United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
EPA-452R-94034
July 1994
Air
Economic Impact Analysis for the
Polymers and Resins II NESHAP
DRAFT
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-n
TABLE OF CONTENTS
SECTION 9 - ECONOMIC IMPACT ANALYSIS 9-1
9.1 INTRODUCTION 9-1
9.1.1 EIA Objectives 9-1
9.1.2 Background 9-2
9.1.2.1 Affected Markets 9-2
9.1.2.2 Regulatory Alternatives 9-3
9.1.3 Summary of Estimated Impacts 9-4
9.1.3.1 Primary and Secondary Impacts . . 9-4
9.1.3.2 Financial Analysis 9-7
9.1.3.3 Sensitivity Analyses 9-7
9.1.3.4 Potential Small Business Impacts . 9-7
9.1.3.5 Economic Costs 9-7
9.1.4 Organization of EIA 9-8
9.2 OVERVIEW OF ECONOMIC IMPACT ANALYSIS 9-9
9.2.1 Overview of Distributional Impacts .... 9-9
9.2.1.1 Impacts on Producers 9-10
9.2.1.2 Impacts on Consumers or Buyers . 9-10
9.2.1.3 Indirect or Secondary Impacts . 9-11
9.2.2 Economic Impact Studies 9-11
9.2.3, Industry Profile 9-12
9.2.4 Primary Impacts 9-12
9.2.4.1 Pre-Control Market Demand and Sup-
ply Functions 9-13
9.2.4.2 Per Unit Emission Control Costs 9-15
9.2.4.3 The Post-Control Supply Function 9-16
9.2.4.4 Post-Control Prices, Output, and
Closures 9-17
9.2.4.5 Reporting Results of Market Analy-
ses 9-17
9.2.4.6 Limitations of the Market Analysis 9-18
9.2.5 Capital Availability Analysis 9-19
9.2.5.1 Evaluation of Impacts on Capital
Availability 9-20
9.2.6 Evaluation of Secondary Impacts .... 9-22
9.2.6.1 Employment Impacts 9-23
9.2.6.2 Energy Effects 9-23
9.2.6.3 Foreign Trade Impacts 9-24
9.2.6.4 Regional Impacts 9-25
9.2.7 Affected Plants 9-25
9.3 INDUSTRY PROFILE 9-25
9.3.1 Product Descriptions and End Uses . . . 9-26
9.3.1.1 DEGBPA 9-26
9.3.1.2 Wet Strength Resins 9-31
9.3.2 Market Structure 9-33
9.3.2.1 DGEBPA 9-33
9.3.2.2 Wet Strength Resins 9-35
9.3.3 Market Outlook 9-36
9.3.3.1 DGEBPA 9-36
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9.3.3.2 Wet Strength Resins 9-38
9.3.4 Foreign Trade 9-39
9.3.4.1 DGEBPA 9-39
9.3.4.2 Wet Strength Resins 9-40
9.3.5 Financial Data 9-41
9.4' PRIMARY ECONOMIC IMPACTS AND CAPITAL AVAILABILITY
ANALYSIS 9-42
9.4.1 Introduction 9-42
9.4.2 Estimates of Primary Impacts 9-43
9.4.3 Capital Availability Analysis 9-46
9.4.4 Limitations of Estimated Primary Impacts 9-47
9.4.5 Summary of Primary Impacts 9-48
9.5 SECONDARY ECONOMIC IMPACTS 9-49
9.5.1 Introduction 9-49
9.5.2 Labor Impacts 9-49
9.5.3 Energy Use Impacts 9-51
9.5.4 Foreign Trade Impacts 9-52
9.5.5 Regional Impacts . . / 9-53
9.5.6 Limitations of Estimated Secondary Impacts 9-53
9.5.7 Summary of Secondary Impacts 9-53
9.6 POTENTIAL SMALL BUSINESS IMPACTS 9-54
9.7 ECONOMIC COSTS 9-55
9.7.1 Economic Costs of Emission Controls: Con-
ceptual Issues 9-55
9.7.1.1 Market Adjustments 9-57
9.7.1.2 Markets for Emission Control Re-
sources 9-57
9.7.1.3 The Social Discount Rate .... 9-58
9.7.1.4 Costs of Imported Goods .... 9-59
9.7.2 Other Costs Associated with NESHAP ... 9-60
9.7.3 Changes in Economic Surplus as a Measure of
Costs 9-60
9.7.4 Estimates of Economic Costs 9-61
APPENDIX A - AFFECTED PLANTS AND EMISSION CONTROL COSTS . 9-65
APPENDIX B - TECHNICAL DESCRIPTION OF ANALYTICAL METHODS 9-6E5
APPENDIX C - ESTIMATION OF INDUSTRY SUPPLY AND DEMAND . . 9-85
APPENDIX D - SENSITIVITY ANALYSES 9-97
REFERENCES 9-101
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FIGURE
9-1 Partial Equilibrium Analysis of DGEBPA and Wet ... 9-14
TABLES
9-1 Summary of Estimated Economic Impacts 9-5
9-2 Estimates of Annualized Economic Costs 9-8
9-3 Biases Resulting if Model Assumptions are Violated . 9-19
9-4 Epoxy End-Use Consumption 9-27
9-5 Companies Producing Unmodified Epoxy Resin, 1980-1991 9-34
9-6 Companies Producing EPA Based Non-Nylon
Polyamide Resins, 1988 and 1990 9-35
9-7 U.S. Trade in Epoxy Resin 9-40
9-8 U.S. Trade in Non-Nylon Polyamide 9-41
9-9 Financial Data for Resin Producers 9-42
9-10 Estimated Primary Impacts on DGEBPA and Wet Strength
Resin Markets 9-45
9-11 Estimated Employment Losses 9-50
9-12 Estimated Energy Use Reductions 9-51
9-13 Estimated Impacts on Net Exports 9-52
9-14 Employment of Resin Producers 9-55
9-15 Estimates of Annualized Economic Costs 9-62
9-16 Estimates of the Annualized Emission Control Costs . 9-64
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SECTION 9
ECONOMIC IMPACT ANALYSIS
9.1 INTRODUCTION
The U.S. Environmental Protection Agency (EPA) is reviewing
National Emission Standards for Hazardous Air Pollutants (NESHAP)
for the basic liquid epoxy resin and wet strength resin indus-
tries . These industries emit several of the hazardous air
pollutants (HAPs) identified by the Clean Air Act Amendments of
1990.x
Section 317 of the Clean Air Act requires EPA to evaluate
regulatory alternatives through an Economic Impact Analysis
(EIA). Accordingly, this EIA has been conducted to satisfy the
requirements of the Clean Air Act.
9.1.1 EIA Objectives
There are two primary objectives of this EIA. The first
objective is to describe the distribution of adverse impacts
associated with the NESHAP among various members of society. The
second objective is to adjust estimated emission control costs so
that these reflect the economic costs associated with the stan-
dard.
Neither the benefits nor the costs associated with the
NESHAP will be distributed equally among different members of
society. Since this study is focused on costs, emphasis is
placed on estimating and describing the adverse impacts asso-
ciated with the NESHAP. Those members of society who could
potentially suffer adverse impacts include:
1 These HAPs are MeOH, HC1 and EPI.
9-1
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Producers whose facilities require emission controls.
Buyers of goods produced by industries requiring con-
trols.
Employees at plants requiring controls.
Individuals who could be affected indirectly such as
residents of communities proximate to controlled facil-
ities, and employees of industries that sell inputs to
or purchase inputs from directly affected firms.
Because of potential distributional impacts, and because of other
policy issues, impacts on both energy consumption and foreign
trade are also considered in this study.
Economic costs generally do not correspond, to emission
control costs because the latter do not reflect market adjust-
ments that occur because of higher production costs caused by the
installation, operation and maintenance of emission controls. A
second purpose of this EIA is to make appropriate adjustments to
estimated emission control costs so that they reflect the econom-
ic costs of the NESHAP.
9.1.2 Background
9.1.2.1 Affected Markets
EPA expects the NESHAP to affect two of the industries in-
cluded in Standard Industrial Classification code 2821. They
are:
Basic Liquid Epoxy Resin (Diglycidyl Ether of Bisphenol
A or DGEBPA).
Wet Strength Resin (Epichlorohydrin Cross-Linked Non-
Nylon polyamide resins).
9-2
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9.1.2.2 Regulatory Alternatives
The Clean Air Act Amendments of 1990 stipulate that HAP
emission standards for existing sources must at least match the
percent reduction of HAPs achieved by either a) the best 12 per-
cent of existing sources, or b) the best five sources in a cate-
gory or subcategory consisting of fewer than 30 sources. This
minimum standard is called a MACT floor.
The NESHAP considered in this EIA is the MACT floor for wet
strength resin plants. The MACT floor for these plants requires
controls on storage tanks and process vents. This EIA considers
an alternative to the MACT Floor for wet strength resin plants.
This alternative, which we refer to as Option I, requires con-
trols only on equipment leaks. The NESHAP for DGEBPA plants is
the MACT floor for storage tanks and process vents, but requires
more stringent controls than the MACT floor for equipment leaks..
Both the DGEBPA and The Wet Strength resin industries con-
sist of fewer than 30 sources. Thus, definition b) was used in
both cases to construct the MACT floor for existing sources. For
new sources the Amendments stipulate that the MACT floor be set
at the highest level of control achieved by any similar source.
There are currently three facilities producing substantial
amounts of DGEBPA. The MACT floor for existing sources was con-
structed by averaging the percentage reduction of HAPs achieved
for each source type by each facility. A source type is a piece
of equipment or component of production which produces HAPs. The
MACT floor requires controls on the following DGEBPA source
types: process vents, storage tanks and equipment leaks. As
noted above, the NESHAP considered in this EIA requires controls
at DGEBPA plants more stringent than the MACT floor for equipment
leaks.
9-3
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There are 17 existing wet strength resin plants. The MACT
floor was constructed by averaging the percentage reduction of
HAPs achieved by the five best controlled sources for each source
type. The MACT floor for wet strength resin plants requires con-
trols on storage tanks and process vents, but no additional con-
trols on equipment leaks.
As noted earlier, Option I, which is an alternative to the
MACT Floor for the wet strength resin industry, requires controls
on equipment leaks, but no controls on either storage tanks or
process vents. We consider Option I because it results in larger
emission reductions at considerably lower costs than the MACT
floor.
9.1.3 Summary of Estimated Impacts
9.1.3.1 Primary and Secondary Impacts
Table 9-1 summarizes the estimates of the primary and sec-
ondary economic impacts associated with the NESHAP.2 Primary
impacts include price increases, reductions in market output
levels, changes in the value of shipments by domestic producers,
and plant closures. Secondary impacts include employment losses,
reduced energy use, changes in net exports, and potential region-
al impacts.
The estimated primary impacts on the DGEBPA market are
small. For example, we estimate that the market price will in-
crease by just 0.05 percent, and that market output will fall by
about Q.08 percent. The estimated impacts of the MACT Floor on
price and output in the wet strength resin market are somewhat
larger than those for the DGEBPA market. We estimate an increase
2 Table 9-1 summarizes the results of the MACT floor for the wet strength
resin industry. We describe the impacts of Option I in the text that follows.
9-4
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Table 9-1
SUMMARY OF ESTIMATED ECONOMIC IMPACTS3
Analysis
Estimated Impacts
Primary Impacts
Price Increases
Market Output
Value of Domestic
Shipments
Plant Closures
Estimated price increases are 0.05 percent
for DGEBPA and 4.19 percent for wet
strength resins.
Estimated reductions in market output are
0.08 percent for DGEBPA and 3.73 percent
for wet strength resins.
Estimated changes range from a decline of
0.03 percent for DGEBPA to an increase of
0.31 percent for wet strength resins.
No plant closures are expected in the
DGEBPA industry and one plant closure is
predicted for the wet strength resin in-
dustry.
Secondary Impacts
Employment
Energy Use
Net Exports
Regional Impacts
No significant employment losses are ex-
pected.
Estimated industry-wide use to decline by
0.08 percent ($8,500) in the DGEBPA indus-
try and by 3.73 percent ($45,000) in the
wet strength resin industry.
Estimated trade impacts are small. Net
exports of DGEBPA predicted to decline by
about $25,000. Lower volume of wet
strength resin exports expected to be off-
set by higher post-control prices.
No significant regional impacts are ex-
pected.
3 Results reported for wet strength resin industry are for the MACT
floor. Results for Option I are described in the text.
9-5
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in price of 4.19 percent and a decrease in U.S. production of
3.73 percent. Note, however, that we expect a slight increase in
the value of shipments by domestic wet strength resin producers.
This occurs because the estimated price increase more than
offsets the lower production volume. Our analysis predicts no
plant closures in the DGEBPA industry, but one wet strength resin
plant closure is possible. This predicted closure, however, may
be due to some "worst case" assumptions adopted in our analysis.
The analysis of the primary impacts on the wet strength
resin market under the implementation of Option I yields substan-
tially less -adverse impacts than the MACT floor. The increase in
wet strength resin price is estimated at 0.22 percent (compared
to a 4.19 percent increase under the MACT floor). We estimate
that market output will decrease by just 0.20 percent under
Option I, with an associated increase (due to the slight increase
in price) in the value of domestic shipments of $7,000 (0.02 per-
cent) . While one plant closure is possible under the MACT floor,
none is expected under Option I.
The estimates of secondary impacts reported in Table 9-1
follow the estimates of primary impacts described above. We
expect only small employment losses and reductions in energy use.
These findings, of course, are consistent with our estimates of
small impacts on market output. We estimate that the reduction
in net exports of DGEBPA will be small, about $25,000, and that
higher post-control prices will offset a slightly lower volume of
wet strength resin exports. Finally, we expect no significant
regional impacts.
The secondary impacts of Option I on the wet strength resin
industry are also smaller than those those of the MACT Floor.
Employment (production job) losses are almost negligible (0.10
production jobs) and energy use is expected to decline by 0.20
percent. The estimated trade impacts are negligible. Wet
9-6
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strength resin exports are estimated to fall by .21 percent.
Also, no significant regional impacts are expected.
9.1.3.2 Financial Analysis
Our financial analysis indicates that capital and annual
emission control costs are small relative to the financial re-
sources of the firms producing DGEBPA and wet strength resin. As
a result, we do not expect that it will be difficult for these
firms to raise the capital required to purchase and install emis-
sion controls.
9.1.3.3 Sensitivity Analyses
In Appendix D of the report, we examine the sensitivity of
the estimated primary impacts to our estimates of market demand
elasticities. The results reported in Appendix D indicate that
the primary impacts summarized in Table 9-1 are relatively insen-
sitive to reasonable ranges of demand elasticity estimates. How-
ever, analysis conducted assuming a "low" elasticity of demand
yields slightly less adverse impacts, including no plant closures
in the wet strength resin industry.
9.1.3.4 Potential Small Business Impacts
All of the affected DGEBPA and wet strength resin producers
are large companies and none satisfies the criteria for a small
business. Consequently, we do not expect any significant small
business impacts to result from implementing the NESHAP.
9.1.3.5 Economic Costs
Table 9-2 reports estimates of the economic costs associated
with the NESHAP. The estimated annualized economic costs are
$120 thousand for the DGEBPA industry and $465 thousand for the
9-7
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wet strength resin industry under the MACT floor. The economic
costs associated with Option I, $51 thousand, are considerably
lower than those of the MACT floor. These estimates measure
changes in economic surplus and include the costs associated with
higher prices of imports to the U.S. economy.
Table 9-2
ESTIMATES OF ANNUALIZED ECONOMIC COSTS
(thousands of 1992 dollars)
Industry
DGEBPA
Wet Strength Resin
MACT Floor
Option I
Loss in
Consumer
Surplus
141
1,607
87
Loss -in
Producer
Surplus
-3
-841
-22
Loss in
Residual
Surplus
-19
-300
-13
Loss in
Surplus
Total
120
465
51
Economic costs are computed as the change in economic sur-
plus associated with the NESHAP. The estimates include the
costs of higher prices of imported products.
9.1.4
Organization of EIA
We describe the analytical methods employed to estimate che
economic impacts associated with the NESHAP in Section 9-2. Sec-
tion 3 contains profiles of the two affected industries. We
report in Section 9-4 estimates of primary economic impacts, in-
cluding those on market prices, market output levels, value of
shipments by domestic producers, and plant closures. Section 9-5
9-8
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presents estimates of secondary impacts, including the effects on
employment, foreign trade, energy use and regional economies. We
describe potential adverse impacts of small businesses in Sec-
tion 9-6. In Section 9-7, we report estimates of the economic
costs associated with the NESHAP.
There are four appendices to this section. We describe the
model plants used in the analyses and report estimates of emis-
sion control costs and other baseline data in Appendix A. Appen-
dix B provides a detailed technical description of the analytical
methods employed to estimate economic impacts and costs. We
describe an econometric model of the resin 'industry in Appen-
dix C. We report in Appendix D the results of sensitivity analy-
ses in which we consider ranges of demand elasticity estimates.
9.2 OVERVIEW OF ECONOMIC IMPACT ANALYSIS
We assess the economic impacts associated with the NESHAP by
conducting studies of the affected industries. These industries
are the DGEBPA and the wet strength resins. We describe the ana-
lytical methods employed in these studies below.
9.2.1 Overview of Distributional Impacts
As noted earlier in the introduction to this section,
several groups might potentially suffer from adverse impacts
associated with the NESHAP. These groups include:
Resin producers.
Resin buyers.
Employees at affected plants.
Individuals affected indirectly by the NESHAP.
9-9
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We describe the potential adverse impacts affecting each of these
groups below.
9.2.1.1 Impacts on Producers
The emission control costs associated with the standard are
likely to reduce the profitability of at least some of the af-
fected plants. Indeed, some affected plants may be forced to
shutdown operations in the face of emission control costs. Ulti-
mately, the magnitude of the adverse impacts incurred by affected
plants will depend on the extent to which emission control costs
can be passed on to buyers. In addition, operators of some af-
fected plants might have difficulty acquiring the capital neces-
sary to purchase and to install emission control equipment.
Some plants in affected industries may not suffer adverse
impacts as a result of the implementation of an emission control
standard. The post-control profitability of an affected plant
will improve if post-control price increases more than offset the
plant's emission control costs. This could occur if control
costs for some plants are substantially higher, per unit of out-
put, than those for other plants in the industry.
9.2.1.2 Impacts on Consumers or Buyers
Both DGEBPA and wet strength resin are purchased primarily
by firms which use these products as inputs to-produce other
goods. These firms and the consumers of the goods which they
produce are likely to suffer from two related adverse impacts.
First, post- control prices for resins produced at the affected
plants are likely to be higher as sellers attempt to pass through
some of the costs of emission controls. This will cause profits
to be smaller, at least in the short run, for firms which pur-
chase DGEBPA and wet strength resin as inputs. It will also
cause prices of final goods to be higher as firms attempt to pass
9-10
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through some of the increase in production costs. Second, the
shift in supply caused by emission control costs is likely to
reduce the amount of resin sold in affected markets, as well as
the level of output sold in markets which use the resin as an
input. These two effects are related in that post-control equi-
librium prices and output levels in affected markets will be
determined simultaneously.
9.2.1.3 Indirect or Secondary Impacts
Two countervailing impacts on employees of affected plants
are likely to result from the implementation of the NESHAP.
Employment will fall if affected plants either reduce output or
close operations altogether. On the other hand, increases in
employment associated with the installation, operation, and
maintenance of emission controls are likely.
A number of other indirect or secondary adverse impacts may
be associated with the implementation of a standard. The indi-
rect impacts we consider in this study include: foreign trade
effects; impacts on regional economies; and, effects on energy
consumption.
9.2.2 Economic Impact Studies
The industry segment studies that follow in this report
include six major components of analysis. These components or
phases of analysis, which are designed to measure and describe
economic impacts, are:
Industry profile.
Direct impacts (market price and output, domestic
production and plant closures).
Capital availability analysis.
9-11
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Evaluation of secondary impacts (employment, foreign
trade, energy consumption, and regional and local
impacts).
Analysis of potential small business impacts.
Each of these phases of analysis is described below.
9.2.3 Industry Profile
The industry profile provided in Section 9-3 describes
conditions in affected industries that are likely to determine
the nature of economic impacts associated with the implementation
of the NESHAP. We discuss the following seven topics in the
industry profile:
Product descriptions.
Prices and output.
Market outlook.
Market structure.
Foreign trade.
Financial conditions.
Employment and energy use.
9.2.4 Primary Impacts
We employ a partial equilibrium model of the DGEBPA and wet
strength resin industries to estimate the primary impacts of
emission control costs, including market equilibrium price,
market output, the value of domestic shipments, and the number of
potential plant closures.4 This analysis is so named because
the predicted impacts are driven by estimates of how the affected
4 The results of the partial equilibrium analyses are also used to esti-
mate employment, energy and foreign trade impacts and the economic costs
associated with the regulatory alternatives.
9-12
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industries achieve market equilibrium after the air quality stan-
dard is implemented.
In a competitive market, equilibrium price and output are
determined by the intersection of demand and supply. The supply
function is determined by the marginal (avoidable) operating
costs of existing plants and potential entrants. A plant will be
willing to supply output so long as market price exceeds its
average (avoidable) operating costs. The installation, opera-
tion, and maintenance of emission controls will result in an
increase in operating costs. An associated upward shift in the
supply function will occur.
The procedures employed in the market analysis are illus-
trated in Figure 9-1. Constructing the model and predicting
impacts requires completing the following four tasks.
Estimate pre-control market demand and supply func-
tions .
Estimate per unit emission control costs.
Construct the post-control supply function.
Solve for post-control price, output and employment
levels, and predict plant closures.
We briefly describe each of these tasks below.5
9.2.4.1 Pre-Control Market Demand and Supply Functions
Pre-control equilibrium price and output levels in competi-
tive markets are determined by market demand and supply. Because
estimates of demand and supply for the relevant industries are
unavailable from the literature, we estimated these functions as
5 See Appendices A, B, and C for more detailed descriptions of the data
and methods employed in the partial equilibrium analysis.
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Pre-Control
Market Data
Specify Demand and
Supply Functions
Estimate Pre-Control
Demand and Supply
Emissions
Control Costs
Discounted Cash
Flow Parameters
Estimate per Unit
Emissions
Control Costs
Construct
Post-Control
Supply Function
Solve for Post-Control
Price and Output, and
Predict Closures
Figure 9-1
Partial Equilibrium Analysis of DGEBPA and
Wet Strength Resin Industries
9-14
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part of this study. Both the market demand and domestic supply
functions were estimated econometrically using time-series
data.6
Market demand in the household segment was specified as a
function of product price and a time trend to capture structural
change in demand over time.7 However, because of uncertainty
regarding the demand elasticity estimates, we report the results
of sensitivity analyses in Appendix D.
Market supply includes domestic supply and foreign supply of
imports. We derived our estimate of domestic supply elasticity
from a production function in which output of is expressed as a
function of capital stock held by the industry, material and
labor inputs, and time. We assume, in the absence of other in-
formation, that the supply elasticity of imports (foreign supply)
is the same as that for domestic supply.8
9.2.4.2 Per Unit Emission Control Costs
Emission control costs will cause an upward vertical shift
of the supply curves in affected markets. The height of the ver-
tical shift for each affected plant is given by the after-tax
cash flow required to offset the per unit increase in production
costs resulting from the installation, maintenance, and operation
of emission control equipment.
6 See Appendix C for detailed descriptions of the data and methods
employed to estimate these functions. Appendix C also reports the estimated
parameters of the functions.
7 Our estimates of demand elasticities are -1.50 for DGEBPA and -0.92 for
wet strength resin.
8 Given this assumption, a one percent change in price causes the same
percentage increase in both domestic and foreign supply.
9-15
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Estimates of the capital, operating and maintenance costs
associated with emission control equipment for affected plants
were obtained from the draft BID document. Per unit, after-tax
costs are estimated by dividing after-tax annualized costs by
annual output. This cost reflects the offsetting cash flow
requirement which, in turn, yields an estimate of the post-
control vertical shift in the supply function.
Computing per unit after-tax control costs requires, as
inputs, estimates of the following parameters:
The useful life emission control equipment.
The discount rate (marginal cost of capital).
The marginal corporate income tax rate.
Estimates of the expected life of emission control equipment were
obtained from the draft BID document. The results presented in
this report are based on a 10 percent real private discount
rate9 and a 25 percent marginal tax rate.
9.2.4.3 The Post-Control Supply Function
Estimated after-tax per unit control costs are added to pre-
control supply prices to determine the post-control supply prices
for domestic producers. We construct the post-control domestic
supply function by sorting affected plants, from highest to
lowest, by per unit post-control costs. We assume that plants
with the highest per unit emission control costs are marginal
9 The discount rate referred to here measures the private marginal cost
of capital to affected firms. This rate, which is used to predict the market
responses of affected firms to emission control costs, should be distinguished
from the social cost of capital. The social cost of capital is used to mea-
sure the economic costs of emission controls. See Section 9.7 for a more
detailed discussion of this issue.
9-16
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(highest cost) in the post-control market.10 Because per unit
control costs differ across affected plants' within an industry
segment, the post-control domestic supply function is segmented.
Total market supply is given by the sum of domestic and foreign
supply. We assume, of course, that foreign supply is unaffected
by emission controls.11
9.2.4.4 Post-Control Prices, Output, and Closures
The baseline, pre-control equilibrium output in an affected
market is taken as the level of observed national consumption
(shipments by domestic producers minus net exports). We compute
post-control equilibrium price and output levels in affected
markets by solving for the intersection of the market demand
curve and the market post-control, segmented supply curve. The
estimated reduction in market output is given by the difference
between the observed pre-control output level and the predicted
post-control output level. Similarly, the estimated increase in
price is taken as the difference between the observed pre-control
price and the predicted post-control equilibrium price.
Because higher market prices lead to higher imports, the
reduction in domestic production is larger -than the reduction in
market output. Specifically, the reduction in output for domes-
tic producers is given by the reduction in market output plus the
increase in imports. We estimate the number of plant closures by
dividing the predicted reduction in domestic output by the pro-
duction levels at plants with post-control supply prices higher
than the post-control equilibrium market price.
10 Note that any other construction of the post-control supply curves
would result in the same or smaller vertical shifts in supply, and according-
ly, the same or smaller economic impacts.
11 This assumption means that no shift in the foreign supply function
occurs as a result of emission controls on domestic producers. The quantity
supplied by foreign producers, however, increases as market price increases.
9-17
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9.2.4.5 Reporting Results of Market Analyses
The results of the partial equilibrium market analyses for
each of the affected industries are presented in Section 9-4 of
this report. In particular, estimates of the following are
reported:
Price increase.
Reduction in market output.
Annual change in the value of domestic shipments.
Number of plant closures.
9.2.4.6 Limitations of the Market Analysis
The partial equilibrium model has a number of limitations.
First, a single national market for homogeneous output is assumed
in the analysis. However, markets may be regional. Then each
region or product type will be affected primarily by cost changes
of plants in the region, rather than all plants in the national
market. Output reductions and price effects will vary across
regions depending on locations of affected plants. In addition,
the assumption of a national market is likely to cause predicted
closures to be overstated to the extent that affected firms are
protected somewhat by regional trade barriers.
Second, the analysis assumes that plants with the highest
per unit emission control costs are marginal post-control. This
assumption produces an upward bias in estimated effects on indus-
try output-and price changes because the control costs of non-
marginal firms will not affect market price. Predicted closures
will also be overstated.
Third, the analysis assumes that the implementation of con-
trols does not induce any domestic producers to expand produc-
tion. An incentive for expansion would exist if some plants have
9-18
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post-control incremental unit costs between the baseline price
and the post-control price' predicted by the partial equilibrium
analysis. Expansion by domestic producers will result in reduced
impacts on industry output and price levels. While plant clo-
sures will increase as expanding producers squeeze out plants
with higher post-control costs, net closures (closures minus
expansions) will be reduced.
Table 9-3 summarizes the biases discussed above. In most
cases, the assumptions embedded in the market analyses produce an
upward bias in estimated impacts on market quantity, market
price, and net closures.
Also, statistical errors in the estimated demand and supply
functions exist. We report the statistical properties of the
estimates of these functions in Appendix C.12 In addition, it
is likely that uncertainty in the estimates of emission control
costs exist, causing control costs for some plants to be either
overstated or understated. The control costs used in this EIA are
study estimates and are accurate within plus or minus 30 percent.
Table 9-3
BIASES RESULTING IF MODEL ASSUMPTIONS ARE VIOLATED
Direction of Bias
Change in Change in
Industry Industry Net
Assumption Quantity Price Closures
i) national market +
ii) controlled plants at margin +
in baseline
iii) no regulation-induced expan- +
sion of domestic producers
Price changes will vary depending on the locations of affected plants and
the levels of regional trade barriers and degree of product differentiation.
12 See Appendix D for estimates of impacts associated with alternative
estimates of demand elasticities.
9-19
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9.2.5 Capital Availability Analysis
We assume in the market analysis that affected firms will be
able to raise the capital associated with controlling emissions
at a specified marginal cost of capital. The capital availabil-
ity analysis, on the other hand, examines the variation in firms'
ability to raise the capital necessary for the purchase, instal-
lation, and testing of emission control equipment.
The capital availability analysis also serves three other
purposes. First, it provides information for evaluating the
appropriateness of the selected discount rate as a proxy for the
marginal cost of capital of the industry; implications for bias
in the partial equilibrium analysis follow. Second, it provides
information on potential variation in capital costs across firms.
Third, it provides measures of the potential impacts of controls
on the profitability of affected firms.
9.2.5.1 Evaluation of Impacts on Capital Availability
For each model plant13 included in the capital availabili-
ty analysis, the impact of the alternative standards on the
following two measures is evaluated:
Net income/assets.
Long-term debt/long-term debt and equity.
Net income is measured before-tax and is defined to include all
operations, continued and discontinued.
The ratio of net income to assets is a measure of return on
investment. The implementation of emission controls is likely to
13 The model plants included in the analysis are described later in this
section and in more detail in Appendix A.
9-20
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reduce this ratio to the extent that net income falls (e.g.,
because of higher operating costs) and assets increase (because
of investments in emission control equipment).
The ratio of long-term debt to long-term debt plus equity is
a measure of risk perceived by potential investors. Other things
being the same, a firm with a high debt-equity ratio is likely to
be perceived as being more risky, and as a result, may encounter
difficulty in raising capital. This ratio will increase if
affected firms purchase emission control equipment by issuing
long-term debt.
9.2.5.1.1 Baseline Values for Capital Availability Analysis --
Baseline values for net income and net income/assets are de-
rived by averaging data for as many years as are available
between 1988 and 1991. Data from these four years are employed
to reduce distortions caused by year-to-year fluctuations. Since
i
changes in the long-term debt ratio represent actual structural
changes, 1990 or 1991 data are used, whichever is the most recent
year the data are available.
9.2.5.1.2 Post-Control Values for Capital Availability Analysis --
Post-control values for the two measures identified above
are computed to evaluate the ability of affected firms to raise
required capital. The post control values are computed as
follows:
Post-control net income pre-control net income minus
the after-tax annualized costs associated with the
purchase, installation, maintenance and operation of
emission control equipment.
Post-control return on assets - post-control net income
divided by the sum of pre-control assets plus invest-
ments in emission control equipment.
9-21
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Post-control long-term debt ratio the sum of pre-
control long-term debt plus investments in emission
control equipment divided by the sum of pre-control
long-term debt, equity, and investments in emission
control equipment.
The calculations are done for a worst-case scenario of the
impact of controls on the measures. First, the total investment
in emission control equipment is assumed to be debt-financed.
Second, it is assumed that there is no increase in the price a
company receives for its output.
9.2.5.1.3 Limitations of the Capital-Availability Analysis --
The capital availability analysis "has limitations. First,
future baseline performance may deviate from past levels. The
financial position of a firm during the period 1988-1991 may not
be a good approximation of the company's position later during
the implementation period, even in the absence of the impacts of
emission control costs. '
Second, a limited set of measures is used to evaluate the
impact of controls. These measures reflect accounting conven-
tions and provide only a rough approximation of the factors that
will influence capital availability.
9.2.6 Evaluation of Secondary Impacts
The secondary impacts that we consider in this study in-
clude :
Employment impacts.
Energy impacts.
Foreign trade impacts.
Regional impacts.
9-22
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9.2.6.1 Employment Impacts
As equilibrium output in affected industry segments falls
because of control costs, employment in the industry will de-
crease. On the other hand, operating and maintaining emission
control equipment requires additional labor for some control
options. Direct net employment impacts are equal to the decrease
in employment due to output reductions, less the increase in
employment associated with the operation and maintenance of
emission control equipment.
Our estimates of the employment impacts associated with the
NESHAP are based on employment-output ratios and estimated
changes in domestic production. Specifically, we compute changes
in employment proportional to estimated changes in domestic pro-
duction. 14
Estimates of the labor hours required to operate and main-
tain emission control equipment are unavailable. Accordingly,
the employment impacts presented in this report are overstated to
the extent that potential employment gains attributable to oper-
ating and maintaining control equipment are not considered.
The estimates of direct employment impacts are driven by
estimates of output reductions obtained in the market analyses.
Biases in these estimates will likely cause the estimates of
employment impacts to be biased in the same direction.
9.2.6.2 Energy Effects
The energy effects associated with the NESHAP include
reduced energy consumption due to reduced output in affected
14 See Appendix B for descriptions of the data and methods used to
estimate employment impacts.
9-23
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industry segments plus the net change in energy consumption asso-
ciated with the operation of emission controls.
The method we use to estimate reduced energy consumption due
to output reductions is similar to the approach employed for
estimating employment impacts.15 Specifically, we assume that
changes in energy use are proportional to estimated changes in
domestic production. Estimates of the net change in energy con-
sumption due to operating emission controls are unavailable.16
9.2.6.3 Foreign Trade Impacts
Other factors being the same, the implementation of the
NESHAP will raise the production costs of domestic resin manu-
facturers relative to foreign producers, causing U.S. net exports
of resin to decrease.
The extent to which imports to U.S. increase will depend on
the supply elasticity of foreign-produced resin to the U.S.
Unfortunately, we have not identified any estimates of resin
import supply elasticities in the literature and the available
data does not permit us to derive our own estimate. Accordingly,
we assume that the import supply elasticity is the same as that
for domestically produced resin.
We report estimates of the dollar value of the increase in
imports associated with the implementation of the standard.
There are two sources of this increase: (1) the increase in the
quantity of goods imported; and (2) increases in prices of-
15
See Appendix B for a more detailed description of this procedure.
16 We view these as short-run estimates of reduced energy consumption.
In the long run, resources diverted from the production of DGEBPA and wet
strength resin will likely be directed to producing other goods and services.
9-24
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imported goods. The estimates we report reflect the contribu-
tions from both sources.
9.2.6.4 Regional Impacts
Substantial regional or community impacts may occur if a
plant that employs a significant percent of the local population
or contributes importantly to the local tax base is forced to
close or to reduce output because of emission control costs.
Secondary employment impacts may be generated if a substan-
tial number of plants close as a result of emission control
costs. Secondary employment impacts include those suffered by
employees of firms that provide inputs to the directly affected
industry, employees of firms that purchase inputs from directly
affected firms for end-use products, and employees of other local
businesses.
9.2.7 Affected Plants
The NESHAP is expected to affect three DGEBPA and 17 wet
strength resin plants-. Because only three DGEBPA plants are
affected, the analysis considers plant specific data for this
industry. However, because of the large number of affected wet
strength resin facilities, the analysis is based on three differ-
ent model plants that have been developed to represent the 17
plants in the industry. Appendix A describes the characteristics
of the affected DGEBPA and wet strength resin plants.
9.3 INDUSTRY PROFILE
This section describes market conditions for products that
will be affected by the NESHAP. The affected products are
diglycidyl ethers of bisphenol A (DGEBPA) which is a type of
9-25
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unmodified epoxy resin, and epichlorohydrin based non-nylon
polyamide resin (wet strength resin).
We cover the following topics in this industry profile:
Product descriptions and end uses.
Market structure.
Market trends and outlook.
Foreign trade.
Financial conditions.
9.3.1 Product Descriptions and End Uses
9.3.1.1 DEGBPA
Diglycidyl ether of bisphenol A (DGEBPA) is a type of un-
modified epoxy resin. There are several types of unmodified
epoxy resin, but the standard and most common commercial epoxy
resin is DGEBPA. In fact, DGEBPA is often referred to as "con-
ventional" epoxy resin. Epoxy resins are plastic materials which
contain a specific molecular group that reacts with different
curing agents or hardeners resulting in hard, infusible solids.
These solids have useful properties including good adhesion to
many substrates, low shrinkage, high electrical resistivity, and
good corrosion and heat resistance. Commonly used curing agents
for DGEBPA include phenolic, urea, melamine, furane, polyester,
vinyl, polyurethane and silicone.
The primary application of epoxy resin is in protective
coatings. Other applications include electrical laminates, adhe-
sives, tooling, and flooring. Industrialized nations are by far
the largest producers and consumers of epoxy resins. Table 9-4
reports patterns of consumption across end-use categories for the
years 1989 and 1990.
9-26
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Table 9-4
EPOXY END-USE CONSUMPTION
(millions of pounds)
End Use 1989
Protective coatings
Reinforced uses
Electrical laminates
Other
Export
Tooling, Casting, Molding
Bonding and Adhesive
Flooring, paving, aggregates
Other
Total
193
57
26
86
30
25
25
41
483
% of
40
11
5
17
6
5
5
8
Total
.0
.8
.4
.8
.2
.2
.2
.5
1990
195
55
31
68
28
28
28
33
464
% of T
42.
11.
6.
14 .
6.
6.
6.
7.
ota
0
9
7
7
0
0
0
1
Source: Plastics World, "Resin Report," January 1991.
9.3.1.1.1 Protective Coatings -
About 40 percent of domestic epoxy resin sales go to protec-
tive coatings markets. The primary uses of these coatings are
automobile primers and finishes, maintenance and marine coatings,
can coatings, and other product finishes. The popularity of
epoxy resins in the coatings industry is due to the high chemical
resistance, toughness, and adhesion properties.
Epoxy coatings are called high performance coatings. A high
performance coating or lining is one that is superior to paint in
adhesion, toughness, and resistance to continuing exposure to
industrial chemicals, food products, water, sea water, weather
and high humidity. These coatings are designed to protect from
corrosive or otherwise detrimental exposure, and to slow the
9-27
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breakdown of industrial structures. The coatings need to be safe
for use with materials in which they come into contact as well as
be dense and have a minimum of absorption with contacting materi-
als. Also, they should have a high resistance to the transfer of
chemicals through the coating. Finally, they should maintain a
generally good appearance even though subject to severe weather
and chemical conditions.
Epoxy surface coatings are the third most common type of
industrial finish behind alkyds and acrylics.17 Epoxies tend
to be more expensive, but have more attractive properties than
other coatings including superior adhesion, flexibility and
corrosion resistance when used on metallic substrates. However,
due to their tendency to chalk or discolor upon exposure to
sunlight they are not often used for architectural purposes.
Solid DGEBPA low-molecular weight resins are the most common type
of epoxy resin used in coatings.
There are several types of epoxy coatings.18 Each has
different properties, but all are resistant and cure by internal
linkage only. This means they need not be exposed to the air to
cure so that thick coatings can be achieved in a single appli-
cation. The primary types of epoxy coatings are amine-cured
epoxies, polyamide cured epoxies, phenolic epoxies, and coal tar
epoxies. DGEBPA can also be reacted with oils or fatty acids to
make epoxy esters and other polymers. The esters are used pri-
marily in floor finishes, primers for appliances, and maintenance
coatings. Epoxy esters accounted for approximately 5 percent of
epoxy coating demand in 1991.
17 Chemical Economics Handbook, Epoxy Surface Coatings.
18 The material in this section was taken from Pulp and Paper (1979) , Modern
Plastics mid-October Encyclopedia issue.
9-28
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Amine-cured epoxies are the most chemically resistant of the
ambient temperature cure variety (they do not require heat or
other processes to cure). However, they can be brittle and chalk
quickly when exposed to the weather. They are mostly used in
industry where an air-dry coating is required and the need for
chemical resistance is high. Urea and Melamine are two of the
curing agents used to make amine-cured epoxies.
Polyamide cured epoxies are somewhat less chemically resis-
tant than amine-cured epoxy. However, they have much better
weather resistant qualities. The coating is non brittle and
fairly flexible. It has excellent resistance to alkali and to
water. The uses of this type of resin are broad based and include
maintenance coatings for most industries including the chemical,
paper, marine, atomic power, and food industries.
Epoxy-phenolic systems offer chemical resistance along with
excellent mechanical properties. When they are heat cured, they
are the strongest and most resistant of the epoxy coatings. For
this reason, they are used for chemically resistant coatings on
process equipment, tank and drum linings, pipe linings, and for
protection from direct exposure to various chemicals. They are
also commonly used for exposure to solvents, vegetable and animal
oils, fatty acids, foods, and alkalis.
Coal tar epoxy coatings have good chemical resistance, rea-
sonable weather resistance, and outstanding resistance to fresh
and salt water, brine, and hydrogen sulfide. More generally,
they are resistant to both acidic and alkaline conditions. They
are one of the most durable coatings for the protection of con-
crete and metal, either under water or above water, against cor-
rosive elements. These resins are black and so have limited
decorative use, and, of course, can be used only where black is
acceptable. They are used throughout the chemical industry and
in the marine industry, both on ships and on offshore structures.
9-29
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The following is a list of some specific uses of epoxy
coatings.
Heavy duty industrial and marine maintenance coatings.
Tank linings.
Industrial floorings.
Coatings for farm and construction equipment.
Aircraft primers.
Floor and gymnasium finishes.
Maintenance coatings.
Metal decorating finishes.
Pipe coatings.
Container coatings.
Electrodeposition primers for automobiles.
Solder masks.
Beverage and food can coatings.
Appliance primers.
Hospital and laboratory furniture.
Coating for jewelry and hardware.
Impregnating varnishes.
9.3.1.1.2 Bonding and Adhesives -
Because of their excellent adhesion to many substrates,
epoxy resins are widely used as high performance adhesives. For
example, because of their extraordinary adhesion to metal they
are used in the automobile, aircraft and construction industries.
According to the September 1990 issue of Chemical Marketing
Reporter, about 80 percent of epoxy adhesive sales go into the
automobile and construction industries. According the Chemical
Economics Handbook, production of epoxy adhesives and sealant
grew at an average annual rate of 8 to 8.5 percent from 1983
through 1989.
9-30
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9.3.1.1.3 Molding, Casting, and Tooling -
Uses in this category include encapsulation of electrical
components by epoxy molding compounds. Also, epoxy casting
resins are used as prototypes and master models in the manufac-
ture of tools. Epoxies based on ultraviolet light stable struc-
tures are used in the casting of outdoor insulators switch gear
components and instrument transformers.
9.3.1.1.4 Laminating and Composites -
Epoxy-based laminates are used in printed wiring boards,
such as those used in computers and complex telecommunication
equipment. Epoxy compounds are used in filament-wound glass
reinforced pipe in oil field applications, in the manufacture of
pressure vessels and tank and rocket motor casings, chemical
plants, water distribution, and as electrical conduits. In the
aerospace industry, graphite fiber-reinforced multifunctional
epoxy resin composites are becoming standard.
9.3.1.1.5 Building and Construction -
Epoxies are used in flooring, to repair bridges, roads, and
cracks in concrete, to coat reinforcing bars, and to perform as
binders for patios, swimming pool decks and the soil around oil
well drills.
9.3.1.2 Wet Strength Resins
Polyamide-epichlorohydrin or wet strength resins are a type
of non-nylon polyamide resin sold almost exclusively in the paper
additives market. Approximately 90 percent of these resins are
used to improve the wet tensile strength of paper products.
Other uses of these resins in the paper industry include floccu-
lent, drainage and drying aids, dry creping aids, cationizing
9-31
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agent for unmodified (pearl) potato and tapioca starch (used for
dry strength), and as a component of paper surface finishes.
Paper which has been treated with a wet strength resin shows
greater resistance to rupture or disintegration when exposed to
water. Note that wet strength is defined as tensile strength
when the paper is completely absorbed with water, not water
repellency. There are three primary types of wet strength
resins: (1) Urea-formaldehyde resins, (2) melamine formaldehyde
resins, (3) polyamide-polyamine epichlorohydrin and modifica-
tions. It is the third category that includes EPI-based non-
nylon polyamide resins. Other wet strength additives include
those made from polyacrylamide, dialdehyde starch, polyacrolein
resin, and cellulosic resin. The wet strength of paper increases
almost linearly with the addition of wet strength resin up to a
point. Beyond this threshold the addition of wet strength resin
has little affect on the wet strength of the paper.
There are a large number of uses for paper which retains
tensile strength when wet. Examples include tea bags, paper
towels, and paper groceries bags.
Demand for this type of paper is most likely inelastic be-
cause of its "necessary" nature and the small percentage of income
which is typically spent on these types of products. Specifically
wet strength resins are used for protection against:19
Exposure to water of paper products used as drying or
wiping media. Examples are paper towels, napkins,
windshield wiping tissue, industrial wiping towels,
lens paper, and facial tissue.
Exposure to weather. Examples are packing cases, out-
door posters, building papers, paper bags, maps, and
mulch paper.
19 This list was drawn from Pulp and Paper (1979) .
9-32
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Wrapping for wet materials. Examples are butcher
wraps, fruit and vegetable wraps and boxes, frozen and
prepared food packages, and foil wrapped wet wipes.
Exposure to water by immersion in a processing opera-
tion. Examples are photographic paper, copy print
paper, filter paper, saturating paper, and tea bag
paper.
Disposables used in place of textiles. Examples are
hospital bed sheets, hospital gowns and other sanitary
single-use garments.
9.3.2 Market Structure
DGEBPA and wet strength resin are produced by a few large
corporations, and many of these are conglomerates. Accordingly,
market concentration is relatively high and vertical integration
is common.
9.3.2.1 DGEBPA
The major producers of basic liquid epoxy resins (DGEBPA)
are Dow Chemical Company, Ciba-Geigy Corporation, and Shell Chem-
ical Company. They are also the largest producers of any type of
unmodified epoxy resin - each having production rates on the
order of 45.4 million kilograms per year. These three large
companies have been producing epoxy resin for at least 12 years.
Shell and Dow Chemical are also major producers of epichloro-
hydrin and bisphenol-A which are the primary feedstocks for
epoxy. While Ciba-Geigy is not similarly backward integrated, it
is a significant player in markets for further processed epoxy
products, including formulated systems, electronic materials and
composite materials.20 These facts suggest that the market is
fairly concentrated. Together, these three producers were
20 CEH (1991) Epoxy Resins.
9-33
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responsible for approximately 60 percent of unmodified epoxy
resin production in 1990.21
DGEBPA and other types of unmodified epoxy resin are rea-
sonably good substitutes. For this reason, entry and exit from
the entire unmodified epoxy resin industry is worth examining.
Table 9-5 lists companies who produced unmodified epoxy resin at
some time over the period 1980 to 1991. An "X" in the column
under a given year indicates that the company produced epoxy
resin in that year. These lists of manufacturers comprise only
those companies which responded to inquiries from the Society of
the Plastics Industry. However, SPI's Committee on Resin Statis-
tics estimates that these manufacturers account for about 95 per-
cent of unmodified epoxy production.22
Table 9-5
COMPANIES PRODUCING UNMODIFIED EPOXY RESIN, 1980-1991
Company Name
Celanese Plastics
Ciba-Geigy
Dow Chemical
Reichold Chemical
Shell
Union Carbide
Morton Industries
Rhone Poulenc Inc.
Interez
Hi-Tek Polymers*
80
X
X
X
X
X
X
X
81
X
X
X
X
X
X
X
82
X
X
X
X
X
X
X
83
X
X
X
X
X
X
84
X
X
X
X
X
X
85
X
X
X
X
X
X
86
X
X
X
X
X
X
87
X
X
X
X
X
X
88
X
X
X
X
X
X
89
X
X
X
X
X
X
90
X
X
X
X
X
X
91
X
X
X
X
X
X
* Hi-Tek Polymers was owned by Rhone Poulenc in 1989
Source: Society of the Plastics Industry 1.
21 SPI I and MRI (1992).
22
Source: SPI II.
9-34
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Over the last 12 years the list of manufacturers has had no
more than 7 companies on it, and, beginning'in 1984, has had only
six. Since 1980, only four companies have entered or exited. The
average duration of manufacture over the 12 years from 1980 to
1991 was 8.3 years.
9.3.2.2 Wet Strength Resins
Firms which produced epichlorohydrin based non-nylon polyam-
ide resins in either 1988 or 1990 are listed in Table 9-6. An
"X" in the column under a given year means that the company pro-
duced the resin in that year, an "0" means that they did not.
Over the two years of data, there were two entries into and one
exit from this industry.
Table 9-6
COMPANIES PRODUCING EPI BASED NON-NYLON POLYAMIDE RESINS,
1988 AND 1990
Borden
Callaway Chemical*
Georgia Pacific Corp.
Henkel of America, Inc.
Hercules Inc.
Trinova Corp.
Pioneer Plastics
Akzo
1988
X
X
X
X
X
X
O
o
1990
X
X
X
X
X
0
X
X
* A subsidiary of Exxon Corporation.
Source: Chemical Economics Handbook and MRI (1992).
9-35
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In 1988, Hercules accounted for approximately 80 percent of
the production of EPI-based polyamide. Henkel, Georgia-Pacific,
Borden and Callaway each accounted for about 5 percent of the
market. Trinova produced very little. It is unclear exactly what
percentage of the market is controlled by Hercules in 1990.
However, two Borden plants, five Hercules plants, and one Akzo
plant together accounted for 80 percent of production in 1990.23
Raw materials for epichlorohydrin based polyamide resin in-
clude adipic acid, diethylenetriamine, and epichlorohydrin. No
producer of epi-based polyamide resins also produced these feed-
stocks as of 1988.
As of 1991 Georgia Pacific owned or controlled over 6 million
acres of timber and timberlands. They were also producing pulp
and paper (8 percent of U.S. annual capacity), containerboard and
packaging, uncoated free sheet paper, tissue, envelopes and other
paper products. Hercules was producing various paper products in
addition to wet strength resins in 1991.
9.3.3 Market Outlook
While domestic production of both DGEBPA and wet strength
resin has fluctuated, the long-term trend has seen increased
output of both products. DGEBPA prices have been relatively
stable recently, but wet strength resin prices have fallen. The
demand for both products is expected to increase moderately over
the next few years.
9.3.3.1 DGEBPA
Domestic production of unmodified resins has fluctuated
somewhat over the twenty year period 1971 to 1990. However, pro-
23 MRI (1992) .
9-36
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duction has increased on average by about 7 percent annually over
this time.24 DGEBPA comprised about 60 percent of total unmod-
ified epoxy resin production in 1990. Nominal prices peaked at
$2.89 (per kilogram) in 1984 and since then have fluctuated
around $2.40.25
Two recently published industry reports predict that U.S.
epoxy resin production will experience healthy growth to the end
of the 1990's. Network Consulting Inc. (1992) expects a 4 per-
cent annual growth in domestic production to last through 1997.
The Freedonia Group (1992) predicts North American production,
which is dominated by U.S. firms, to grow at an annual rate of
4.4 percent to 1995.
v -
The Freedonia Group attributes expected growth to an expand-
ing export market which they predict will reach 300 million
pounds by 1995. However, they expect the heavy growth in exports
to be countered by a slower growth in North American consumption,
which they expect to be just 3 percent per year.
Network Consulting, Inc. (1992) base their projections of
growth on the recovery of the U.S. economy and the advent of en-
vironmental regulations which favor the use of epoxies in high
solids and powder coatings. In recent years, environmental pres-
sures have resulted in the rapid development of these epoxy pro-
ducts because they use substantially less organic solvent but
retain the useful chemical and physical properties of epoxies.
The Freedonia Group expects epoxy adhesives to grow at
4.4 percent per year to 1995, reaching 37 million pounds. They
expect epoxy coatings to grow four tenths of a percent faster
24 Computed from data in USITC I.
25 USITC I.
9-37
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than the overall coatings market at 2.8 percent per year to 1995.
This means that by 1995, 235 million pounds of epoxy resin will
be used in coatings.
Chemical Economics Handbook estimates that between 1983 and
1988 the use of epoxy resins in adhesives and sealants grew at an
average rate of about 8.5 percent per year. An increase of about
7 percent occurred in 1989. Between 1989 and 1994, growth in the
consumption of epoxy adhesives is expected to slow slightly to a
6 percent annual rate. They expect growth to be driven by the
increasing use of resin based composites in aerospace, automotive
and recreational markets. Also, there is a trend toward using
epoxies instead of more expensive welds, especially in the auto-
motive market. Technological advances may also contribute to the
growth of epoxy adhesives. Improvements have been made in
various properties including adhesion to plastics and toughness,
and new systems have been introduced that allow faster bonding at
lower initiation temperatures.
Chemical Economics Handbook estimates that epoxy surface
coatings grew at an average annual rate of 3.5 to 4 percent
between 1986 and 1990. They expect this growth to slow to 3 to
3.5 percent presently. Furthermore, they report that the con-
sumption of epoxy esters will decline due to their adverse
effects on the environment. On the other hand powder coatings
are projected to grow at 5 to 10 percent annually because of the
high quality of the coating and the lack of adverse environmental
effects. Consumption of epoxy resins in surface coatings is pro-
jected by CEH to reach 215-220 million pounds by 1995.
9.3.3.2 Wet Strength Resins
The growth rate of production for non-nylon polyamide was
more volatile than that of epoxy over the period 1971-1990. For
example, production increased by 73 percent in 1974 and fell by
9-38
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49 percent in 1975. However, the average growth rate of produc-
tion was somewhat greater than that of epoxy, about 10 percent
annually. The nominal price reached $2.54 per kilogram (dry
weight basis) in 1985, but has since declined. Production and
prices both fell sharply in 1990. Production fell by about 26
percent in 1990 and price declined substantially to $1.50 a
level it had not been below since 1972.26
In 1987, Chemical Economics Handbook reported that the grow-
ing trend to use neutral-cure wet-strength resins as replacements
for formaldehyde based (melamine and urea) resins would continue
through 1992, and that it would account for strong increases in
the demand for wet strength resins. Urea formaldehyde and
melamine formaldehyde resins are inferior as wet strength addi-
tives in unbleached paper production because of their acid curing
characteristics. Specifically, they can cause embrittlement and
deterioration of paper as well as reduce absorbency. Demand for
epichlorohydrin based polyamide was predicted to continue to in-
crease at a rate of 5 to 6 percent annually from 1987 through
1992. Production of non-nylon polyamide was somewhat erratic
over the period 1987 through 1990, experiencing 10 percent
decline in volume in 1990.
9.3.4 Foreign Trade
9.3.4.1 DGEBPA
Table 9-7 shows exports and imports of epoxy resin in mil-
lions of kilograms per year from 1981 through 1991 as reported by
the U.S. Department of Commerce. The table also reports imports
divided by exports.
26 USITC I (various issues).
9-39
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Table 9-7
U.S. TRADE IN EPOXY RESIN
(millions of kilograms)
Year
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
Exports
42.3
45.7
41.5
44.5
40.5
44.0
55.7
69.0
85.1
94.4
97.9
Imports /Exports
.05
.05
.07
.09
.14
.18
.12
.09
.07
.09
.11
Source: U.S. Department of Commerce, Bureau of the Census.
According to the Bureau of the Census, exports in 1991
i
amounted to 97.9 million kilograms. In 1989 the principle desti-
nations were: Far East countries other than Japan, which accounted
for 27 percent; Canada which accounted for 23 percent; Western
Europe, 21 percent; Japan, 11 percent; and Mexico, 7 percent.
Imports have been fairly stable and relatively small in
volume through the eighties. In 1989, an estimated 50 percent of
the imported epoxy resins were used in coatings, and the remain-
der went primarily into adhesives and electronic encapsulation.
9.3.4.2 Wet Strength Resins
Table 9-8 shows exports and imports of non-nylon polyamide
resins in millions of kilograms per year from 1981 through 1991.
The ratio of exports to domestic production, import to domestic
production and imports to exports are also reported.
9-40
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Table 9-8
U.S. TRADE IN NON-NYLON POLYAMIDE
(millions of kilograms)
Year
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
Exports
5.0
3.6
4.1
4.4
5.3
4.5
6.1
10.2
5.9
6.2
n. a.
Imports
n. a .
n. a .
0.8
1.1
1.1
1.2
1.2
1.1
3.8
4.7
6.1
Imports/
Exports
n.a .
n.a.
.19
.24
.21
.26
.19
.11
.64
.76
n.a.
Sources: U.S. Department of Commerce (1992), USITC.
Exports fluctuated considerably during the 1980's, reaching
a high of 10.2 million kilograms in 1988 and a low of 3.6 million
kilograms in 1982. However, in most years exports ranged between
4 and 6 million kilograms. Imports were more stable over the
period hovering around 1 million kilograms until 1988. However,
in 1989 and 1990 imports of non-nylon polyamide increased.
9.3.5
FINANCIAL DATA
Baseline financial data for firms producing resins are
displayed in Table 9-9. The ratio of net income to assets and
the ratio of long term debt to long term debt plus equity are
reported in the table. In order to compensate for cyclical fluc-
tuations, net income over assets figures were averaged over the
years 1988 through 1991. The long term debt ratio is reported
for 1991.
9-41
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Table 9-9
FINANCIAL DATA FOR RESIN PRODUCERS
Hercules
Shell
Dow
Ciba Geigy
Borden
Exxon
Georgia Pacific
Henkel
NI/A*
(average 1988-1991)
.02
.03
.09
.05
.05
.06
.04
.05
LTD/ (LTD+E)
(1991)
.22
.11
.39
.20
.41
.20
.58
.14
Source: Moody's Industrial Manual 199T, Annual Reports 1991
* NI = net income
LTD = long term debt
A = assets
E = equity
Most of the resin producers are earning between a 4 and 6
percent return on their assets. Dow is earning by far the
largest return at 9 percent. Hercules and Shell show the poorest.
returns at 2 and 3 percent, respectively.
Shell and Henkel have the smallest long term debt ratios at
less than 0.15 each. Hercules, Ciba Geigy and Exxon are a little
larger at around 0.2 each. Dow and Georgia Pacific have the
highest ratios.
9.4 PRIMARY ECONOMIC IMPACTS AND CAPITAL AVAILABILITY ANALYSIS
9.4.1
Introduction
This section presents estimates of the primary economic im-
pacts which would result from the implementation of the NESHAP
9-42
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and the results of the capital availability analysis. We also
present results for Option I for the wet strength resin industry.
Primary impacts include changes in market prices and output
levels, changes in the value of shipments by domestic producers,
and plant closures. The capital availability analysis assesses
the ability of affected firms to raise capital and the impacts of
control costs on plant profitability.
9.4.2 Estimates of Primary Impacts
As explained earlier in Section 9-2, we use partial equilib-
rium models of the affected industries to estimate primary im-
pacts. The increase in production costs resulting from the pur-
chase and operation of emission control equipment causes an
upward, vertical shift in the domestic supply curves. The height
of this shift is determined by the after tax cash flow required
to offset the per unit increase in production costs. Because
control costs vary across plants within each industry segment,
the post-control supply curves are segmented. We assume a worst
case scenario in which plants with the highest control costs (per
unit of output) are marginal (highest cost) in the post-control
market.
Foreign supply (net imports) is assumed to have the same
elasticity as domestic supply in both markets.27 Foreign and
post-control domestic supply are added together to form total
market post-control supply. The intersection of post-control
market supply curve with market demand determine the new market
equilibrium price and quantity. The post-control domestic
27 The United States is a new exporter of both DGEBA and wet strength
resin. Trade in DGEBA is substantial. Net exports accounted for approximately
15 percent of production in 1990. However, trade in wet strength resin is
insignificant. The small volume of trade is due to the custom of shipping only
the polyamide and letting the receiving company complete the epichlorohydrin
reaction. In 1988 exports accounted for about 1 percent of domestic wet
strength resin production, and imports were only a small fraction of exports.
9-43
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output is given by post-control market output less post-control
imports.
Table 9-10 presents the primary impacts predicted by the
partial equilibrium analysis for the DGEBPA and wet strength
resin industries. For example, we estimate that the NESHAP will
result in a 0.12 cent per kilogram (0.05 percent) increase in the
price of DGEBPA and an annual reduction in domestic production of
about 106 metric tons (0.08 percent of baseline production). We
also estimate that the NESHAP will cause the annual value of
domestic shipments to fall by about $108,000 (0.03 percent). No
plant closures are predicted.
Table 9-10 also shows the estimated impacts on the wet
strength resin industry, both for the MACT Floor and Option I.
Estimated price and output changes range from very small impacts
associated with Option I to larger impacts under the MACT Floor.
Under the MACT Floor, estimated increases in price and decreases
in domestic production are approximately 4 percent, and about
I plant closure is possible28. However, under Option I, price
and output impacts are only 0.22 percent and 0.20 percent,
respectively, and no plant closures are predicted.
We emphasize that the assumptions we adopt in our analysis
are likely to cause us to overstate predicted plant closures.
First, we assume that the plant with the highest per unit emis-
sion control costs also is the least efficient in that it has the
highest baseline per unit production costs. Second, we assume a
national market, but regional trade barriers might afford some
protection for some plants. Finally, the production of wet
strength resin is intermittent. When our analysis predicts a
2 8
Table 4-1 reports fractions of plant closures. The 0.63 plant
closure predicted for the wet strength resin industry means that we estimate
that the marginal plant would lose 63 percent of its annual production.
9-44
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Table 9-10
ESTIMATED PRIMARY IMPACTS ON DGEBPA
AND WET STRENGTH RESIN MARKETS
IMPACT
Price Change
C/kilograma
Percent
Annual Change in
Domestic Output
Metric Tonsb
Percent
Annual Change in
Value of Domestic
Shipments
$l,000a
Percent
Plant Closures
DGEBPA
.12
.05
-106
-.08
-108
-.03
.00
WET STRENGTH RESIN
MACT Floor Option I
.84
4.19
-7347
-3.73
-
-123
-.31
.63
.04
.22
-404
-.20
7
. 02
. 03
a 1992 dollars.
b Wet weight basis.
plant closure, it means that the plant will cease production of
wet strength resin, but not close operations altogether.
The estimated primary impacts reported above depend on a set
of parameters used in the partial equilibrium model of the wet
strength and DGEBPA resin industries. One of the parameters, the
elasticity of demand, measures how sensitive buyers are to price
changes. The estimated impacts reported above are based on a
demand elasticity of -0.92 for the wet strength market and -1.5
for the DGEBPA market. In Appendix D, we report the results of
analyses that show the sensitivity of the estimated impacts to
changes in the demand elasticity. The "low" elasticity case
9-45
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adopts a demand elasticity of -0.5 for the wet strength resin
industry and -0.62 for the DGEBPA industry. The results -show
slightly larger price increases, smaller reductions in market
output and less adverse impacts on domestic producers than
results reported above.29 The "high" elasticity case uses a
demand elasticity of -1.34 for the wet strength resin industry
and -3.10 for the DGEBPA industry. In general, this case shows
slightly smaller price increases but more adverse impacts on
domestic producers. However, the sensitivity analysis generally
shows that the estimated primary impacts are relatively insensi-
tive to reasonable ranges of demand elasticity estimates.
Also, the estimated impacts reported in Table 9-10 is based
\.
on the assumption that plants with the highest emission control
costs (per unit of output) are marginal (highest cost) producers
in the post-control market. This assumption causes the adverse
impacts associated with the regulatory alternatives to be over-
stated.
9.4.3 Capital Availability Analysis
The capital availability analysis involves examining pre-
and post-control values of selected financial ratios. These
ratios include net income divided by assets and long term debt
divided by the sum of long term debt and equity. In order to
reduce the effects of year-to-year fluctuations in net income, a
four-year average (1988 through 1991) of net income over assets
was used as the baseline. Changes in the long term debt ratio
represent structural changes and so are not subject to the same
cyclical fluctuations. Long term debt ratios from 1991 were used
as the baseline.
29 Also, the plant closure previously predicted for the wet strength
resin industry under the MACT Floor is no longer predicted when a "low"
elasticity of demand is assumed.
9-46
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As explained in Section 9-2, these financial statistics lend
insight into the ability of affected firms to raise the capital
needed to acquire emission controls. They provide estimates of
the changes in profitability which would arise from the implemen-
tation of the NESHAP.
To calculate the post-control ratio of net income to assets,
annualized control costs were subtracted from pre-control net
income, and capital control costs were added to pre-control
assets. To calculate the post-control long term debt ratio,
capital control costs were added to pre-control long term debt,
both the numerator and denominator of this ratio. Note that both
post-control ratios reflect a worst-case assumption that affected
firms are required to absorb emission control costs without the
benefit of higher market prices.
Financial data are available for all three DEGBPA producers
and 5 of the 7 wet strength resin producers. The 5 wet strength
producers own 15 of the 17 facilities.
All of the companies that produce DGEBPA and wet strength
resins are large corporations. As a result, emission controls
costs, which are relatively small, have no perceptible impacts on
the firm's financial ratios after rounding. Accordingly, we con-
clude that affected companies will not find it difficult to raise
the capital necessary to purchase and install the required emis-
sion controls.
9.4.4 Limitations of Estimated Primary Impacts
Several qualifications of the estimated primary impacts
presented in this section need to be made. A single market for
homogeneous output is assumed in the partial equilibrium analy-
sis. However, there may be some regional trade barriers which
would protect producers. Furthermore, the analysis assumes that
9-47
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plants with the highest per unit emission control costs are
marginal post-control. This assumption will cause the impacts
presented above to be overstated since market impacts are deter-
mined by the costs of marginal plants. Finally, some plants may
find that the price increase resulting from regulations make it
profitable to expand production. This would occur if a firm
found its post-control incremental unit costs to be smaller than
the post-control market price. Expansion by these firms would
result in a smaller decrease in output and increase in price than
otherwise would occur.
We have also noted that the estimated primary impacts depend
on the parameters of the partial equilibrium model. The results
of the sensitivity analyses presented in Appendix D, which are
based on a larger (more elastic) estimate of demand elasticity,
show slightly more adverse impacts on domestic producers.
The capital availability analysis also has limitations.
First, future baseline performance may not resemble past levels.
Second, the tools used to measure the impact of controls are
limited in their scope. Finally, the financial analysis is based
on a worst-case assumption that affected establishments will
fully absorb emission control costs without the benefits of
higher prices.
9.4.5 Summary of Primary Impacts
The estimated impacts of the NESHAP on the DGEBPA industry
is relatively small. Predicted price increases, reductions in
domestic output and the value of domestic shipments for the
DGEBPA industry are 0.08 percent or less. The impacts estimated
under the MACT Floor for the wet strength resin industry are
somewhat more adverse. Predicted price increases, reductions in
domestic output and the value of domestic shipments for the MACT
Floor are about 4 percent, and one plant closure is possible.
9-48
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Under the Option I Scenario, however, predicted price increases,
reductions in domestic output and the value of domestic shipments
are 0.22 percent or less, and no plant closures are expected. As
noted earlier, these results are likely to overstate the true
adverse impacts. Finally, because emission control costs are
very small relative to the financial resources of affected pro-
ducers, they should not find it difficult to raise the capital
necessary to finance the purchase and installation of emission
controls.
9.5 SECONDARY ECONOMIC IMPACTS
9.5.1 Introduction
This section presents estimates of the secondary economic
impacts that would result from the implementation of the NESHAP.
Secondary impacts include changes in employment, energy use, and
foreign trade and regional impacts.
9.5.2 Labor Impacts
The estimated labor impacts associated with the NESHAP are
based on the results of the partial equilibrium analyses of the
two resin industries. These estimated impacts depend primarily
on the estimates of reduction in domestic production reported
earlier in Section 9-4.30 Note that changes in employment due
to the operation and maintenance of control equipment have been
omitted from this analysis due to lack of data. Also, the esti-
mated employment impacts reported below do not include potential
employment gains in industries which produce substitute commodi-
30 More specifically, we estimate employment impacts by assuming that
labor use per unit of output will remain constant when the quantity of output
changes. Production worker hours per dollar of output was calculated from
1989 Annual Survey of Manufactures and a producer price index for chemicals
and allied products obtained from the Economic Report of the President 1991.
See Appendix B for a more detailed discussion.
9-49
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ties that might benefit from reduced DGEBPA and wet strength
resin production. Thus, the changes in employment estimated in
this section reflect only the direct employment losses due to
reductions in domestic production of DGEBPA and wet strength
resin.
Table 9-11 presents estimates of employment losses for each
of the two industries. As Table 9-11 indicates, the estimated
job losses are small (up to two production jobs). As expected,
the estimated employment losses in the wet strength resin indus-
try are smaller for Option I than for the MACT Floor. The
generally small impacts occur primarily because only small reduc-
tions in output are expected to occur as a result of the imple-
mentation of the NESHAP. Also, the industry is characterized by
a relatively high output/employment ratio or low labor intensity.
Table 9-11
ESTIMATED EMPLOYMENT LOSSES
IMPACT
Lost Jobs
Percent Loss
DGEBPA
0.34
0.08
Wet Strength
Resin, MACT
Floor
1.84
3.73
Wet Strength
Resin,
Option I
0.10
0.20
NOTE: Estimates do not include potential employment gains due to operating and
maintaining emission controls.
9-50
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9.5.3
Energy Use Impacts
The approach we employ to estimate reductions in energy use
is similar to the approach employed to estimate labor impacts.
Again, these impacts depend primarily on the estimated reductions
in domestic output reported earlier in Section 9-4. Note that
the changes reported below do not account for the potential
increases in energy use due to operating and maintaining emission
control equipment. This omission is due to lack of data.
Table 9-12 presents changes in the use of energy by each
industry. As expected, the estimated changes in energy use are
minor because only small reductions in ^output are expected as a
result of the implementation of the NESHAP. The change in the
use of energy by the wet strength resin industry differs substan-
tially between the MACT Floor and Option I. Much smaller energy
use reductions are expected under Option I.
Table 9-12
ESTIMATED ENERGY USE REDUCTIONS
INDUSTRY/ IMPACT
DGEBPA
Wet
Wet
$1,000 1992
Percent Reduction
Strength Resins (MACT Floor)
$1,000 1992
Percent Reduction
Strength Resins (Option I)
$1,000 1992
Percent Reduction
8
0
45
3
2
.51
.08
.55
.73
.50
.20
NOTE: Estimates do not include potential increases in energy use due to
operating and maintaining emissions controls.
9-51
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9.5.4
Foreign Trade Impacts
Other factors being the same, the implementation of the
NESHAP will raise the production costs of domestic resin manufac-
turers relative to foreign producers, causing U.S. imports of
resin to increase and U.S. exports to decrease. The effects of
the regulation on both the quantity and the value of net exports
(exports-imports) are reported in Table 9-13.
The estimated trade impacts are small, both because of small
predicted domestic price increases and because of the relatively
small amount of trade that exists currently for the two products.
For example, we estimate that the implementation of the standard
will result in reduced DGEBPA net exports of about 20 metric tons
annually (about .12 percent of baseline net exports) or about
$38,000 per year. Note that we predict only a slight change in
the dollar value of wet strength resin exports under both the
Table 9-13
ESTIMATED IMPACTS ON NET EXPORTS
INDUSTRY /IMPACT
DGEBPA
Volume (metric tons)
Percent Change (volume)
Value ($1,000 1992)
Wet
Wet
Strength Resins (MACT Floor)
Volume (metric tons)
Percent Change (volume)
Value ($1,000 1992)
Strength Resins (MACT Floor)
Volume (metric tons)
Percent Change (volume)
Value ($1,000 1992)
-20
-.12
-38
-73
-3.73
1.23
-4
-.21
.06
NOTES: Dollar estimates of trade impacts are adjusted for higher post-
control prices. Changes in trade volumes are reported on a wet
weight basis.
9-52
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MACT Floor and Option I, even though we estimate that the volume
of exports will fall by about 73 metric tons annually under the
MACT Floor, and 4 metric tons annually under Option I. In either
case, the higher post-control prices offset (approximately) the
reduced physical volume of exports.
9.5.5 Regional Impacts
No significant regional impacts are expected from the imple-
mentation of the NESHAP because estimated employment impacts are
small.
9.5.6 Limitations of Estimated Secondary Impacts
v
Our estimates of the secondary impacts associated with the
NESHAP are based on changes in market equilibria predicted by the
partial equilibrium models of the two affected markets. Accord-
ingly, the caveats we discussed earlier in Section 9-4 for the
primary impacts apply as well to our estimates of secondary
impacts.
As noted earlier, the estimates of employment impacts do not
include potential employment gains due to operating and maintain-
ing emission control equipment or employment gains in the manufac-
turing of substitute products. Similarly, the estimates we report
exclude potential indirect employment losses in industries that
supply inputs to the resin industries. In short, the reported
estimates of employment impacts include only direct production job
losses in the DGEBPA and wet strength resin industries.
9.5.7 Summary of Secondary Impacts
The estimated secondary economic impacts of the alternative
NESHAP are generally small. Estimated employment and energy
impacts are small because only small reductions in industry out-
9-53
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put are expected. The estimated trade impacts are minor because
only small domestic price increases are expected and because
baseline trade volumes for the affected products are small. No
significant impacts on regional economies are expected.
9.6 POTENTIAL SMALL BUSINESS IMPACTS
Firms in the DGEBPA and wet strength resin industries are
classified as "small businesses" if they employ fewer than 750
employees.31 No DGEBPA producer satisfies the criteria for a
small business.32 The three DGEBPA producers, Shell, Ciba-
Geigy and Dow Chemical, employed over 30 thousand people in 1991.
Ciba-Geigy employed over 90 thousand people in 1991. Employment
data are available for 5 of the 7 wet strength facilities. Of
the five, the company employing the fewest people was Hercules at
approximately 15 thousand employees. No wet strength resin pro-
ducer for which we have employment data comes close to qualifying
as a small business. Table 9-14 shows the total employment of
resin producing companies in 1991.
The Small Business Administration defines a small business
as one which is not dominant in its field. There are three pro-
ducers in the DGEBA industry. Each producer has a substantial
market share.
The EPA Guidelines for Implementing the Regulatory Flexibil-
ity Act state that the definition of a small business is "any
business which is independently owned and operated and not domi-
nant in its field." The three corporations producing DGEBA each
31 EPA (1992) . EPA Guidelines for Implementing the Regulatory Flexibility
Act, Revised April 1992, Appendix C. Small Business Size Regulations, 13 CFR
Part 121.
32 EPA may adopt an alternative definition of a small business if an alter-
native size cutoff can be justified.
9-54
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Table 9-14
EMPLOYMENT OF RESIN PRODUCERS
Company Name
Employment in 1991
Georgia Pacific
Henkel
Hercules
Dow
Borden
Exxon
Ciba-Geigy
Shell
over 52,000
41,000
15,000
62,000
44,000
101,000
91,000
30,000
Source: 1991 Annual Reports
have substantial market share. Similarly, the producers of wet
strength resin are typically large conglomerates which employ
well over 750 people.
9.7 ECONOMIC COSTS
Estimates of the economic costs associated with the imple-
mentation of the NESHAP for the DGEBPA and wet strength resin
industries are presented below in this section of the report.
9.7.1 Economic Costs of Emission Controls: Conceptual Issues
Air quality regulations affect society's economic well-being
by causing a reallocation of productive resources within the
economy. Specifically, resources are allocated to the production
of cleaner air and away from other goods and services that could
otherwise be produced. Accordingly, the economic costs of emis-
sion controls can be measured as the value that society places on
those goods and services not produced as a result of resources
being diverted to the production of improved air quality. The
conceptually correct valuation of these costs requires the iden-
9-55
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tification of society's willingness to be compensated for these
foregone consumption opportunities that would otherwise be avail-
able.33
In the discussion that follows, we distinguish between emis-
sion control costs and the economic costs associated with the
regulatory alternatives. The former are measured simply as the
annualized capital and annual operating and maintenance costs of
controls under the assumption that all affected plants install
controls. As noted above, economic costs reflect society's will-
ingness to be compensated for foregone consumption opportunities.
Estimates of emission control costs will correspond to the
conceptually correct measure of economic costs only if the fol-
lowing conditions hold:
Marginal plants affected by an alternative standard
must be able to pass forward all emission control costs
to buyers through price mark-ups without reducing the
quantity of goods and services demanded in the market.
The prices of emission control resources (e.g., pollu-
tion control equipment and labor) used to estimate
costs must correspond to the prices that would prevail
if these factors were sold in competitive markets.
The discount rate employed to compute the present value
of future costs must correspond to the appropriate
social discount rate.
Emission controls do not affect the prices of goods
imported to the domestic economy.
33 Willingness to be compensated is the appropriate measure of economic
costs, given the convention of measuring benefits as willingness to pay.
Under this convention, the potential to compensate those members of society
bearing the costs associated with a policy change is compared with the
potential willingness of gainers to pay for benefits. See Mishan (1971).
9-56
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9.7.1.1 Market Adjustments
A plant is marginal if it is among the least efficient pro-
ducers in the market and, as a result, the level of its costs
determine the post-control equilibrium price. A marginal plant
can pass on to buyers the full burden of emission control costs
only if demand is perfectly inelastic. Otherwise, consumers will
reduce quantity demanded when faced with higher prices. If this
occurs, estimated control costs will overstate the economic costs
associated with a given air quality standard.
The emission control costs estimates do not reflect any
market adjustments that are likely to occur as affected plants
and their customers respond to higher post-control production
costs. The estimates of economic costs presented later in this
section do reflect estimates of such market adjustments.
9.7.1.2 Markets for Emission Control Resources
Other things being the same, estimated emission control
costs will overstate the economic costs associated with an alter-
native air quality standard if the estimates are based on factor
prices (e.g., emission control equipment prices and wage rates)
which reflect monopoly profits earned in resource markets.
Monopoly profits represent a transfer from buyers to sellers in
emission control markets, but do not reflect true resource costs.
The extent to which sellers in emission control markets
possess monopoly power has not been investigated. Consequently,
we assume in this study that emission control resources are
traded in competitive markets. The estimated economic costs
reported in this section are overstated if this assumption does
not hold.
9-57
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9.7.1.3 The Social Discount Rate
The estimates of annualized emission control costs presented
earlier in this report were computed by adding the annualized
estimates of capital expenditures associated with the purchase
and installation of emission control equipment to estimates of
annual operating and maintenance costs. Capital expenditures
were annualized using a 7 percent discount rate. The private
cost of capital is appropriate for estimating how producers
adjust supply prices in response to control costs.34 In order
to estimate the economic costs associated with the NESHAP, an
appropriate measure of the social discount rate should be used in
the amortization schedule.
There is considerable debate regarding the use of alterna-
tive discounting procedures and discount rates to assess the eco-
nomic benefits and costs associated with public programs.35
The approach adopted here is a two-stage procedure recommended by
Kolb and Scheraga (1990).
First, annualized costs are computed by adding annualized
capital expenditures (over the expected life of emission con-
trols) and annual operating costs. Capital expenditures are
annualized using a discount rate that reflects a risk-free
marginal return on investment.36 This discount rate, which is
referred to below as the social cost of capital, is intended to
reflect the opportunity cost of resources displaced by invest -
34 In other words, a discount rate reflecting the private cost of capital
to affected firms should be used in analyses designed to predict market
adjustments associated with emission control costs. The private cost of
capital, assumed to be 10 percent in this analysis, is higher than the 7 per-
cent social discount rate because it reflects the greater risk faced by
individual procedures related to the risk faced by society at large.
35
See Lind, et al. (1982) for a more detailed discussion of this debate.
36 The risk-free rate is appropriate if the NESHAP, as a program, does not
add to the variance of the return on society's investment portfolio.
9-58
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ments in emissions controls. Kolb and Scheraga (1990) recommend
a range of 5 to 10 percent for this rate. We adopt a midpoint
value of 7.0 percent in this analysis.37
Second, the present value of the annualized stream, of costs
is computed using a consumption rate of interest which is taken
as a proxy for the social rate of time preference. This discount
rate, which is referred to below as the social rate of time pref-
erence, measures society's willingness to be compensated for
postponing current consumption to some future date. Kolb and
Scheraga (1990) argue that the consumption rate of interest
probably lies between 1 and 5 percent. We do not, however,
present estimates of the present value of the costs associated
with the NESHAP in this report.
The resulting estimates of the present value of the economic
costs associated with the NESHAP can be compared with estimates
of the present value of corresponding benefits in the BCA. The
social rate of time preference should be employed to discount the
future stream of estimated benefits.
9.7.1.4 Costs of Imported Goods
The NESHAP is expected to cause an increase in prices paid
for imports. From the perspective of the world economy, higher
prices paid for imported goods represent a transfer from domestic
consumers to foreign producers. However, from the perspective of
the domestic economy alone, higher prices on imported goods
represent an economic cost.
Since we do not consider the welfare of foreign producers in
this analysis, we treat expenditures on DGEBPA and wet strength
37 The 7 percent discount rate is also consistent with recent OMB recommen-
dations .
9-59
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resin due to higher prices as a cost. Note that there are two
sources of this cost: (1) higher prices paid for baseline im-
ports; and (2) higher prices paid for the additional imports
induced by emission control costs faced by domestic producers.
9.7.2 Other Costs Associated with NESHAP
It should be recognized that the estimates of costs reported
later in this section do not reflect all costs that might be asso-
ciated with the NESHAP. Examples of these include administrative,
monitoring, and enforcement costs (AME), and transition costs.
AME costs may be borne by directly affected firms and by
different government agencies. These latter AME costs, which are
likely to be incurred by state agencies and EPA regional offices,
for example, are reflected neither in the estimates of emission
control costs, nor in the estimates of economic costs.
Transition costs are also likely to be associated with the
alternative standards. Analyses described in previous sections
of this report, for example, predict that some plants will close
because of emission control costs. This will cause some individ-
uals to suffer transition costs associated with temporary unem-
ployment and affected firms to incur shutdown costs. These
transition costs are not reflected in the cost estimates reported
later in this section.
9.7.3 Changes in Economic Surplus as a Measure of Costs
As was noted earlier, willingness to be compensated for
foregone consumption opportunities is taken here as the appropri-
ate measure of the costs associated with the NESHAP. In this
case, compensating variation is an exact measure of willingness
to be compensated. In practice, however, compensating variation
is difficult to measure; consequently, the change in economic
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surplus associated with the air quality standard is used as an
approximation to compensating variation.
The degree to which a change in economic surplus coincides
with compensating variation as a measure of willingness to be
compensated depends on whether the surplus change is measured in
an input market or a final goods market. The surplus change is
an exact measure of compensating variation when it is measured in
an input market, but it is an approximation when measured in a
final goods market.38
The direction of the bias in the approximation of compensat-
ing variation when the surplus change is measured in a final
goods market depends on whether affected parties realize a wel-
fare gain or suffer a welfare loss, but in either case, the bias
is likely to be small.39 Affected firms (and their customers)
will suffer a welfare loss as the result of the implementation of
emission controls. In this case, the change in economic surplus
will exceed compensating variation, the exact measure of willing-
ness to be compensated.40
9.7.4 Estimates of Economic Costs
Estimates of the annualized total economic costs associated
with the NESHAP are reported in Table 9-15 (for a social cost of
capital equal to 7.0 percent). The estimates of total annual
costs of the NESHAP are $120 thousand for the DGEBPA industry,
$465 thousand for the wet strength resin industry under the MACT
Floor, and $51 thousand for the wet strength resin industry under
Option I.
38 See Just, Heuth, and Schmitz (1982) for a more detailed discussion.
39
See Willig (1974).
40 See Appendix B for a detailed, technical description of the methods
employed to compute changes in economic surplus.
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Table 9-15
ESTIMATES OF ANNUALIZED ECONOMIC COSTS
(thousands of 1992 dollars)
Industry
DGEBPA
Wet Strength Resin
MACT Floor
Option I
Loss in
Consumer
Surplus
141
1,607
87
Loss in
Producer
Surplus
-3
-841
-22
Loss in
Residual
Surplus
-19
-300
-13
Loss in
Surplus
Total
120
465
51
NOTE: Estimates are computed as the annualized reduction in economic surplus
to the domestic economy.
We measure economic costs as net losses in economic surplus.
Table 9-15 shows how losses in surplus are distributed among con-
sumers, domestic producers and society at large. The latter is
referred to as "residual" surplus in the table.
The loss in consumer surplus includes higher outlays for
foreign and domestically produced DGEBPA and wet strength resin
plus a dead weight loss due to foregone consumption. As Table
9-15 indicates, consumers in each market suffer a loss in sur-
plus . These losses are due mostly to higher expenditures on
DGEBPA and wet strength resin.
We compute the loss in producer surplus as annualized emis-
sion control costs incurred by plants remaining in operation plus
the dead weight loss in surplus due to reduced output less in-
creased revenue due to higher post-control prices. The estimated
losses in producer surplus reported in Table 9-15 are negative,
meaning that domestic producers would realize a net gain in eco-
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nomic surplus. This occurs because higher post-control market
prices more than offset emission control costs.
Surplus losses to society at large are computed as "resid-
ual" adjustments to account for differences in private and social
discount rates and transfer effects of taxes. The estimates of
changes in producer surplus reflect a 10 percent real private
rate on emission control capital costs. Recall that social costs
are discounted at a 7.0 percent real rate.41
We note that the distribution of economic costs between con-
sumers and domestic producers depends, in part, on the way we
have constructed the post-control supply curve. As explained
earlier, we have assumed that plants with the highest emission
control costs (per unit of output) are marginal in the post-
control market. This assumption is worst case in that it results
in large increases in prices (relative to an alternative assump-
tion that plants with high control costs are not marginal), thus
shifting the cost burden to consumers and away from plants that
continue to operate in the post-control market. Any alternative
construction of the post-control supply curve would result in
smaller price increases and shift a larger share of economic
costs away from consumers to domestic producers. In other words,
smaller price increases would reduce the economic rent realized
by domestic producers in the post-control market.
Earlier, we explained that economic costs differ from emis-
sion control costs. Recall that the latter are computed simply as
annualized capital costs plus annual operating and maintenance
costs, assuming that all plants install controls. Table 9-16
reports estimates of annualized emission control costs. These
estimates are $145 thousand for the DGEBPA industry and range from
41 Since the loss in producer surplus measures the burden of the alternative
borne by producers, we calculate it using the private cost of capital.
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$52 thousand under the MACT Floor to $519 under Option I for the
Wet Strength resin industry. The emission control costs reported
in Table 9-16 exceed the economic costs reported in Table 9-15
under the MACT Floor scenario. This occurs because the estimated
economic costs reflect market adjustments away from marginally
expensive production.
Table 9-16
ESTIMATES OF THE ANNUALIZED EMISSION CONTROL COSTS
(thousands of 1992 dollars)
DGEBPA
145
145
Wet Strength
Resin
MACT Floor
519
N.A.
Wet Strength
Resin
Option I
N.A.
52
Total
664
197
NOTE: Estimates are computed as annualized capital costs plus annual operating
and maintenance costs, assuming all plants continue to operate after
controls are installed. Capital costs are annualized at a 7 percent
discount rate.
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APPENDIX A
AFFECTED PLANTS AND EMISSION CONTROL COSTS
This appendix describes the-affected DBGEPA and wet strength
resin plants and the estimates of emissions and emission control
costs used in this study.
AFFECTED PLANTS
There are three major DBGEPA producers. Consequently, we are
able to use plant specific data for baseline emissions, emissions
reductions, and control costs. Data on production rates at DBGEPA
plants, however, is considered confidential and is not available
to the public. We use an average annual production rate of 45,000
metric tons (wet weight) as baseline output for each of the three
DGEBPA facilities.42
There are 17 wet strength resin facilities nationwide. How-
ever, only five of these plants are expected to incur emission
control costs under the MACT Floor and nine under Option I. We
assume that each of these plants produce 11,600 metric tons annu-
ally.43
EMISSION CONTROL COSTS
Table A-l reports emission control capital costs and annual-
ized costs for the three DGEBPA facilities. Table A-2 shows the
same information for the five affected wet strength resin plants.
Annualized costs include amortized capital costs plus the annual
operating and maintenance costs associated with emission controls.
42 Draft BID, Section 6, Appendix A (wet weight).
43 Draft BID, Section 6, Appendix A (wet weight).
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Table A-3 shows capital and annualized costs for the nine wet
strength resin plants expected to be affected by Option I (esti-
mated costs are the same for all nine plants).
Table A-l
CONTROL COSTS AT DGEBPA PLANTS
PLANT
DOW
Ciba-Geigy
Shell
CAPITAL
COSTS
(1992$)
254,873
104,778
67,618
ANNUALIZED
COSTS
(1992$)a
31,207
75,461
38,266
Capital costs annualized at a 7 percent
discount rate.
Table A-2
MACT FLOOR CONTROL COSTS AT AFFECTED WET STRENGTH RESIN PLANTS
PLANT ID #
1
2
3
12
14
CAPITAL
COSTS
(1992$)
24,500
37,400
360,000
48,000
39,500
ANNUALIZED
COSTS
(1992$)a
86,000
112, 000
91, 000
111, 000
119, 000
Capital costs annualized at a 7 percent
discount rate.
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Table A-3
OPTION I CONTROL COSTS
AT AFFECTED WET STRENGTH RESIN PLANTS
NUMBER OF
PLANTS
CAPITAL
COSTS
(1992$)
ANNUALIZED
COSTS
(1992$)a
15,348
5,782
a Capital costs annualized at a 7 percent
discount rate.
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APPENDIX B
TECHNICAL DESCRIPTION OF ANALYTICAL METHODS
This technical appendix provides detailed descriptions of the
analytical methods employed to conduct the following analyses:
Partial equilibrium analysis (i.e., computing post-
control price, output and trade impacts).
Estimating changes in economic surplus.
Labor and energy impacts.
Capital availability.
We also present the baseline values used in the partial equilib-
rium analysis.
PARTIAL EQUILIBRIUM ANALYSIS
The partial equilibrium analysis requires the completion of
four tasks. These tasks are:
Specify market demand and supply.
Estimate the post-control shift in market supply.
Compute the impact on market quantity.
Compute the impact on market price.
Predict plant closures.
Market jjemand and Supply
Baseline or pre-control equilibrium in a market is given by:
Qd = aP6 (B.I)
(B.2)
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(B.3)
where , Q = output ;
P = price;
e = demand elasticity;
7 = supply elasticity;
a, /3 and p are constants;
Subscripts d and s reference demand and supply, respec-
tively; and,
Superscripts d and f reference domestic and foreign
supply, respectively.
The constants a, j3 and p are computed such that the baseline
equilibrium price is normalized to one. Note that the market
specification above assumes that domestic and foreign supply
elasticities are the same.
Market Supply Shifts
Supply price for a model plant will increase by an amount
just sufficient to equate the net present value of the investment
and operation of the control equipment to zero. Specifically,
[(C-Q) - (V+D) ] (1-t) +D =k (B_5)
where C is the change in the supply price;
Q is output;
V is a measure of annual operating and maintenance
control costs.
t is the marginal corporate income tax rate;
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S is the capital recovery factor;
D is annual depreciation (we assume straight-line depre-
ciation) ;
k is the investment cost of emissions controls.
Solving for C yields the following expression:
C =
kS-D
Q(l-t)
V+D
~
(B.G;
Estimates of k and V were obtained from EPA (1991). The
variables, D, I, and S are computed as follows:
and
D = k/T
S = r(l+r)T/((l+r)T-l)
(B.7)
(B.8!
where r is the discount rate or cost of capital faced by
producers;
T is the life of emission control equipment.
Solving for P in Equation (B.2) yields the following expres-
sion for the baseline inverse market supply function for domestic
producers.
P =
(B.9!
Emission control costs will raise the supply price of the
ith model plant by Ci (as computed in Equation (B.6)). The ag-
gregate domestic market supply curve, however, does not identify
the supply price for individual plants. Accordingly, we adopt
the worst-case assumption that model plants with the highest
after-tax per unit control costs are marginal in the post-control
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market. Specifically, we write the post-control supply function
as
P = (C4/|3)1/T + C(Ci/qi) (B.10)
where q^_ is the total output of all model plants of type i.
The function C(Ci,qi) shifts segments of the pre-control
domestic supply curve vertically by C^. The width or horizontal
distance of each segment is q^_. The resulting segmented post-
control domestic supply curve is illustrated in Figure B-l as S2,
compared with pre-control supply S^44
Figure B-l.
Domestic Market Supply Shift Due to Emission Control Costs
44 The supply curves in Figure B-l are drawn as linear functions for ease
of exposition. Because the supply curves are specified as Cobb-Douglas, they
are log-linear.
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Impact on Market Price and Quantity
The impacts of the alternative standards on market output
are estimated by solving for post-control market equilibrium and
then comparing that output level, Q2, to the pre-control output
level, Q1. Because post-control domestic supply is segmented, a
special iterative algorithm was developed to solve for post-
control market equilibrium. The algorithm first searches for the
segment in the post-control supply function at which equilibrium
occurs and then solves for the post-control market price that
clears the market.
Since the market clearing price occurs where demand equals
post-control domestic supply plus foreign supply, the algorithm
simultaneously solves for the following post-control variables.
Equilibrium market price.
Equilibrium market quantity.
»
The quantity supplied by domestic producers.
The net quantity supplied by foreign producers.
We assess the market impacts of control costs by comparing
baseline values to post-control values for each of the variables
listed above.
Trade Impacts
We report trade impacts as the change in both the volume and
dollar value of net exports. We assume that exports comprise an
equivalent percentage of domestic production in the pre- and
post-control markets. We also assume that foreign and domestic
supply elasticities are the same. As the volume of imports rises
and the volume of exports falls, the volume of net exports will
decline. However, if demand is inelastic, it is uncertain
whether the dollar value of net exports will rise or fall. The
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dollar value of imports will increase due to increases in both
volume and price. Exports will decrease in volume, but price
will increase. If demand is inelastic then the dollar value of
exports will increase. If the increase in the dollar value of
exports is greater than that of imports then the alternative will
result in an increase in the dollar value of net exports.
We use the following algorithms to compute trade impacts:
Change in volume of imports =
Qsl - OB* (B.ll.a)
Change in dollar value of imports - =
Po(of-Qf ) + (Po-Pj-of (B.ll.b)
Change in volume of exports =
~^r (QS* - Qsd) (B.ll.c)
Change in dollar value of exports =
-^.(P.Qjf - P,Q*) (B.ll.d)
where the subscript e references exports by domestic producers
We report the change in the volume of net exports as
(B.ll.c) minus (B.ll.a). We report the change in the dollar
value of net exports as the difference between (B.ll.d) and
(B.ll.b).
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We also report the change in the dollar value of shipments
by domestic producers. This value, AVS, is given by
AVS = P2-Qsd2 - P.C4 (B.12)
Plant Closures
We predict that any plant will close if its post-control
supply price is higher than the post-control equilibrium price.
Post-control supply prices are computed by Equation (B.10). We
round fractions of plant closures to the nearest integer.
CHANGES IN ECONOMIC SURPLUS
The shift in market equilibrium will have impacts on the
economic welfare of three groups:
Consumers.
Producers.
Society at large.
The procedure for estimating the welfare change for each group is
presented below. The total change in economic surplus, which is
taken as an approximation to economic costs, is computed as the
sum of the surplus changes for the three groups.
Change in Consumer Surplus
Consumers will bear a dead weight loss associated with the
reduction in output. This loss represents the amount over the
pre-control price that consumers would have been willing to pay
for the eliminated output. This surplus change is given by:
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Ql
dQ - PI (Qi-Qa) (B.13)
In addition, consumers will have to pay a higher price for
post-control output. This surplus change is given by.
(B.14!
The total impact on consumer surplus, ACS, is given by
(B.13) plus (B.14). Specifically,
ACS = / (Q/a)1/£ dQ - P1Q1 + P2Q2 (B.151
Q2
This change, ACS, includes losses of surplus incurred by
foreign consumers. In this report we are only concerned with
domestic surplus changes. We have no method for identifying the
marginal consumer as foreign or domestic.
To estimate the change in domestic consumer surplus we
assume that total consumer surplus is split between foreign and
domestic consumers in the same proportion that sales are split
between foreign and domestic consumers in the pre-control market
That is, the change in domestic consumer surplus, ACSd, is:
1-1
QS:
AC5 (B.16!
While ACS is a measure of the consumer surplus change from
the perspective of the world economy, ACSd represents the con-
sumer surplus change from the perspective of the domestic economy,
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Chancre in Producer Surplus
To examine the effect on producers, output can be divided
into two components:
Output eliminated as a result of controls.
Remaining output of controlled plants.
The total change in producer surplus is given by the sum of the
two components.
Note that post-tax measures of surplus changes are required
to estimate the impacts of controls on producers' welfare. The
post-tax surplus change is computed by multiplying the pre-tax
surplus change by a factor of (1-t) where t is the marginal tax
rate. As a result, every one dollar of post-tax loss in producer
surplus will be associated with a complimentary loss of t/(l-t)
dollars in tax revenues.
Output eliminated as a result of control costs causes
producers to suffer a dead-weight loss in surplus analogous to
the dead-weight loss in consumer surplus. The post-tax dead-
weight loss is given by:
dQ
(1-t)
-------
(B.18)
The total post-tax change in producer surplus, APS, is given
by the sum of (B.17) and (B.18). Specifically,
APS =
m
I ciqi
(1-t)
(B.19)
Recall that we are interested only in domestic surplus
changes. For this reason we do not include the welfare gain
experienced by foreign producers due to higher prices. This pro-
cedure treats higher prices paid for imports as a dead-weight
loss in consumer surplus. Higher prices paid to foreign pro-
ducers represent a transfer from the perspective of the world
economy, but a welfare loss from the perspective of the domestic
economy.
Residual Effect on Society
The changes in economic surplus, as measured above, must be
adjusted to account for two effects which cannot be attributed
specifically to consumers and producers. These two effects are
caused by tax impacts and differences between private and social
discounts rates.
Two adjustments for tax impacts are required. First, per
unit control costs C.j_, which are required to predict post-control
market equilibrium, reflect after-tax control costs. The true
resource costs of emissions controls, however, must be measured
on a pre-tax basis. For example, if after-tax control costs
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exceed pre-tax control costs, C± overstates the true resource
costs of controlling emissions.
A second tax-related adjustment is required because changes
in producer surplus have been reduced by a factor of (1-t) to
reflect the after-tax welfare impacts of emissions control costs
on affected plants. As was noted earlier, a one dollar loss in
pre-tax producer surplus imposes an after-tax burden on the
affected plant of (1-t) dollars. In turn, a one dollar loss in
after-tax producer surplus causes a complimentary loss of t/(l-t)
dollars in tax revenues.
A second adjustment is required because of the difference
between private and social discount rates. The rate used to
shift the supply curve reflects the private discount rate (or the
marginal cost of capital to affected firms). This rate must be
used to predict the market impacts associated with emission con-
trols. The economic costs of the NESHAP, however, must be
computed at a rate reflecting the social cost of capital. This
rate is intended to reflect the social opportunity cost of
resources displaced by investments in emission controls.45
The adjustment for the two tax effects and the social cost
of capital, which we refer to as the residual change in surplus,
ARS, is given by:
m
ARS = - [ (Ci-pci)qi + APS- [t/(l-t) ] (B.20)
where pCj_ = per unit cost of controls for model plant type
i, computed as in (B.5) with t=0 and r=social
cost of capital.
45 See Section 7 for a more detailed discussion of this issue.
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The first term on the right-hand-side of (B.20) adjusts for
the difference between pre- and post-tax differences in emission
control costs and for the difference between private and social
discount rates. Note that these adjustments are required only on
post-control output. The second term on the right-hand-side of
(B.19) is the complimentary transfer of the sum of all post-tax
producer surplus.
Total Economic Coats
The total economic costs, EC, is given by the sum of changes
in consumer and producer surplus plus the change in residual
surplus. Specifically,
EC = ACSd + APS + ARS (B.21)
LABOR AND ENERGY IMPACTS
Our estimates of the labor and energy impacts associated
with the alternative standards are based on input-output ratios
and estimated changes in domestic production.
Labor Impacts
Labor impacts, measured as the number of jobs lost due to
domestic output reductions, are computed as
AL =
(B.22;
2000
where AL is the change in employment, Lx is the production
worker hours per dollar of output, and all else is as previously
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defined. The number 2000 is used to translate production worker
hours into jobs (i.e., we assume a 2000 hour work year).
Energy Impacts
We measure the energy impacts associated with the alterna-
tive standards as the reduction in expenditures on energy inputs
due to output reductions. The method we employ is similar to the
procedure described above for computing labor impacts. Specifi-
cally,
AE -EQ-Q* (B-23)
where AE is the change in expenditures on energy inputs, El is
the baseline expenditure on energy input per dollar output and
all else is as previously defined.
BASELINE INPUTS
The partial equilibrium model described above requires, as
inputs, data on the characteristics of affected plants and base-
line values for variables and parameters that characterize each
market. The characteristics of affected plants have been de-
scribed earlier in Appendix A. These include the number of
plants by model type and a measure of output for each model
plant. Appendix A also reports estimates of capital and annual
emission control costs.
Table B-l reports the baseline values of variables and param-
eters for each market. The baseline price of DGEBPA is taken from
the Chemical Economic Handbook (p. 580.601G); the baseline price
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Table B-l
BASELINE INPUTS
Variable /Parameter
Price (Pja
Domestic Output (Q^) b
Import Ratio0
Export Ratiod
Supply Elasticity (e)
Demand Elasticity (7)
Tax Rate (t)
Private Discount Rate (r)
Social Discount Rate
Equipment Life (T)e
Labor (L-, ) f
Energy (E-J5
MARKET
DGEBPA
$2.59
135.0
0.028
0.178
3.76
-1.50
0.25
0.1
0.07
10
0.0025'
0.031
Wet Strength Resin
$.20
197.2
0
0.010
3.76
-0.924
0.25
0.1
0.07
10
0.0025
0.031
Notes: a Dollars (1992) per kilogram (wet weight).
b Thousands of metric tons (wet weight).
c Imports divided by domestic production.
d Exports divided by domestic production.
e Years.
f Production worker hours per dollar of output.
g Energy expenditure per dollar of output.
of wet strength resin is from Synthetic Organic Chemicals.46 47
Baseline domestic output in each market is computed as the sum of
46 Prices were converted to 1992 dollars using the producer price index for
chemicals and allied products (Economic Report of the President).
47
Wet strength resin prices were converted from a dry weight to wet weight
basis using a wet-to-dry weight conversion factor of 7.7 (computed from data in
the Chemical Economics Handbook, p. 580.1000X).
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production at all domestic plants (see Appendix A from production
rates at DGEBPA and wet strength resin plants).
The import and export ratios reported in Table B-l were com-
puted from production and trade data for DGEBPA (unmodified epoxy
resins) and wet strength resin (epi-based non-nylon polyamide)
reported in Chemical Economics Handbook (pp. 580.601M, 580.60IK
and 580.1000Y). Imports of wet strength resin were reported to
have been "insignificant."
We describe the data and procedures employed to estimate
supply and demand elasticities (7 and e, respectively) in Appen-
dix C. Note that we use the estimates of the demand elasticities
reported in Table B-l for the "base case" results presented in
Sections 4, 5, and 7 of this report. We assess the sensitivity
of the estimated impacts to demand elasticity by reporting in
Appendix D results based on "low" and "high" estimates.
We use a marginal tax rate of 25 percent to assess the
impacts of emission controls. 'We adopt a 10 percent private
discount rate (real marginal cost of capital) and a 7.0 percent
social discount rate. The expected life of emission control
equipment is 10 years.
Finally, the values for labor hours per unit of output (Lx)
and energy use per unit of output (Ex) were obtained from the
Annual Survey of Manufactures. Data from the ASM used to derive
these estimates include 1989 annual values for total production
worker hours used, total expenditures on energy; and the value of
shipments. Recall that these data are available at the 4-digit
SIC code level. DGEBPA, wet strength resins and other resin
products are included in SIC code 2821. For this reason, L^ and
E-L are the same in both resin markets.
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CAPITAL AVAILABILITY ANALYSIS
Pre- and post-control values of the following financial
measures are compared in the capital availability analyses:
Net income/assets.
Long-term debt/long-term debt plus equity.
Pre-Control Financial Measures
Pre-control measures of net income and net income/assets are
computed by averaging data for the period 1988 through 1991 where
these data are available. The long-term debt ratio is computed
from 1991 data, or the most recent year available.
All figures are adjusted to 1991 dollars by the producer
price index for chemicals and allied products. Then, pre-control
values are estimated by:
1991
i) n £ iii/4 (B.24)
i=1988
1991
ii) r £ (ni/ai)/4 (B.25)
i=1988
iii) 1 = 11991/(11991 + e!99i) (B.26)
where n = average net income
n.j_ = net income in year i
r = average return on assets
ai = assets in year i
1 = long-term debt ratio
9-83
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-t-1987 = long-term debt in 1991
ei987 = equity in 1991
Post-Control Values
To determine the impact of controls, an estimate of the cost
of controls is made. In order to get an idea of the steady- state
cost, an annualized cost is used. The annualized cost, AC, for a
plant is :
AC = V + kS (B.27)
where the variables are as defined previously.
Annualized costs and capital costs are estimated for each
model plant type. For each establishment, post -control measures
are given by :
(B.28)
pn .
i=1988 4
pr=
(B.291
i=1988 4
pi = (B.30:
I1991+e1991+k
where pn = post -control average net income
AC = annualized cost for the company
pr = post -control return on assets
k = capital cost for the company
pi = post-control long-term debt ratio
9-84
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APPENDIX C
ESTIMATION OF INDUSTRY SUPPLY AND DEMAND
INTRODUCTION
This appendix describes the analytical approach and the data
we employed to estimate the supply and demand elasticities used
in this EIA. We also report and evaluate the statistical proper-
ties of the estimates.
APPROACH
The approaches we adopt to estimate supply and demand elas-
ticities are consistent with economic theory and, at the same
time, exploit the available data. Briefly, we derive an indus-
try-wide estimate of supply elasticity from an estimated produc-
tion function. Because the data required to estimate the produc-
tion function are available only at a four-digit SIC level (SIC
2821 which includes both the epoxy and wet strength resin indus-
tries) , we obtain a single estimate of supply elasticity. We
adopt this single estimate for both the DGEBPA and wet strength
resin industries, implicitly assuming that the two industries
face similar production functions.
Because both DGEBPA and wet strength resin are used as
intermediate inputs to produce other goods, the demand for these
inputs is derived from the goods they are used to produce. The
data required to estimate the derived demand functions are
available separately for both DGEBPA and wet strength resin. As
a result, we obtain estimates of demand elasticities for each of
the two industry segments.
9-85
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Supply Elasticity
As noted above, we derive an estimate of the market supply
elasticity from an industry-wide estimate of the production
function. Given the production function, we solve for the dual
cost function. Then, exploiting the result that market price is
established at marginal production cost, we derive the inverse
supply curve as the derivative of the cost function with respect
to output. The important result is that the parameters of the
supply function can be stated in terms of the parameters of the
estimated production function.
We assume that the industry is economically efficient in
that production costs are minimized subject to a production
constraint. In equation form, this can be written as:
minimize £ rixi (C.I)
xi
subject to: Q = f(Xi)
where x± = factor inputs (used to produce resins)
r.j_ = factor prices
Q = output (of resins)
The solution to this problem is a set of input demand
functions:
x* = g(ri,Q) (C.2)
If the input demand functions are substituted back into the
objective function, one obtains a cost function in terms of input
prices and output.
C = h(ri;Q) (C.3)
9-86
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Equilibrium in the market is established at the point where
price equals marginal cost. That is:
P = dC/dQ = h'(ri;Q) (C.4)
where P is output price. Equation (C.4) is a relationship
between output and output price and thus represents the industry
supply curve.
An explicit functional expression for the right-hand side of
(C.4) can be determined if one makes a specific assumption on the
form of the production function. For this analysis, we assume a
multiplicative form for the production function with two variable
inputs and a capital factor. Because we use time series data to
estimate the production function, we also include a time factor
to account for changes in technology. Specifically,
Qt =
where Qt is industry output in year t
Kt is real capital stock in year t
Lt is production man-hours in year t
Mt is an index of materials input in year t
t is time in years
A, aL,aM,A are parameters to be estimated.
Equation (C.S) can be written in linear form by taking the
natural logarithms of both sides. Thus, linear regression
techniques can be applied.
Given a particular form for the production function, the
steps described by Equations (C.2) to (C.4) can be used to derive
the implied supply function. For this analysis, we assume that
9-87
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capital stock is fixed.48 The derived supply function can be
written as:
where
In Q
B0 +
B3 lnPL
In P + B2 In K
(C.6)
B4 In PM
B5 In t
M
K
factor price of labor input
factor price of material input
fixed real capital stock
The B.J_ and j coefficients are functions of the o^, the coeffi-
cients of the production function. For example, j, the supply
price elasticity, can be shown to be equal to
T =
(C.7;
It is clear from (C.7) that it may be necessary to place
restrictions on the estimated coefficients of the production
function in order to have well-defined supply function coeffi-
cients. For example, the sum of the coefficients for labor and
materials should be less than one. Otherwise, 7 is undefined or,
if both coefficients are positive, y would be negative. For this
reason, the production function is estimated with the restriction
that the sum of coefficients for the inputs should equal one.
This is equivalent to assuming long-run constant costs in the
48 This specification, which treats in place capital as sunk, is consistent
with our objective of modeling how supply adjusts to price changes in the post-
control market. This response will depend on the behavior of avoidable
production costs and emission control costs.
9-88
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industry, an assumption that seems reasonable on a priori grounds
and appears to be consistent with the data.49
Demand Functions
Wet strength resin is used primarily in the production of
pulp and paper products (SIC 2851). DGEBPA is used to produce a
variety of products; about 50 percent of industry output is used
to sealants and adhesives (SIC 2621) and coatings and paints (SIC
2891). As intermediate inputs, the demand for both wet strength
resin and DGEBPA are derived from the demand for the products
they are used to produce.
We assume that firms using wet strength resin and DGEBPA as
inputs attempt to maximize profits subject to a production
constraint. The profit function can be written
Max TT = Pe-g(Q,W) - P-Q - rw-w (C.8)
Q,W
where TT = profit;
Pe = the price of the final good (e.g., pulp and
paper products);
Q = input use of wet strength resin or DGEBPA;
W = a vector of other inputs
P = the price of wet strength resin or DGEBPA;
and,
rw = a vector of prices of other inputs.
Note that the function g(Q,W) defines the production function for
the end product, say Qe.
49 The unrestricted estimates of the production function coefficients summed
nearly to unity. Thus, the restriction on the coefficients is only marginally
binding.
9-89
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The solution to C.8 yields a system of input demand equa-
tions of the form
Q = h(P,Pe,rw) (C.9]
In words, C.9 states that the derived demand for wet strength
resin or DGEBPA depends on its own price, the price of the final
good, and the prices of other inputs.
We adopt a multiplicative function form for equation C.9.
Specifically, we write the derived demand function as
Q
where Q = the quantity demanded of wet strength resin or
DGEBPA;
P = the price of wet strength resin or DGEBPA;
Pe = the price of the end product; and,
B, /?, |Se are parameters to be estimated.
The parameter f3, of course, is the demand elasticity for the
input either wet strength resin or DGEBPA.
Note that equation C.10 excludes variables for the prices of
other inputs (rw of equation C.9). Unfortunately, data on these
prices are unavailable. This requires us to adopt the implicit
assumption that the use of wet strength resin and DGEBPA in end
products is fixed by technology.
Because the markets for wet strength resin and DGEBPA are
simultaneous in P and Q, it is necessary to apply a systems
estimator in order to obtain consistent estimates of the coef-
9-90
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ficients for the demand equations. We employ a two-stage least
squares estimator (2SLS) to estimate the demand equations. In.
order to estimate consistent demand equation coefficients, one
uses as instruments the exogenous variables included in the
system of demand and supply equations. The supply-side instru-
ments used to estimate the demand functions include capital stock
(K), a cost index (Pv) measuring the weighted-average cost of
variable inputs (labor and materials), and time.
DATA
Table C-l identifies the variable names, units of measure,
and variable descriptions for the data available for the analy-
sis. Those variables directly related "to a specific SIC were
obtained from the Annual Survey of Manufactures (ASM).50 These
data are defined for 4-digit SICs and represent annual values
which cover the years 1958-1989. Recall that both DGEBPA and wet:
strength resins belong to SIC 2821 code. Industry segment price
and output data, obtained from the ITC and SPI, were used to
estimate demand elasticities. These data are available for the
years 1971-1990.
Items 1 through 9 of Table C-l were used to estimate the
production function (see Equation C.5) for SIC 2821. We formed
the industry output variable, Q, as VSHIP/PISHIP; this ratio
yields the real value of shipments in SIC 2821. The capital
stock variable, K, is measured as CAP, the real value of capital
stock in millions of 1972 dollars. Labor input, L, is measured
as PRODH, millions of production worker hours. The time trend,
t, is measured by the variable YEAR. Finally, we measure materi-
als use, M, as the ratio of COSTMAT/PIMAT;
50 We thank Eric Bartlesman of the Federal Reserve Board for providing the
data set to us.
9-91
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Table C-l
VARIABLES AND DEFINITIONS OF PRIMARY DATA
Variable3
i. YEAR
2. SIC
3 . PISHIP
VSHIP
5. CAP
6 . COSTMAT
7 . PIMAT
8 . PRODW
9 . PRODH
10. PRICE
11 . SALES
12. IPD
Unit
4-digit
index
millions $
millions 1972
$
millions $
index
millions $
millions
hours
dollars per
kilogram
millions of
kilograms
index
Description
Observation identifier, 1958-1989
Industry identifier
Producer price index for Value of Ship-
ments (SICs 2821, 2891 and 2851)
Value of industry shipments
Real capital stock (SIC 2821)
Cost of materials inputs (SIC 2821)
Price index for materials inputs (SIC
2821)
Production- worker wages (SIC 2821)
Production worker hours (SIC 2821)
Price per kilogram (Type A Liquid Res-
in, DGEBPA Resin and Non-Nylon
Polyamide Resin)
Quantity sold by domestic producers
annually (DGEBPA use in protective
coatings, DGEBPA use in bonding and
adhesives and Non-Nylon Polyamide
Resin)
Implicit Price Deflator (1.0 in 1972)
a Items 1-9 obtained from the ASM. Items 10 and 11 obtained from the ITC and
the SPI. Item 12 obtained from 1991 Economic Report of the President.
this ratio yields the real cost of material inputs for SIC 2821
in millions of 1972 dollars.
Items 3, 10, 11 and 12 were used to estimate the derived
demand equations. The dependent: variable for the wet strength
resin equation, quantity demanded, is measured as sales of non-
nylon polyamides in millions of kilograms per year. The "real"
price variable for this equation is measured as the nominal price
of non-nylon polyamides (item 10) divided by IPD (item 12). The
9-92
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"real" price of the end-product good is measured as PISHIP for
SIC 2821 (pulp and paper) divided by IPD.
We estimate two derived demand functions for DGEBPA one
for DGEBPA use in coatings and paints and another for DGEBPA use
in sealants and adhesives. The dependent variables for each
equation are measured as sales for the respective use in millions
of kilograms annually. The real price variable for DGEBPA use in
coatings and paints is measured as the nominal price of Type A
liquid resin divided by IPD; the real price for DGEBPA use in
coatings and adhesives is measured as the nominal price of DGEBPA
resin divided by IPD. Both price variables are expressed as
dollars per kilogram. Finally, the real prices of end-products
are formed by the ratios of PISHIP/IPD 'for SICs 2891 (coatings
and paints) and 2621 (sealants and adhesives).
The 2SLS estimates of the derived demand equations require
data for three instrumental variables time, capital stock and a
cost index for variable inputs. Time and capital stock are
measured as the variables YEAR and CAP (for SIC 2821). We form
the cost index for variable inputs as a weighted index of PIMAT
and PRODH (for SIC 2821), expressed in constant 1972 dollars.
STATISTICAL RESULTS
Production Function/Supply Equation
A restricted least squares estimator was used to estimate
the coefficients of the production function shown in Equation
(C.5). A log-linear specification was estimated with the sum of
the ai restricted to unity. The results are shown in Table C-2.
The equation explains about 96 percent of the variation in the
output variable. While the coefficients on labor and time are
significant at the 99 percent confidence level, the coefficients
9-93
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Table C-2
ESTIMATED PRODUCTION FUNCTION COEFFICIENTS
(t-ratios in parentheses)
Industry
SIC 2821
Time
.323
(7.118)
Capital
.211
(.632)
Labor
.485
(3.036)
Materials
.304
(1.552)
Adjusted R2
.96
on capital and materials are not statistically significant at
conventional confidence levels.
Using the estimated coefficients reported in Table C-2 and
the result shown in Equation C.7, we derive a supply elasticity
estimate of 3.76. Note that the calculation of statistical sig-
nificance for the elasticity is not straightforward since it is a
)
non-linear function of the production function coefficients. No
attempt has been made to assess the statistical significance of
the estimated elasticity.
Demand Equations
Table C-3 reports estimates of the derived demand equations
for wet strength resin and DGEBPA. The reported coefficients are
2SLS estimates of the parameters of Equation C.10. We have also
corrected the estimates of all three equations for first-order
serial correlation using the Prais-Winston algorithm51 and the
two DGEBPA equations for heteroschedasticity.
51 The Prais-Winston algorithm is similar to the more familiar Cochrane-
Orcutt estimator. However, unlike the Cochrane-Orcutt method, the Prais-Winston
algorithm does not skip the first observation and uses the'full generalized least
squares (GLS) transformation.
9-94
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Table C-3
2SLS ESTIMATED DERIVED DEMAND COEFFICIENTS
(t-ratios in parentheses)
Industry
Wet strength resin
DGEBPA (in coatings
and paints)
DGEBPA (in sealants
and adhesives)
Own Price
(0)
-.924
(4.363)
-1.474
(1.780)
-1.481
(2.620)
End-Product Price
1.136
(1.023)
.097
(.115)
2.040
(2.445)
We have estimated the derived demand function for wet
strength resin consistently with the approach described earlier
in this appendix. The estimated own-price coefficient is cor-
rectly signed and highly significant. The estimated coefficient
I
on the end-product price (SIC 2621) is correctly signed but not
statistically significant.52
The estimated own-price coefficients for DGEBPA are sen-
sitive to the instruments used in the two-stage procedure and to
corrections for autocorrelated errors. As a result, it was
necessary to modify the general approach described earlier in
this appendix. Specifically, the estimated equation for DGEBPA
used in coatings and paints includes only the cost index for
variable inputs and includes a time trend variable as an explana-
52
Note that we do not report adjusted R2 for the derived demand equations.
First, Basemann (1962) warns that low multiple correlation coefficients for
simultaneous equation estimators are not evidence of poor fit or lack of joint
significance of the set of explanatory variables. Second, the correction for
autoregressive errors renders R2 meaningless.
9-95
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tory variable.53 The estimated equation for DGEBPA used in
sealants and includes both time and the variable cost index as
instruments, but not the capital stock variable.
The estimated own-price coefficients are -1.474 and -1.481,
respectively, for DGEBPA used in coatings and paints, and in
sealants and adhesives. Accordingly, we adopt a mid-point demand
elasticity of -1.5 for DGEBPA. We caution, however, that this
estimate is not robust. As noted above, the estimates for DGEBPA
are sensitive to the specification of instrumental variables and
to corrections for autocorrelated errors.
We acknowledge the uncertainty in our estimate of demand
elasticities for wet strength resins and especially for DGEBPA.
Accordingly, we assess the sensitivity of our estimated economic
impacts by reporting in Appendix D results corresponding to "low"
and "high" demand elasticity cases. The low demand elasticities
are -.50 and -.62, respectively, for wet strength resin and
DGEBPA; the corresponding high demand elasticities are -1.34 and
-3.10. The low and high demand elasticities are, respectively,
minus and plus two standard deviations of the mid-point esti-
mates .54
53 The estimated coefficient for the time trend variable is .468 and the
associated t-ratio is 5.104.
54 We use the standard error of the estimate for DGEBPA used in coatings and
paints for the high demand elasticity case and the standard error for DGEBPA use
in sealants and adhesives for the low demand elasticity case. This procedure
causes us to use relatively higher demand elasticities for both cases, thus
representing "worst" case scenarios.
9-96
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APPENDIX D
SENSITIVITY ANALYSES
INTRODUCTION
This appendix presents the results of a sensitivity analysis
that explores the degree to which the results presented earlier
in this report are sensitive to estimates of demand elasticity.
SENSITIVITY ANALYSIS: DEMAND ELASTICITY
The "base case" results presented earlier in this report are
based on demand elasticities of -1.50 for DGEBPA and -.92 for wet:
strength resin. Below, we report results for "low" and "high"
demand elasticity cases. These alternative cases use the follow-
ing values for demand elasticities:
Low demand elasticity: -.62 for DGEBPA and -0.50 for
wet strength resins.
High demand elasticity: -3.10 for DGEBPA and -1.34 for
wet strength resins.
The greater the elasticity of demand (in absolute value"),
the more consumers will reduce the quantity they purchase in
response to a given change in price. Therefore, we expect that
when we use a higher demand elasticity in the partial equilibrium
analysis, the reduction in market output will be greater and the
price change will be smaller than in the base case. Similarly,
when we use a lower elasticity, we expect the change in price to
be greater, and the change in market quantity to be smaller,
relative to the base case.
Tables D-l through D-4 present estimates of the primary
economic impacts associated with the NESHAP for each of the two
industry segments in the case of low and high demand elastic!-
9-97
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ties. Tables D-l and D-2 report results based on low demand
elasticities and Tables D-3 and D-4 report results based on high
demand elasticities.
In general, the results of the sensitivity analysis are
consistent with the base case results presented earlier in this
report. For the DGEBPA industry, no plant closures are predict-
ed, and even in the high demand elasticity case, the estimated
reduction in market output is just 0.12 percent. However, for
the sensitivity analysis of the wet strength resin market, when a
low elasticity of demand is employed, the plant closure predicted
in the previous analysis is less probable. Also, when a "low"
elasticity of demand is assumed, the impacts on domestic pro-
duction, the value of domestic production, net exports, employ-
ment and energy are reduced. The estimated impacts of Option I
on the wet strength resin industry are very small, even when a
high elasticity of demand is assumed.
Table D-l
SENSITIVITY ANALYSIS: ESTIMATED PRIMARY IMPACTS ON THE
DGEBPA MARKET WITH LOW ELASTICITY OF DEMAND
Price
Change ( % )
.06
Market
Output
Change
-. 04
Change in Value of
Domestic Shipments
($1,000
1992)
51
(%)
.01
Plant
Closures
.00
Note: Results are based on a demand elasticity of -.62.
9-98
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Table D-2
SENSITIVITY ANALYSIS: ESTIMATED PRIMARY IMPACTS ON THE
WET STRENGTH RESIN MARKET WITH LOW ELASTICITY OF DEMAND
Regulatory
Option
MACT Floor
Option I
Price
Change
(%)
4.60
0.24
Market
Output
Change
(%)
-2.23
-.12
Change in Value of
Domestic Shipments
($1,000
1992)
897
48
(%)
2.28
.12
Plant
Closures
.02
.38
Note: Results are based on a demand elasticity of -0.50
Table D-3
SENSITIVITY ANALYSIS: ESTIMATED PRIMARY IMPACTS ON THE
DGEBPA MARKET WITH HIGH ELASTICITY OF DEMAND
Price
Change ( % )
.04
Market
Output
Change ( % )
-.12
Change in Value of
Domestic Shipments
($1,000
1992)
-293
(%)
-.08
Plant
Closures
.00
Note: Results are based on a demand elasticity of -3.10
9-99
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Table D-4
SENSITIVITY ANALYSIS: ESTIMATED PRIMARY IMPACTS ON THE
WET STRENGTH RESIN MARKET WITH HIGH ELASTICITY OF DEMAND
Regulatory
Option
MACT Floor
Option I
Price
Change
(%)
3.86
.20
Market
Output
Change
(%)
-4.95
-.27
Change in Value of
Domestic Shipments
($1,000
1992)
-505
-27
(%)
-1.28
- .07
Plant
Closures
.84
.05
Note: Results are based on a demand elasticity of -1.34.
9-100
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\
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TECHNICAL REPORT DATA
(Please read Instructions on reverse before completing)
1. REPORT NO.
EPA-453/D-94-034
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
Economic Impact Analysis of the Polymers and Resins
NESHAP
5. REPORT DATE
July 1994
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emission Standards Division
Research Triangle Park, NC 27711
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68D10144
12. SPONSORING AGENCY NAME AND ADDRESS
Director
Office of Air Quality Planning and Standards
Office of Air and Radiation
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
EPA/200/04
15 SUPPLEMENTARY NOTES
16. ABSTRACT
An economic analysis of the industries affected by the Polymers and Resins n National Emissions
Standard for Hazardous Air Pollutants (NESHAP) was completed in support of this proposed standard.
The industries for which economic impacts were computed were the epoxy resins and wet strength resins
industries.
The faciities in these industries must control epichlorohydrin emissions by the level of control
required in the standard. Several types of economic impacts, among them product price changes, output
changes, job impacts, and effects on foreign trade, were computed for the selected regulatory
alternatives.
n.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
c. COSATI FieWGroup
Control Costs
Industry Profile
Economic Impacts
Air Pollution control
18 DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (Report)
Unclassified
21. NO. OF PAGES
101
20. SECURITY CLASS (Page)
Unclassified
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION IS OBSOLETE
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