2
147.7
3.5
24
Sources: Data Resources Inc., Chemical Service,
DRI Chemical Model
1982
Benchmark Case, Juiy3, 1984
and DRI Chemical Model
. 1988 Forecast
Results, May 14, 1986; ITC,
Synthetic
Organic Chemicals:
Prices and
Production for 1982, 1984;
Textile Org
anon, January 1984;
U.S.
Department of Commerce, 1983, U.S. Indu3Crustrial Outlook.
^1988 production based on DRI forecast where available, or 1982,
1983, and 1984 production levels and ITC growth rate from Synthetic Organic
Chemicals.
»
n
Less Tar and Tar Crudes.
5-18
-------
Figure 5-4
Outlook for OCPSF Product Groups
(1982-1908)
TOTAL PRODUCTION VOLUME
100
90
80
70
60
50
40
30
20
10
0
1 2 3 4- 5 6 7 8 9 101112
OCPSF Product Croup
V~A 1982 im 1988
KEY TO OCPSF PRODUCT GROUPS
1 PLASTICS AND RESINS
2 SYNTHETIC FIBERS
3 MISC END USE CHEMICALS
4 PLASTICIZE&S
5 CKT.I.ITLQS1C ELEERS
6 DYES
7 ORGANIC PIGMENTS
8 RUBBER PROCESSING CHER
9 FLAVOR AND PERFUME
10 MISC CYCLIC AND ACYCLIC
11 CYCLIC INTERMED
12 tapa AND TAR CRUDES
I
/s
m.
£
n [ M
I
A
A
/N
A
I
J4-
5-19
-------
Figure 5-5
Outlook for OCPSF Product Groups
(1962-1988)
PRODUCTION GROWTH
90
80 -
70 -
60 -
50 -
40 -
30 -
20 -
3
4
5
7
9
2
1
10
OCPSF Product Group
KEY TO OCPSF PRODUCT GROUPS1
1 PLASTICS AND RESINS
2 SYNTHETIC FIBERS
3 MISC END USE CHEMICALS
4 PLASTICIZERS
5 CELLULOSIC FIBERS
6 DYES
7 ORGANIC PIGMENTS
8 RUBBER PROCESSING CHEM
9 FLAVOR AND PERFUME ,
10 MISC CYCLIC AND ACYCLIC
11 CYCLIC INTERMED
12 TARS AND TAR CRUDES
^No growth predicted for flavors and perfumes. Data for tars and
tar crudes is unavailable.
5-20
-------
Table 5-8
PROOUCTION, CAPACITY AND CAPACITY UTILIZATION, 1982 AND 1908®
1982 1986 Percent Change 1982-1988
Segment .
SIC
Production
(10 pounds)
Capacity
<10 pounds)
Capacity
Ut11ization
Prj
<10*
3ductlon
pounds)
Capacity
<10 pounds)
Capacity
l)t 11 Ization
Product Ion
Capac i1y
Capaci ty
Ut i1ization
Plastics
& Resins
2821
35.6
54.8
65
49.7
62.2
80
39.6
13.5
23.1
Cel1ulose
F ibers
2823
0.6b
n/a
n/a
0.8C
n/a
n/a
25.0
n/a
n/a
Non-ceilo-
iose Fibers
2824
5.7
9.3
61
6.7
7.9
85
17.5
-15.0
39.3
Cycl Ic
Crudes A
Interme-
diates
2865
31 . 1
51.1
61
42.5
48.6
87
36.6
-4.9
42.6
Industr iai
Organic
Chenlcais
2869
47.8
77.1
62
56.4
78.1
72
18.0
1.3
16.1
aAII data from DRI (May 1986) unless otherwise indicated.
''Synthetic Organic Chesicals, ITC, 1982.
cHased on ITC growth rate, 1982-1984.
-------
manufacturing and wastewater treatment, described elsewhere, and from Dun's
Financiai Profile data which includes selected financial data on firms in the OCPSF
industry. Relevant Section 308 plant level data include 1982 production and sales data,
(both for OCPSF and non-OCPSF products), discharge status, employment figures, and
SIC codes relevant to plant production. Since 1988 has been designated as the baseline
year, sales data were forecast forward to 1988 using a formula based on DRI projections
for production, the chemical price index, and the implicit price deflator (see Section
3.3.1.4). Plant level estimates of cash flow, liquidation values, and profits were then
developed using projected plant sales and regression equations based on Dun's Financial
Profile data. A baseline closure analysis was conducted, comparing cash flow (net of
yet-to-be-incurred RCRA costs) to liquidation value. See Section 3.3.4. This analysis
showed no baseline closures. In addition, estimated plant level profit margins were
compared to those of the Dun's firms by 3-digit SIC and size. No plants fell into the
lowest decile, i.e., there were no plants with very low baseline profitability. The
specifics of these analyses are described in more detail below.
5.4.1 Baseline Sales and Employment
Table 5-9 presents the distribution of estimated 1988 plant sales values by size
and by SIC group. For SIC 2821, 2865 and 2869, the largest group of plants fall into the
$10 to 50 million dollar sales (OCPSF) range. SIC 2824 plants tend to be somewhat
larger. The largest number of plants in that category fall into the $100 to $500 milion
category. In SIC 2821, 2865 and 2869 only about one third to one fourth of the plants
have OCPSF sales of greater than $50 million annually, in the baseline.
Plant OCPSF employment, in 1988, the baseline year, has been estimated to
remain constant at the 1982 levels. This information was provided in the Section 308
survey. Employment distribution by SIC category is shown in Table 5-10.
5.4.2 Baseline Plant Closwe Analysis
The baseline plant and product line closures were estimated based on 1988
projected sales, and on financial parameters estimated from Dun's financial profile
data, by four digit SIC codes. 1988 sales were projected based on three factors
expected to change from 1982 to 1988: production rate change (by 4-digit size),
chemical price index change, and change in the implicit price deflator. The 1988 to
1982 sales ratios are shown by SIC in Table 5-11. (See Section 3.3.4). Cash Flow,
liquidation values and profits for plants in the Section 308 data base were projected via
5-22
-------
Table 5-9: DISTRIBUTION OF 1988 PLANT SALES VALUE BY
OCPSF SIC GROUP
MO SMC
2821
b Uitill HA J UK uursr SIL UKUUf
2823 2824
2865
2869
ALL
OCPSF SALES
VALUE
(H1LLION S)
NO. OF I NO. OF I NO. OF I NO. OF I NO. OF I HO. OF I NO. OF
PLANTS PERCENT PLANTS PERCENT PLANTS PERCENT PLANTS PERCENT PLANTS PERCENT I PLANTS PERCENT PLANTS PERCENT
HISSING
39
100.0
ft
•
ft
•
ft
*
ft
•
*
•
39
ZERO
*
ft
11
2.9
ft
*
2
4.9
ft
*
8
2.0
21
0-1
*.
*
29
7.6
•
*
*
*
5
4.5
37
9.3
71
1-5
*
*
64
16.7
ft
•
2
4.9
20
18.0
54
13.6
140
5-10
*
•
61
15.9
ft
3
7.3
12
10.8
47
11.8
123
10-50
*
•
129
33.7
2
33.3
8
19.5
43
38.7
134
33.7
316
50-100
•
*
40
10.4
*
*
4
9.8
13
11.7
44
11.1
101
100-500
*
•
42
11.0
4
66.7
21
51.2
17
15.3
58
14.6
142
500 PLUS
•
«
7
1.8
*
*
1
2.4
1
0.9
16
4.0
25
ALL
39
100. p
383
100.0
6
100.0
41
100.0
111
100.0
398
100.0
978
100.0
TOTAL SALES
VALUE
(MILLION $>
HISSING
10
25.6
•
*
•
ft
*
*
*
*
•
•
10
1.0
ZERO
3
7.7
5
1.3
«
ft
2
4.9
*
*
6
1.5
16
1.6
0-1
2
5.1
14
3.7
•
ft
*
*
4
3.6
25
6.3
45
4.6
15
8
20.5
27
7.0
*
ft
1
2.4
13
11.7
41
10.5
90
9.2
5-10
4
10.3
54
14.1
*
ft
3
7.3
16
14.4
33
a-J
110
11.2
10-50
8
20.5
155
40.5
2
33.3
9
22.0
44
39.6
140
35.2
358
36.6
50-100
3
7.7
64
16.7
*
«
4
9.8
14
12.6
46
11.6
131
13.4
100-500
1
2.6
50
13.1
4
66.7
19
46.3
19
17.1
89
22.4
182
18.6
500 PLUS
*
•
14
3.7
*
*
3
7.3
1
0.9
18
4.5
36
3.7
ALL
39
100. p
383
100.0
6
100.0
41
100.0
111
100.0
398
100.0
978
100.0
-------
Table 5-10: DISTRIBUTION OF 1982 PLANT EMPLOYMENT BY OCPSF SIC GROUP
HO SIC
2821
4 DIGIT HAJOR OCPSF SIC CROUP
2B23
in
I
hJ
&
OCPSf
EMPLOYMENT
HISSING
4
10.3
3
0.8
ZERO
1
2.6
2
0.5
0-1
•
•
8
2.1
1-S
6
15.4
39
10.2
5-10
3
7.7
38
9.9
10-50
12
30.8
170
44.4
50-100
e
20.5
51
13.3
100-500
5
12.8
56
14.6
500 PLUS
•
*
16
4.2
ALL
39
100.0
383
100.0
TOTAL
EMPLOYMENT
MISSING
1
2.6
2
0.5
ZERO
1
2.6
•
•
0-1
*
*
2
0.5
1-5
1
2.6
10
2.6
5-10
3 -
7.7
17
4.4
10-50
15
38.5
Hi
17.3
50-100
5
12.8
58
15.1
100-500
11
28.2
112
29.2
500 P^US
2
5.1
39
10.2
ALL
39
100.0
303
100.0
2824
2865
2869
ALL
ALL
NO. OF
HO. OF
NO. Of
NO. OF
ERCENI
PLANTS PERCENT
PLANTS PERCENT
PLANTS PERCENT
PLAN IS
PERCENT
•
1
2.4
•
9
2.3
17
1.7
•
a
•
•
•
4
1.0
7
0.7
•
*
•
1
0.9
10
2.5
19
1.9
•
*
•
3
2.7
34
8.5
82
8-4
*
1
2.4
6
S.4
26
6.5
74
7.6
*
1
2.4
49
44.1
140
35.2
372
38.0
*
6
14.6
15
13.S
57
14.3
137
14.0
16.7
11
26.8
29
26.1
86
21.6
188
19.2
83.3
21
51.2
8
7.2
32
8.0
82
a-4
100.0
41
100.0
111
100.0
398
100.0
978
100.0
•
1
2.4
*
*
1
0.3
5
0.5
*
•
•
#
•
•
•
1
0.1
*
*
*
1
0.9
*
ft
3
0.3
*
•
*
1
o.»
12
3.0
24
2.5
*
1
2.4
4
3.6
13
3.3
38
3.9
*
1
2.4
37
3J.3
117
29.4
313
32.0
*
4
9.B
18
16.2
66
16.6
151
15.4
16.7
12
29.3
37
33. J
110
32.7
303
31.0
83.3
22
53.7
13
11.7
59
14.8
140
14.3
100.0
41
100.0
111
100.0
390
100.0
9/8
100.0
-------
Taoie 5-M
Values Used
in Estimation of
1988 Sales3
SIC
1982
Production
(10^ Pounds)
1988
Production
(10^ Pounds)
1988 Production
1982 Production
1988 CPI
1982 CPI
1982 IPD
1988 IPD
1988 Sales
1982 Sales
2321
35.6
49.7
1.396
1.075
0.822
1.234
2823
0.6b
0.8C
1.250
1.075
0.822
1.105
2824
.5.7
6.7
1.175
1.075
0.822
1.038
2865
31 .1
42.5
1.366
1.075
0.822
1.207
286»
47.8
56.4
1.180
1.075
0.822
1.043
aAII data from QRI (May 1986 and January 1987), unless otherwise indicated.
''Synthetic Organic Chemicals, ITC, 1982.
c8ased on ire growth rates, 1982-1984.
5-25
-------
regression equations developed using the Dun's Financial Profile data. Estimated 1988
plant sales were then input to the equations in order to forecast plant level values. The
median values of each of these parameters relative to sales for firms in the Dun's
Financial Profile and for plants in the §308 data base are presented in Table 5-12.
(Note that these medians are presented to give the reader some information on the
relative magnitude of the parameters. The median values are not used in the closure
analysis.)
A baseline plant closure analysis was then performed to identify those plants
which would be likely to close even in the absence of the proposed effluent limitation
guidelines. Costs related to the Resource Conservation and Recovery Act (RCRA) liner
regulations were included in this baseline analysis. Since the data used to estimate
plants' financial conditions cover principally 198^ to 1986, it is assumed that other
RCRA costs as well as Superfund costs are already reflected in the data as part of the
cost of doing business. The determination of plant closures was based on a comparison
of a plant's baseline present value of cash flow to its liquidation or salvage value. If a
plant's liquidation value exceeded its discounted cash flow, it was considered to be a
baseline closure, as a company would be likely to liquidate a plant if it were beneficial
to stockholders to do so. (See plant closure methodology for further detail). If less
than 80 percent of a plant's production involved OCPSF products, the closure was
labeled a product line closure, rather than a plant closure. As noted above, the baseline
analysis showed no plant or product line closures.
As described in Chapter 3.0, plants with post-compliance profit to sales ratios
less than the lowest decile of that ratio from the Dun's data were labelled as
significantly impacted. This comparison was made by 3-digit SIC and size. Both the
median and lower decile values are shown in Table 5-13. Figures 5-6 and 5-7 show the
frequency distributions by percentiles for - §308 plants in SICs 282 and 286,
respectively. As shown by the figures, no plants fell into the lowest decile in the
baseline analysis.
5.5 Firm Baseline
A baseline firm level financial viability analysis was performed. The purpose
was to isolate firms which would be considered potentially financially weak even in the
absence of costs related to the proposed regulations. The analysis consisted of
computation of four financial ratios indicating potential strength or weakness in
liquidity, interest coverage, capital structure, and return to investors. (The current
5-26
-------
Table 5-12
Median Financial
Ratios
Dun's Financial Data
Sect i on 308 P1 an ts
Cash Flow
Liquidation Value
Prof 11
Cash Flow
Liquidation Value
Prot i 1
SIC
Sales
Sal es
Sales
Sa I es
Sa 1 es
Sa 1 es
2021
Plastics and Resins
0.0974
0.2109
0.04B3
0.0903
0.2405
0.0422
2823
Synthetic Cellulosic Fibers
0.1091
0.251 1
0.0584
0.0936
0.2773
0.051 1
/B24
Synthetic Non-Ce|1u1osic Fibers
0.0969
0.1750
0.0526
0.0936
0.2773
0.051 1
2865
Cyclic Crudes and Intermediates
0.0704
0.1999
0.0325
0.0795
0.244 1
0.0315
2B69
Industrial Organic Chemicals, n.e.c.
0.0855
0.1877
0.0461
0.1045
0.2394
0.0494
-------
Table 5-13
Profit Margin by SIC and Size*
SIC Size Median Lowest Dec ile
282 <12.5 M 0.0571 0.0076
I2.5-SIO M 0.0364 0.0087
>110 M 0.0301 0.0154
286 <12.5 M 0.0454 0.0125
$2.5-510 M 0.0220 0.0064
>110 M 0.0335 0.0089
•Source: Dun's Financial Profile.
5-28
-------
Figure !3-6
FREQUENCY OF 308 OATA PROFITABILITY ACCORDING TO DECILES OF D&B DATA
BASELINE FOR ALL PLANTS INCLUOED IN THE ANALYSIS
SIC3-2S2
FREQUENCY BAR CHART
FREQUENCY
| *****
160 ~ *****
*****
*****
*****
HO ~ *****
120 +
100 ~
80 +
60 ~
AO +
20 ~
*****
*****
*****
*****
*****
30*35% 35-40* 50-60X 60-70%
PROFIT/SALES
-------
Figure 5-7
FREQUENCY OF 308 DATA PROFITABILITY ACCORDING TO DECILES OF DU DATA
BASELINE FOR ALL PLANTS INCLUDED IN THE ANALYSIS
SIC3=286
FREQUENCY BAR CHART
FREQUENCY
90 ~
80 ~
70 ~
60 ~
u>
O
SO
40
30 ~
20 +
10
*****
*****
***••
*****
*****
*****
*****
*****
*****
25-30* 30-3SX 35-40* 40-50X 50-60X 60-70X 70-80X 80-90X >90X
PROFIT/SALES
-------
ratio, interest coverage, debt to worth, and return on assets were chosen for the
analysis).
Firms in the lower quartiles for both liquidity ratios, current ratio and interest
coverage, were considered to be potentially weak financially. Firms falling into the
lower quartiles for both return on assets and debt to worth were likewise considered to
be potentially weak. The quartiles and medians used for comparison were the medians
of the quartile and median ratios from 1.978 to 1984 from Robert Morris Associates
(RMA).
The financial data to perform these calculations were Compustat-derived for
those firms owning plants covered in the study which were included within the
Compustat database. These were publicly held, medium and large sized firms for the
most part. RMA ratios used for comparison in this case were taken from the largest
size category firm data ($10-$50 million in assets), by three digit SIC. Dun's Profile-
derived financial data were used for those firms owning plants covered by the study
(i.e., part of the Section 308 database), not included in the Compustat database. These
consisted of small single plant firms and some multiplant firms. Since this group of
firms included small as well as medium and large firms, the analysis was performed for
three size categories by three-digit SIC.
The results of the baseline analysis indicated that of the firms covered by
Compustat data (102 firms owning approximately half the plants covered in the Section
308 survey), only one firm (SIC 282) appeared to be financially weak, with zero return
on assets and a high debt ratio. This company also manufactured products in six other
non-organics related SIC categories. The fact that this firm was identified as being
weak in the baseline means that a weak post-compliance condition can not be attributed
to the 'regulation. The remaining firms, analyzed using median financial data from
Dun's, appeared to be in moderately good financial condition.
5.6 Foreign Trade Baseline
The foreign trade issues discussed briefly at the outset of this chapter are
examined in more detail. Because of significant changes taking place in foreign trade
and the importance of the international market to the OCPSF industry, this subsection
*Since actual firm-level data were not available for those firms not covered by
Compustat, the median values were used as a baseline from which to measure post-
compliance change.
5-31
-------
presents the 1988 forecast baseline conditions for foreign trade. The purposes of this
subsection are: (1) to describe the general trade situation in the 1988 baseline; and (2)
identify products which in the baseline suffer low production growth as a result of trade
issues. While most of this qualitative information is" not directly factored into the
impact analysis, it, nevertheless, provides a context within which to interpret the
foreign trade and new sources analyses. The foreign trade analysis portion of the
impact analysis examines the impacts of production loss due to predicted closures on
foreign trade. (See Section 5.6.2 for a discussion of identification of trade sensitive
chemicals inciuded in the foreign trade analysis).
The primary factors influencing foreign trade are U.S. feedstock prices and
availability; capacity expansion in Europe and developing countries, and U.S. and
inernationai demand for OCPSF products. In the product baseline, forecasts are based
on work by the DRI Chemical Service and incorporate the Service's judgments regarding
these factors.
5.6.1 General International Trade Factor Forecasts
The DRI industry forecast between 1982 and 1988 includes deregulation of
natural gas prices and good feedstock availability (see Section 5.2). The trade forecasts
take into account various capacity expansions planned in such areas as Europe, Canada,
and the Middle East. Table 5-14 presents international trade forecasts for selected
products. The outlook indicates export growth in the Middle East and Canada and
stagnation or decline of growth in U.S. exports. In the period to 1990, a major factor
affecting international trade will be the start-up of several Saudi Arabian complexes.
The effects of these complexes will mainly be felt in methanol and various ethylene
derivative markets. By 1990, Saudi Arabian capacity for both ethylene and methanol is
expected to be about 3.5 billion pounds annually each. In addition, significant capacity
in LDPE, ethylene glycol, and styrene is also expected to be in place.
In addition to the factors affecting those specific products mentioned above, it
is useful to observe that announced capacity expansion through 1990-1991 in organic
chemicals and plastics production throughout the world is massive. Most of this
expansion will indeed take place in developing countries,- especially Mexico, Brazil and
China. To provide some estimate of the magnitude of the situation, announced world
capacity expansion (1986 through 1991—new plants and expansions) is approximately 75
5-32
-------
Tab Ie 5-1^
PETROCHEMICAL EXPORTS AND IMPORTS
FOR SELECTED
PRODUCTS FOR
1981, 1985 AND
1990
Net exports'
Thousand
metric tons/year
1901
1985
1990
Low-density Polyethylene/
Linear Low-density Poiyethiyene
Western Europe
323
—
(100)
U.S.
424
180
15
Canada
84
270
455
Japan
135
30
(180)
Middle East
(81)
110
Hiqh Density Polyethylene
Western Europe
250
170
165
U.S.
350
135
180
Canada
36
75
70
Japan
131
45
(120)
Middle East
(87)
10
125
Ethylene Glycol
Western Europe
100
30
(120)
U.S.
75
83
(50)
Canada
94
195
220
Japan
(30)
(80)
(280)
Middle East
(35)
(12)
360
Styrene
Western Europe
(100)
(100)
(100)
U.S.
508
500
295
Canada
157
200
210
Japan
(161)
(250)
(390)
Middle East
<5)
( 12)
450
Methanol
Western Europe
(580)
(1,740)
(3,105)
U.S.
300
155
(1,400)
Canada
200
1 ,370
1,440
Japan
(326)
(1,030)
(1,970)
Middle East
3452
1,2002
2,0652
Source: U.S. Office of Technology Assessment (as reported in Chemical Week, 21 November 1984).
'Net exports equal exports minus imports. When imports are greater than exports the net value is
reported in parentheses.
2
Includes Africa.
5-31
-------
*
billion pounds per year. Of chat, the U.S. will add only 3.6 billion pounds, or about 4.S
percent of the world total. Table 5-15 shows a breakdown of this announced expansion
by region. These figures bury the composition of what chemicals will be produced; in
general, commodity chemicals, including cyclic intermediates, miscellaneous cyclic and
acyclic chemicals, and some plastics, are the primary products to be produced in
developing countries. Specialty chemicals, e.g. some resins and polymers, are less
likely to be produced in the developing countries.
5.6.2 Product Group Foreign Trade Forecasts
This discussion examines the product level foreign trade forecasts. The
product trade forecasts are limited to the coverage of DRI Chemical Service,, which
includes nearly ail large volume intermediate and finished products, as well as a few
small volume products.
The identification of foreign trade sensitive products must involve a number of
issues: level of export and import activity, price/cost differences between U.S. and
foreign markets, transportation costs, tariffs, and national government regulatory and
industrial development policy. This last issue includes such issues as national effluent
standards, degree of government subsidies of pollution control, and industry
protectionism. For this economic impact analysis, susceptibility of products to
international trade issues is based wholly on the level of product exports and imports.
Significant international trade sensitive products are identified according to three
criteria:
(1) 1988 forecast levels of either exports or imports are more than
ten percent of forecast production levels;
(2) the sum of the export and import percentages is greater than 15
percent; and
(3) the level of net export (exports less imports) as a percent of
production declines by over ten percentage points between 1982 and
1988.
Hydrocarbon Processing, Section 2, June 1986. Numbers derived by adding
capacities exclusive of refining, gas, renovation, treatment facilities and nitrogen
compound plants such as nitric acid and urea announced throughout the world. Real
figures may be somewhat higher, since capacities were not announced for a relatively
small fraction of the projects.
5-34
-------
Tadle 5-15
ANNOUNCED WORLD CAPACITY EXPANSION1
(Mill ions of Pounds per Tear)
United States
Canada
Other Western Hemisphere
Eurooe (including Eastern
Europe and USSR)
1986 - 1991 1986 only
3,562 2,380
622 470
17,187 5,687
7,002 i ,aaft
Afr i ca
Middle East
Far East
Australasia (Indonesia)
Worl d
U.S. Percent
6,069 1,160
9,074 4,228
27,007 18,663
4,293 1,440
74,816 35,914
4.31 6.6{
Source: Hydrocarbon Processing, Part 2, June 1986.
^Hydrocarbon Processing, Section 2, June 1986. Numbers derived by adding capacities exclusive
refining, gas, renovation, treatment facilities and nitrogen compound plants, such as nitric
acid and urea announced throughout the world. Real figures may be somewhat higher, since all
firms do not announce all intended expansions and/or new construction.
5-35
-------
Table 5-16 presenrs rhe foreign trade data by products for 1984 and 1988 for
plastics and resins (SIC 2821) and synthetic fibers (SIC 2324). Overall for SIC 2821,
exports are forecast to decline by 8 percent between 1984. and 1988 and, as a
percentage of production, fall from eight to six percent. Meanwhile imports are
forecast to grow by 77 percent between 1984 and 1988, but will only be equal to about
three percent of 1988 production.
For SIC 2824, overall exports decline by 15 percent between 1984 and 1988,
and fail to 9 percent to 8 percent of production. Imports increase by 27 percent, but
remain 1 percent of production.
By the three criteria, the following plastics, resins and synthetic fiber
products have a significant international trade market: LPDE* polyvinyl (PV) alcohol,
SAN, polypropylene, polyurethane (non-foam), polycarbonate, epoxy resins, nylon resins,
urea and mel formaldehyde resins and acrylic fiber. Of these products, all except urea
and mel formaldehyde resin, PV alchol and acrylic fibers are expected to have strong
domestic consumption growth of over 15 percent between 1984 and 1988 and melamine
formaldehyde resins. For PV alcohol, domestic consumption is expected to rise by
about 6 percent; for urea, domestic consumption is expected to grow by 11.7%; and for
acrylic fibers, the growth in domestic consumption is forecasted at only 1.5 percent.
Table 5-17 presents foreign trade data for the major products of SIC 2869.
Between 1984 and 1988, exports for these products are forecast to decrease by six
percent and imports to increase by 17 percent. As a percent of production, exports
remain at eight percent, and imports rise from four to five percent. Of the products in
this category, the following are expected to have significant international trade
markets in L988: methanol, synthetic ethanol, ethylene glycol, VCM, VAM, isopropanol,
propylene glycol, propylene oxide, butyl acrylate, ethyl acrylate, acrylonitrile, and
MEK.
Of these products, the majority will have domestic consumption growth of
under 15 percent, and several are forecasted to have consumption declines between
1984 and 1988. The low growth products are: Methanol, VCM, propylene glycol,
isopropanol, butyl acrylate, and MEK. The products that are expected to experience
*An annual growth rate of 3% for GNP is considered reasonable. Therefore, a
15% growth rate over four years should be considered sufficient for a product line.
5-36
-------
Table 5-16
U.S. Foreign Trade by Chemical Product tor Plastics and Resins (SIC 2821) and Synthetic Fibers (SIC 2824)
1984 and 1988
1984
1988
(a)
(b)
(c)
(d)
(e)
(<)
-------
Table 5-17
U.S. Foreign Trade Situation by Product for Miscellaneous Cyclic and Acyclic Chemicals (SIC 2869-'/)
1984 and 1988
(a)
(b)
1984
(c)
(d)
(e)
(t >
1988
(g)
(h)
(I)
(i>
(k)
( 1 )
Percent
of
Percent
of
Percent
Percent
Exports
Imports
Production
Exports
Imports
Product Ion
Change
Oi f ference
—
-------
declines in domestic consumption are: synthetic ethanol, ethylene glycol, and
acrylonitrile.
Table 5-18 presents foreign trade data for the major products of SIC 2865.
Exports of products in this group are expected to increase moderately; 4 percent over
the period 1984 through 1988. Imports are forecast to increase by 78 percent and are
predicted to be 3 percent of production in 1988. The following products are forecasted
to have significant trade markets in 1988: cumene, TDl, styrene, p-xvlene, terephthalic
acid, o-xylene and bisphenol-A.
Of the trade sensitive products, cumene, terephthalic acid and o-xylene are
expected to have consumption growth of less than 15 percent. (A 9.2 percent increase
is projected for terephthalic acid. Consumption growth for o-xylene is forecasted at
9.6 percent, while 10.6 percent growth is expected for cumene).
5.6.3 Summary of Foreign Trade Sensitive Products
This subsection summarizes products listed above with significant foreign
trade involvement which, while not leading to low production growth, may indicate
potential foreign trade impacts from pollution control costs. Products which have
significant and usually decreasing foreign trade markets yet have strong growth in
domestic consumption are:
SIC 2821 SIC 2865 SIC 2869
LDPE TDI VAM
SAN styrene propylene oxide
polypropylene p-xylene ethyl acrylate
polyurethane; non-foam
polycarbonate
epoxy resin
nylon resins
These form a subset of all trade sensitive chemicals identified from those
covered by DRI which included in Table 6.6.1. The international trade issue is quite
complicated and full of uncertainty. While the DRI trade projections used in the
foreign trade analysis implicitly incorporate best estimates of feedstock availability,
announced capacity expansions, changes in U.S. and world demand, etc., the
environment changes constantly. In terms of uncertainty, for example, the on-line date
of Saudi Arabian petrochemical complexes has been continually delayed. A recent
Chemicai Week editorial traced a series of articles starting over 12 years ago discussing
such production; this production is finally appearing on the market. As to the
5-39
-------
Table 5
-18
U.S. Foreign Trade Situation
by Product
lor Cyclic Intermediates (SIC
2865-1) Fibers (SIC
2824)
1984 and
1988
1984
1988
(a)
(b)
(c)
(d)
(e)
(f)
(9)
(h>
(i)
(j)
(k)
(1 )
Percent of
Percent of
Percent
Percent
Exports
Imports
Product ion
Exports
Imports
Product Ion
Change
Di1ference
-(million 1b)~
Exports
Imports
-(mi 11 ion lb)—
Exports
Imports
Export
1mpor t
Export
Import
eyelohexane
133
21
7
1
125
0
6
0
- 6
-100
- 1
-1
curoene
5
340
0
9
21
598
1
15
308
76
0
7
phenol
112
31
4
1
89
67
3
2
-21
123
- 1
1
blsphenol A
95
0
13
0
93
0
10
0
- 2
0
- 2
0
monon i troDenzene
0
0
0
0
0
0
0
0
0
0
0
0
an i|i ne
0
0
0
0
0
0
0
0
0
0
0
0
tolyenediamine
0
0
0
0
0
0
0
0
0
0
0
0
IPI
138
0
21
0
125
0
16
0
9
0
- 5
0
ethyl benzene
122
30
1
0
125
30
1
0
2
-0
0
0
a 1 yrene
1 170
102
15
1
900
499
12
7
-23
38B
- 3
5
p-xylene
951
108
22
3
1050
125
21
3
10
16
- 2
0
tcrephthalic acid
671
0
34
0
1000
0
39
0
49
0
5
0
DMT
120
0
3
0
120
0
3
0
0
0
- 0
0
o-xy1ene
66
157
9
22
60
65
a
a
-9
-59
- 2
-14
phtalic anhydride
10
10
1
1
10
10
1
t
4
-2
0
-0
Subtotal
3593
799
9
2
3718
1424
9
3
4
78
0
1
Notes: Column (i)= column (e)/column (a) minus one times 100.
Column (j) = co I uian ID/column (b) minus one times 100.
Column (k) = column (g) minus column (c).
Column (I) = column (h) minus column (d).
Source: Data Resources, Inc. Chemical Service, PR I Chemical Model 1984 Benchmark Case, and ORI Chemical Model I98B Forecast Results.
-------
iomplexity of the trade issue, a number factors are important to an in-depth
assessment of foreign trade impacts. These factors are discussed in Chapter S, Limits
of the Analysis.
5-41
-------
APPENDIX 5A
DETAILED PRODUCT GROUP BASELINE
The purpose of the product level detail presented in this appendix is to identify
products which are projected to perform more or less favorably than average. In this
appendix, the 1988 outlook is discussed for the 12 OCPSF product groups by examining
production, price, capacity utilization and international trade trends. In addition,
product level detail within each group is presented whenever possible.
Coverage is limited to those chemicals included in DRI Chemical Service
forecasts which, on a production basis, cover about 75 percent of the OCPSF industry.
This coverage centers on the largest product groups: (1) plastics and resins; (2)
synthetic fibers; (3) miscellaneous cyclic and acyclic chemicals; and (<*) miscellaneous
cyclic intermediates. Plastics and resins (SIC 2821), the largest group, is expected to
exhibit stable growth over the period. The weakest SIC is 2869, which includes
miscellaneous cyclics and acyclics; seven chemicals are expected to have low growth.
5A.I Plastics and Resin Materials (SIC 2821)
Accounting for about 55 percent of both the production and sales value of
finished OCPSF chemicals in 1982, plastics and resin materials is by far the single most
important product group in the OCPSF industry. The DRI Chemical service covers
more than 85 percent of the production of this group. DRI forecasts indicate an
approximate increase of *»0 percent in plastics and resins production between 1982 and
1988. During this period real prices are expected to increase by about 27 percent and
value of pro-ductioh by nearly 60 percent. Capacity utilization is projected to increase
from 65 percent in 1982 to about 80 percent in 1988. Forecast results, based on DRI
coverage of this product group, are shown in Table 5A-1.
Growth in domestic consumption1 is expected to be strong, whereas
international markets are projected to be weak with exports falling and imports rising
significantly. In 1982, this group had one of the strongest export markets in the
industry; however, by 1988 this group is projected to have very small trade surpluses.
* Domestic consumption is defined as production plus imports less exports.
5A-1
-------
Table 5A-1
PLASTICS AND RESIN MATERIALS BASELINE
Real Growth 1982-1988
Economic Indicators
1982
Value
1988
Value
Annual
Percent
Tota
Percei
Production (millions of pounds)
35,600*
49,700
5.7
40
Domestic Consumption
(millions of pounds)
32,700
48,000
6.7
47
Net Exports/Production (percent)
10.7
3.2
-l.L
-8
Exports (millions of pounds)
4,20a
3,100
-3.7
-26
Imports (millions of pounds)
384
i,5aa
25.5
291
Average Price (cents/pound)
37
35
-.7
-5
Value of Production (millons of $)
13,000
O
o
4.9
34
Capacity (millions of pounds)
54,000
62,200
2
14
Capacity Utilization (percent)
65
80
3.3
23
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1982
Benchmark Case, July 3, 1984 and DRI Chemical Model 1988 Forecast,
May 14, 1986.
^¦The 1982 ITC production level for this group is 38,300 million
pounds.
Net exports (exports less imports) as percent of production.
5A-2
-------
Table 5A-2 presents price and production data for individual plastics and resins.
Capacity and capacity utilization are shown in Table 5A-3.
The international trade situation for plastics and resins is projected to
deteriorate significantly between 1982 and 1988, as shown in Table 5A-4. In 1982, net
exports were greater than 10 percent of production for ten chemicals; by 1988, only
three chemicals are projected to maintain these high export levels. Two chemicals are
projected to show significant (greater than ten percent) decreases in export levels.
(High and Low density polyethylene). Projected production growth for these two
chemicals is moderately high, however, because of domestic consumption demand.
5A.2 Synthetic Fibers (SIC 2224)
Although synthetic fiber production accounts for only about 10 percent of the
production of finished OCPSF chemicals, it accounted for 25 percent of the value of
industry sales in 1982. The DRI Chemical Service, which covers about 90 percent of
this group, anticipates about a 17 percent increase in production between 1982 and -
1988. No price data were available, but based on projected real price decreases in
other chemical groups, there is likely to be little change or a slight decrease in real
prices for this group as well, leading to. a 15 to 20 percent increase in production
value. Capacity utilization is expected to increase from about 60 percent in 1982 to
well over 80 percent in 1988. DRI Chemical Service forecasts are presented in Table
5A-5.
Domestic consumption for this group is projected to grow significantly faster
than production because of declining exports and increasing imports. This is anticipated
to be the trend for the entire OCPSF industry in general.
The growth in domestic demand for acrylic fiber is expected to be very low
(about 2%). This will be compounded by stable rather than increasing exports. Exports
are a major market for acrylic fiber. The declining international market will not.
significantly affect nylon and polyester fibers (see bottom part of Table 5A-4.), whose
projected domestic consumption growths are 38 and 13 percent respectively. Projected
1988 capacity utilization levels are near or above 80 percent for ali fibers (see bottom
part Table 5A-3).
5 A-3
-------
Table 5A-2
PRICE, PRODUCTION, AND VALUE OF PRODUCTION BY PRODUCT FOR PLASTICS
AND RESINS (SIC 2821) AND SYNTHETIC FIBERS (SIC 2824) 1982 AND 1988
1982
1988
TOTAL
PERCENT
CHANGE
Prod.
Price
Va 1 ue
Prod.
Pr i ce
Va I ue
(mil lb)
(c/ib)
(mil $)
(mil lb)
(C/ltJ>
(mil S)
Pr i ce
Prod.
Va 1 u«
PLASTICS/RES INS
HOPE
4,927.8
37.1
1 ,823
7,543.0
30.8
2,338
-17
53
28
LOPE
7,502.6
28.5
2,138
9,381 .6
29.8
2,815
5
25
32
PVC
5,325.9
22.1
1 ,177
6,917.1
26.2
1 ,812
19
JO
51
PV Acetate
520.0
—
—
830.9
--
—
—
60
—
PV Alcotial
108.0
90.0
97
182.7
82.4
150
-8
69
55
Polystyrerm
3,190.6.
38.7
1 ,235
4,595.3
31.1
1 ,424
-20
44
15
SAN
91.1
—
—
93.4
~
—
—
3
—
ABS
739.6
79.0
584
1.063.3
82.4
876
4
44
50
Polyprooylene
3,477.4
38.3
1 ,332
5,897.4
33.2
1,946
-13
70
46
Polyester, unset
865.2
66.0
571
1,350.0
65.4
883
-1
56
J5
Polyurethane,
flex foam
852.2
—
—
1,157.1
--
—
--
36
--
Pol yurethane,
rigid foam
132.3
--
--
176.0
~
~
--
33
--
Polyurethane.
non-foam
124.0
~
~
201 .9
~
--
—
63
--
Polycarbonate
260.0
—
~
527.5
~
—
—
103
—
Epoxy Resin
286.0
~
--
428.7
--
—
—
50
--
EVA Polymer
388.0
--
—
466.8
—
—
20
—
Pheno1 i c Res i n
1,155.7
48.0
555
1 ,594.3
53.9
861
12
38
55
Ny I on 6 Res i n
68.0
—
—
130.7
--
—
~
93
—
Nylon 66 Resin
156.0
~
—
274.4
~
—
—
76
--
Polyester, sat.
4,302.0
57.0
2,453
5,415.9
80.4
1,333
41
26
77
Urea ~ Mel
Formaldehyde
Res i n
1,131.0
13,000
1,540.9
--
~
—
36
--
SUBTOTAL
35,600.0
37.0
49,700.0
35.0
16,600
-5
40
28
FIBERS (SIC 2824)
Nylon Fiber
1,926.6
94.5
1 ,821
2,612.9
—
—
--
36
—
Aery lie F iber
624.1
10.5
655
628.6
—
—
i/a
1
n/a
Polyester Fiber
3,168.8
53.1
1 ,692
3,450.8
~
~
—
9
—
SUBTOTAL
5,720.0
73.0
4,168
6,692.a
—"*
—~
17
Source: Data Resources Inc.,
Chemical
Service, DRI
Chemi cal
Model 1'
988 Benchmark
Case,
July 3,
1984 and
ORl Chemical
Model 1988 Forecast
ResuIts,
May 14,
1986.
5A-4
-------
Table 5A-3
PRODUCT I ON, CAPACITY, AND CAPACITY UTILIZATION BY CHEMICAL FOR PLASTICS AND RESINS (SIC 2821) AND
SYNTHETIC FIBERS (SIC 2824) 1982 AND 1988
1982
1988
Percent Change
Production
Capac1ty
C.U.
Product ion
Capacity
C.U.
Product
(Mil lbs)
(Mil lbs)
(I)
(Mil lbs)
(Mil lbs)
(!)
Production
Capac i ty
C.U,
PLASTICS/RESINS
HDPE
4,927.8
6,250.0
78.8
7,543.0
9,060.0
83.3
53.1
45.0
4.5
LDPE
7,502.6
10,045.0
74.7
9,381.6
11,125.0
84.3
25.0
10.0
9.8
PVC
5,325.9
8,050.0
66.2
6,917.1
8,140.0
85.0
29.9
1. 1
18.8
PV Acetate
520.0
1,050.0
49.5
830.9
1,050.0
79.1
59.8
0.0
29.6
PV Alcohol
108.0
230.0
47 .0
182.7
345.0
53.0
69.2
50.0
6.0
Polystyrene
3,190.Q
5,735.0
55.6
4,595.3
6,936.0
66.3
44.0
20.9
10.7
SAN
91.1
195.0
46.7
93.4
195.0
47.9
2.5
0.0
1.2
ABS
739.6
1 ,575.0
47.0
1,063.3
1,730.0
61.5
43.8
9.8
14.5
Polypropylene
3,477.4
5,120.0
67.9
5,897.4
6,485.0
90.0
69.6
26.7
25.0
Polyester, unsat
865.2
1 ,650.0
52.4
1 ,350.0
1,800.0
75.0
56.0
9. 1
22.6
Polyurethane, flex foam
852.2
1,750.0
48.7
1 ,157.1
1.750.0
66.1
35.8
0.0
17.4
Polyurethane, rigid foam
132.3
950.0
13.9
176.0
950.0
18.5
33.0
0.0
4.6
Polyurethane, non-foam
124.0
--
--
201 .9
—
—
62.8
--
--
Polycarbonate
260.0
415.0
62.6
527.5
735.0
71.8
102.9
77.1
9.2
Epoxy Resin
286.0
557.0
51 .5
428.7
727.0
69.0
49.9
30.5
17.7
EVA Polymer
388.0
600.0
64.7
466.8
750.0
62.2
20.3
25.0
-2.5
Phenolic Resi n
1 ,155.7
1 ,900.0
60.8
1 ,594.3
1,900.0
83.9
38.0
0.0
23. 1
Nylon 6 Resin
68.0
166.0
41 .0
130.7
140.0
93.4
92.2
-15.7
52.4
Nylon 66 Resin
156.0
233.0
67.0
274.4
275.0
99.0
75.9
18.0
32.8
Polyester, sat.
4,302.9
6,163.0
69.8
5,415.9
5,952.0
91.0
25.7
-3.4
22.0
Urea ~ Mel Formaldehyde
Res i n
1,131.0
2,000.0
56.6
1 ,540.9
2,000.0
77.0
36.2
0.0
20.4
SUBTOTAL
35,600.0
54,800.0
65.0
41,700.0
62,200.0
00.0
39.6
43.2
15.0
FIBERS
Nylon Fiber
1,926.6
3,236.0
59.5
2,612.9
2,985.0
87.5
35.6
-7.8
28.0
Acrylic F iber
624.)
847.0
73.7
628.6
805.0
78.1
0.7
-4.9
4.4
Polyester Fiber
3,168.8
5,166.0
61.3
3,450.8
4,136.0
83.4
B.9
-19.9
22. 1
SUBTOTAL
5,719.5
9,249.0
61.8
6,692.3
7,926.0
84.4
17.0
-14.3
22.6
SOURCE: Data Resources
, Inc. Chemical Service,
DRI Chemical
Model 1982
Benchmark
Case. July 3.
1984 and DRI
Chemical Model
198f
Forecast Results, Hay 14, 1986.
-------
Table 5A-4
INTERNATIONAL TRADE SITUATION BY CHEMICAL FOR PLASTICS AND RESINS (SIC 2021) AND SYNTHETIC FIBERS (SIC 2624) 1982 AND 1988
1982 1988 Total Percent Change
Production
Exports
1 raports
Net Exp
Product ion
Exports
Imports
Net Exp
Produc-
Net Exp
(Mil lbs)
(Mil lbs)
(Mil lbs)
{ of Prod
(Mil lbs)
(Mil lbs)
(Mil lbs)
$ of Prod
11 on
Exports
Imports
% of Pro
PLASTICS/RESINS
HOPE
4,927.8
951.3
26.0
18.7
7,543.0
700.0
49.8
8.6
53.1
-26.4
190.5
-10. 1
LDPE
7,502.6
1,223.6
36.2
15.8
9,381.6
739.0
548.2
2.0
25. 1
-39.6 .
1,414.4
-13.8
PVC
5,325.9
560.7
116.0
8.8
6,917.1
179.1
428.2
-3.6
29.9
-68.1
269.4
-4.7
PV Acetate
520.0
6.1
10.0
-0.8
830.9
6.0
10.0
-0.5
59.8
-1 .6
0.0
-0.3
Pv Alcohol
108.0
23.0
22.4
0.6
182.7
30.9
41.3
-5.7
69.2
34.3
84.4
-6.3
Polystyrene
3,190.6
94. S
4.0
2.9
4,595.3
88.2
29.9
1.3
44.0
-6.9
647.5
-1 .6
SAN
91 .1
9.6
0.3
10.2
93.4
10.4
4.0
6.9
2.5
8.3
1 .233.3
-3.3
ABS
739.6
59.4
13.2
6.3
1,063.3
75.0
74.7
0.0
43.8
26.3
465.9
-6.3
Pot ypropylene
3,477.4
809.0
5.8
23.1
5,897.4
830.1
14.9
13.8
69.6
2.6
156.9
-9.3
Po yester, unsat
865.2
8.0
1 .8
0.7
1,350.0
8.3
6.0
0.2
56.0
3.8
23.8
-0.5
yurethane, flex foam
852.2
118.5
0.0
13.9
1.157.1
72.6
0.0
6.3
58.4
-38.7
0.0
8.2
Polyurethane, rigid foam
132.3
9.5
0.0
7.2
176.0
5-2
0.0
0.5
33.0
-45.3
0.0
-5.7
Po>yurethane, non-foam
124.0
16.5
0.0
13.3
201.9
25.9
0.0
12.8
62.8
56.9
0.0
0.0
Poiycarbonate
260.0
49.5
1.5
18.5
527.5
145.3
4.5
26,7
102.9
193.5
200.0
8.2
Epoxy Resin
286.0
38.8
4.6
1 1.9
428.7
41.5
14.9
6.2
49.9
6.9
223.9
-5.7
EVA Polymer
3Q8.0
0.0
0.0
0.0
466.8
0.0
0.0
0.0
20.3
0.0
0.0
0.0
Phenolic Resin
1,555.7
27. 1
17.7
0.8
1,594.3
2S.9
35.9
-0.6
3.3
-4.4
102.8
-1.4
Ny1 on 6 Res i n
66.0
9.3
1.5
1 1 .5
130.7
12.5
9.6
2.2
92.2
34.4
540.0
-9.3
Nylon 66 Resin
156.0
21.5
3.6
1 1 .5
274.4
26.1
20. |
2.2
75.9
21 .4
458.3
-9.3
Polyester, sat.
4,302.9
60.0
0.0
1 .4
5,415.9
50.0
0.0
0.9
25.9
-16.7
0.0
-0.5
Urea * Mel Formaldehyde
Res i n
1,131.0
19.8
8.7
0.9
1,540.9
17.6
26.9
-0.6
36.2
-1 1 . 1
209. 1
-1 .5
SUBTOTAL
35,604.3
4,116.0
273.3
10.8
49,769.0
3,089.6
1,319.2
3.2
39.6
-26.2
275.0
-7.6
'IBERS
Nylon Fiber
1,926.6
118.7
11.5
5.7
2,612.9
129.7
34.9
3.6
35.6
9.3
203.5
-2.1
Aery 1i c F i ber
624.1
174.3
7.9
26.7
628.6
181.6
20.0
25.7
0.7
4.2
153.2
-1 .0
Po1yester Fiber
3,168.8
276.9
7.3
8.5
3,450.8
207.5
39.9
4.9
8.9
-25.1
446.6
-3.6
SUBTOTAL
5,719.5
569.9
26.7
9.5
6,692.3
518.a
94.B
6.3
17.0
-8.9
255.1
-3.2
SOURCE: Data Resources, Inc. Chemical Service, PRI Chemical Model 1982 Benchmark Case. July 3, 1984 and DRI Chemical Model 1988 Forecast Rksulib. May W
'Net exports (= exports less imports) as a percent of production ,
^1988 level minus 1982 level.
-------
Table 5A-5
SYNTHETIC FIBERS BASELINE
Real Growth 1982-1988
Economic Indicators
1982
Value
1988
Value
Annual
Percent
Total
Percent
Production (millions of pounds)
5 ,7001
6,692
2.6
17
Domestic Consumption
5,200
6,300
3.2
21
Net Exports/Production (percent)
9.5
6.3
-.5
-3.2
Exports
570
519
-1.4
-9
Imports
27
95
23.5
255
Average Price (cents/pound)
73
NA
NA
NA
Value of Production (millons of
$) 4,200
NA
NA
NA
Capacity (mil pounds)
9,249
7,926
-2.5
-17
Capacity Utilization (percent)
62
84-
5.0
35
Source: Data Resources Inc., Chemical Service, DRI Chemical Model
1982
Benchmark Case, July 3,
1984, and
DRI Chemical
Model 1988
Forecast
Results, May 14, 1986.
^The 1982 ITC production level for the group is 6,400 million pounds.
JA-7
-------
5A.3 Miscellaneous End-Use Chemicals and Chemical Products (SIC 2869-6)
Because this group is composed of a collection of unrelated chemicals,
assessing its outlook requires identification of its major subgroupings as of 1982. These
subgroups are listed in Table 5A-6. According to this breakdown, polymers for fiber
production account for about 50 percent of this product group on a production basis. In
terms of value of sales, additives for lubricating oil and greases for fuels account for 33
percent and 23 percent, respectively, of the product group.
The production outlook for this group is presented in Table 5A-7 as a weighted
average of projected growth of four of its five major subgroups. The growth estimates
are based on the assumptions discussed in the three following subsections.
Lubricant Additives. The market for these chemicals is primarily (80 percent)
for automobiles and other vehicles. The outlook for these additives is
favorable because of the increase in performance standards for vehicle
lubricants. Therefore, as a conservative growth projection, it was assumed
that these additives would grow slightly faster than real GNP, or by about 25-
30 percent. We have no specific information on the level of imports.
Fuel Additives. Gasoline additives compose over 95 percent of the fuel
additives market. Of this total market, methyl-t-butyl ether (MTBE) and the
various organo-lead and related chemicals accounted for 57 and 36 percent,
respectively, of production in 1982. The organo-lead compounds include
tetraethyl - and tetramethyl - lead and ethylene dibromide which is usually
included as part of the octane booster. The DRI Service forecasts 32 percent
•production growth for MTBE. This growth, together with the continuing
decrease in leaded additives (assumed to be about 50 percent over the period
to 1982 and 1988), leads to a conservative zero growth forecast for 1982 to
1988.
Cellulose Acetate. A 1975 production breakdown for cellulose acetate end
uses is presented in Table 5A-8. The weighted average growth from 1982 to
1988 for cellulose acetate is based on projected changes in its major end uses
over the baseline period. Using production indices for the growth indicators
for end uses, weighted by the percent share of cellulose acetate production
used for each end use, a real growth rate for the period is estimated. The
5A-8
-------
TabLe 5A-6
MAJOR SUBGROUPS1 OF MISCELLANEOUS END-USE CHEMICALS
AND CHEMICAL PRODUCTS (2869-6)
Subgroup
Product ion
(mi 1L ion
pounds)
1982 1984
SaLes VoLume
(milLion
pounds)
1982 1984
VaLue of Sales
(mi 11 ion
dollars)
1982 1984 Produce Type
Lube Oil and
Grease Additives
Gasoline and Other
Fuel Additives
Cellulose Acetate
Cellulose Ethers
and Esters
Polyester, Nylon and
Acrylic Polymers
TOTAL
1,520 1,080 1,100 1,222
1,440 1,914 1,160 1,225
1,000 N.A. 300 N.A.
150
235 120 178
4,750 6,264
90
566
930
650
350
230
60
882
504
N.A.
255
598
Finis hed
Chemicals
Finished
Chemicals
Intermediate
Chemicals
to Fibers
Intermediate
Chemicals to
Plastics
Intermediate
Chemicals to
Fibers
8,860 9,493 2,270 3,191
2,220 2,239
Source: U.S. International Trade Commission, Synthetic Organic Chemicals, 1982, 1984.
1
Based on. 1982 data.
These totals represent 40 percent of the ITC 1982 Total Miscellaneous Products
production voLume, 85 percent of the 1982 ITC sales volume and 80 percent of the 1982
sales value, respectively. However, the high 1982 production level of 22 billion
pounds listed by ITC for this product group includes 12.7 billion pounds of "other
miscellaneous: chemicals, of which only one percent were sold. Production in this
"other" subgroup increased by over 10 billion pounds from 1981 to 1982 despite the
significant decreases experienced by most OCPSF chemicals. Historically, production
of this "other" chemicals subgroup has only been about several hundred million
pounds. This unlikely increase might reflect some sort of reporting error; and if
ignored, the five subgroups listed above account, for about 90 percent of the ITC
production level for this product group.
^In 1984, production represented 40 percent of ITC Total Miscellaneous Products
Production volume, 21 percent of ITC sales volume, and 58 percent of sales value,
excluding cellulose acetate, which was not reported. The "other" category in 1984 was
reported as 266 million pounds of production.
5A-9
-------
Table 5A-7
Miscellaneous End-Use Chemicals Real Growth, 1982-1988 (2869-6)
Subgroup Group Production
Polymers for Synthetic 50
Fibers
1
Lubricant Additives
Gasoline Additives
Cellulose Acetate
Other
Weighted Average
15
15
10
10
Growth
40
30
0
25
25
30
Percent End-Use
Share of Product
Growth Indicators
2
Synthetic fibers
GNP (see text)
GNP (see text)
Cellulosic fibers
Real GNP
Source: Data Resources, Inc., Chemical Service, Data Resources, Inc., Chemical
Service, DRI Chemical Model 1982 Benchmark Case, July 3, 1984 and DRI
Chemical Model 1988 Forecast Results, August 21, 1984, and U.S.
International Trade Commission, Synthetic Organic Chemicals, 1982.
Based on 1982 production levels.
See Section 5.3.2.
5 A-10
-------
TabLe 5A-8
CeLlulose Acetate Real Growth, 1982-1988 (2869-6)
Major End-Use
Textile Yarn
Cigarette Filter Tow
Plastics 20
Non-Cigarette StapLe Tow
Weighted. Average
(% of Total)
Product ion^
48
24
Growth Indicator
Textile mill products
Tobacco products
Plastics and resin
materials
Real GNP
(percent'
172
42
402
25
19
Source: Data Resources, Inc., Chemical Service, DRI Chemical Model 1988
Forecast Results, May 7, 1984, and Lowenheim, Frederick A. and
Marguerite K. Moran, Faith, Keyes, and Clark's Industrial Chemicals,,
Fourth Edition, John Wiley & Sons, 1975, p. 241.
^Based on 1975 production levels in Faith, Keyes, and Clark's Industrial
Chemicals, Fourth Edition.
^Derived from production indices in DRI Chemical Model 1988 Forecast
Results.
5A-11
-------
Table 5A-9
PLASTICIZERS REAL GROWTH, 1982-1988 (2869-3)
Percent End-Use Indicator Growth
Share of Product from 1982-1988
Major End-Use Group Production Growth Indicator (percent)
Flexible PVC
65
Chemical specific
production forecast
30
Other Plastics
20
Average plastics production
40
Rubber
10
Rubber production index
19
Other
5
ReaL GNP
25
Weighted Average*
31
Source: Data Resources, Inc., Chemical Service, DRI Chemical Model 1988 Forecast-
Results , May 14, 1986, and Kline Guide to the Chemical Industry, Fourth
Edit ion, Charles H. Kline and Company Inc., 1980.
''Based on end-use share of 1979 production..
^See Section 5.3.1.
5A-12
-------
weighted average growth rate shown in this table (i.e., 19 percent) is probably
slightly low due to the heavy reliance on textile mill products growth as
defined by the 1975 production breakdown. Therefore, a 25 percent production
growth estimate from 1982 to 1988 for cellufose acetate (as shown in Table 5-
16) would be more realistic and consistent with less emphasis on this
component.
5A.4 Plasticizers (SIC 2869-3)
Although plasticisers are finished chemicals,, their end-uses are nearly totally
within the OCPSF industry; 65 percent are used in vinyl plastics, 20 percent in other
plastics, ten percent in rubber compounds, and five percent in other products. The
growth outlook for this group primarily depends on that for flexible plastics, most
importantly polyvinylchloride (PVC). The 1988 outlook presented in Table 5A-9, based
on the weighted average of the end-use growth forecasts.
5A.5 Cellulosic Fibers (SIC 2823)
The breakdown of cellulosic fiber end-uses in 1979 are shown in Table 5-10,
together with projected baseline growth estimates. The use of these proxy growth
indicators by end-use segment and the corresponding forecast production indices by DRI
leads to an anticipated production weighted average growth from 1982 to 1988 of 32
percent. However, this projection does not take other potentially significant
circumstances into account, such as the relative demand for cellulosic fibers versus
synthetic fibers.
5A.6 Dyes (SIC 2865-2)
The forecast for growth in the demand for dyes is based on projected changes
in textiles and paper, since the major use of dyes is for coloring these products. Using
the production indices for these end-uses forecast by DRI, the expected growth for dyes
is presented in Table 5A-11.
5 A.7 Organic Pigments (SIC 2865-3)
The 1988 outlook for organic pigments is shown in Table 5A-12. The estimated
growth rate of 30 percent is based on DRI production indices, as described above for
other product groups.
5A-13
-------
Table 5A-10
CELLULOSIC PIBERS REAL GROWTH, 1982-1988 (SIC 2823)
Major End-Use
Percent End-Use
Share of Produce
Croup Production
Growth Indicator
Indicator Growth
from 1982-1988
(percent)
Apparel
MedLcal, Surgical,
Sanitary Goods
Home Furnishings
Other
Weighted Average
1
40
20
20
20
Apparel and allied products
Household furniture (proxy)
Drugs and medicine (proxy)
ReaL CUP
28
48
34
25
32
Source: Data Resources, Inc., ChemicaL Service, DRI Chemical Model 1988 Forecast
Results, August 21, 1984 and May 14, 1986, and Textile Organon,
September/October 1983.
1
Based on end-use share of 1982 production.
5A-U
-------
TabLe 5A-11
DYES REAL GROWTH, 1982-1988 (2865-2)
Percent End-Use Indicator Growth
Share of Product from 1982-1988
Major End-Use Group Production Growth Indicator (percent)
Textiles 75 Textile mill products 17^
Paper 20 Paper and. products 28
Weighted Average* 19
Source: Data Resources, Inc., Chemical Service, DRI Chemical Model 1988 Forecast
Results, May 7, 1986, and Kline Guide to the Chemical Industry, Fourth
Edition, Charles H. Kline and Company Inc., 1980.
^Based on end-use share of 1979 production.
2
Historical anaysis of U.S. shipments of dyes between 1960 and 1980 indicates a
very close relationship to shipments of textile mill products, according to the
Kline Guide to the Chemical Industry, Fourth Edition, Charles H. Kline and
Company, 1980, p. 285.
5A-15
-------
Table 5A-12
ORGANIC PIGMENTS REAL GROWTH, 1982-1988 (2865-3)
Major End-Use
Printing Ink3.
Paints
Plastics
Weighted average
Source
Percent End-Use
Share of Product
Group Production
45
35
10
Growth Indicator
Printing and
publishing
Paints production
Plastics and resins
Indicator Growth
from 1982-1938
(percent)
28
30
Data Resources Inc., Chemical Service, DRI Chemical Model 1988
Forecast Results, August 21r 1986 and May 14, 1986, and Kline Guide
to the Chemical Industry, Fourth Edition, Charles H. Kline and Co.
Inc., 198Q.
'"Based on end-use share of 1979 production.
^See Section 5.3.1.
5A-16
-------
•5A.8 Rubber Processing Chemicals (SIC 2869-3)
Rubber processing chemicals production is expected to grow by 45 percent
over the period from 1982 to 1988 based on DRI production indices forecasts (see Table
5 A-13).
5A.9 Flavor and Perfume Materials (SIC 2869-3)
The 1988 outlook for flavor and perfume materials is shown in Table 5A-14.
5A. 10 Miscellaneous Cyclic and Acyclic Chemicals (SIC 2869-7)
This product group consists primarily of chemical intermediates (about 90
percent acyclic on a production basis) and, to a lesser degree, finished chemicals such
2
as solvents. In 1982, production amounted to 81 billion pounds, roughly 40 percent of
total OCPSF industry production. The DRI Chemical Service covers about 65 percent
of the production of the group (including implicit intermediates such as ethylene _
dichloride (EDC)). This coverage includes all chemicals (except two chloromethanes)
produced in excess of 500 million pounds as well as each of the different chemical
subgroups. Real growth of economic indicators for this group is presented in Table 5A-
15.
Overall, production volume is expected to increase by 16 percent, driven
primarily by a 26 percent increase in domestic consumption. Export markets, which
accounted for nearly ten percent of production in 1982, are projected to decline to only
three percent in 1988. Net exports are projected to decline by over 40 percent, from
4.4 to 2.6 billion pounds.. Capacity utilization is projected to increase from the low
1982 level of about 62 percent to a more attractive level of about 84 percent in 1988.
Real prices are expected to decrease an average of 2 cents per pound, or 10 percent.
Production value is anticipated to increase by only 16 percent by 1988. Table 5A-16
presents chemicals in this group which are covered by the DRI Chemical Service. The
following brief discussions examine individual chemical forecasts in order to identify
those that are projected to perform significantly poorer than average and the
underlying reasons for the low expected performance (see Table 5A-17).
J
Ethanol and other salts, alcohols and esters derived from fatty substances are
all 2869-5, although some are included here.
5A-17
-------
Table 5A-13
RUBBER PROCESSING CHEMICALS REAL GROWTH, 1982-1988 (2869-3)
Major End-Use
Tires
Mechanical goods
Footwear
Weighted average
Percent End-Use
Share of Product
Group Production
65
20
Growth Indicator
(percent share
of end-use)
Ti res
Rubber excluding
tires (19)
Non-mechanical
machinery (52)
Rubber excLuding
tires (19)
Apparel and applied
products (28)
Indicator Growth
from 1982-1988
(percent)
28
36
24
30
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1988
Forecast Results May 7, 1986, and Kline Guide to the Chemical
Industry, Fourth Edition, Charles H. Kline and Company Inc., 1980.
^"Based on end-use of 1979 product group production and growth
indicator proportion for each end-use with more than one growth indicator.
5A-18
-------
Table 5A-14
Flavor and Perfume Materials Real Growth, 1982-1988 (2869-3)
Major End-Use
Food and Soft Drinks
Toiletries
Cosmetics,
Detergents
Percent' c,nd-Use
ohare of Product.
Group Production
1
Other
Weighted average
10
1
65
25
Growth Indicator
Food and allied
products
Other Non-durables
Real GNP
Indicator Growth
Rate (percent)
15
13
25
15
Source: Data Resources, Inc. Chemical Service, DRI Chemical Model 1988
Forecast Results, May 7, 1986, and Kline Guide to the Chemical
Industry, Fourth Edition, Charles H. Kline & Co. Inc., 1980.
1
Based on end-use share of 1979 production.
5A-19
-------
Table 5A-15
MISCELLANEOUS CYCLIC AMD ACYCLIC CHEMICALS BASELINE (2869-7)
ReaL Growth 1982-1988
Economic Indicators
1982
Value
1988
Value
Annual
Percent
Total
Percent
Production (millions of pounds)
47,850
56,428
2.5
16
Domestic Consumption
(millions of pounds)
44,300
55,700
3.9
26
Net Exports/Production (percent)^
9.2
3.0
-1.0
-6.2
Exports (millions of pounds)
5,231
4,380
-1.5
-16
Imports (millions of pounds)
800
2,700
21.3
237
Average Price (cents/pound)
20
18
-1.4
-9
Value of Production (millons of $)
8,774
10,167
2.5
16
Capacity (millions of pounds)
77,019
72
2.5
16
Capacity Utilization (percent)
62
84
3.5
22
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1982
Benchmark
Case, July 3, 1986 and DRI
Chemical
Model 1988
Forecast Results
, May 14,
1986.
^Net exports as a percent of production where net exports is equal to exports
less imports.
5A-20
-------
Table 5A-I6
PRICE, PROOUCTION. AND VALUE OF
PROOUCTION
Br PROOUCT
FOR MISCELLANEOUS
CYCLIC AND ACYCLIC CHEMICALS
(SIC 2669-
7) 1982 AND 1988
1982
1988
Total Percenl
Change
Production
Price
Va 1 ue
Product ion
Price
Va l ue
Produc-
Product
(mil of lb)
c/lb
(1 mil)
(mil of lb)
c/lb
(S mi 1)
t ion
Pr i ce
Value
Methanol
7,554.6
8.0
'604.368
8,062.1
5.9
475.664
7
-26
-21
Formaldehyde
4,816.5
14.0
674.310
5,988.6
1 1.8
706.655
24
-16
5
Phosgene
972.7
—
~
1,299.2
~
—
33
—
--
Ethanol, Synthetic
1,023,3
—
—
116.1
—
-88
—
--
Ethylene Glycol
4,309.3
21.7
935.118
4,320.4
19.9
859.759
0
-8
-8
VCM
5,967.6
16.5
984.654
8,150.5
16.3
1,326,532
36
-1
35
Acetaldehyde
613.7
—
—
584.7
~
-5
—
--
Ethylene Oxide
5,152.9
27.3
1,406.742
5,710.6
22.6
1 ,290.596
11
-17
-9
Acetic Acid
2,748,0
—
—
3,054.7
—
---
11
—
--
VAM
1 ,797.2
28.0
503.216
2,335.4
22.6
527.800
30
-19
5
Isopropanol
1,380.0
—
—
1,378.7
—
—
0
—
--
Propylene Glycol
399.6
40.0
159.840
582.4
34.3
19,976.3
46
-14
25
Acetone
1,694.2
22.0
372.724
2,098.0
16.7
35,036.6
24
-24
-6
Propylene Oxide
1,613.1
43.8
706.538
2,410.4
46.6
1,123.246
49
6
59
Acrylic Acid
535.4
—
—
788.0
—
—
47
—
--
Butyl Acrylate
310.0
50.0
155.000
451 .6
48.1
217.219
45
-4
40
Ethyl Acrylate
54.0
57.0
30.780
93.9
56.9
53.429
74
0
74
Methyl Acrylate
721 .0
54.0
389.340
983.7
47.1
463.323
36
-13
19
Aery Ion i tr ile
2,035.2
33.0
671.616
2,246.4
32.4
727.834
10
-2
a
N-butanol
730.4
' —
--
969.4
—
—
33
--
MEK
462.0
33.0
152.460
594.0
27.5
163.350
29
-17
7
Caprolactam
792.7
69.0
546.963
1,125.4
64.7
728.134
42
-6
33
Adipic Acid
1,122.4
34.0
381.616
1,563.5
50.3
786.441
39
48
106
HMDA
782.8
—
--
1,113.2
--
42
--
--
Maleic Anydrjde
259.5
38.0
98.610
411.3
40.2
165.343
58
6
68
SUBTOTAL
47,848.0
20.2
8,773.895
55,666.0
18.3
10,167.545
16
-9
16
SOURCE: Data
Resources, Inc.
Chemical Service, DRl
Chemical Model 1982 Benchmark
Case, July 3, 1984 and DRl
Chem i cal
Model 1988
Forecast Results, May 14, 1986.
-------
TabLe 5A—17
LOW GROWTH MISCELLANEOUS CYCLIC AMD ACYCLIC CHEMICALS
Chemical
Real Crowth 1982-1988
( percent )
Produce Lon Consumpt ion
Causes
Acetaldehyde
-5
-5
Process change
Methanol
36
International trade
Ethylene Glycol
13
Low demand;
International trade
Ethanol, Synthetic
-88
-6
Low demand;
International trade
Isopropanol
Acrylonicrile
Ethylene Oxide
Acetic acid
10
11
11
-1
17
10
10
Process change
International trade
Low demand
Process change;
International trade
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1982
Benchmark. Case, July 3, 1984 and DRI Chemical Model 1988 Forecast,
May 14, 1986.
5A-21
-------
Acetaldehyde: Negative growth is expected as a result of its replacement as
the feedstock for acetic anhydride production by a new coal-based process.
Ethylene Glycol: Domestic consumption is projected to grow by only 13
percent between 1982 and 1988. In addition, net exports which make up 11 percent of
production in 1982, are expected to fall by nearly 40 percent by 1988.
Isopropanol: Domestic consumption is expected to decrease 1 percent between
1982 and 1988 due to the continuing trend toward acetone production from cumene.
Feedstock use for acetone has historically been the major end use of isopropanol.
Acrylonitrile: The low production forecast is due to an unfavorable
international trade situation. In 1982, net exports were 39 percent of production; this
level of exports is expected to remain the same through 1988. Consequently,
production is expected to grow by only 10 percent; whereas domestic consumption is
expected to grow by 17 percent. Acrylonitrile production growth is also limited
indirectly by unfavorable trade conditions for acrylic fiber, the major end use of
acrylonitrile. Exports of acrylic fiber are expected to increase by only h percent.
Ethylene Oxide: The low growth forecast is due to low domestic demand for
its derivatives such as ethylene glycol.
Acetic Acid: Relatively weak growth of acetic acid is primarily due to two
factors: - (1) a process change in the production of acetic anhydride; and (2) a
deteriorating international trade situation. Trade effects are mainly indirect, resulting
from trade problems affecting vinyl acetate monomer (VAM, see below), which
accounts for about 50 percent of acetic acid demand. The direct trade effect is not
large but places a drag on demand growth. A new coal-based process to produce acetic
anhydride (AAH) is expected reduce the AAH end-use share of acetic acid production
from ahout 25 percent in 1982 to less than 10 percent in 1988. Strong growth in other
end-used is expected to counteract these negative effects.
Vinyl Acetate Monomer (VAM): The moderate growth of VAM production will
result from a declining export market. In 1982, exports accounted for 39 percent of
VAM production; they are expected to decline to 22 percent of production by 1988. A
very strong market for vinyl acetate and- alcohol plastics balances this negative trade
situation somewhat.
Table 5A-18 presents projected capacity utilization levels for chemicals in this
product group. Those chemicals with levels projected to be less than 70 percent are
listed in Table 5A-19. Four of these ten chemicals have been discussed earlier. Of the
5A-22
-------
Table 5A-I8
CAPACITY AND CAPACITY UTILIZATION FOR MISCELLANEOUS CYCLIC AND ACYCLIC CHEMICALS (SIC 2869-7)
1982-
,986-
-% CHANCE-
Product
Production
Capac i ty
Cap UtiI (2)
Product ion
Capac it y
Cap Uti \(%)
Product ion
Capac i ty
Capac i ty
(rail lb)
(ml 1 b)
(mi 1 lb)
(mil lb)
Ut i I i zat i ci
Methanol
7,554.6
9,116.3
82
8,062.1
9,447.8
85
7
4
3
Forma 1dehyde
4 ,816.5
8,634.0
54
5,988.6
8,749.0
6B
24
-1
14
Phosgene
972.7
2,249.0
43
1,299.2
2,199.0
59
34
-2
16
Ethanol, Synthetic
1,023.3
3,611.0
28
116.1
4,821.0
2
-87
34
-26
Ethy 1ene Glycol
4,309.3
6.335.0
68
4,320.4
5,475.0
79
0
-14
11
VCM
5,967.6
9,330.0
64
8,150.5
8,750.0
93
37
-6
29
Aceta1dehyde
613.7
1 ,460.0
42
584.7
1,185.0
49
-5
-19
7
Ethylene Oxide
5,152.9
7,600.0
68
5,710.6
7,355.0
78
11
-3
10
Acetic Acid
2,748.0
4,650.0
59
3,054.7
5,120.0
60
11
10
1
VAM
1 ,797 .2
2,300.0
78
2,335.4
2,485.0
94
30
8
16
1sopropanol
I ,380.0
2,900.0
48
1,378.7
2,685.0
51
0
-7
2
Propylene Glycol
399.6
940.0
43
582.4
990.0
59
46
5
16
Acetone
1 ,694.2
2,867.0
59
2,098.0
3,078.0
68
24
7
9
Propylene Oxide
1,613.1
2,760.0
58
2,410.4
2,860.0
B4
49
4
26
Aery lie Ac i d
535.4
900.0
59
788.0
900.0
68
47
0
29
Butyl Aery late
310.0
1,000.0
31
451 .6
1 ,350.0
33
46
35
2
Ethyl Acrylate
54.0
125.0
43
93.9
195.0
48
74
56
5
Methyl Acrylate
721 .0
1,100.0
66
983.7
1,190.0
83
27
8
17
Acrytonltrile
2,035.2
2,290.0
89
2,246.4
2,525.0
89
10
10
0
N-butanol***
730.4
1,350.0
54
969.4
1 ,355.0
72
33
0
18
MEK
462.0
753.0
61
594.0
683.0
87
29
-9
26
Caprolactam
792.7
1,188.0
67
1 ,125.4
1,248.0
90
42
5
23
Adipic Acid
1 , 122.4
1,770.0
63
1 ,563.5
1,665.0
94
39
-6
31
HMDA
782.8
1,190.0
66
1,113.2
1,190.0
94
42
0
28
Maleic Anydride
259.5
401 .0
65
411.3
591.0
70
58
47
5
SUBTOTAL
47 ,B48
77,079
62
56,428
78,092
72
18
1
10
>
ro
v»i
SOURCE: Data Resources, Inc. Chemical Service,
Forecast ResuIts, May 14, 1986.
DRl Chemical Model 1982 Benchmark Case, July 3, 198"} and DRl Chemical Model 19B8
-------
TabLe 5A-19
LOW CAPACITY UTILIZATION
MISCELLANEOUS
CYCLIC AND ACYCLIC
CHEMICALS1 (2869-7)
Chemical
1982
1988
Trend
Acetaldehyde
42
49
increasing slightly
Isopropanol
48
51
increasing slightly
Propylene Glycol
43
59
increasing
Butyl Acrylate
31
33
increasing slightly
Ethyl Acrylate
43
48
increasing slightLy
Formaldehyde
54
68
increasing
Phosgene
43
59
increasing
Ethanol, synthetic
28
2
decreasing
Isopropanol
48
51
increasing slightly
Acetic acid
59
60
increasing slightly
Acetone
59
68
increasing
Maleic anhydrideC???)
65
70
increasing slightly
Source: Data Resources Inc., Chemical Service, DRI Chemical Model 1982
Benchmark Case, July 3, 1984 and DRI Chemical Model 1988 Forecast
Results, August 21, 1984.
^Capacity Utilization less than 70 percent in 1982 and 1988.
5A-2f
-------
.others, capacity can be used for the production of a number of related chemicals. The
acrylates provide a good example of this situation; although they show low utilization
levels, an unknown amount of capacity double-counting makes this figure misleading. A
similar situation exists for n-butanol which is produced by the OXO process common to
a large number of alcohols.
Table 5A-20 presents the international trade outlook for the major chemicals
in this group. Exports were a major end market (net exports greater than 10% of
production) for nine chemicals in 1982; this situation is projected to change moderately
by 1988. Imports will increase significantly, while exports decrease by an average of a
few percent per year.
5A.ll Cyclic Intermediates (SIC 2S65-I)
This product group primarily consists of feedstocks for plastics and fibers, and
is the third largest product group in the industry in terms of 1982 production. DRl
Chemical Service coverage of this group extended to about 85 percent of production.
DRI forecasts a 37 percent increase in production between 1982 and 1988. Domestic
consumption is expected to grow at the same rate; net exports, which made up 9
percent of production in 1982, are projected to fall by about 17 percent. Between 1982
and 1988, real prices are expected to decrease by about 8 percent and the value of
production to increase by about 2
-------
Table 5A-20
INTERNATIONAL TRADE MISCELLANEOUS CYCLIC AND ACYCLIC CHEMICALS (Millions Of lbs) (2869-7)
¦1982 1988 Total Percent Change
Net Net Change
EXP as % EXP as Total % Net EXP/
Product Production Exports Imports of Prod Production Exports Imports t of Prod EXP IMP Prod
Methanol
7,554.6
1,118.6
299.2
11
8,062.1
51.9
1,600.0
-19
-95
435
-30
Formaldehyde
4,816.5
9.7
19.7
0
5,988.6
8.3
8.0
0
-14
-58
0
Phosgene
972.7
0.0
p.o
0
1,299.2
0.0
0.0
0
0
0
0
Ethanol, Synthetic
1,023.3
52.0
147.0
-9
116.1
60.0
50.0
9
15
-59
18
Ethylene Glycol
4,309.3
518.8
37.4
11
4,320.4
426.0
438.5
0
-18
1073
-1 1
VCM
5,967.6
922.1
50.6
15
8,150.5
980.0
124.6
1 1
6
146
-4
Aceta1dehyde
613.7
0.0
0.0
0
584.7
0.0
0.0
0
0
0
0
Ethylene Oxide
5,152.9
3.3
9.5
0
5,710.6
77.8
19.9
1
2,258
1 10
1
Acetic Acid
2,748.0
126.1
25.3
4
3.054.7
186.8
49.8
5
48
97
1
VAM
1,797.2
697.6
6.6
38
2,335.4
518.8
1.0
22
-26
-85
-16
1sopropanol
1,380.0
141.1
76.7
5
1,378.7
207.5
134.5
5
47
75
0
Propylene Glycol
399.6
44.7
8.7
9
582.4
57.1
24.9
6
28
186
-3
Acetone
1,697.2
1 14.8
55.8
4
2,098.0
77.8
109.6
-2
-32
96
-6
Propylene Oxide
1,613.1
146.4
510.
6
2,410.4
300.9
19.9
12
106
-61
6
Acrylic Acid
535.4
1 1.9
0.0
2
788.0
15.6
0.0
2
31
0
0
Butyl Aery late
310.0
71.1
0.0
23
451 .6
95.0
0.0
21
34
0
-2
Ethyl Aery late
54.0
20.0
0.0
37
93.9
25.0
0.0
27
25
0
-10
Hethyl Aery late
721 .0
86.4
0.1
12
983.7
83.0
0.1
8
-4
0
-4
Acrylonitrile
2,035.2
602.6
0.0
39
2,246.4,
882.0
0.0
39
10
0
0
N-butanol
730.4
163.1
3.4
22
969.4
88.2
5.0
9
-46
47
-13
MEK
462.0
70.3
40.9
6
594.0
81.2
65.3
3
15
60
-3
Caprolactam
792.7
62.3
0.1
8
1,125.4
78.5
0.1
7
26
0
-1
Adipic Acid
1 ,122.4
31 .6
2.5
3
1,563.5
51.9
10.0
3
64
3
0
HMDA
782. a
1 1 .0
0.2
1
1,113.2
10.4
0.2
1
-6
0
O
Maleic Anydride
259.5
5.7
1.4
2
4 11.3
15.6
5.0
3
1 74
257
1
SUBTOTAL
47,848
5,231
835
9
56,438
4,379
2,667
3
-16
219
-6
SOURCE: Data Resources, Inc.
Chemi caI
Service, DRl
Chemi ca1
Model 1982 Benchmark Case,
July 3, 1984
and OKI
Chem i ca1
Model
1988 Eo
Results, May 14, 1986."
-------
TabLe 5A-2L
CYCLIC INTERMEDIATES
Real Crowth 1982-1988
1982
1988
Annua 1
Total
Economic Indicators
Value
Value
Percent
Percent
Production (millions of pounds)
31,077
42,541
5.3
37
Domestic Consumption
29,129
40,219
5.4
38
Met Exports/Production (percent)
9
6
-.4
-3
Exports (millions of pounds)
3,308
. 3,718
2
12
Imports (millions of pounds)
495
1,397
19.0
182
Average Price (cents/pound)
26
24
-1.2
-8
Value of Production (millons of
$) 6,678
8,309
3.5
24
Capacity (mil pounds)
51,107
48,573
-0.7
-5
Capacity Utilization (percent)
61
88
3.9
27
Source: Data Resources Inc., Chemical Service
, DRI Chemical Model
1982
Benchmark Case, July 3,
1984, and DRI
Chemical
Model 1988
Forecast
Results, May 14, 1986.
5A-27
-------
Table 5A-22
PRICE, PRODUCTION AND VALUE OF PRODUCTION BY PRODUCT FOR
Ol
>
i
to
00
CYCLIC
INTERMEDIATES
(SIC 2865-1)
1982 AND 1988
1982
1988
TOTAL
t CHANGE
Product ion
Price
Value
Product i on
Pr ice
Value
Product
(rail lb)
(c/lb)
(mil I)
(mil lb)
(c/lb)
(oil 1)
Product ion
Pr i ce
V a 1 u<
eyelohexane
1,274.8
23.0
293
2,068.1
24.5
507
62
7
73
cumene
2,743.5
23.0
631
3,835.6
21 .6
829
40
-6
31
phenol
2,174.8
26.0
566
3,185.9
29.4
937
47
13
66
bisphenol A
479.8
49.0
235
908.3
47.1
427
69
-4
82
monon i troDenzene
785.2
—
—
1,029.9
—
--
31
--
—
an iIi ne
557.4
33.0
184
846.2
28.4
237
52
-14
29
toluened i ami ne
434.6
--
—
409.1
—
—
-6
--
--
1DI
556.0
51 .0
284
795.2
70.6
564
43
38
99
ethy1 benzene
6,656.2
21 .0
1 ,398
8,605.2
20.6
1 ,807
29
-2
29
s* yrene
5,942.0
29.9
1 ,783
7,423.7
21.3
1 ,581
25
-29
-1 1
p-< i1ene
3,391.4
27.0
916
5,067.8
20.4
1,033
49
-24
16
terephthalie ac i d
1,551 .8
—
—
2,624.5
--
—
69
--
--
DMT
3,042.7
—
~
4,041.4
--
--
33
--
--
o-xy1ene
802.4
22.0
176
797.8
14.7
117
-1
-33
-34
phthalic anhydride
684.4
31 .0
212
900.5
26.5
239
32
-16
13
r0T AL
31,077
26
6,678
42,539
24
8,309
37
-8
21
Source: Data Resources, Inc. Chemical Service, DRI Chemical Model 1982 Benchmark Case. July 3, 1984 and DRI Chemical Model 1988 Forecast
Results, May 14, 1986.
-------
The relatively low growth of o-xylene production is entirely due to the decline
in exports. Domestic consumption is projected to grow very strongly because of the
strong growth of phthalic anhydride and because the o-xylene synthesis process is
capturing an increasing share of phthalic anhydride production.
Table 5A-23 presents the projected capacity utilization levels of this group.
The chemicals listed in Table 5A-24 have 1988 projected capacity utilization levels
below 70 percent. A number of chemicals with relatively low capacity utilization in
1982 are projected to increase utilization to above 90 percent by 1988. These include
cumene, phenol, bisphenol A, ethylbenzene and o-xylene.
Table 5A-25 presents the projected international trade situation for the cyclic
intermediates. In 1982, five of these chemicals had significant export markets:
bisphenol A, styrene, p-xylene, terepthalic acid, and o-xylene. O-xylene was mentioned
above. Net exports are expected to drop to 0 by 1988. TDl, also mentioned above, had
a relatively minor export market in 1982, but because of new end uses, is expected to
increase in both domestic consumption and exports quite dramatically. The major
component of this increase is its use in polyurethane, which is used in automobile
manufacture.
The international market for bisphenol A is expected to remain at the same
level, with net exports continuing to be about ten percent of production. Net exports of
styrene, which were 17 percent of production in 1982, will drop to 5 percent, because of
increased imports. Another chemical with a sizable export market in 1982, terephthalic
acid, will experience a greater than 200 percent growth in exports.
5A-29
-------
Table 5A-23
PpOOUCTION, CAPACITY ANO CAPACITY UTILIZATION UY PRODUCT FOR
CYCLIC
INTERMEDIATES
(SIC 2865-1)
1982 ANO 1988
1982
1988
TOTAL 2 CHANGE
Production
Capacity
C.U.
Product ion
Capacity
C.U.
Product
(mil lb)
(nil lb)
(X)
(mil lb)
(oil lb)
<*>
Production Capacity
C.U,
cyclohexane
1,274.8
3,365.0
38
2,068.1
3,565.0
58
62
6
20
curoene
2,743.5
4.700.0
58
3,835.6
4,090.0
94
40
-13
36
phenol
2,174.8
3,608.0
60
3,185.9
3,363.0
95
47
-7
35
bisphenol A
479.8
910.0
53
908.3
990.0
92
89
9
39
morion i trobenzene
785.2
1,560.0
50
1,029.9
1,507.0
68
31
-3
18
an 11i ne
557.4
1 ,394.0
40
846.2
1,234.0
69
52
-12
29
toluenedi ami ne
434.6
—
--
409.1
—
--
-6
—
—
IDI
556.0
710.0
78
795.2
620.0
128
43
-13
50
ethyl benzene
6,656.2
10,050.0
66
8,605.2
8,710.0
99
29
-13
33
styrene
5,942.0
8,270.0
72
7,423.7
8,280.0
90
25
0
18
p-*ylene
3,391.4
6,086.0
56
5,067.8
6,355.0
80
49
4
24
lerephthalic acid
1,551.8
3,240.0
48
2,624.5
3,240.0
81
69
0
33
DMT
3,042.7
4,150.0
73
4,041.4
4,150.0
97
33
0
24
o-xy1ene
802.4
1.355.0
59
797.8
845.0
94
-1
-38
35
phthalic anhydride
684.4
1,275.0
54
900.5
1,215.0
74
32
-5
20
TOTAL
31.077
51,107
61
42,539.2
48,573
88
37
-6
27
Source: Data Resources,
Inc. Chemical
Service, DRI Chemical Model 1982 Benchmark Case,
July 3,
1984 and OKI
Cheaticut Model
I9B8 fo
Results, May 14, 1986.
-------
Table 5A-24
LOW-CAPACITY UTILIZATION CYCLIC INTERMEDIATES
Capacity Utilization
(percent)
Chemical
1982
1988
Trend
Ani1ine
40
69
Increas ing
Cyclohexane
38
58
Increas ing
Mononitrobenzene
50
68
Increas ing
Source: Data. Resources Inc., Chemical Service, DRI Chemical Model 1982
Benchmark Case, July 3, 1984 and DRI Chemical Model 1988
Forecast Results, Ma.y 14, 1986.
5A-31
-------
Table 5A-25
INTERNATIONAL TRADE SITUATION BY PRODUCT FOR CYCLIC INTERMEDIATES (SIC 2865-1)
1982 and 1988
1982-
-1988-
-TOTAL PERCENT CHANGE-
Product
Product ion
(mil 1bs)
Exports
(ml 1 lbs)
Imports
(mil lbs)
Net
Exp t
of Prod
Production
(mil lbs)
Exports
(mi 1 lbs)
Imports
(mi 1. lbs)
Net
Exp as
It Prod
Exports
Imports
Net E
1 of
Proc
Cyclohexane
1,27-1.8
139.9
30.6
9
2,068.1
124.5
0.0
6
-II
-100
-3
Cumene
2,743.5
21.1
171.4
-5
3,835.6
20.8
598.0
-15
-1
249
-I0
Phenol
2,124.8
111.0
0.
5
3,185.9
88.8
69.7
1
-2
-99
-4
Bisphenol A
479.8
48.0
0.0
10
908.3
93.4
0.0
10
95
0
0
Monon1trobenzene
785.2
0.0
0.0
0
1.029.9
0.0
0.0
0
0
0
0
An i1i ne
557.4
0.0
0.2
0
846.2
0.0
0.2
0
0
0
0
Toluenedi ami ne
43^.6
0.0
0.0
0
409.1
0.0
0.0
0
0
0
0
IDl
556.0
169.7
149.5
4
795.2
125.3
0.2
16
-26
-99
12
t thy 1 benzene
6,656.2
114.1
20.0
1
8,605.2
124.5
29.9
1
9
50
0
Styrene
5.942.0
1,024.6
21 .0
17
7,423.7
900.0
498.5
5
-12
2274
-12
P-xy1ene
3,391.4
863.8
76.6
23
5,067.8
1,050.0
125.0
18
22
63
-5
Terephthalic acid
1,551.8
320.7
0.0
21
2,624.5
1,000.0
0.0
38
212
0
17
DMT
3,042.7
97.9
0.0
3
4,041.4
120.0
0.0
3
2333
0
0
0-xy1ene
802.4
384.6
2?.7
45
797.8
60.0
65.0
0
-84
186
-45
Phthalic anhydride
684.4
11.1
1.9
1
900.5
10.0
10.0
0
-98
426
-1
>
i
N>
TOTAL
31,07?
3,308
495
42,541
3,718
1,397
12
182
-3
SOURCE: Data Resources, Inc. Chemical Service, DRI Chemical Model 1982 Benchmark Case, July 3, 1984 and DRI Chemical Model 1988 Forecast
Results, May 14, 1986.
-------
6.0
ECONOMIC IMPACT ASSESSMENT RESULTS
6.1 Introduction
This chapter presents the results of the Economic Impact Analysis for BPT,
BAT and PSE5 Options. Impacts have been estimated for plants themselves, new (yet-
to-be-built) plants and expansions, parent firms, communities where closures are
expected, industry-wide foreign trade, and the resources of the nation as a whole.
[n the course of the analysis, numerous options were examined. Many of these
are no longer considered viable and are, therefore, not included in the impact analysis.
Full impact analyses were donducted for BPT Option I, BAT Options IIA and !IB and
PSES Options 1VA, IVB, and VII. In addition, plant level summary impacts are presented,
for BAT Options I and V.
6.2 Plant Level Impacts
As described in Chapter 3.0, the plant is the primary unit of analysis. It is the
entity to be regulated and, hence, is the basis for developing treatment cost
estimates. In performing the economic impact analysis, it was also assumed that each
plant represents its own profit center. Hence, the decision to close a plant or plant-
specific product line is based on the financial viability of that plant or product line as a
profit-making entity.
The primary plant-level impact measures examined include: 1) closures, 2)
profitability, 3) cost-to-sales. The bases for these measures were described in Chapter
3. In addition, since employment losses result from plant and product closures, they are
presented in this section as well.
6.2.1 Direct Dischargers
A total of 283 direct discharging plants were included in the impact
£
analysis. Table 6-1 summarizes impacts for these plants under the BPT and BAT
£
Under BPT, five plants expected to incur treatment costs could not be
analyzed due to incomplete data. For BAT options, this number increased to six. Note,
however, that costs presented in the tables reflect totals for all plants incurring costs.
6-1
-------
Table 6-1
SUMMARY OF RESULTS: DIRECT DISCHARGERS
BAT costs and lapacts are incremental to BPT I
(198? Mi 11 ion Dollars)
BPT 1
BAT l»
REGULATORY OPTION
BAT 11A BAT 1 IB
BAT V«
NUMBER OF PLANTS ANALYZED
209
283
283
283
283
NUMBER OF PLANTS INCURRING COSTS
214
289
289
289
289
COSTS OF COMPLIANCE
CAPITAL INVESTMENT
193.04
165.58
333.20
322.73
1,100
.77
OPERATING AND MAINTENANCE
39.38
115.30
230.52
157.39
578
.05
TOTAL ANNUAL COMPLIANCE COST
66.53
139.93
280.85
206.08
744
.12
PLANT CLOSURES
0
a
12
11
26
PfttOUCT LINE CLOSURES
0
10
12
9
16
PROFIT OR SALES IMPACTS**
8
7
21
17
44
EMPLOYMENT REDUCTION
0
1 .335
1 .743
1 .359
6.
475
•Impact analyses are based on costs Iran the December 1986 Notice of Availability.
••Non-closures only.
-------
options. BAT costs and impacts are incremental to 8PT ! and do not reflect the result
of setting BAT equal to BPT for small direct dischargers.
BPT Options
Under BPT I, some 214 plants are expected to incur costs. Capital costs are
projected to total $193 million (1982 dollars), while annual operating and maintenance
costs are estimated at $39 million. Annualized costs are expected to total
approximately $68.5 million. No plant or product line closures are projected under this
option. However, it is expected that 8 plants will sustain significant profit or sales
*
impacts.
BAT Options
Some 289 plants are expected to incur costs to meet priority pollutant
limitations under the BAT options. The costs and impacts associated with the four
options presented vary widely. For example, incremental annualized compliance costs
range from $140 million under BAT I to over $744 million for BAT V. Combined plant
and product line closures vary from 18 (BAT I) to 42 (BAT V).
The above examples represent extremes. The mid-range options (BAT IIA and
BAT IIB) merit closer examination. Compliance with BAT IIA will require an
incremental capital investment of about $333 million. Operating and maintenance costs
are estimated to be about $231 million, for an annualized compliance cost of
approximately $281 million. These costs are expected to result in 12 plant and 12
product line closures and a loss of 1,743 jobs. An additional 21 plants are expected to
sustain significant profit or sales impacts.
Costs are somewhat lower and impacts less severe under BAT IIB. Incremental
capital investment is expected to total $323 million — approximately $10 million less
than BAT IIA. Operating and maintenance costs are estimated at $157 million per year
— $73 million, or almost 30 percent less than BAT IIA. As a result, the total annualized
compliance costs of $206 million for BAT IIB are about 26 percent lower than those
Recall from Chapter 3.0, that 1) a significant sales impact is defined as
annualized treatment costs in excess of 5 percent of sales and 2) a significant profit
impact is said to occur when a plant's after-tax profit to sales ratio falls into the lowest
decile for a given SIC code.
6-3
-------
Table 6-2
SUMMARY OF CUMULATIVE RESULTS: DIRECT DISCHARGERS
(1982 Hi I lion Dollars)
BPT 1
REGULATOR*
BAT 1 •
OPTION
BAT 11A
BAT 1 IB
BAT V«
NUMBER OF PLANTS ANALYZED
209
283
283
283
283
NUMBER OF PLANTS INCURRING COSTS
214
289
289
289
289
COSTS OF COMPLIANCE
CAPITAL INVESTMENT
193.04
358.62
526.24
515.77
1 ,293.81
OPERATING AND MAINTENANCE
39.38
154.68
269.90
196.77
617.43
TOTAL ANNUAL COMPLIANCE COST
68.53
208.46
349.38
274.61
812.65
PLANT CLOSURES
0
8
12
1 1
26
PRODUCT LINE CLOSURES
0
10
12
9
16
PROFIT OR SALES IMPACTS'"
8
15
29
25
52
EMPLOYMENT REDUCTION
0
1 ,335
1 ,743-
1,359
6,475
•Impacts are based on costs from the December 1986 Notice of Availability.
»"Non-closures only.
-------
associated with BAT IIA. Eleven plant and nine product line closures are expected as a
result of compliance with BAT IIB. The associated employment loss is estimated at
1,359 jobs — about 22 percent fewer than BAT IIA. In addition to the closures, 17 more
plants are expected to incur significant profit or sales impacts.
Table 6-2 presents cumulative (to BPT I) costs and impacts for the four BAT
options. Since there were no plant or product line closures under BPT I, the number of
projected closures and the resulting job losses are identical to the incremental
estimates presented in Table 6-1 and discussed above. Compliance cost estimates and
the number of non-closure plants expected to sustain sales or profit impacts are simply
the sum of the BPT I figure and the relevant incremental BAT option estimate.
6.2.2 Indirect Dischargers
A large number of interim PSES options were evaluated. However, upon
analysis, only several were considered to be the most likely candidates. The remainder
*
were dropped from the economic impact analyses . Table 6-3 summarizes costs and
impacts for the three principal options considered.
As shown in the table, some 365 plants are expected to incur costs associated
4 *
with PSES options; 362 of these were included in the analysis. As with the BAT
options, the costs and associated impacts of the various options vary widely — total
annualized costs range from $183 million under PSES IVB to $312 million under PSES
IVA. Similarly, closures range from 52 (PSES IVB) to 67 (PSES IVA).
Under PSES IVA, capital investment is expected to total over $318 million,
while annual operating and maintenance costs are estimated at approximately $263
million. This results in a total annualized compliance cost of about $312 million.
Thirty-seven plants are projected to close completely; another 30 are expected to shut
down their organic chemicals and plastics product lines. The reduction in employment
associated with these closures is estimated at 3,736 jobs. An additional 86 plants are
expected to sustain profit or sales impacts, bringing the total number of significantly
£
A number of alternative options, designed to provide regulatory relief to
small plants, are presented in the Regulatory Flexibility Analysis.
The remaining three had incomplete economic data and could, therefore,
not be included in the analysis.
6-5
-------
Table 6-3
SIM4ARY OF RESULTS: INDIRECT DISCHARGERS
(1962 Million Dollars)
PSES IVA
REGULATORY OPTION
PSES IVB
PSES VII
NUMBER OF PLANTS ANALYZED
362
362
362
NUMBER OF PLANTS INCURRING COSTS
365
365
365
COSTS OF COMPLIANCE
CAPITAL INVESTMENT
318.89
260,71
319.35
OPERATING AND MAINTENANCE
262.79
142,75
152.41
TOTAL ANNUAL COMPLIANCE COST
311.65
182,70
201.29
PLANT CLOSURES
37
25
27
PRODUCT LINE CLOSURES
30
27
27
PROFIT OR SALES IMPACTS*
86
63
66
EMPLOYMENT REDUCTION
3,736
2, 190
2,561
•Non-closures only.
-------
ifnpacted plants to 153, or 42 percent of the indirect discharging piants included in the
analysis.
Both costs and impacts are reduced considerably under PSES IVB. Capital
investment required to comply with this option is estimated at $261 million -- almost 20
percent less than PSES [VA. Annual operating and maintenance costs, expected to total
$143 million, are close to 50 percent lower. Thus, total annualized compliance costs —
about $183 million per year — are 41 percent less than those associated with PSES
[VA. As would be expected, economic impacts are considerably less severe. Some 25
plant and 27 product line closures are projected, with a resultant employment loss of
2,190 jobs. This represents a reduction of about 40 percent, as compared with
employment impacts under PSES IVA.
Under PSES VTI, capital and annual operating and maintenance costs are
estimated at $319 million and $152 million, respectively. Total annualized compliance
costs are expected to total $201 million per year — about $20 million more than PSE5
IVB. Impacts are slightly greater than those associated with PSES IVB. Two additional
plants are projected to close, raising the employment loss to 2,561 jobs — 371 more
than PSES IVB.
The remaining analyses in this chapter are based on a slightly different set of
costs and, in some cases, closure and employment loss projections. These costs and
impacts are contained in Appendix 6A. Costs for BPT and BAT options used in the
detailed analyses presented in Sections 6.3 to 6.7 are slightly higher than those
presented above. This earlier version of treatment cost estimates was projected to
result in two product line closures under BPT I. Closures under the BAT options were
identical to those presented above. Hence, impact estimates based on closures
(community impacts and foreign trade), are accurate; those based on treatment costs
(firm level, new sources, and national social costs) will slightly overstate impacts on
direct dischargers.
The revised treatment costs presented above for indirect dischargers are
somewhat higher than those used for the more detailed analyses. These higher costs
result in six additional closures, an increase of about 10 percent. Hence, the detailed
impact estimates presented' in the remaining sections of this chapter are somewhat
understated.
6-7
-------
6.3 Firm-Level Impacts
Firm-level impacts focus on a firm's ability to meet its fixed cost obligations
and its attractiveness to financial institutions and investors after treatment costs have
been absorbed. As described in Chapter 3, a firm's ability to meet fixed cost
obligations is measured by the firm's current ratio and its EBIT/interest ratio.
Attractiveness to lending institutions and investors is measured by the company's
debt/worth ratio and its return on assets. Firms that fall into the lower quartiles for
one or both sets of ratios, based on standard industry norms, may have difficulty
financing treatment costs.
Prior to presenting the impacts, a few more explanatory nates are necessary.
First, since plants or OCPSF product lines that close will not incur costs, these plants
are excluded from the analysis. In the case of single plant firms, this means that the
firm is excluded. In the case of multi-plant firms, treatment costs associated with the
closed plant or product line are assumed to be zero. Secondly, for multi-plant firms
which own both direct and indirect discharging plants, the following combinations have
been used:
• For BAT Options, PSE5 IVB costs are included as well as BAT
option costs.
• For PSES Options, BAT IIB costs are included as well as PSES
option costs.
The baseline analysis presented in Chapter 5 showed that no firms were likely
to have difficulty meeting fixed cost obligations prior to compliance with the
regulations. Table 6-4 shows that several firms may have difficulty meeting fixed cost
obligations as a result of costs associated with BAT and PSES Options. No firms appear
as weak under BPT Option I.
Under both BAT IIA and BAT IIB, one of the 120 firms evaluated may have
liquidity problems as a result of financing compliance costs. Relatively more firms
are put into weak liquidity positions as a result of costs associated with the PSES
options, however. Under PSES IVA, four of the 183 firms analyzed may have difficulty
meeting fixed obligations as a result of compliance with this option.. For PSES. Options
*Compliance costs for BAT used in this analysis are cumulative, i.e., include
costs associated with BPT [.
6-8
-------
Table 6-4
Firm-Level Financial Impacts — Interest Coverage and Liquidity
Number of Firms Weak
Analyzed Post-Compliance
BPT I
108
0
BAT IIA*
120
1
BAT IIB*
120
1
PSES IVA**
183
A
PSES VIB**
193
6
PSES VII**
193
6
*For firms who also own indirect discharging plants, impacts
include coses associated with PSES IVB.
**For firms who also own direct discharging plants, impacts
include cost associated with BAT IIB.
-------
fVB and VII, both the number of firms analyzed and the number which may have
difficulty meeting fixed obligations increase. A total of 193 firms are included in the
analyses of these two options; six of these may experience liquidity problems. These
increases reflect the fact that there are fewer closures under these options. That is,
there were 10 single plant firms flagged as closures under PSES IVA which are expected
to remain open under PSES options IVB and VII. Two of these may have problems in
meeting fixed cost obligations.
The second component of the firm level analysis, the leveraging and
profitability analyses, or attractiveness to financial institutions and investors, shows
that no significant impacts are anticipated as a result of financing treatment capital
costs. That is, no firm moved from an acceptable baseline position to a weak post-
compliance posture. Under the PSES options there was, however, one firm that
appeared as weak in the baseline. The addition of compliance investment coses a ill
further weaken this firm's financial standing.
6.4 Community Impacts
As described in Chapter 3, community impacts are considered significant if
the job losses due to plant or product line closures exceed 0.^4- percent of the total
community population. Since the employment to population ratio may be misleading if
a small community is located adjacent to or close to a much larger labor market, the
populations of the surrounding areas have been examined for those communities showing
significant impacts under the first criterion.
No significant community impacts are expected under BPT I. No closures,
and, hence, no job losses are projected.
Significant impacts on several communities are, however, expected under each
of the BAT and PSES options considered. Somewhat surprisingly, given the relative
numbers of closures under BAT and PSES options, a larger number of community
impacts are found under BAT. This results principally from the fact that direct
dischargers tend to be located in smaller and more isolated communities, where even
small employment losses are significant. Under the BAT options, two or three
communities are likely to sustain significant impacts, depending upon the option
considered. For each of the three PSES options examined, one community is expected
to sustain a significant impact, and another is a borderline case. No additional impacts
occur when BAT and PSES options are considered jointly. These results are summarized
in Table 6-5 and discussed below.
6-10
-------
TabLe 6-5
Summary of Cowminity Impacts
Option
Plane Closures
Product Line
Closures
Communities
Communi ties
Signif icantly
Affected
BPT I
BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
0
12
11
33
21
23
0
12
9
28
25
25
0
24
2Q
54
46
45
0
3
2
1*
1*
1*
-As noted in the text, there is a second community which may expe-
rience a significant impact.
6-11
-------
5.
-------
Under BAT IIB, 11 plant and 9 product line closures are expected. Eight of
these 20 communities have employment-loss-to population estimates in excess of 0.44
percent. These 8 are a subset of the 10 communities with ratios greater than 0.44
percent under BAT I1A. Two of these are expected to experience significant community
impacts under BAT IIB. These are both plant closures and correspond to the first and
third communities described in the BAT IIA discussion above. Impacts on one or more
of these communities may be mitigated if reduced standards are adopted for small
direct discharging plants.
6.4.2 PSE5 Impacts
PSES Option IVA is expected to result in 33 plant and 28 product line closures,
involving a total of 54 communities. (Multiple closures are projected in several large
cities.) Twelve of these 54 communities have employment loss-to-population greater
than the 0.44 threshold. The ratios range from 0.47 to 3.9 percent. However, ten of
these twelve communities are located close to large urban industrial centers and are,
therefore, not expected to experience significant impacts. Of the remaining two, one is
likely to sustain a significant impact, and the other is a borderline case.
The projected closure of a plant which employs 114 workers in a community of
4,132 people is expected to have a significant impact. The community is relatively
isolated, and displaced workers may have difficulty finding employment within
reasonable commuting distances. Considering indirect and induced effect, the total
employment loss resulting from this closure is estimated at 624 jobs.
This borderline case is a product line closure involving 89 of the plant's 885
employees. The employment loss-to-population ratio is 0.51 percent, slightly above the
threshold of 0.44 percent. Some of the workers may be retained to produce other
products at this plant. However, there are no large urban areas nearby. Thus, if at
least some of the plant's OCPSF workers are not absorbed by other product lines, this
community may experience significant impacts.
Under PSES IVB, 21 plants and 25 product line closures in 46 communities are
projected. Six of these communities have employment loss-to-population ratios greater
than the 0.44 percent criterion.: Due to locational factors, four of these are not
expected to experience significant impacts. The remaining two communities are those
described in the PSES IVA discussion. As noted there, one is expected to sustain a
significant impact, and the other is a borderline case.
6-13
-------
These two communities remain significantly and marginally affected under
PSES VII, as well. This option is projected to result in 23 plant and 25 product line
closures, involving 45 communities. Seven have employment loss-to-population ratios in
excess of 0.44 percent. Five of these communities are located close to urban industrial
areas where displaced workers are likely to find employment.
6.5 Small Business. Impacts
The Regulatory Flexibility Act (RFA) of 1980 (P.L. 96-354), which amends the
Administrative Procedures Act, requires Federal regulatory agencies to consider "small
entities" :hroughout the regulatory process. The RFA requires that an initial screening
analysis be performed to determine if a substantial number of small entities will be
significantly affected by a regulation. If so, regulatory alternatives that eliminate or
mitigate the impacts must be considered.
The results of the preliminary analyses suggest that there may be significant
and disproportionate adverse impacts on small plants. Therefore, a detailed analysis
which considers possible regulatory alternatives has been conducted. The results of this
analysis are presented in a separate report entitled "Regulatory Flexibility Analysis for
Effluent Guidelines for the OCPSF Industry."
6.6 Foreign Trade Impacts
This analysis addresses both the potential production loss of trade sensitive
chemicals which could result from the plant and product line closures predicted in the
closure analysis and the resultant impacts on the balance of trade for the U.S. chemical
industry. Since there were no closures under BPT, BAT estimates represent both
incremental and cumulative impacts.
Trade sensitive chemicals have been identified using DRI data by eight-digit
SIC for the major chemical groups in which plant and product line closures were
predicted, including thermoplastic resins and plastics materials (28213007),
thermosetting resins and plastics materials (28214005), synthetic fibers (28243, acrylic
fiber), cyclic (coal .tar) intermediates (28651008), and miscellaneous cyclic and acyclic
chemicals (28697001). DRI trade data also include synthetic ethanol production data;
however, while ethanol is seen to be trade sensitive, none of the projected plant or
product line closures manufacture ethanol. The criteria used to indicate sensitivity are
discussed in the methodology, and are listed again in Table 6-6.
Production losses by eight-digit SIC and by option are shown in Table 6-7. The
table also indicates the chemical product groups included in the DRI listing of trade
6-14
-------
Table 6-6
FOREIGN TRADE SENSITIVE CHEMICALS IN SIC CATEGORIES COVERED BY [XI
CHEMICAL
CRITERIA
INDICATING
SENSITIVITY*
Product SIC
Name
1
2
3
Thermoplastics 28213007
LDPE
X
PV Alcohol
X
X
SAN
X
X
Nylon Resins
X
X
Polypropy1ene
X
Polycarbonate
X
X
Thermosets 28214005
Polyurethane, Non-Foam
X
Epoxy Resin
X
Urea and Mel Form Resin
X
Acrylic Fiber 28243319, 335, 392
Acrylic Fiber
X
X
Cyclic Intermediates 28651008
Cumene
X
X
Bisphenol A
X
TDI
X
X
Styrene
X
X
P-Xylene
X
X
Terephthallc Acid
X
X
O-Xylene
X
X
Ethanol, Denatured
Synthetic 2869521
Ethanol, Synthetic
X
X
Miscellaneous Cyclic 28697001
Methanol
X
X
and Acyllc Chemicals
Propanol
X
X
Propylene Glycol
X
Ethylene Glycol
X
X
X
VCM
X
VAM
X
X
Propylene Oxide
X
Butyl Aery late
X
Ethyl Aery late
X
X
Aery Ion 1tr1le
X
MEK
X
X
*Cr1terla:
1. Either exports or Imports are more than ten
percent of 1988 production.
2. The sum of the export and Import percentages
Is greater than 15 percent of
1988 production.
3. The level of net exports (I.e., exports less
Imports) as a percentage of production declines
by over ten percentage
points between 1984 to 1988.
-------
LE 6-7
PRODUCTION OF LOSS DUE TO PLANT AND PRODUCT LINE CUJSURES
(Thousands of Tons)
PRODUCT
SIC
BPT I
BAT IIA
BAT IIB
PSES IVA
PSES IIB
PSES VII
*+THERMOPLASTICS
28213007
0.0
31.79
0.87
183.55
115.36
115.36
*+THERMOSETS
28214005
0.0
12.91
12.91
59.87
12.48
12.47
*+CYCLIC COAL TAR INTERMEDIATES
28651008
0.0
45.98
43.14
90.68
38.64
38.94
*+MISCELLANEXXJS CYCLIC AND
ACYCLIC CHEMICALS
28697001
0.0
149.2
92.32
299.64
246.00
226.HI
CYCLIC COAL TAR CRUDES
28655009
0.0
57.30
57.30
69.28
0.0
0.0
CYCLIC DYES
28652006
0.0
1.38
1.38
12.36
1.12
0.80
SYNTHETIC ORGANIC PIGMENTS,
LAKES TONERS
28693004
0.0
0.003
.003
1.43
1.43
1.43
PESTICIDES & OWIER SYNTHETIC
ORGANIC AGENTS
28694008
0.0
6.08
5.80
5.60
0.0
15.32
MISCELLANEOUS END USE CHEMICALS
28696003
0.0
50.48
49.73
8.96
7.60
8.80
RUBBER PROCESSING CHEMICALS
28693315
0.0
0.67
0.0
15.72
0.96
.96
PLASTICISERS
28693515
0.0
0.0
0.0
0.0
0.0
0.0
CHEMICALS USED AS FLAVOR MATERIAL
28693133
0.0
0.0
0.0
7.72
7.72
7.72
OTHER INDIVIDUAL CHEMICALS N.E.C.
28695989
0.0
2.24
2.24
19.32
9.80
9.80
NATURAL ORGANIC CHEMICALS N.E.C.
28695534
0.0
0.05
0.05
0.16
0.16
0.16
NON-CELLULOSIC TEXTURED FIBERS
(POLYOLEFIN)
28246627
0.0
16.82
16.82
0.0
0.0
0.0
TOTAL OCPSF PRODUCTION LOSS
PERCENT PRODUCTION LOSS IN SIC's COVERED BY DRI
EXPORT/IMPORT PROJECTIONS
100%
374.9
64%
•
282.56
53%
774.32
82%
421.16
98%
438.48
90%
*SIC's covered by DRI.
+These product groups contain trade-sensitive chemicals, based on DRI export and import data.
.Source: Basec) on 1982 Production data from S30H database.
-------
sensitive chemicals. As can be noted, not all production loss is expected to occur in
trade sensitive chemicals. Approximately 50 percent of the production loss projected
for direct dischargers and almost all of the production loss for indirect dischargers is
expected to fail into the trade sensitive product groups covered by DRI. To the extent
that production loss for direct dischargers occurs in a chemical group not identified as
trade sensitive which actually is trade sensitive, the accompanying analysis could
*
slightly understate trade impacts.
Table 6-8 shows the percent of production in trade sensitive' chemicals
compared to overall production in the eight-digit SIC covered by the analysis. This
percentage ranges from a low of 34 percent for thermosets to a high of 57 percent for
miscellaneous cyclic and acyclic chemicals.
Table 6-9 applies the percentages of trade sensitive chemicals to overall
production from Table 6-8 to the potential production loss associated with the OCPSF
regulation. The two right hand columns present the predicted export loss and the
percent that export loss represents of overall projected exports for 1988. As can be
noted, the greatest percentage impact occurs with thermosets where as much as a 10
percent loss in exports could occur; however, this percent relates to an overall small
base of 43,000 tons and an overall dollar value (assuming $700 per ton) of about $3.1
million. The greatest quantity impact occurs with miscellaneous cyclic and acyclic
chemicals where 140,000 tons of exports could be affected. The dollar value of this
chemical group (assuming $360 per ton) is approximately $50 million.
Balance of Trade Effects
The total dollar impact of the regulatory options on the trade balance was
estimated using 1988 DRI estimates of average chemical prices corresponding to the
SIC codes covered by the OCPSF regulation as follows:
SIC 2821 $700 per ton
SIC 2865 480 per ton
SIC 2869 360 per ton
$
Appendix 6B includes a table showing the percentage of production lost due
to closures for product groups not covered by DRI. Even if one assumes that the entire
production loss in an eight-digit SIC is trade sensitive, the percentages of production
lost for direct dischargers are consistently less than 1.5 percent.
& Ik
DRI estimates of average price per ton in respective SIC code.
6-17
-------
.^BLE 6-8
Trade Sensitive Chemicals As A Percent of Total Production
PRODUCTS
SIC
TOTAL
PRODUCTION
(1000 TONS)
TOTAL PRODUCTION
OF TRADE SENSITIVE
CHEMICALS (1000 TONS)
Trade Sensitive Chemical
Production As a Percent
of Total Production
THERMOPLASTICS
RPT I
BAT IIA
BAT I IB
PSES IVA
PSES IVB
PSES VII
THERMOSETS
BPT I
BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
28213007
28214005
15,525
15,525
15,524
15,524
15,524
15,524
2,273
2,273
2,273
2,273
2,273
2,273
5,831
5,831
5,831
5,831
5,831
5,831
771
771
771
771
771
771
37.6%
33.9%
CYCLIC INTERMEDIATES
BPT I
BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
28651008
15,539
15,539
15,539
15,539
15,539
15,539
7,734
7,734
7,734
7,734
7,734
7,734
49.8%
MISC. CYCLIC AND
ACYCLIC CHEMICALS
BPT I
BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
28697001
23,413
23,413
23,413
23,413
23,413
23,413
13,296
13,296
13,296
13,296
13,296
13,296
56.8%
Source: Based on §308 production figures at the plant level and PRI information for the industry (NOTE: DRI
does not cover 100% of production in these SIC groups, leading to worst case results. Approximate
percentages covered are: Plastics & Resins, 93%; Cyclifc Intermediates, 83%; Miscellaneous Cyclic and
Acyclics, 58%).
-------
TABLE 6-9
FOREIGN TRADE IMPACfS DUE TO PLANT AND PRODUCT LINE CLOSURES
1988 BASELINE
(a)
(b)
Production loss in Trade Sensi-
Loss in Trade
PRODUCTION
Ratio of Trade Sensitive
tive Chemicals = col iron (a) x
Sensitive Chemicals
EXPORT
LOSS
Chemicals to Total
column (b).
As A Percent of
SIC
(1000 Tons)
(1000 Tons)
Production
(1000 TONS)
Exports
BPT OPTION 1
28213007
897
0.0
.376
28214005
43
0.0
.339
N/A
N/A
28651008
1625
0.0
.498
28697001
1855
0.0
.568
RAT OPTION IIA
28213007
897
31.8
.376
12.0
1.3
28214005
43
12.9
.339
4.4
10.2
28651008
1625
46.0
.498
22.9
1.4
28697001
1855
149.2
.568
84.7
4.6
BAT OPTION IIB
28213007
897
0.9
.376
0.3
0.03
28214005
43
12.9
.339
4.4
10.2
28651008
1625
43.1
.498
21.5
1.3
28697001
1855
92.3
.568
52.4
2.8
PSES OPTION IVA
28213007
897
183.6
.376
69.0
7.7
28214005
43
59.9
.339
20.3
47.2
28651008
1625
90.7
.498
45.2
2.8
28697001
1855
299.6
.568
170.2
9.2
PSES OPTION IVB, VII
28213007
897
115.4
.376
43.4
4.B
28214005
43
12.5
.339
4.2
9.8
28651008
1625
38.6
.498
19.2
1.2
28697001
1855
246.0
.568
139.7
8.0
Source: DRI Export Data (1988)
-------
The results are presented in Table 6-LO. As can be noted, the total dollar
trade impact does not exceed $150 million, even under the most stringent option
considered. Given that net exports for the chemical industry in 1986 were
approximately $10 billion (Survey of Current Business), the trade balance effect is very
small at 1.5 percent. When compared with the total U.S. 1986 merchandise export
trade of about $225 billion, the impact is negligible at 0.07 percent.
To summarize foreign trade impacts:
• The production lost as a result of plant and product Line closures in
any SIC is a small percent of total production in that SIC, and of
production of trade sensitive chemicals only.
• Thermosets are the most significantly affected of the four major
SIC groups covered by DRI in terms of percent loss in exports of
trade sensitive chemicals. However, the greatest quantity
production loss occurs in miscellaneous cyclic and acyclic
chemicals.
• The total effect on the U.S. trade balance is predicted to be very
small — approximately 0.07 percent.
6.7 New Sources Analysis
The purpose of the New Sources Analysis, as described in the Methodology,
Chapter 3.0, is to estimate the impact of the proposed regulation on the entry of new
sources, i.e., new plants, into the OCPSF industry. The analysis has two components:
* Estimation of the percentage increase in the total cost of con-
structing and equipping a new plant as the result of the need to
comply with effluent guidelines.
* Use of a net present value analysis to assess the impact of compli-
ance costs on the prof itability of the investment and, hence, on the
likelihood that new plants will be built in the U.5.
The costs of constructing "typical" plants by size and SIC were estimated using
data published in the Box Score section of Hydrocarbon Processing and in Chemical
Engineering.* These estimated construction costs were assigned to actual plants in the
Hydrocarbon Processing, Boxscore Section, June 1986, p. 3-8; October 1986,
p. 3-7; Chemical Engineering, April 15, 1985, p. 77ff; March 19, 1984, p. 16lff;
November'10, 1986, p. 109ff.
6-20
-------
TABLE 6-10
DOLLAR LOSS IN EXPORTS DUE TO PLANT AND PRODUCT LINE CLOSURES
(S millions)
1988
SIC
PRODUCT GROUP
BPT I BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
28213007 Thermoplastics
0.0
8.4
0.2
48.3
30.4
30.4
28214005
28651008
28697001
TOTAL LOSS
Thermosets
Cyclic
Intermediates
Misc. Cyclic and
Acyclic Chemicals
0
0.0
0.0
0.0
3.1
11.0
30.5
53.0
3.1
10.3
18.9
32.5
14.2
21.7
61.3
145.5
2.9
9.2
50.3
92.8
2.9
9.2
50.3
92.8
-------
Section 308 database with characteristics similar to those described as new plants under
construction (or in the design/engineering phase), i.e., based on capacity and SIC code.
Construction cost estimates were not available for some size and SIC combinations;
hence, the analysis uses only a subset of existing dischargers. The costs to comply with
the regulations are based on the actual treatment cost estimates for these plants and
assumes that new direct and Indirect dischargers will need to comply with limitations
equivalent to those which apply to existing dischargers.
As described in the methodology and baseline sections, foreign capacity
(particularly developing country capacity) will continue to expand more rapidly than
domestic capacity. The number of new plants being built in this country is relatively
small. Much of the added capacity stems from debottlenecking and renovation of
existing facilities. Smaller, high value-added plastics plants (e.g., engineering plastics)
are among those likely to be built over the analysis period. Unfortunately, there is a
scarcity of data on the costs of constructing new plants. No data were available for
small plants in SIC 2865 (cyclic intermediates) and SIC 2869 (miscellaneous cyclic and
acyclic chemicals), or tor SIC 2823 (synthetic fibers). Costs of construction also tend
to vary rather widely within an SIC and size category. The results presented below
should, therefore, be treated as approximations of impact only.
6.7.1 Increase in Plant Construction Costs
Projected treatment capital costs under the proposed regulation represent a
small portion of the total costs of constructing new plants, small or large. The
percentages are in the range of 1 percent for all options, with standard deviations of
to 12 percent for small plants (for which only SIC 2821 cost data were available). For
medium to large plants, capital compliance costs are estimated to comprise about 0.5
to 2.7 percent of total construction costs with standard deviations of 0.2 to 2 percent
depending on the option. (See Table 6-11.) The percent of total capital investment
represented by treatment capital costs does not vary widely for direct or indirect
dischargers. The increase in plant construction costs would apparently be potentially
most severe for small SIC 2821 plants, for which the standard deviation is sizeable.
Thus, for some small plants, treatmerrtcapitalcostscouid.be in the range of 13 percent
of construction costs. It should be noted that this may be a worst case evaluation, as
the capital compliance costs should be less for new plants than for existing plants
requiring retrofits. (See discussion of other limitations in Chapter S.)
6-22
-------
Table 6-11
COMPLIANCE CAPITAL INVESTMENT COSTS AS A PERCENTAGE Of TOTAL COST OF CONS I RUCTION
OF A "TYPICAL" NEW PLANT
PLANT SIZE
SMALL
MEDIUM-LARGE
SIC/OPTION
PERCENT
S.D.
SAMPLE SIZE
PERCENT
S.D.
SAMPLE SIZE
282|
BPTI
0.72
4.02
7
0.5*
0.5*
16
BAT 1IA
0.7}
4.92
7
1.32
1.2*
17
BATIIB
0.7*
5. 12
7
1.2*
1.2*
1 7
PSESIVA
1.0*
11.72
29
0.82
1.3*
25
PSESIVB
0.32
6.92
29
0.7*
0.8*
25
PSESVI1
0.32
11.52
29
0.7*
1.2*
25
2665
BPTI
0.42
0.4*
11
BAT| IA
1.2*
0.8*
14
BATIIB
NO
INFORMATION
1.12
0.7*
14
PSESIVA
0.72
0.2*
3
PSESIVB
0.72
0.3*
3
PSESVI1
0.7*
0.3*
3
2869
BPTI
1.5*
1 .6*
13
BATI1A
2.7*
1.92
18
BATIIB
NO
INFORMATION
2.31
1.9*
18
PSESIVA
1.7*
1 .9*
21
PSESIVB
1 .3*
1 .8*
21
PSESVII
1.7*
1.9*
21
NOTE: PI ant s coaled under I he different options represent different subsets ol plants in
scope. Plonl s i it: is based on est imated production capacity. (See text of Suction J.)
S.D. equals standard deviation. "Percent" equals Total Capital and Land Compliance- Costs/
Estimated Cosls of Construction. Estimated construct ion'costs are based on i n form.it ion
pub Ii shed in Hydrocarbon Processing and Chemical engineering.
-------
6.7.2 Net Present Value of Cash Flow
The baseline cash flow of newly constructed plants over the lifetime of the
investment (20 years) was calculated in a manner similar to that used for the plant
closure analysis. The real weighted average cost of capital and a hurdle rate two
percentage points higher were used as discount rates. Under post-baseline conditions,
projected compliance costs of capital (capital and land costs) were added to the initial
investment, and compliance operating costs (times one minus the tax rate) were
subtracted from annual profits (see Chapter 3 for further detail.) Again, the
compliance costs are those projected for existing dischargers. As in the previous
analysis, only that subset of plants having characteristics similar to those of announced
new plants with cost estimates are included in the analysis.
The analysis examined the net present value of cash flow, and the net present
value as a percent of initial investment (Profitability Index) under baseline and post-
baseline conditions for the "typical" plants in SIC 2821, 2865 and 2869 for option BPT
I. The calculations were performed using the weighted average cost of capital and a 2
percentage higher "hurdle rate1*. Recall that a net present value (NPV) greater than
zero indicates that the investment will exceed the required rate of return on the
investment. The Profitability Index (NPV/Investment) is typically a means of ranking
non-interdependent, non-mutually exclusive investments in a capital budgeting process,
since it normalizes for the size of the investment. Tables illustrating the results for
regulatory options BAT IIA, BAT IIB, and PSES IVA, IVB, and VII are contained in
Appendix 6C. The findings are summarized below.
In general, addition of compliance capital costs to the initial investment
changes the profitability index modestly within a size and SIC category, even for plants
in the upper quartile of net present value for the projected investment. However, most
median values are negative to begin with, suggesting that rational managers would not
*
construct new plants under the existing industry profitability conditions, unless above
average profits are anticipated. Although these estimations are rough, they do
approximate what is happening in the industry—i.e., relatively fewnew plants are being
constructed, and those are more frequently in higher value added, polymers or resins,
etc.
*The cash flow for these projected investments is based on the projected 19SS
profits of existing Section 308 plants.
6-24
-------
The small plants in SIC 2321 (plastics) begin with a low net present value and
are affected most significantly in this analysis. However, the Profitability Index is still
in a similar range for these plants as for the larger plants. Overall, not unexpectedly,
the impacts are slightly more severe under the PSES options than under BPT I or BAT
IIA or BAT 11B. As mentioned, the compliance costs do cause a substantial decrease in
net present value; however, the choice of discount rate (WACC vs. WACC +¦ 2%) has a
greater influence on the net present value than the compliance costs in many cases.
Using the WACC, under baseline conditions, rational managers/executives
might construct new medium to large plants in SIC 282L, 2865, and 2S69 if they
expected higher than average profits, under all options evaluated. (The upper quartiies
for NPV for these categories are positive). The small SIC 2821 plants have negative
Net Present Values for ail quartiies, but the upper quartiie plants are close to zero,
suggesting that anticipated upper quartiie plants might still be built. If firms require a
rate of return higher than the weighted average cost of capital (e.g. 2 percent higher)
then fewer new plants would be constructed. The net present values change by 100
percent or more in some instances in moving from use of WACC to a hurdle rate 2
percentage points higher. (See Chapter 8.0 for discussion of limitations of this
analysis.)
With respect to differences by regulatory option, relatively small differences
in the magnitude of net present value change due to compliance costs are observed by
option. SIC 2821 and SIC 2865 plants appear to be slightly more severely affected
overall under PSES options than BPT or BAT, with PSES IVA being the most severe.
BPT I results in a relatively modest change in profitability index for ail plant sizes and
SICs examined. Costs associated with this option would most likely not alter
investment decisions.*
In summary, capital costs of compliance for the proposed regulation do not
appear to present a tremendous barrier to the entry of new plants into the industry,
except perhaps, in the case of some small plants/firms. It is possible, however, that the
Note: Comparison across options is complicated by the fact that different
plants are costed under different options. Thus, the quartiie values for NPV across
options varies under baseline conditions in this analysis. Thus, the magnitude of the
change in profitability index for a given median or quartiie value going from baseline to
post-compliance under any option was used to judge the severity of the effect of
compliance costs.
6-25
-------
change in profitability index due to compliance costs would be sufficient to shunt some
potential new plant construction into more profitable areas, especially if a return
greater than the cost of capital is required (which is increasingly likely in today's
environment) and if PSES regulatory option(s) are implemented. Although the above
analysis is based on projected 1988 sales and, therefore, theoretically accounts for
market factors, the rational firm financial planner would look at other analyses as
well: for instance, foreign trade, market restructuring, and the possible decrease in
price of a product due to construction of a plant producing that product. It is, in fact,
highly likely that much of the new plant construction by U.S. firms will be based in
foreign countries, as discussed in a previous chapter of this report, and that foreign
competition will be a major barrier to entry in the U.S.
6.3 National Social Costs
As described in Chapter 3, the total cost of the regulations to society differs
somewhat from the compliance costs borne by private firms. For example, tax
deductions which defray the firms' cost represent a shift in cost from the private sector
to the government. In addition, while the economic impact analysis uses a plant or
firm's weighted average cost of capital, the social cost analysis uses a discount rate
that reflects the cost of capital to the government, i.e., the yield on long-term
government securities. Finally, in addition to the direct costs of compliance, there are
indirect costs borne by other sectors of the economy, e.g., job search by laid-off
workers.
The total social costs of the regulations fall into three areas:
• Real Resource Costs: compliance expenditures
• Dead Weight Welfare Loss: changes in consumer and producer
surplus resulting from production decreases
• Worker Adjustment Costs: wages lost by laid-off workers during
job search.
These costs are summed to arrive at an estimate of national social cost.
Table 6-12 shows each cost component, as well as the total social cost for
selected options. The real resource cost, i.e., the capital investment and operating and
maintenance costs, is the major cost component. Note that these resource cost
estimates reflect costs associated with non-closures only, since closures will not incur
treatment costs. They do, however, result in other social costs, including a dead weight
6-26
-------
Tat) It 6-12
TOTAL SOCIAL COST
(1982 Mi I I ion Dol lars)
REGULATORY OPTION
BPI I BAI IIA BAT I IB PSES IVA PStS IVB HSES VII
Real Resource Cost
Dead Weight (_oss
Worker Adjustment
Toldl National Social Cost
58.42
-0.05
0.08
58.45
275.80
-0.71
12.31
287.37
213.26
223.36
172.85
-4.07
22.38
191.16
105.67
-I .66
1 I .46
115.47
1 14.83
-I .79
14.08
127.12
-------
toss and worker adjustment costs. The dead weight loss, which is estimated as lost
economic profits'due to closures, is generally negative. This results from the fact that
closure plants tend to be earning profits at margins which are below the industry
average. Worker adjustment costs are small relative to the total social costs, generally
representing two to three percent of the total.
6-28
-------
Appendix 6A
SUMMARY OF PLANT LEVEL COSTS AND IMPACTS USED
FOR DETAILED ANALYSES
As discussed in Section 6.2, some minor changes to the treatment estimates
were not incorporated in the detailed impact analyses of Sections 6.3 to 6.7. The costs
and impacts used in these sections are shown in Tables 6A-1 and 6A-2 for direct and
indirect dischargers, respectively.
6A-1
-------
Table 6A-1
SlfMARY OF CUMULATIVE RESULTS: DIRECT DISCHARGERS
(1962 Ml II Ian
Dollars)
BAT casts
and lapacts are
Incr eaental
to BPT 1
REGULATORY
' OPTION
BPT 1
1 BAT l«
BAT IIA
BAT 1 IB
BAT V«
NUMBER OF PLANTS ANALYZED
209
286
286
286
286
NUMBER OF PLANTS INCURRING COSTS
224
292
292
292
292
COSTS OF COMPLIANCE
CAPITAL INVESTMENT
203.19
365.81
533.81
523. 19
1,304.01
OPERATING AND MAINTENANCE
41.50
156.73
270.57
197.34
619.47
TOTAL ANNUAL COMPLIANCE COST
72.18
212.05
351.19
276. 30
816.22
PLANT CLOSURES
0
8
12
II
26
PRODUCT LINE CLOSURES
2
10
12
9
16
PROFIT OR SALES IMPACTS"
11
13
23
19
47
EMPLOYMENT REDUCTION
12
1,335
1,743
1,359
6,475
'Impacts are based cm cost from the December 1986 Notice of Availability.
••Non-closures only.
-------
Table 6A-2
SIM4ARY Of RESULTS: IIOIRECT DISCHARGERS
(1982 Ml 11 ion Dollars)
PSES IVA
REGULATORY OPTION
PSES IVB
PSES VII
NUMBER OF PLANTS ANALYZED
362
362
362
NUMBER OF PLANTS INCURRING COSTS
365
365
365
COSTS OF COMPLIANCE
CAPITAL INVESTMENT
318
.51
260.56
319.20
OPERATING AND MAINTENANCE
256
.47
136,21
145.87
TOTAL ANNUAL COMPLIANCE COST
305
.41
176.08
194.67
PLANT CLOSURES
33
21
23
PRODUCT LINE CLOSURES
28
25
25
PROFIT OR SALES IMPACTS*
87
62
65
EMPLOYMENT REDUCTION
3.
169
1,623
1,994
*Non-c losures only.
-------
Appendix 6B
FOREIGN TRADE IMPACTS FOR CHEMICAL GROUPS
NOT COVERED BY DRI
As discussed in Section 6.6, some of the OCPSF chemical groups are not
covered by DRI. Table 6B-1 shows the percent of total production lost due to plant and
product line closures using total production from the U.S. ITC, Synthetic Organic
Chemicals: U.S. Production and Sales. The results indicate that the percent of total
production lost due to closures is quite small with the exception of cyclic dyes and
rubber processing under PSES IVA. The greatest loss is seen for rubber processing
chemicals — 13.6 percent under PSES IVA.
6B-1
-------
TABLE 6B-1
PERCENT OF TOTAL PRODUCTION LOST IN CHEMICAL GROUPS
NOT COVERED BY DRI IMPORT/EXPORT PROJECTIONS
Chemical
Group
Total
Production
(1000 tons)
Lost
Production
(1000- tons)
Percent o£ Production
Lost IXie to Closures
CYCLIC COAL TAR
CRUDES
CYCLIC DYES
BPT I
BAT II-A
BAT II—B
PSES IV-A
PSES IV-B
PSES VII
not available
111.0
0.00
1.38
1.38
12.36
1.12
0.80
0.00
1.24
1.24-
11.14
1.01
0.72
PIGMENTS, LAKES,
TONERS
35.5
BPT I
BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
0
0.01
0.01
1.43
1.43
1.43
0
0.03
0.03
4.03
4.03
4.03
PESTICIDES AND OTHER not
SYNTHETIC ORGANIC available
AGENTS
MISCELLANEOUS END*
5140.5
USE CHEMICALS
BPT I
BAT II-A
BAT II-B
PSES IV-A
PSES IV-B
PSES VII
RUBBER PROCESSING
CHEMICALS
BPT I
BAT II-A
BAT II-B
PSES IV-A
PSES IV-B
PSES VII
116.0
0.00
50.48
49.73
8.96
7.60
8.80
0.00
0.67
0.00
15.72
0.96
0.96
0.00
0.98
0.97
0.17
0.17
0.17
0.00
0.58
0.00
13.55
0.83
0.83
6B-2
-------
- 2 -
FLAVOR AND PERFUME
CHEMICALS
bpt r
BAT IIA
BAT IIB
PSES IVA
PSES IVB
PSES VII
0.00
0.00
0.00
7.72
7.72
7.72
0.00
0.00
0.00
9.9
9.9
9.9
Other Individual
Chenicals N.E.C.
Natural Organic
Chemicals N.E.C
Non-Cellulosic
Textured Fibers
not available
not available
not available
SOURCE: ITC, Synthetic Organic Chemicals; U.S. Production and Sales.
*1981 data (1982 figure for miscellaneous end use chemicals apparently
contains a reporting error).
6B-3
-------
Appendix 6C
DETAILED TABLES FOR NEW SOURCES ANALYSIS
Tables 6C-1 and 6C-2 show the net present value of cash flow, and the net
present value as a percent of initial investment (Profitability Index) under baseline and
post-baseline conditions for the "typical" plants in SIC 2S21, 2865 and 2S69 for option
BPTI. The calculations have been performed using the weighted average cost of capital
(Table 6C-1) and a 2 percentage higher "hurdle rate" (Table 6C-2). Recall that a net
present value (NPV) greater than zero indicates that the investment will exceed the
required rate of return on the investment. The Profitability Index (NPV/Investment) is
typically a means of ranking non-interdependent, non-mutually exclusive investments in
a capital budgeting process, since it normalizes for the size of the investment. Tables
6C-3 through 6C-L2 illustrate the results for regulatory options BAT IIA, BAT TIB, and
PSES IVA, IVB, and VII.
6C-1
-------
Table 6C-I
DECREASE IN NPV AND NPV/INVESTMENT DUE TO COMPLIANCE COS1S
BPT I
USING WACC
BASELINE
POST-BASELINE
SIp/OPTION
NPV
(ml|I Ions I)
PROFITABILITY
INDEX
NPV
(mill ions)
PROFITABILITY
INDEX
PERCENT CHANGE
IN NPV
SIC 2821 (N=7)
S^ALL
LQ
Median
"9
MEP-LG (N-16)
LQ
Median
UO
-2.6
-2.4
-0.2
-13.2
-6.1
5.5
-0.26
-0.24
-0.02
-0.16
-0.07
~0.07
-2.8
-2.7
-0.5
-14.3
-6.6
4.2
-0.28
-0.27
-0.05
-0.17
-0.08
~.05
N/A
N/A
N/A
N/A
N/A
-23.6
SIC 2865 (N-lI)
mep-lg
LQ
Median
UQ
SIC 2869 (N=13)
HfD-LG
LQ
Medi an
UQ
3.6
8.2
42.3
-4.6
-0.8
5.6
~0.02
~ 0.06
• 0.28
-0.09
-0.02
0. I I
2.1
7.9
39. I
-6.7
-2.2
4.4
~ 0.01
~ 0.05
~0.26
-0. 13
~0.04
~0.09
-41.7
-3.7
-7.6
N/A
N/A
-21.4
-------
Table 6C-2
DECREASE IN NPV AND NPV/INVESTMENT DUt TO COt*n,IANCE COS IS
BPT I
USING HURDLE = WACC t 2}
SIC/OPTION
NPV
(mill ions J)
BASELINE
POST-BASELINE
PROFITABILITY
INDEX
NPV
(ml I I Ions)
PROFITABILITY
INDEX
PERCENT CHANGE
IN NPV
SIC 2821 (N-7)
SMALL
LQ
Med I an
UQ
-3.2
-3.1
-1 .0
-0.32
-0.31
-0.10
-3.5
-3.3
-1.4
-0.35
-0.33
-0.14
N/A
N/A
N/A
cr>
n
i
u>
MEU-LG (N=16)
LQ
Medi an
LKJ
-19.7
-13.5
-3.5
-0.23
-0.16
-0.04
-20.8
-14.0
-4.7
-0.24
-0. 16
-0.06
N/A
N/A
N/A
SIC 2865 (N=11)
MEQ-LG
LO
Med i an
UQ
-II .5
-7.5
~ 22.1
-0.08
-0.05
~0. 14
-12.9
-7.8
19.1
-0.09
-0.05
~0. 13
N/A
N/A
-13.6
SIC 2869 (N-13)
HEP-IC
LO
Median
UQ
-8.9
-5.5
0.0
-0.18
-0. I I
0.00
-10.7
-7.0
-1 .2
-0.21
-0. 14
-0.0?
N/A
N/A
NMF
-------
Table 6C-3
DECREASE IN NPV AND NHV/INVES1MENT IXJt TO COMPLIANCE COSTS
BAT I IA
USING WACC
BASEL INE
POST-BASELINE
SIC/OPTION
NPV
(mi I I Ions S)
PROFITABILITY
INDEX
NPV
(mi I I ions)
PROF ITABILITY
INDEX
PERCENT CHANGE
IN NPV
SIC 2821 (N= 7)
SMALL
LP
Med i an
U9
HtP-LG (N=17)
LQ
Median
U9
-2.6
-2.4
-0.2
-13.1
-6.7
1.9
-0.26
-0.24
-0.02
-0.15
-0.08
~0.05
-5.0
-2.9
-I.I
-15.1
-9.3
I . 1
-0.50
-0.29
-0.11
-0. IB
-0.)|
~0.01
N/A
N/A
N/A
N/A
N/A
-71 .8
SIC 2865 (N=14)
HEP-LG
LQ
Med I an
UQ
-0.6
10.9
60.7
-0.00
0.07
0.41
-21 .6
7.2
51.5
-0.14
~0.05
~0.34
N/A
-35.9
-15.2
SIC 2869 tN—10)
MED-LG
LQ
Medi dn
U(?
-6.2
-I .4
3.6
rO. 12
-0.03
~ 0.07
-8.4
-5.5
~0.1
-0.17
-0.11
0.0
N/A
N/A
¦II .2
-------
Table 6C-4
DECREASE IN NPV AND NPV/INVESTMENT DUE TO COMPLIANCE COS1S
BAT IIA
USING HURDLE = MACC * 2*
BASELINE POST-BASELINE
NPV PROFITABILITY NPV PROFITABILITY PERCENT CHANGE
SIC/OPTION (ml I I ions t) INDEX (mi I I ions) INDEX IN NPV
SIC 2821
SMALL
LQ -3.2 -0.32 -5.5 -0.55 N/A
Median -3.1 -0.31 -3.6 -0.36 N/A
LK) -I.I -0.11 -2.0 -0.20 N/A
MEp-LG (N=I 7)
cn
O LQ -19.6 -0.23 -21.6 -0.25 N/A
ui MedI an -14.1 -0.16 -16.5 -0.19 N/A
UQ -4.9 -0.06 -7.5- -0.09 N/A
SIC 2865
-------
Table 6C-5
DECREASE IN NPV AND NPV/INVESTMENT DUE TO COMPLIANCE COSTS
BAT I IB
USING WACC
SIC/OPTIO^
NPV
(nl 11 ions })
BASELINE
POST-BASELINE
PROF IIABILITT
INDEX
NPV
(mi I I ions)
PROF ITABILITY
INDEX
PERCENT CHANGE
IN NPV
SIC 2921 (N-7)
S^ALL
L Q
Median
UQ
-2.6
-2.4
-0.2
-0.26
-0.24
-0.02
-5.3
-2.9
-I.I
-0.53
-0.29
-0.11
N/A
N/A
N/A
cr>
0
1
HED-LG (N-1 7)
Lg
Medi an
MO
-13.1
-6.7
3.9
-0.15
-0.08
~ 0.05
15.1
-6.9
I . I
-0. IB
-o.pa
~0.01
N/A
N/A
-71 .8
SIC 2865 (N=14)
MED-LG
Medi an
UQ
-0.6
10.9
60.7
0.00
0.07
0.41
-6.4
7.2
54.7
-0.04
~0.05
~0.37
N/A
-33.9
-9.9
SIC 2869 (N=18)
MED-LG
LO
Medi an
UQ
-6.2
-1.4
3.6
-0.12
-0.03
0.07
-7.9
-3.9
~ 0.3
-0. 16
-O.OB
0.0
N/A
N/A
-91.7
-------
Table 6C-6
DECREASE IN NPV AND NPV/INVES1HENT DUE TO COMPLIANCE COSTS
BAT lib
USING HURDLE - WACC * 2*
BASELINE
POST-BASEL INE
SIC/OPTION
NPV
(mill ions i)
PROF I TAB ILITY
INDEX
NPV
(mi I I Ions)
PROF I TAB ILITY
INDEX
PERCENT CHANGE
IN NPV
SIC 282I (N-7)
SHALL
L9
Madi an
u9
MEP-LG (N-I7>
(-
-------
Table 6C-7
DECREASE IN NPV AND NPV/INVESTMENT DUE TO COMPLIANCE COSIS
PSES IVA
USING WACC
SIC/OPTION
NPV
(mi|I Ions I)
BASEL INE
POST-BASELINE
PROFITABILITY
INDEX
NPV
(m i I I i on s)
PROFITABILITY
INDEX
PERCENT CHANGE
IN NPV
cr>
0
1
od
SIC 2621 (N-29)
SMALL
LQ
Med i an
MEP-LG (N-25)
LQ
Med Ian
ug
-2.2
-1.5
-0.1
14.3
-5.2
3.4
-0.22
-0. 15
-0.01
-0.17
-0.06
~0.04
-3.5
-2.5
-1.7
-20.0
-15.3
-2. I
-0.35
-0.25
-0. )7
-0.24
-o. ia
-0.03
N/A
N/A
N/A
N/A
N/A
-i6i .a
SIC 2865 (N=3)
MED-LG
L9
Medi an
ug
-18.4
29.0
83.4
0. 12
0. 19
0.56
-23.2
12.8
83. I
-0.16
~ 0.09
~0.55
N/A
-55.9
-0.4
SIC 2869 (N-21)
MED-LG
LQ
Medi an
IX?
-5.5
-2.4
5.9
-0. I I
-0.05
• 0.12
-9.5
-7.1
0.0
-0. 19
-0. 14
0.00
N/A
N/A
-KHJ.0
-------
Table 6C-8
DECREASE IN NPV AND NPV/INVESTMENI DUE 10 COMPLIANCE COSTS
PSES IVA
USING HURDLE .= MACC ~ 2%
SIC/OPTION
NPV
(ml I I Ions i)
BASEL INE
POST-BASELINE
PROF ITABILITY
INDEX
NPV
(mi I I ions)
PROF I TAB!LI TV
INDEX
PERCENT CHANGE
IN NPV
SIC 2821 (N-29)
SMALL
LQ
Mad i an
ug
-2.9
-2.3
-1.0
-0.29
-0.23
-0.10
-4.0
-3.3
-2.5
-0.40
-0.33
-0.25
N/A
N/A
N/A
-------
Table 6C-9
DECREASE IN NPV AND NPV/INVESTMENI OUt TO COMPLIANCE COSTS
PSES IVB
USING WACC
SIC/OPTION
NPV
(ml 11 Ions t)
BASELINE
POST-BASELIN£
PROFITABILITY
INDEX
NPV
(oil I I ions)
PROFITABILITY
INDEX
PERCENT CHANGE
IN NPV
CTi
0
1
SIC 2821 (N=29)
SMALL
lq
Median
UQ
MED-IG (N=25)
LQ
Median
U?
SIC 2$65 (N=3)
MED-LG
LQ
Med I an
HQ
SIC 2869 (N-21)
HED-LG
LQ
Med I an
UQ
-2.2
-I .5
-0.1
-M.3
-5.2
3.4
-t8.4
29.0
83.8
-5.5
-2.4
5.9
-0.22
-0.15
-0.01
-0. I 7
-0.06
*0.04
0.12
0.19
0.56
-0.11
-0.05
~ 0.12
-3.4
-2.4
-1.5
-17.3
-10.6
-0.4
-20.3
12.3
63.1
-7.3
-4.3
3.3
-0.34
-0.24
-0.15
-0.20
-0.13
0.00
-0.08
*0.14
*0.55
-0.15
-0.09
tO.07
N/A
N/A
N/A
N/A
N/A
¦111.8
N/A
-57.6
-O.B
N/A
N/A
N/A
-------
IdbIe 6C-10
DECREASE IN NPV AND NPV/INVESTMENT DUE TO COMPLIANCE COSTS
PSES IVB
USING HURDLE = MACC * 2%
BASELINE POST-BASELINE
NPV PROFITABILITY NPV PROFITABILITY PERCENT CHANGE
SIC/OPTION (nil I ions S) INDEX (mi I I ions) INDEX IN NPV
SIC 2621 (N=29)
SMALL
LQ -2.9 -0.29 -4.0 -0.40 N/A
Median -2.3 -0.23 -3.1 -0.31 N/A
UQ -1.0 -0.10 -2.3 -0.23 N/A
cn
V MEP-LG (N-25)
LQ -20.7 -0.24 -23.3 -0.2? N/A
Median -12.8 -0.15 -17.6 -0.2| N/A
UQ -5.3 -0.06 -8.7 -0.10 N/A
SIC 2665
-------
Table 6C-11
DECREASE IN NPV AND NPV/INVESTMENT DUE TO COMPLIANCE COSTS
PSES VI I
USING WACC
BASEL INE
POST-BASELINE
SIC/OPTION
NPV
(tni 11 Ions J)
PROFITABILITY
INDEX
NPV
(mi I I ions)
PROFITABILITY
INDEX
PERCENT CHANGE
IN NPV
SIC 2821 (N=29)
SMALl
LQ
Median
U9
MED-t-G (N-25)
LQ
Median
ug
SIC 2865 (N=3)
MED-lG
Lfl
Median
ug
SIC 2869 (N=2I)
MED-LG
LQ
Median
UQ
-2.2
-1.5
-O.I
-14-3
-5.2
3.4
- ie. 4
29.0
83.8
-5.4
-2.4
5.9
-0.2?
-0. 15
-0.01
-0. 17
-0.06
-0.02
0. 12
0. 19
0.56
-0. I I
-0.05
0. 12
-3.5
-2.6
-\.5
-17.3
-10.8
-0.6
-20.5
I I .9
82.8
-7.5
-4.6
3.3
-0.35
-0.26
-0.15
-0.20
-0.13
-0.01
-0.14
0.08
0.55
-0.15
-0.09
~ 0.07
N/A
N/A
N/A
N/A
N/A
-117.6
N/A
-t>y.o
-I .2
N/A
N/A
-44. I
-------
Table 6C-I2
PECREASE in npv and mpv/investment due to compliance COS1S
PSES VI I
USING HURDLE = NACC + 2|
BASELINE POST-BASELINE
NPV PROFITABILITY NPV PROFITABILITY PERCENT CHANGE
SIC/OPTI ON (ml I I ions %} INDEX (mi I I ions) INDEX IN NPV
SIC 2321 (N=29)
SMALL
LQ -2.9 -0.29 -4.0 -0.40 N/A
Median -2.3 -0.23 -3.3 -0.33 N/A
UQ -1.0 -0.10 -2.3 -0.23 N/A
MfP-LG tN-25)
LQ -20.7 -0.24 -23.3 -0.27 N/A
Median -12.8 -0.15 -17.7 -0.21 N/A
UQ -5.3 -0.06 -8.9 -0.1| N/A
SIC 2865 (N=3)
MEO-LG
ig -30.6 -0.20 -32.6 -0.22 N/A
Median +0.5 *0.07 -4.5 -0.03 NMF
UQ 58.1 *0.39 57.1 -0.38 -1.7
SIC 2869 (N=2I)
MEO-LG
LQ -9.6 -0.19 -11.4 -0.23 N/A
Median -7;0 -0.14 -9.0 -0.18 N/A
UQ 0.2 0.00 -2.3 -0.05 NMF
-------
•7.0 SENSITIVITY ANALYSIS
The purpose of the sensitivity analysis is. to determine the degree of sensitivity
of the model to changes in the values of various parameters. In this economic analysis,
a sensitivity analysis has been performed, varying the following parameters:
• Compliance costs. Treatment costs were increased by 10 percent
and 20 percent.
• Cost pass through. The zero cost pass through assumption used in
the impact analysis was modified to assume that plants could pass
through 20 percent of their treatment costs.
• Weighted average cost of capital (WACC). The weighted average
cost of capital was increased by 2 percentage points and decreased
by 2 percentage points.
The sensitivity of the economic impacts to each of these changes is presented
in Table 7-1 and is described below.
Increase in Compliance Costs
The economic impacts are relatively insensitive to compliance cost
increases. This is particularly true for direct dischargers. As shown in Table 7-1, a 20
percent increase in treatment costs results in no closures under BPT. For the BAT
options, one more plant closure would be expected under BAT IIA; no additional closures
would occur under BAT IIB. The increase in the number of non-closure plants that
would sustain sales or profits impacts is somewhat greater, increasing from 21 to 29
plants under BAT IIA and from 17 to 23 under BAT IIB.
Indirect discharging plants sustain slightly greater impacts as a result of
treatment cost increases. Under PSES IVA, a 20 percent cost increase would result in
an additional nine plant and ten product line closures. Employment impacts associated
with these closures would be almost twice those projected by the standard analysis.
The number of non-closure plants sustaining sales or profit impacts would increase only
slightly.*
*Note that increasing costs by 10 and 20 percent results in 89 and 88
significant sales or. profit impacts, respectively. This is because some plants which
would sustain a significant sales or profit impact if costs were to increase by 10 percent
will close if costs rise by 20 percent. Thus, the closure number increases and the
number of significantly affected non-closures drops by one plant.
7-1
-------
fable 7-1
SENSITIVITY ANALYSIS RESULTS
(I) (2) (3) (1) (5) \6)
Compliance Compliance 201 Cost
Standard Costs Inc. Costs inc. WACC WACC °3ss
Analysis I0t 201 * 2 Points - 2 Points Througn
BPT I
ants Analyzed
ants Incurring
Number of PI
Number of PI
Costs
Plant Closures
Product Line Closures
Profit or Sales Impacts
Employment Loss
209
214
0
0
a
o
o
o
11
0
0
0
8
0
3AT I IA
Number of Plants Analyzed 283
Number of Plants Incurring
Costs 289
Plant Closures 12 13 13 13 12 12
Product Line Closures 12 12 12 12 10 10
Profit or Sales impacts 21 27 29 22 24 15
Employment Loss 1743 1856 1856 1856 1626 1626
BAT 118
Number of Plants Analyzed
Number of Plants Incurring
Costs
Plant Closures
Product Line Closures
Profit or Sales Impacts
Employment Loss
283
289
11 II 11
9 9 9
17 20 23
1359 1359 1359
11 II 11
9 8 7
18 18 13
1359 I 306 I 242
7-2
-------
fable 7-! (continued)
SENSITIVITY AHAIYSIS RESULTS
(1) (2) (3) (4) (5) (6)
Compliance Comoliance 20< Cos*
Standard Costs inc. Costs inc. WACC WACC 3ass
Analysis 102 20t * 2 Points - 2 Points Througn
PSES IVA
Number of Plants Analyzed 362
Number of Plants Incurring
Costs 365
Plant Closures 37 41 46 39 35 51
Product Line Closures 30 33 40 33 27 27
Profit or Sales Impacts 86 89 88 85 89 70
Employment Loss 3736 4229 7000 3857 3286 2955
PSES IVB
Number of Plants Analyzed 362
Number of Plants Incurring
Costs
365
Plant Closures
25
28
30
27
22
20
Product Line Closures
27
29
29
29
25
23
Profit or Sales Impacts
63
62
64
59
63
54
Employment Loss
2190
2372
2752
2349
1896
1706
PSES VII
Number of Plants Analyzed 362
Number of Plants Incurring
Costs
365
Plant Closures
27
28
30
29
24
20
Product Line Closures
27
29
29
29
25
23
Profit or Sales Impact?
66
62
64
62
70
54
Employment Loss
2561
2669
2752
2720
2025
1706
7-3
-------
Under PSES IVB, increasing costs has substantially less dramatic effects
relative to PSES IVA. A 20 percent increase in treatment costs would result in five
additional plant closures and two more product line closure. The number of plants
incurring significant sales or profit impacts would rise from 63 to 64 plants.
Cost Pass Through
The economic impact analysis assumes that none of the treatment costs can be
passed on to customers of OCPSF products. Thus, it represents a worst case analysis at
the industry plant level. To the extent that at least some of the costs associated with
compliance can be passed through to customers, the economic impacts will be less
severe at the manufacturing level.
This sensitivity analysis examines the change in economic impacts that would
occur if plants were to pass on 20 percent of their treatment costs in the form of higher
prices. A number of simplifying assumptions were made in order to carry out this
analysis. First, demand elasticity is assumed to be unitary, i.e., the percentage
increase in price is exactly offset by the percentage decline in quantity so that there is
no change in total OCPSF sales. Secondly, to the extent that treatment costs are
related to production, they would decrease as a result of the decline in the quantity
OCPSF products manufactured. This is not taken into account; all compliance costs
remain at their original levels. Hence, the impacts may be interpreted as those that
might occur from a 20 percent cost pass through as well as those resulting from a 20
percent decrease in treatment costs.
The economic impacts on direct discharging plants are relatively insensitive to
the cost pass through assumptions; Since there were no closures under BPT in the
standard analysis, one could not expect a decrease as a result of cost pass through
assumptions. Two fewer product line closures would be expected under both BAT [IA
and BAT [IB. The number of non-closure plants projected to sustain profit or sales
impacts would fall by 25 to 30 percent.
Indirect dischargers are somewhat more sensitive to the cost pass through
assumption. Assuming a 20 percent cost pass through, six plants and three product lines
expected to close under PSES IVA would probably remain open. Under PSES IVB, three
fewer plant and two fewer product line closures would be expected. The number of
non-closure plants expected to incur sales or profit impacts would be reduced by 15 to
20 percent.
7-4
-------
Weighted Average Cost of Capital (WACC)
The impacts are relatively insensitive to changes in the WACC. Increasing the
WACC by 2 percentage points has no effect on BPT or BAT IIB closures. Under BAT
IIA, one additional product line closure would be expected. The number of direct
discharging plants sustaining sales or profit impacts would increase by one under each
of the two BAT options. Decreasing the WACC has similar, although opposite, effects.
Impacts on indirect dischargers are also insensitive to changes in the WACC.
For PSES Options IVA, IVB and VII, increases in the WACC result in two additional plant
closures. Product line closures would increase by two for PSES IVB and PSES VII and by
three under PSES IVA. The number of plants expected to sustain sales or profit impacts
would decrease by one to four plants, depending upon the option considered. Reductions
in the WACC have opposite effects of similar magnitudes.
7-5
-------
S.O LIMITS OF THE ANALYSIS
The organic chemicals industry is a large, diverse industry made up of plants
with production systems ranging from simple to highly complex. EPA estimates that
the industry includes about 2,100 manufacturers producing over 25,000 different organic
chemicals, plastics and synthetic fibers polymerized from organic chemicals. Some
plants produce chemicals in large volumes, while others produce only small volumes of
"specialty" chemicals. Large volume production tends toward continuous processes,
while small volume production tends toward batch processes, minimizing water use and
optimizing the consumption of raw materials in the process. Different products are
made by varying raw materials, chemical reaction conditions, and the chemical
engineering processes. Furthermore, the products being manufactured at a single large
chemical plant frequently vary on a weekly or even daily basis. A single plant may
simultaneously produce many different products in a variety of continuous and batch
operations, and the product mix may change frequently.
To control the wide variety of pollutants discharged by the industry, a broad
range of in-plant controls, process modifications, and end-of-pipe treatment techniques
are used. At most plants, programs have been implemented that combine elements of
both in-plant control and end-of-pipe wastewater treatment. The configuration of
controls and technologies differs from plant to plant, corresponding to the differing
mixes of products manufactured by different facilities.
The industry is also highly complex in terms of its financial and competitive
structure. It contains, at one extreme, very large multinational firms owning a large
number of individual plants which may operate as independent profit centers or as part
of larger divisions of the firm. At the other extreme are small single plant firms.
Ownership is about evenly divided between publicly-held companies for which financial
data are readily available at the firm level and privately held firms for which only
limited financial data are available. In addition, the industry is closely integrated with
the international petrochemicals industry and responds to stimuli that may originate in
the United States or abroad.
The intent of this economic impact analysis has been to consider the complex
technical and economic structures ot the industry to the extent possible. However, the
analysis is limited by available data and methods. Major limitations of data and
methodology are discussed in the following sections covering the plant closure, new
sources and foreign trade analyses.
8-1
-------
8.1 Plant Closure Analysis
Limitations in the types and quality of data available restrict the plant closure
analysis in a number of ways. The major limitations discussed below include the
following:
Plant level data
• Selection of a base year for the analysis
• Calculation of the Weighted Average Cost of Capital
• Calculation of Salvage Value
Firm-Level Data
• Impacts of Other Regulations
I. Plant-level data. The principal source of plant level information is the
Section 308 database (1982), which contains information on production, sales,
wastewater flow, SIC group and other variables. Financial data necessary for cash flow
and salvage value calculations are not available at the plant level in this database.
Therefore, industry level financial data from publicly available sources were used to
estimate plant level financial parameters including cash flow, salvage value, and
profits. Regression equations relating these financial parameters to sales were
developed based on Dun and Bradstreet data (combined with Robert Morris Associates
data for depreciation and interest expense — variables not available from Dun and
Bradstreet). These equations were then applied to plant level OCPSF sales from the
§308 data base to estimate plant level financial variables. It is important to note that
the Dun and Bradstreet data are firm level data, rather than plant level data. Although
80 firms are single plant firms* 110 firms are not. (Detailed data on this issue are
shown in Table 3-1 in the methodology chapter.)
An attempt to restrict the Dun and Bradstreet data to those from single.plant,
non-subsidiary firms failed due to insufficient data of that type. Other sources of
financial data were also investigated; however, plant level, financial data for multi-
plant firms were not available. Some information indicates that some companies do not
keep financial data for each plant. Thus, the analysis assumes that firm level data are
an acceptable proxy for plant level financial data. (This assumption does not alter the
use of a plant level sales figure which was available from the §308 survey.)
8-2
-------
2. Selection of 1988 as Baseline Year. The year 1988 was chosen as the
baseline year for the analysis; thus, 1982 sales data utilized in the plant closure analysis
*
were projected forward to 1988. This was performed utilizing DRI macroeconorruc
and chemical industry projections for various indicators such as production, chemical
price index, implicit price deflator, etc. DRI projections for exports and production
were used in the foreign trade analysis. The use of such projections introduces unavoid-
able uncertainty into the economic impact calculations.
DRI projections reflect anticipated changes in the chemical industry
environment to a certain degree (for instance, capacity changes and projected price
changes for certain chemicals). However, the impact analysis is static; it cannot fully
capture the changes in the chemical industry which have occurred in the 1980s. For
example, a significant amount of capacity has already been shut down, due to
overcapacity in the industry at the end of the 1970s. The decreased capacity appears in
DRI projections, but the less tangible changes — restructuring, debottlenecking vs. new
plant construction, movement from commodities towards higher value added chemicals,
the shift from a market-driven to a cost-driven industry — cannot be taken into
account. These influence industry decision-making, and consequently can be expected
to influence the impact of the proposed regulations. These factors are not quantifiable,
and thus impose a constraint on the accuracy with which the analysis can model
reality.
3. Weighted Average Cost of Capital
While the actual weighted average cost of capital (WACC) may vary from
company to company, three different industry average weighted average costs of
capital were selected for use in the impact analysis. Based on evidence that smaller
firms are typically riskier than larger ones, the smallest firm size category was
assigned the prime rate, as projected by DRI for 1988 plus 2.5 percentage points..
Lower rates were assigned to middle market firms (prime plus 1.5 percentage points);
large firms were assigned the prime rate. Given that risk is the principal determinant
of interest rates, not size, the choice of WACC based on firm-size is a limitation in the
analysis. However, as indicated, by the. sensitivity analysis, this limitation is relatively
minor.
Section 308 data were collected in 1982; hence, information is reported in
1982 dollars.
8-3
-------
Calculation of Liquidation Value
The plant closure analysis utilizes a comparison of projected discounted cash
flow with salvage value to estimate the impact of the various, effluent limitation
options. If the liquidation or salvage value of a plant exceeds the discounted cash flow,
a plant is a closure candidate, (n practice, liquidation value is difficult to estimate; the.
calculation employed is based on fitted regression equation at the four-digir SIC level,
since this information was not reported in the §308 survey. Industry financial data do
not allow plant location, age, etc. to be factored into the analysis. Thus, the equation
used in the calculation is inexact. The proportion of inventory, plant and equipment,
and real estate that are. salvageable are estimates. The fact that book value and
market value are frequently not identical further complicates the calculation. For
example, it is possible that the real estate value may be nearly zero (or even negative)
in some cases, because of environmental concerns over land used for chemical
operations. On the other hand, a plant sold as a going concern might be worth more
than book value, even though the current management was not operating the plant
profitably.
5. Firm Level Analysis
The financial health of parent firms is examined through a limited ratio
analysis. For some parent firms, Compustat data (publicly available financial data) are
available; for these firms, the analysis is accurate. For a substantial fraction of non-
publicly traded firms, no financial data are available. Consequently, industry averages
from Dun and Bradstreet are employed. The firms' estimated compliance costs are used
to measure the degree of movement away from the median ratio value for that size and
SIC group under post-compliance conditions.
A second limitation in the firm-level analysis is the use of ratios in general.
Only four have been chosen for examination, and only firms falling into lower quartiles
for two pairs of ratios are isolated as potentially financially weak. It is well known that
ratio analysis used in isolation is not always accurate. However, given that the purpose
here is only to isolate those firms most likely to be weak financially, the use of ratios
alone provides a reasonable approach to identifying financial impacts at the firm level.
8-4
-------
6. Impacts of Other Regulations
An effort was made to assess the cumulative impacts of other regulations on
the organic chemicals industry. This analysis was necessarily not as detailed as the
analysis performed for the effluent guidelines. In particular, EPA is currently
developing regulations under the 1984 Hazardous and Solid Waste Amendments to
RCRA restricting the land disposal of certain hazardous wastes. The effects of the
regulations were accounted for in the analysis by including estimates of RCRA costs
attributable to the 1984 amendment in the baseline.
S.2 New Sources Analysis
The new sources analysis determines whether compliance costs would impose
potential barriers to entry into the industry. The most severe limitation is the lack of
good data on the cost of constructing new plants of various types and sizes and
expanding existing ones. Because relatively few new plants are being built, and because
only a fraction of those report cost of construction in publicly-available sources, the
cost estimations are very rough. Consequently, the discounted cash flow calculations
used to determine net present value of the investment and the profitability index are at
best indicative of the relative magnitude of the impact.
A second limitation is the lack of wastewater treatment compliance costs for
new plants. In this case, the compliance costs for existing plants are utilized in the new
sources analysis. This is an acceptable limitation, since it leads to a worst case
analysis; retrofitting is almost always more expensive than including the same pollution
control equipment in the original plant design.
One final limitation in this analysis is the use of the profitability of existing
plants as a proxy for the profitability of new plants. Presumably, new plants would be
expected to generate better-than-average returns. However, the results of the analysis
indicate that under baseline profitability conditions, utilizing the estimated
construction costs, most U.S. firms would not build new plants. It is difficult to discern
how much additional error is introduced through the use of profitability of existing
plants over what is introduced through the cost estimations.
In conclusion, the assumptionsand limitations of this analysis are such that the
analysis should only be considered an estimate of barriers to entry into the industry.
8-5
-------
S.3 Foreign Trade Analysis
The foreign trade methodology and results are similarly limited by the quality
and quantity of available data. Ideally one wouid examine the production loss on a
product level, the price changes that result, the ultimate effects on other parts of the
market (suppliers, customers), and the total effect on balance of trade. The available
data do not support such an analysis. Predicted production loss is known only at the 8-
digit SIC level, which can include many chemicals. This; is one limitation.
Secondly, an analysis encompassing price change calculations requires demand
elasticity information at the product level, in U.S. and international markets. This
information is not publicly available. Although this economic impact analysis assumed
no cost pass through, i.e. no. price increases, in reality, the loss of some production as a
result of the proposed regulation may affect supply (and thus prices) subsequent to the
closures. It has been assumed in the foreign trade analysis that the loss of production is
small enough that the supply-demand balance remains unaffected. It has also been
assumed that remaining U.S. suppliers would not increase production to compensate for
production lost through closures. This conservative assumption tends to overstate
foreign trade impacts.
Thirdly, the analysis utilizes DRI projections of exports and production by
chemical. Because DRI does not cover all SICs in which loss of production is predicted,
the trade impacts cannot be examined for all chemical groups. However, the overall
effect on balance of trade can still be estimated.
A final limitation is the use of predicted plant closures to predict trade
effects. The plant closure analysis is designed to project the number and types of
plants that may close. To the extent that the number and types of plants which
actually close varies from that predicted, the product mix of the plants which actually
close will vary as well. Consequently, the distribution and relative magnitude of trade
impacts may differ somewhat from those presented.
8-6
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