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This is to certify that the

dissertation entitled

Induced Institutional Change in the Trade and
Environment Debate:
A Computable General Equilibium Application to NAFTA With

Endogenous Regulation Setting
presented by

Heinz J. Jansen

has been accepted towards fulﬁllment
of the requirements for

Ph.D. degree in Agricultural
Economics

4

Major professor

 

 

 

Date 8/20/98

 

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INDUCED INSTITUTIONAL CHANGE IN THE TRADE AND
ENVIRONMENT DEBATE:
A COMPUTABLE GENERAL EQUILIBRIUM APPLICATION TO NAFTA WITH
ENDOGENOUS REGULATION SETTING

By

Heinz J. Jansen

A DISSERTATION

Submitted to
Michigan State University
in partial ﬁilﬁllment
of the requirements for the degree

DOCTOR OF PHILOSOPHY
Department of Agricultural Economics

1998

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ABSTRACT

INDUCED INSTITUTIONAL CHANGE IN THE TRADE AND
ENVIRONMENT DEBATE:
A COMPUTABLE GENERAL EQUILIBRIUM APPLICATION TO NAFTA \VITH
ENDOGENOUS REGULATION SETTING

By

Heinz J. Jansen

Because of the assumption of constant emission factors, economy-environment models
often show that free trade has negative environmental consequences. However, this pessimistic
view ignores the possibility of trade strmgthening the demand for regulatory institutions. An
"institutional optimism hypothesis", stating that the net environmental result of trade
liberalization is benign, is thus formulated in this paper. The hypothesis can be understood as
application of the “environmental Kuznets curve” to a trade context. The hypothesis is
examined with a specially developed CGE model that allows decomposing the environmental
inﬂuence of economic policies into growth effect, allocation effect, composition eﬂ‘ect and
regulation eﬂ‘ect The latter is achieved by treating institutional change as an endogenous
process dependent on income. Application of the CGE model to NAFTA, using a broad range
of scenarios, supports the institutional optimism hypothesis. The net pollution eﬂ'ect of trade
liberalization is beneﬁcial or insigniﬁcant, even for the country specializing in polluting
industries. The implication is that in many cases environmental interests are served better by a
focus on institution building in trading partners, than on the process of trade liberalization itself.

The dissertation is organized in six chapters. Chapter 1 reviews the literature on trade
and the environment; Chapter 2 develops the institutional optimism hypothesis in a simple
theoretical model; Chapter 3 describes the CGE model designed to empirically examine the
research question; Chapter 4 describes the model calibration; Chapter 5 presents the simulation
results; and Chapter 6 concludes.

Cop
HEI

Capyﬁsht by
HEINZ J. JANSEN
1998

To Daniel

iv

ACKNOWLEDGEMENTS

"Though I am suspicious of CGE models, I am very fond of CGE modelers. It must be
that the process of model building and calibration leave in their wake a great deal of
understanding about how real economies function”. (Edward E. Learner, 1993).

The learning experience of writing this dissertation lasted substantially longer than I
anticipated In particular, after I started my job at the European Commission four years ago, the
completion of the dissertation was often a strain.

Numerous people contributed in their own way to its completion. The longest-lasting
encouragement comes from my parents who always inspired me to follow an academic path
More than anyone, my parents wanted to see me complete my studies, thus providing the
important impetus of giving me a bad conscience about procrastinating. I thank them for their
love and support

Undoubtedly, I owe most to my wonderful friend and wife Wanda who suﬁ‘ered with me
all the way. Her love, patience, and encouragement made life in the all-but-dissertation limbo
endurable; her proofreading skills helped to substantially speed-up and improve my writing;
and ﬁnally she put things into perspective by giving birth to our son Daniel (sometime during
the ﬁrst draft of Chapter 4), whose broad smile makes this dissertation appear insigniﬁcant.

I am grateful to my boss and friend, Manfred Bergmann, for holding my back free so that
I could ﬁnally move this paper to completion ﬁ'om its everlasting near-ﬁnished status.

Academically, I am indebted to the members of my dissertation committee: Charley
Ballard, Sandra Batie, John Hoehn and Tom Reardon. Ted Tomasi provided guidance and
ﬁnancial assistance, before his departure from Michigan State University. My committee
members made the long-distance completion of this paper as smooth as possible, and willingly
accepted printing out hundreds of pages sent to them by email. All provided thoughtful critical
comments. I am especially indebted to Charley who guided me though the long process of
completing the CGE model. Finally, I owe my gratitude to Tom for being my committee chair
who guided me wisely and swiftly through the ﬁnal stages of the process.

TABLE Oi
TABLE OI

CHAPTER
1.]. lntrodu
1.2. Posmor
1.3. Key Cc
1.3.1. Ta
1.3.2. En
1.4. Tradinc
1.4.1. En
1.4.2 Fa:
1.4.3. En
1.4 4. P0]
14.5. Err.
1.5. Poverty
1.5.1. Cor
1.5.2. Em
1.6 Regard
16.1. C0:
1.6.3. Em

Climax:
2.1.1. De.

TABLE OF CONTENTS

TABLE OF FIGURES
TABLE OF TABLES

CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW
1.1. Introduction
1.2. Position of this Dissertation within the Trade and Environment Literature
1.3. Key Concepts for Understanding the Trade and Environment Interaction
1.3.1. Taxonomy of Trade Effects Inﬂuencing the Environment
1.3.2. Environmental Endowment
1.4. Traditional Pessimism Hypothesis of Trade and Environment
1.4.1. Environment and Comparative Advantage
1.4.2. Factor Mobility and the Industrial Flight Hypothesis
1.4.3. Empirical Findings on Industrial Flight Hypothesis
1.4.4. Pollution Haven Hypothesis
1.4.5. Empirical Evidence of the Pollution Haven Hypothesis
1.5. Poverty Attraction Hypothesis
1.5.1. Conditions for the Hypothesis
1.5.2. Empirical Findings on Poverty Attraction Hypothesis
1.6. Research Gaps and Purpose of this Paper
1.6.1. Contribution to Empirical Research
1.6.2. Inclusion of Environmental Extemality
1.6.3. Endogenous Treatment of Pollution Factors

CHAPTER 2 THE INSTITUTIONAL OPTIMISM HYPOTHESIS
2.1. Economic Development as Explanation of Environmental Stringency
2.1.1. Development and Production Patterns
2.1.2. Development and Institutions
2.1.3. Trade and Environmental Regulation
2.2 Trade Model with Endogenous Environmental Regulation
2.2.1. The Standard Model
2.2.2. The Modiﬁed Model
2.3. The Institutional Optimism Hypothesis
2.3.1. Formulation of the Hypothesis
2.3.2. Empirical Evidence

2.4. An Illustrative Application of the Institutional Optimism Hypothesis: A decomposition

procedure
2.4.1. Introduction and Case Description
2.4.2. Decomposition with Constant Regulation Level
2.4.3. Decomposition with Endogenous regulation level
2.5. Preliminary Conclusions

CHAPTER 3 MODELING TRADE AND ENVIRONIVIENT IN A GENERAL

EQUILIBRIUM FRAMEWORK

3.1. Empm
31.1. E.
3.1.2. C.
31.3 $1

3.2. NorrT
3.2.1.0
3.2215:

3.3. Model
3.3.1. Pl
3.3.2. 11
3.3.3.11
3.3.4. L
33.5. T
3.3.6. I
3.3.7. C

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4.1.1. 8
4.1.2. A
4.1.3.13
4.1.4. T
4.1.5. E

4.2. Ennrc
42.1. S
4.2.2. 8
4.2.3. A
42.4. E
4.2.5. (
4.2.6. I?
4.2.7. }
4.2.8. 2
4.2.9.\
4.2.10,

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3.1. Empirical Modeling Approaches
3.1.1. Econometric Approaches
3.1.2. Case Studies
3.1.3. Simulation Approaches
3.2. Non-Technical Model Description
3.2.1. Overview
3.2.2 Economy-Environment Nexus in the Model
3.3. Model Equations: Technical Speciﬁcation
3.3.1. Production
3.3.2. Households
3.3.3. Regulation Setting and Supply of Productive and Abatement Capital
3.3.4. Labor Supply
3.3.5. Trade
3.3.6. Taxes and Government
3.3.7. Closure

CHAPTER 4 DATA DESCRIPTION AND MODEL CALIBRATION
4.1 Stylized facts of the North American Free Trade Area
4.1.1. Social Accounting Matrix
4.1.2. Asymmetric Structure of NAFTA
4.1.3. Diﬁ'erences in Economic Development of NAFTA States
4.1.4. Trade Protection before NAFTA
4.1.5. Elasticities
4.2. Environmental Components
4.2.1. Sectoral Emission Coeﬁicients in the United States
4.2.2. Sectoral Abatement Costs in the United States
4.2.3. Abatement Functions
4.2.4. Extension of Environmental Relationships to Canada and Mexico
4.2.5. Calculation of Total Emissions
4.2.6. Relationship of Total Emissions to Air Quality
4.2.7. Health Effect of Air Quality
4.2.8. Effect of Health on Labor Productivity
4.2.9. Welfare Eﬁ‘ect of Pollution
4.2.10. Political Income Elasticity for Pollution Abatement

CHAPTER 5 SIMULATION RESULTS
5.1. Building up the Model Structure of the Central Case
5.1.1. Simple Trade Scenario with Internationally Immobile Capital
5.1.2. Introducing the Extemality
5.1.3. Introducing the Regulation Eﬁ'ect
5.2. Introducing Factor Mobility
5.3. Importance of the Oil Sector
5.3.1. Leaving out the Emission Eﬁ‘ect
5.3.2. Exclusion of Mexican Oil Sector from NAFTA
5.4. Sensitivity to Calibration Parameters
5.4.1. Using a toxicity weighted emission factor
5.4.2. Various Pollution Indicators
5.4.3. Abatement Elasticity

83
84
87

101
107
107
110
114
116
117
119
121

123
123
123
126
127
137
141
143
144
147
152
155
158
158
160
161
162
162

164
164
164
174
176
178
183
183
184
186
186
187
188

5.4.4. Abatement Function
5.4.5. Labor Supply Elasticity
5.4.6. Demand Elasticities
5.4.7. Elasticity of Scale
5.4.8. Revenue Recycling
5.5. Variations of the Regulation Equation
5.5.1. Various Regulation Elasticities
5.5.2. Policy Function Connected to Wages
5.5.3. Quantitative Restrictions
5.6. Unilateral Actions
5.6.1. Unilateral Changes in Abatement Intensity
5.6.2. Sectorally Optimal Regulation
5.6.3. Some Considerations on the Optimal Emissions Level
5.7. Tentative Conclusions

CHAPTER 6 SUMMARY AND CONCLUSIONS
6.1. Research Question

6.1.1. Introduction

6.1.2. Literature Review. Traditional Pessimism

6.1.3. The Envirornmental Kuznets Curve

6.1.4. Decomposition of Pollution

6.1.5. Institutional Optimism Hypothesis
6.2. Model Description and Calibration

6.2.1. Social Accounting Matrix

6.2.2. Production

6.2.3. Households

6.2.4. Government

6.2.5. Trade

6.2.6. Emissions and Abatement

6.2.7. Extemality

6.2.8. Institutions
6.3. Polity Scenarios and Baseline

6.3.1. Policy Scenarios

6.3.2. Dependence of Results on Pre-NAFT A Trade Barriers
6.4 Macroeconomic Effects of Policy Scenarios

6.4.1. Scenario 1: Full Trade Liberalization with Immobile Capital
6.4.2. Scenario 2: Full Trade Liberalization with Mobile Capital

6.4.3. Scenario 3: Leaving out the Petroleum Sector

6.4.4. Scenario 4: Unilateral Increase irn Environmental Stringency

6.5 Environmental Eﬂ‘ects of Policy Scenarios

6.5.1. Scenario 1: Full Trade Liberalization with Irnmobile Capital
6.5.2. Scenario 2: Full Trade Liberalization with Mobile Capital

6.5.3. Scenario 3: Leaving out the Petroleum Sector

6.5.4. Scenario 4: Unilateral Increase in Environmental Stringency

6.6. Conclusions

1 89
190
192
194
I94
194
194
198
199
201
201
205
206
208

214
214
214
215
217
218
220
222
223
223
224
224
224
225
226
227
228
228
229
23 1
23 l
232
233
233
235
235
237
238
239
240

APPENDIX: CALCULATION ON OPTIMAL REGULATION-NCOME ELASTICITY 254

viii

Figure M. De
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Figure 2-3: Ira
Figure 2-4. Em

 

Figure 3-2.
Figure 5-1: Cor
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TABLE OF FIGURES

Figure 2-1. Decomposition of the environmental Kuznets curve 52
Figure 2-2. Trade liberalization with constant environmental regulations 68
Figure 2-3: Trade liberalization with endogenous environmental regulation setting 71
Figure 24. Environmental effect of trade liberalization: Decomposition into scale, allocation
and composition eﬁ‘ect 79
Figure 3-1. Structure of the production function in ETERNA 100
Figure 3-2. Economy and Environment Interaction in ETERNA 102
Fignn'e 5-1: Contribution of Individual Sectors to Overall Emission Changes (igrnoring
regulation effect) 172
Figure 5.2: The impact of various levels of regulation elasticity on GDP and welfare (Zero
elasticity case set to 1) 196
Figure 5.3. The impact of regulation elasticity on total pollutiorn, growth and composition eﬁ‘ect
(percentage changes ﬁom pre NAFTA base case) 197
Figure 6-1. Decomposition of Pollution Causation 218

Table 2-1: 5
Table 3-1. (
11
Table 5-1. 11
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Table 5.2. S
c
Table 53. I
Table 5-4. 1
(1
Table 5.5. C
Table 56 C
Table 5-7. S

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Table 5-8 In
Table 59. E
Table S-lO. .
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Table 5-1 1. .
Table 5.12. .'
Table 5-13_ 1
Table 5-14. I
Table 5-16.
Table 5-17. 1
Table 5-18. 1
Table 5-19. 1
Table 5-20. I
Table 521. 1
Table 5.21 4

TABLE OF TABLES

Table 2-1: Summary of model results

Table 3-1. Comparison of different empirical approaches to assess trade and environment

interactions

Table 5-1. Macroecononnic eﬂ‘ects of trade liberalization (immobile capital; no
extemalities)

Table 5-2. Sectoral calculation of ennissions impact of trade liberalization (immobile
capital; no extemalities)

Table 5-3. Emissions impact of trade liberalization (immobile capital; no extemalities)

Table 5-4. Trade Liberalization when Extemalities are included: Welfare Change
(irrnrnobile capital)

Table 5-5. Central case simulation with immobile capital

Table 5-6. Central case simulation with mobile capital

Table 5-7. Sectoral calculation of emissions impact of trade liberalization (mobile capital;

no extemalities)

Table 5-8. Inﬂuence of the petrol sector on the overall emissions impact

Table 5-9. Exclusion of Mexican petroleum sector from NAFTA

Table 5-10. Replacing TSP in base case (immobile capital) with toxicity weights:
Macroecornonnic impact

Table 5-11. Comparison of the Composition effect for various pollutants

Table 5-12. Sirnulatiorns with a low abatement elasticity

Table 5-13. Central case with labor supply elasticity of zero

Table 5-14. Central case with inﬁnite labor supply elasticity

Table 5-16. Regulation eﬂ‘ect as function of wages

Table 5-17. Deﬁnition of restriction target in quantities of each sector

Table 5-18. Unilateral reduction in unit emissions by one third in the United States

Table 5-19. Unilateral reduction in unit emissions by one third in Mexico

Table 5-20. Unilateral reduction in unit emissions by one third in Canada

Table 5-21. Optimal sectoral regulation level

Table 5-22. Analysis of different factors on their inﬂuence on modeling results

72

95

166

170
173

175
177
179

182
184
185

187
188
189
191
192
198
199
202
204
204
205
211

1.1. Tntrodu

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CHAPTER 1

INTRODUCTION AND LITERATURE REVIEW

1.1. Introduction

The increasing globalization of the world’s econorrnies has resulted in recent years in a
sharp rise in interest in the interaction between intemational trade, environmental quality and
pollution Several international bodies have reacted to the political pressure and the recogrnition
that trade might have a negative impact on the environmental situation in various countries.
Notably, the newly established World Trade Organization (WT O) has established a committee
to study trade and environment issues. Similarly, tlne creep and tlne UNC'TAD have set up
study groups to review the relationship between trade and environment. Rarely has this
problem entered the political debate more forcefnnlly than in the context of the North American
Free Trade Agreement (NAFTA). NAFTA brought to the forefront of discussion the
environmental eﬁ‘ects of trade due to unequal economic development and regulatory standards
of the nations involved. The opening of borders was feared to turn the Mexico into a pollution

haven dnat erodes American environmental standards.

The number of articles published in the last few years on the environmental aspects of
NAFTA, or on trade and environment in general, certainly goes into the hundreds. It will
therefore be diﬁcult to provide any substantive new argument to the debate that has not been
made somewhere. Despite the richness in argumentative material, however, there is a
surprising lack of quantitative information on the various factors that shape the environment
and trade interaction. This nnissing information on the relative importance of the economy-
environment interactions is matched by a lack of coherence in the tlneoretical conclusions on

what to expect when trade barriers are removed.

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This paper will advance the discussion in several ways. A ﬁrst contribution will be to sort
the mechanisms and arguments. Other authors have provided literature reviews before. Here
the approach will have the sole focus of what happens when countries witln diﬂ‘erent
environmental standards engage in trade. This approach allows the organization of the existing
literature around two empirically testable hypotheses: the traditional pessimism hypothesis and
the poverty attraction hypothesis. The traditional pessimism hypothesis has two parts. Its ﬁrst
part, the industrial ﬂight hypothesis, predicts that polluting industries end up in the countries
with the most lax environmental regulation. Its second part, the pollution haven hypothesis,
states that countries use this mecharnism to relax environmental standards to attract industries.
The poverty attraction hypothesis states that underdeveloped countries have a comparative
advantage in polluting industries, which they cannot strictly regulate. Under these two

hypotheses trade would likely to be bad for the environment.

The second contribution of this paper is the formulation of a counter hypothesis to the
poverty attraction hypothesis, which we call the institutional optimism hypothesis. Its starting
poirnt in contrast to the other two hypotheses is that the regulation stringency of a country
cannot be treated as a cereris paribus condition. By making poor countries wealthier, trade
contributes to increasing the countries’ capacity and willingness to improve its environment
This tendency will in many cases outweigh the effect of any shift in the location of polluting

industry. This hypothesis will be illustrated in a simple theoretical model.

The third contribution of this paper is the empirical test of all three hypotheses in a
computable general equilibrium model of the North American Free Trade Agreement. The
interest of this paper goes beyond that of the narrow goal of only analyzing the trade-

environment relationship of the NAFTA. Due to the large diﬂ‘erences in the econonnic

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development between the USA and Canada on the one side and Mexico on the other, the case
of NAFTA can also be seen as a rrnicrocosm of the forces at work in North/South trade
liberalization in general. Therefore, the present paper understands the analysis of NAFTA as a
case study of a nnore general phenomenon, where it takes advantage of the fact that this case is
probably better documented than any other case of trade liberalization between trading partners

of such nmequal development levels.

The computable general equilibrium (CGE) tool, which is developed in this paper to
analyze trade and environment interactions, incorporates a number of components that other
models have neglected. In particular, (i) it fully incorporates a pollution extemality, which is
both necessary to gain a correct welfare assessment and the production feedback of
environmental policy. (ii) It is a three country model, which allows testing as to whether there
are systematic diﬁ‘erences between Nortlnem and Southern countries, to test the poverty
attraction hypothesis. (iii) It treats the regulation levels as endogenous. This feature allows the
analysis of the irnstitutional optirrnism hypothesis. (iv) It provides a full disaggregation of the
various eﬁ‘ects of trade on the environment. Other authors focus on aggegate numbers which
tend to give faulty impressions.

The empirical results show that (at least for local pollutants), the net result of trade

liberalization is an environmental improvement. Therefore, in general, trade is good for the

environment, even where large regulatory differences exist.

The remainder of this introductory chapter further motivate the arguments just sketched
To tlnis end it will ﬁrst position the empirical questions with the remainder of the trade and

environment literature. It will tlnen brieﬂy discuss some methodological prelinninaries. After this

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it will go on to discussing the theoretical and empirical literature on the traditional pessirnnism

and ﬁne poverty attraction hypothesis.

Chapter 2 formulates the institutional optimism hypothesis. This idea is developed in a
simple theoretical model that incorporates an endogenous policy formation process into ﬁne
arnalysis of trade-environment relationships. The system of equations hr the computable general
equilibrium model for the empirical testing is shown in Chapter 3. Chapter 4 describes the data
set and calibration of the model to NAFTA. Chapter 5 presents various simulation runs.

Chapter 6 provides a summary and concluding remarks.

1.2. Position of this Dissertation within the Trade and Environment Literature

The present paper focuses on assessing the econorrnic interactions between environmental
regulation and the pattern of trade. The issue can be divided into two sub-problems. First, ﬁnere
is the question of what effect a given differential in environmental stringency has on the trade
specialization of countries. This effect will be important in deterrnirning the degree to which
trade liberalization results in an improvement or a deterioration of the environmental situatiorn
of the aﬁ‘ected countries. The following chapter will provide an overview over ﬁne aburndant

ﬁneoretical literature and ﬁne more scarce empirical literature on ﬁnis aspect.

Second, trade liberalization directly and (mostly) indirectly inﬂuences ﬁne level of
regulatory stringency of conmtries, as it shapes boﬁn ﬁne economy and society of a country.
Chapter 2 will attempt to shed some light on this issue and develop a simple but irnstructive
model ﬁnat shows ﬁnat ﬁne internalization of the regulatory standards can fundamentally alter ﬁne

ﬁndings of standard models.

The twin questions of how trade influences ﬁne environment and how regulation
inﬂuencestradedoesnotexhaustﬁneliteratureﬁnatcanbefoundurnderﬁne“tradearnd

environment” label. At least ﬁve furﬁner topics exist, which will not be addressed in ﬁnis paper.

1W

Probably ﬁne most important driver of ﬁne environmental component of ﬁne NAFTA
debate was ﬁne emotional and political argument ﬁnat ﬁee trade erodes ﬁne national sovereignty
irn setting environmental standards (Shrybman 1990)‘. Hostility against ﬁee trade was focused
especially ﬁnrough ﬁne notorious tuna-dolphin case. The United States imposed an embargo
against ﬁne import of Mexican tuna ﬁsh caught wiﬁn purse-seine nets, which kill dolphins irn a
greater number ﬁnan US. law permits (Audley 1993,). The GATT (General Agreement on
Tariﬂ‘s arnd Trade) Dispute Settlement Panel ruled ﬁrat ﬁne import ban violated ﬁne irnternatiornal
trade code on grounds ﬁnat regulating ﬁne production process of a good falls nrrnder ﬁne
jurisdiction of ﬁne producing country only.2 The importing country has no right to impose its
particular environmental preferences for production processes on anoﬁner courntry (Arden-
Clarke 1992b). The Standards Code of ﬁne GATT does, however, allow a country to impose
import restrictions on goods which do not meet national product standards, such as certain

chemicals, pharmaceuticals, and wastes. On a multilateral level, examples of ﬁnis kind are ﬁne

 

lInthisrconterlrt, ithas beenproposcdtouseﬁneterrn "deregulatedtrade" overthemore enotionally
positive expression ”free trade” (Daly 1993).

2 The panel has a point in stating that environmental restrictions should nn principle not be treated
diﬁerenﬁy from diﬁ‘erences nn labor and capital use among countries. However, it evidenﬁy did not
take into consideration ﬁnat both Mexican and U. S. comparnies ﬁsh in the same body of water,
ratherthanwithintheirnational waters. Because everytunaﬁshharvestedby Mexicansennno
longer be ﬁshed by American ﬁshers, the case should have been treated like a transboundary
extenality.

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Basel Convention on ﬁne Control of Trans-boundary Movements of Hazardous Wastes and ﬁne
Convention on International Trade in Endangered Species of Wild Fauna and Flora

(ClTESXStevens 1993, GATT 1992).

In light of ﬁnese concenns, amendments to ﬁne original NAFTA treaty have been made.
Political pressure led to an inclusion of side agreements about environmental standards ﬁnat
allow for heavy ﬁnes and even possible trade sanctions, if national trade laws are not enforced
An overview of ﬁne agreements is provided by Hufoauer and Schott (1993, p. 1590. There
exists, however, some agreement ﬁnat ﬁne NAFTA side agreements are desigrned mainly to
pacify environmental interests, wiﬁn limited practical implications (Audley 1993). Additionally,
a US. court ordered to undertake an "Environmental Impact Statement" of ﬁne Norﬁn American

Free Trade Agreement (Wall Street Journal, 1 July 1993; Hufbauer and Schott 1993, p.159).

While ﬁne eﬁnical considerations of trade liberalization certairnly merit attention, in
particular insofar as ﬁney affect countries wiﬁn substantially diﬁ‘ering pollution standards, ﬁney
have already been spelled out in oﬁner places (e.g., Bhagwati 1993, Daly 1993). This paper will

concentrate on ﬁne narrower economic issues involved.
223 a. 2 m .5 nm- ' u ' WC - Vi onmen.:. uoehavir' H v.0 __. 11';

Related to ﬁne ﬁrst issue, ﬁnere exists a link between trade and environment in ﬁne
political sense ﬁrat it has been proposed to use trade sanctions as a means of pushing countries
wiﬁn lax environmental regulations into complying wiﬁn stricter standards (Anderson 1995).
The link between trade and ﬁne environment can be seen as analogous to ﬁnat between trade and
human rights issues. There is no pretext of a causality. Trade policy (such as ﬁne refusal to
grant most favored nation status) is used only for want of a better leverage point on ﬁne

achievement of a policy goal. This political aspect will also be neglected in ﬁne present paper.

t:-
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4-1-.1- H 5 l’ = ardinintem ' a .r it a -* ' 0'1. " 2:. amen-

Of a diﬁ‘erent nature and more focused on environmental issues are questions of how to
assure ﬁnat unilateral or international environmental policies are not undermined ﬁnrough trade.
For several tools, ﬁneoretical research and practical applications can be found. First, ﬁnere are
various schemes to introduce environmental labelling (e.g., Jha, Vossenenaar, and Zarilli 1993;
UNCT AD 1995, OECD 1997a). This approach means that environmentally ﬁiendly products
(produced at home and abroad) can obtain a label ﬁnat informs consumers about ﬁne
environmental standards applied in its production process. These cornsumer awareness schemes
exert a certain pressure on producers to apply clean technologies. Second, in accordance wiﬁn
ﬁne WTO treaty, signatories to international environmental agreements can limit trade on ﬁne
product in question (OECD 1997b). Third, ﬁnere exists a (mostly ﬁneoretical) literature on
border tax adjustments, i.e. a compensation boﬁn for imports and exports for diﬁ‘erences in

environmental taxes. (Mani 1996, Scherp and Suardi 1997).

4 T ' e

There exists a broad array of literature on trade wiﬁn hazardous products (see for
instance: Hackrnann 1994; Kummer 1994). While ﬁnis is an interesting ecornonnic topic in its
own right, ﬁne present paper focuses on ﬁne inﬂuence of environmental regulation on ﬁne broad
economy, not on a narrow set of individual products. In practice, ﬁnis exclusiorn means ﬁnat

pollution is only considered insofar as it aﬁ‘ects ﬁne production process of ﬁnose goods ﬁrst are

oﬁnerwise not considered harmful. The trade in hazardous waste is ﬁnerefore ignored.
5Di of tim liiinan nm
Game ﬁneory is one of ﬁne most fruitful areas of ﬁneoretical research in ﬁne ﬁeld of trade

and environment. There exist numerous models looking at ﬁne policy outcome when ﬁne trade

7

and mum
commas.

global), m
(perfect cc
more), etc
interactive
models. A
this heat.

literature u

L3.Kgy(

and environmental policy irn one country is not seen as independent from ﬁne policies of other
countries. Variations of ﬁnese models include ﬁne type of extemality (local, cross-horde,
global), market structures (monopoly, oligopoly, duopoly, atomistic), types of belnaviour
(perfect competition, Nash, Bertrand competition), ﬁne number of countries involved (two or
nnore), etc. However, very few papers of ﬁnis type attempt any quantiﬁcation of ﬁnese
interactive aspects. At best, ﬁney tend to be limited to numerical examples of ﬁneir ﬁneoretical
models. As our focus is more of an applied nature, raﬁner ﬁnan one of (optimal) policy design,
ﬁnis literature is also largely ignored. As it would be diﬁicult to provide a brief review of ﬁne

literature in ﬁne ﬁeld, the reader is referred to Ulph (1994).

1.3. Key Concepts for Understanding the Trade and Environment Interaction

The task of reviewing ﬁne literature is facilitated through ﬁne fact ﬁnat ﬁne dispute between
proponents and opponents of free trade, in light of differing environmental regulations, is not a
dispute over meﬁnodological issues. Boﬁn sides use similar economic models and largely agree
on ﬁne relevant mechanism ﬁnat trade liberalization will induce. The starting point is ﬁnat trade
will change ﬁne structure of the economy. Some sectors will suffer under ﬁne burden of new
competition, some industries will relocate into ﬁne country ﬁnat gives ﬁnem a competitive
advantage. Labor-intensive irndustnies might have an incentive to relocate to ﬁne country wiﬁn
lower wage rates (in ﬁnis case, Mexico). This could be because of lax environmental
regulations or oﬁner factors, such as low labor cost. Other sectors will beneﬁt ﬁom ﬁne enlarged

markets. Others may resettle, because ﬁney seek lax environmental regulations. On ﬁne oﬁner

hand, some it
mauve :
able to buy rr
an economic
magnitudes .

cmsequent s

Todrs

following tax

1.3.1. Tuon
Gtossr

hand, some industries in ﬁne wealﬁnier country (United States3) will expand because ﬁney have a
comparative advantage over ﬁneir Mexican counterparts, or simply because a richer Mexico is
able to buy nnore products ﬁom ﬁne US. The dispute about what ﬁne net eﬁ‘ect of ﬁnese changes
on economic welfare and ﬁne environment are, lies in different beliefs about ﬁne respective
magnitudes of ﬁne likely changes (as well as in differences in ﬁne willingness to accept

consequent sectoral and regional redistribution of economic activities).

To disentangle ﬁne various eﬁ‘ects of trade liberalization on ﬁne environment, ﬁne

followirng taxonomy is useful:

1.3.1. Taxonomy of Trade Effects Inﬂuencing the Environment
Grossman and Krueger (1995) have disaggregated ﬁne economic changes ﬁnat aﬂ‘ect ﬁne

environmental quality into ﬁnree components, ﬁne scale effect, ﬁne composition effect, and ﬁne

technique eﬁ‘ect.4

Salim If trade increases ﬁne size of an economy wiﬁnout changing anyﬁning else,
ﬁne resource use and pollution level will increase by ﬁne same proportion. The intuition behind
ﬁne scale eﬁ'ect is simple. If, for example, twice as many vehicles drive on ﬁne roads, fossil ﬁnel
emission will double, too. If trade ﬁnerefore increases ﬁne national income, ceterr’s paribus ﬁne

eﬁ‘ect on ﬁne environment is deleterious.

 

3 Because of the relatively minor role of the Canada-Mexico interaction and the relative similarity
between the Canadian and United States economy, the following discussion treats NAFTA as a
bilateral treaty between Mexico and ﬁne US. In general, the arguments concenning the situation of
the United States are equally valid for Canada.

" Compare also Stevens (1993).

gm
mmpositlm
beneﬁts of f.-
the contracti
the composi

scale effect

._g
2

about output
i‘OWCVBI, als

World Dcve]

W The conclusion of ﬁne previous paragraph is only valid if ﬁne
composition of ﬁne economy does not change. Wiﬁnin ﬁne economy, ﬁne distributiorn of costs and
beneﬁts of free trade is uneven. If ﬁne expanding sectors are relatively pollution-intensive while
ﬁne contracting ones are non-polluting, ﬁne scale effect will be reinforced. In ﬁne reverse case,
ﬁne composition eﬁ‘ect works to reduce ﬁne pollution level, and may potentially outweigh ﬁne
scale eﬂ‘ect.

W The composition eﬁ’ect again provides additional information only
about output changes of ﬁne economy. Change in ﬁne environmental intensity of production can,
however, also be ﬁne result of changing techniques used in ﬁne production processes. The
World Development Report 1992 (World Bank 1992, p. 39) decomposes ﬁne technique eﬁ‘ect
furﬁner into two components. First, an increase in ﬁne input-output efﬁciency reduces ﬁne
demand for resource inputs. Secondly, polluting inputs can be substituted wiﬁn nnore
environmentally benign inputs. Modiﬁcations in ﬁne production technique are ﬁne ﬁnird
important linkage ﬁnrough which trade can change ﬁne quality of ﬁne environment Of ﬁne ﬁnree
eﬁ‘ects, ﬁnis technique effect is ﬁne least understood, and ﬁne most diﬁicult to model analytically.
Beyond ﬁne assertion of certain elasticities of substitution between factor inputs as prices

change, economic ﬁneory still does a poor job of explaining what induces techrnical change.

In altering ﬁne scale, ﬁne composition, or ﬁne production techrnique of an economy, trade
policy is environmentally relevant. The paﬁnways ﬁnrough which ﬁnese alterations takes place
are many, and usually concern more ﬁnan one of ﬁnese ﬁnree effects. Fundamentally, ﬁne dispute
between proponents and opponents of trade liberalization lies in diﬁ‘erent beliefs about ﬁre
respective magnitudes of ﬁne likely changes, as well as in differences in ﬁne willingness to

accept ﬁne consequent sectoral and regional redistribution of economic activities and ﬁneir

10

mrmmcrnral
the eﬁ'em imn
throng the en
through empn

scopeofanan

environmental consequences. Because ﬁnere is a lack of studies ﬁnat quantify ﬁne magnitude of
ﬁne eﬁ‘ects involved, positions in ﬁne discussion are based largely on faiﬁn, a riﬁ ﬁnat goes right
ﬁnrough ﬁne envirornmental movement itself. While ﬁne issue can (at least in principle) be settled
ﬁnrough empirical analysis, emotional issues accompany ﬁnese disputes and go beyond ﬁne

scope of a narrow economic analysis.

1.3.2. Environmental Endowment

As a second preliminary, it is necessary to deﬁne ﬁne economic concept of "endowment"
as it is used in ﬁne following review of ﬁne trade literature. The literal interpretation of ﬁne term
would simply mean ﬁne number of units of a given factor ﬁnat is available to ﬁne economy at ﬁne
beginning of ﬁne analysis. For ﬁne purposes of ﬁne trade literature, ﬁne term needs to be
interpreted more loosely in two important aspects. First, endowment is an aggegation of sub-
urnits of diﬁ‘erent qualities. Wiﬁnout actually boﬁnering about ﬁre ﬁneoretical complexities
involved in ﬁne economic aggregation, it should be understood ﬁnat ﬁne concept denotes simply
a vague descriptiorn of relative availability of a certain class of input factors. Second, practically
no factor is really ﬁxed in its supply. Given ﬁne right incentives, ﬁne availability of any factor-
for production purposes- can be increased. People can change ﬁne amount ﬁney work, plow

more land, and so forﬁn.

Natural endowment in ﬁne way it is used here is ﬁnerefore not identical wiﬁn ﬁne natural
assirnilative capacity, i.e., ﬁne ability of ﬁne environment to absorb pollutants or to provide raw
materials for production. Availability of resources for production results from ﬁne interactiorns
of demand for assirnilative services, and from ﬁne public preferences and irnstitutional settings

ﬁnat make ﬁnem accessible (Blackhurst 1977).

ll

don‘t worl
Ofcollaps:
Bed in pn

caning“

The concept of environmental endowment and of ﬁne pollution-intensity of a good are
amorphous, as production may affect a wide number of envirornmental media to a varying
mt They should be understood here in the broad ﬁneoretical sense of general availability and
use of ﬁne environmental medium (Leonard 1988). The treatment of environment irn economic
nnodeling can be as understood analogous to ﬁnat of labor, which is also ﬁne aggregatiorn
connponents ﬁnat diﬁ‘er in qualities like skills and training.

The absorptive capacity of ﬁne environment is only ﬁne ceiling to ﬁne use of environmental
inputs. This limit is usually only reached under duress, in ﬁne same way ﬁnat people usually
don't work all hours ﬁney are awake. In boﬁn cases, ﬁne ceiling can be exceeded only at ﬁne cost
of collapse, and is eﬁ‘ectively binding.5 The usual amount of boﬁn labor and environment ﬁnat is
used inn production falls below ﬁnis ﬁneoretical extreme, and people keep leisure time as well as

certain environmental factors out of production.

The availability of environment is ﬁne result of economically and institutiornally
determined artiﬁcial scarcity and demand for assinnilative services ﬁnat result ﬁonn
consumption, production, and technology. Environmental availability is similar to ﬁne supply of
labor, which is not simply a linear function of ﬁne population, but depends on wage rates,
irndividual preferences, and cultural and structural idiosyncrasies of countries ﬁnat may keep
certain groups like women and minorities from working, or may force some to work against

ﬁneir wills.

 

’Undcrextrenecircumstances,theymaybeexceeded overashortperiod oftinne, but in botheases
their future production potential will be reduced.

12

milabilitjr
neural ph)

economy 1

denote the
quantity in
resource at
States, be
magnitude
Nuke-st
US. has, 1

lighter env

The

Inﬁnesamewayﬁnatchangesinwagescanalterﬁnesupplyoflaborinaneconomy,ﬁne
availability of environment also varies wiﬁn changes in ﬁne opportunity cost of resources. The
actual physical availability of environment is ﬁnerefore relevant for ﬁne compositiorn of ﬁne
ecornonny and ﬁne determination of trade pattenns only irnsofar as it inﬂuences ﬁne political and
institutional availability of environment for ﬁne production process. Factor endowment does not
denote ﬁne maximum ﬁneoretical level of availability of environment or labor-capital, but ﬁne
quantity used in equilibrium. It is in ﬁnis sense ﬁnat Mexico, for instance, could be called
resource abundant, because it is relatively cheaper and easier to pollute here ﬁnan in ﬁne Urnited
States, because regulations and enforcement are relatively lax. If one looks ornly at ﬁne
magnitude of resources per capita, one would come to ﬁne opposite conclusion ﬁnat Mexico is
resource—scarce compared wiﬁn ﬁne United States. Relative environmental abundance in ﬁne
US. has, however, been tunned into relative scarcity, ﬁnrough ﬁne force of ﬁne law ﬁlat sets
tighter environmental standards for American producers ﬁnan ﬁnose ﬁneir Mexican counterparts

face.

There exist a variety of mechanisms ﬁnrough which ﬁne supply of environmental
resources may be restricted. This restriction could be achieved ﬁnrough regulatory instrummts
ﬁnat are enforced by ﬁne government, or ﬁnrough a sale of ﬁne rights to exploit ﬁne resources,
eiﬁrer ﬁom private owners or a state agency. The same level of environmental quality can be
attained using eiﬁner quality standards or monetary instruments such as taxes or emission
permits. As most of ﬁne models in ﬁne following discussion abstract from transactions costs and
pay no attention to ﬁne distributional consequences of different regulations, no distinction- of ﬁne
type of instruments is necessary. The implicit price of regulatory instruments could be

translated into ﬁne explicit price ﬁnat results from a limitation of ﬁne endowment ﬁnrougln

l3

emissm perm
market value 0:
nreouroe as ir

sl incremental ;

In the fol
measure that c
with the letter 0;
not enforced in
”Mg pm
0056, of entire
cUltstralm is not
‘9831 Wills.
My. Such as it
hunting the use
mm a re
“WWI Uri
Worms] 5

0051:.

 

 

emission permits issued by ﬁne state. It is ﬁnerefore easiest to understand price as ﬁne explicit
market value of ﬁnese tradable permits to avoid ﬁne complex rhetoric of interpreting ﬁne price of
a resource as its shadow productivity (i.e., the increased output ﬁnat would have resulted ﬁom

an incremental increase in its use).

In ﬁne following discussion, environmental regulation is to be understood only as ﬁnose
measures ﬁnat enterprises actually have to undertake. This requirement need not be identical
wiﬁn ﬁne letter of ﬁne law. Many countries have very strict regulations on ﬁne books which are
not enforced irn practice, eiﬁner ﬁnrough corruptiorn, lack of enforcement tools, or a political
bargaining process. National or local governments may grant exemptions from, or carry ﬁne
costs, of envirorunental regulations in order to attract irnvestrnents, so ﬁne environmental
cornstraint is not binding ﬁnat for ﬁne ﬁrms. In oﬁner cases, ﬁne de facto constraints may exceed
legal constraints, as social pressures can block certain types of investment ﬁnat are perceived as
risky, such as waste dumps and power plants (Leonard 1988, 65). Whatever is ﬁne cause of
limiting ﬁne use of environmental functions for ﬁne economic process, for ﬁne following
discussiorn, a restricted availability is interpreted as economically equivalent to a limited
endowment Unless explicitly stated, ﬁne discussion will also neglect any reductiorn in
envirornmental extemalities. This means ﬁnat environmental policies always imply increase

costs.

14

1.4. Tradiri

otpressnon
predictien 0
there are us
in an ecornor
n the theo
relemt inn
one or two
Swim we

ﬁndings.

1.4. Traditional Pessimism Hypothesis of Trade and Environment

The complexity of ﬁne interactions between trade and ﬁne environment ﬁnds is
expressiorn in a cornsiderable and rapidly growing body of literature‘. An exact theoretical
prediction of ﬁne net eﬁ‘ect of trade liberalization on ﬁne level of pollution is diﬁcult, because
ﬁnere are usually a number of counteracting mechanisms at work Since ﬁne level of complexity
irn an economic analysis rises rapidly wiﬁn ﬁne inclusion of additional elemens, ﬁnere is no work
in ﬁne ﬁneoretical literature on trade and ﬁne environment ﬁnat attemps to incorporate all
relevant interactions between ﬁne environment and ﬁne economy. Raﬁner, most papers focus on
one or two important aspecs ﬁnat could be brought forward by a trade liberalization. In a late
section we will report on what empirical literature ﬁnere is to corroborate ﬁne ﬁneoretical

ﬁndings.

1.4.1. Environment and Comparative Advantage

The simplest modelling approach in ﬁne literature is based on ﬁne classical Heckscher-
0hlin model with two countries, two goods, and two factors. Environment simply serves as one
input factor while ﬁne oﬁner factor is a composite good, consisting of labor and capital (Ohlirn
193 5). Under a number of special conditions (perfect competitiorn, zero transportation coss,
incomplete specialization, identical linearly homogenous production furnctions, identical
homoﬁnetic preferences, absence of external econorrnies, constant relative factor intensities at all
relative factor prices, factors homogeneous in quality, and ﬁne number of factors no greater ﬁnarn

the number of commodities), ﬁne ﬁnree basic ﬁneorems of international trade can be derived

 

‘ An earlier review ofthe literature has been undertaken by Dean (1992).

15

The ﬁrs
output and in
trade) output
of the input f:
that is recur:
compared wl

country Whel
marginal pr0<

As trac
countries. 1h
”imitations,

lmnobile be

The ﬁrst is ﬁne factor price equalization ﬁneorem. It states ﬁne basic interaction between
output arnd input prices irn an open economy. In a situation of autarky (i.e., in ﬁne absence of
trade) output prices in ﬁne two countries will generally diﬁ‘er, reﬂecting ﬁne diﬂ‘erent scarciﬁes
of ﬁne input factors. In a country ﬁnat is relatively abundant in environmental resources, a good
ﬁnat is resource—intensive will be relatively cheaper ﬁnan in a country where resources are scarce
compared wiﬁn labor and capital. Similarly ﬁne input factors will be nnore expensive in a
country where ﬁney are scarce ﬁnan where ﬁney are abundant, reﬂecting ﬁneir decreasing
marginal productivity.

As trade barriers are removed, ﬁne prices of ﬁne traded goods are equalized across ﬁne
countries. The factor price equalization ﬁneorem now states ﬁnat, under ﬁne above listed set of
assumptions, ﬁne factor prices will also be equal in ﬁne two countries, even when ﬁne factors are
immobile between ﬁlem. Factor prices are a function of output prices only. Wiﬁn ﬁnis
equalization of boﬁn output and input prices established, ﬁne standard result of trade ﬁneory
follows automatically: A country exports goods ﬁnat are intensive in ﬁne use of ﬁne factor wiﬁn
which ﬁne country is well endowed A resource-abundant country ﬁnerefore exports resource
intensive goods, and imports goods ﬁnat are intensive in ﬁne use of capital and labor. In ﬁne
jargon of trade ﬁneory, a resource-abundant country has a comparative advantage in producing

pollution-intensive goods.

The Stolper-Samuelson ﬁneorem states ﬁne direction in which factor intensities move
when ﬁne relative output prices change, be ﬁnis as a result of trade liberalization or a shift in ﬁne
demarnd curve (Stolper and Samuelson 1941). An increase in ﬁne relative price of ﬁne
environmentally intensive good raises ﬁne demand for environment as an input factor and wiﬁn

it, its price. An adjustment process takes place ﬁnat equalizes marginal productivity to ﬁne new

16

price 1
ans-tron:
taking l:
Howey:
good in

slgnsifﬁ

price levels. This adjustnnnent means a substitution away from ﬁne more expensive
environmental irnput towards the now cheaper capital and labor input This substitution is
taking place in boﬁn irndustries so ﬁnat ﬁney will boﬁn be less resource-intensive ﬁlan before.
However, ﬁne overall use of resources will not fall, because ﬁne share of ﬁne resource-intensive
good in ﬁne overall output increases. Obviously, ﬁne same process takes place wiﬁn opposite

signs if ﬁne original change is a drop in ﬁne price of ﬁne resource intensive good.

The ﬁnird important ﬁneorem of trade is ﬁne Rybczynski (1955) ﬁneorenn It deals wiﬁn ﬁne
question of what happens if one of ﬁne endowments of a country changes. An irncrease in ﬁne
availability of natural resources brings ﬁne intuitive result ﬁnat production of ﬁne environmentally
intensive good will expand. Less intuitively, but as a direct result of ﬁne above listed
assumptions, ﬁne production of ﬁne capital and labor intensive good shrinks. If ﬁne country is
previously a net exporter of the pollution-intensive good, its exports will rise furﬁner, as will its
imports. If ﬁne country is an importer of ﬁne pollution intensive good, ﬁne good will be
substituted for by home production and ﬁne trade volume will drop. The Rybczynski ﬁneorem
means ﬁnerefore ﬁnat specialization increases as ﬁne differences in endowments between
countries become larger. A country ﬁnat sets strict emission standards ﬁnerefore exports its
pollution problem via trade. Conversely, in an open economy oﬁner countries share ﬁne beneﬁts

of increased output ﬁnat may result from lax emission standards.

The ﬁnree ﬁleorems ﬁnat result ﬁom ﬁne Heckscher-Olnlin model are based on quite
restrictive assumptions. However, ﬁle ﬁamework has served as a starting point for much of ﬁne
ﬁneoretical literature on trade and environment. Next to ﬁne elegance of ﬁne model, its
attractiveness lies in ﬁne modeling assumptions themselves, which make initial factor

endowments carry ﬁne entire burden of ﬁne explanation of trade patterns. If environment is

17

countrie

Mexico,

Onecou

simply interpreted as if it is also a factor endowment, ﬁne eﬂ‘ects of a change in policy can be
irntepreted in a straightforward manner. Most models, however, have moved beyond ﬁnis two-

cornmodity, two-factor, two-country world ﬁnat fornns the core of classical trade ﬁneory.

In ﬁne followirng review, it is mostly assumed ﬁnat trade takes place between two stylized
countries wiﬁn unequal endowments, because ﬁne political concern about ﬁne environment-trade
irnteractiorn is centered around asymmetric alliances, such as ﬁnose between ﬁne USA arnd
Mexico, between Europe's North and Souﬁn, or between OECD countries and ﬁne Third World
One courntry is ﬁnerefore presumed to be rich and well-endowed wiﬁn capital, but relatively
scarce in labor and in environmental endowment, reﬂecting its comparatively strict pollution
regulations. The oﬁner country is taken to represent a prototype of a Third World courntry, wiﬁn
little capital, many working hands, and lax environmental regulations. Alﬁnough ﬁnis caricature
of a trade agreement is not stricﬁy needed for ﬁne ﬁneoretical analysis it is useful irn focussing

ﬁne discussion on ﬁne cases most relevant to ﬁne problem.

Alﬁnough it is not strictly an environmental paper, Jones (1971) provides an important
early contribution to ﬁne issue, by presenting an analysis of ﬁne Heckscher-Ohlin ﬁamework
wiﬁn ﬁnree instead of two input factors. In his analysis, only labor can be used for ﬁne production
of boﬁn outputs, while capital is only used for one good, and land (environment) is used
exclusively for ﬁne production of ﬁne oﬁner output. An important conclusion of his analysis is
ﬁnat ﬁne factor price adjustment mecharnism need not hold true. This conclusiorn mearns ﬁnat
factor prices are not uniquely determined by ﬁne price level of outputs, but also by ﬁne general
availability of factors wiﬁnin an individual country. Even in a trade equilibrium wiﬁn equal
prices for goods, ﬁne rewards for factors between two countries can diﬁ‘er. A greater supply of

environmental goods ﬁnus can entail an increase in ﬁne compensation for oﬁner factors.

18

throughoa

model, g:

directly tr

It is consistent wiﬁn Jones's model ﬁnat the return to boﬁn labor and capital was
ﬁnroughout history persistently higher in ﬁle United States ﬁnan in Britain, as ﬁne US had a
greater abundance of natural resources, especially land. Under ﬁne assumptions of Jones'
rrnodel, govemment policies ﬁnat regulate ﬁne availability of environmental inputs ﬁnus aﬂ‘ect
directly ﬁne wage rate and interest rate of a country. Jones shows ﬁnat ﬁnis seemingly minor
generalization of ﬁne Heckscher-Ohlin model leads potentially to different policy cornclusions.
For a small country in ﬁne Heckscher-Ohlin model, ﬁne reward for one input stays unaﬂ‘ected by
changes in ﬁne supply of ﬁne oﬁner input. It is of no sigrniﬁcance for owners of inputs, if ﬁney live
in a country wiﬁn resource abundance or not. Due to its limitation in ﬁne movement of factors
between sectors, Jones's model produces ﬁne result ﬁnat it very well matters for ﬁne returrn on
labor and capital what environmental regime rules the availability of resources. Capitalists' and

workers' incomes depend here on ﬁne restrictiveness of environmental policy.

Itslnouldbenotedhereﬁnatusuallyﬁne factorretumsdonotreactinasymmetrical way.
The extent to which a certain factor beneﬁts ﬁom a decrease in ﬁne price of ﬁne natural resource
is positively related to two econonnic parameters, namely ﬁne factor intensities arid ﬁne
elasticities of substitution: Ifﬁne goods ﬁlat are intensive in ﬁne use of environmental irnputs are
also relatively intensive in labor inputs, labor will overproportionally proﬁt from lower resource
prices. In addition, a great elasticity of substitution between labor and environment (compared
to ﬁnat between capital and environment) will beneﬁt labor. The higher ﬁnis elasticity diﬁ‘erence
is, ﬁne more labor ﬂows towards ﬁne resource-using sector in order to equalize productivity of
resources among sectors. Movement of labor out of ﬁne capital-using sector lowers ﬁne
productivity of capital. In ﬁne extreme case, ﬁne net return to capital may even fall, depending

on ﬁne model parameters. The reverse case can be made analogously. The ambivalence in ﬁne

19

net results in Jones' model stresses ﬁne furndamerntal importance of having good empirical
estimates of input substitution possibilities and factor intensities, in order to avoid qualitative

erors in ﬁne analysis.

McGuire (1982) shows ﬁnat factor-price equalization breaks down as countries
implement different environmental regulations, which he models as neutral technical regress.
Regulatory diﬁ‘erences violate ﬁne condition of identical technologies in the standard rrnodel. In
contrast to Jones, however, in McGuire's model ﬁne reward for ﬁle factor used intensively irn ﬁne
non-regulated industry will increase urnambiguously. While giving clear proof of ﬁne possibility
of deviations ﬁom ﬁne factor-pnce-equalization ﬁneorerrn, ﬁne use of Jones' arnd McGuire's
analysis for policy conclusions has limitations in ﬁnat ﬁne analysis takes important parameters as
externally given even ﬁnough ﬁnese parameters are really inﬂuenced by ﬁne policy itself. One
critical assumption is ﬁnat output prices are not inﬂuenced by domestic policy. In ﬁne case of
NAFI' A or ﬁne European Union, for at least some sectors, ﬁne assumptiorn carnrnot hold ﬁnat
price levels will remain unaffected by changes in ﬁne national environmental policies. Of
course, ﬁne degree to which competitiveness is changed depends not simply on ﬁne permissible
emissions but also on ﬁne type of environmental policies chosen. For irnstance, an industry
might be nnore sensitive to a tax instrument ﬁnan to a regulation. Clearly, however, irnsofar 3
environmental policies alter ﬁne competitive position of an econonnic sector of a country, ﬁne

analysis will have to include effects on ﬁne balance of payments and ﬁne terms of trade.

Furﬁnermore, as factor rewards change, factors supplies generally also change. Demand
growﬁn for a pollution-intensive good raises ﬁne productive value of pollution Cornsequenﬁy
pollution tends to rise. The assumption of ﬁxed factor supply in ﬁne Heckscher-Ohlin model,

however, implies ﬁlat changing price levels do not affect ﬁne level of environmental quality of a

20

mum

maiys

ObVlOL'
and 01
under ti
lax regt
Mesa
overall p
coma}, v

yerSl'orl of

in It
Qumran 0
meme. 8
Producuon
production
Pinning ch
belt625:0, Suﬁ

We “Moll

courntry. A step towards incorporating demand and factor supply eﬁ‘ects is urndertaken in ﬁne

analysis of Baumol and Oates (1988).

The authors consider a model ﬁnat is based on ﬁne aggregation of ﬁne supply and demand
curves of two trading countries. Assume ﬁnat a country induces an upward shift in ﬁne supply
curve of its pollution intensive good by imposing stricter environmental regulations. This
increases ﬁne global price level of ﬁne polluting good, and reduces ﬁne quantity cornsumed
Obviously, ﬁne pollution level irn ﬁne home country will be reduced. The proposition by Baumol
arnd Oates ﬁnat ﬁne global pollution level must fall, however, seems to hold urnambiguously only
under ﬁne limiting assumption ﬁnat ﬁne country ﬁnat increases ﬁne regulatory stringency has rrnore
lax regulations ﬁnarn ﬁne oﬁner country. It is conceivable, however, ﬁnat in some sectors an
increase irn ﬁne environmental standards of ﬁne more regulated courntry leads to an increase in
overall pollution ennissions, if it induces an increase in pollution-intensive production in ﬁne
courntry wiﬁn ﬁne less stringent regulation. It would be straightforward to construct a nnodiﬁed

version of ﬁne Baumol and Oates model ﬁnat produces ﬁnis result.

In ﬁne model, ﬁne balance-of-payments effect on environmental regulation depends on ﬁne
question of wheﬁner ﬁne regulating economy is a net importer or exporter of ﬁne pollution-
irntensive good. For importing countries ﬁne balance of payments will deteriorate as home
production falls and ﬁne price level of imports increases. For exporters, decreases irn home
productiorn arnd price increases point in opposite directions. The direction of balance-of-
payments changes is ﬁnerefore not clear a priori. Also, wheﬁner non-environmental factors
beneﬁt or suﬂ‘er urnder regulatory policies will depend on ﬁne shape of ﬁne demand curve. A low
price elasticity of demand can mean that ﬁne return to labor and capital actually rises, as. ﬁne

sector extracts a quasi-monopoly rent from its price increase.

21

In ﬁne same way as ﬁne Jones model cautions us to consider ﬁne irrnportance of input
substitution elasticities in deriving qualitative results, ﬁne Baumol-Oates model stresses ﬁle
sensitivity of modelling to demand elasticities. The sensitivity of ﬁne result to elasticities may be
even furthered by ﬁne omission in boﬁn models of substitutiorns in demand between diﬂ‘erenﬁy
polluting goods. If ﬁne government regulates one sector only, ﬁne pollution level may actually
rise (even wiﬁnin a country) as ﬁne pollution reduction in one sector may be overcompensated

by ﬁne pollution increase in anoﬁner sector.

1.4.2. Factor Mobility and the Industrial Flight Hypothesis

The results presented are based on models ﬁnat use ﬁne critical assumption ﬁnat factors of
production are internationally immobile. In most cases, such as ﬁne European Union and
NAFTA, ﬁne assumption of capital immobility is, however, unrealistic. Mundell (1957) has
shown ﬁnat movements in factors can substitute for ﬁne movement in commodities and lead to
an identical price-equalization phenomenon as in ﬁne Heckscher-Ohlin ﬁarnework. In a two-
factor/two-good world, ﬁne mobility of only one factor is needed to produce ﬁne result Ifcapital
is ﬁne mobile factor, it would move into ﬁne capital-scarce country until factor-price
equalization is reached. The capital-abundant country loses productiorn, while ﬁne labor-
abundant country increases overall production. As a ﬁrm has ﬁne choice of eiﬁner servirng a
foreign market ﬁnrough exports or ﬁnrough production in ﬁne foreign market, capital ﬂows in
general will reduce ﬁne level of trade between countries, alﬁnough it is possible ﬁnat investrnert

and trade are supplements (Markusen 1983; Wong 1986).

McGuire (1982) demonstrates ﬁnat, in a Heckscher-Ohlin type model, ﬁne regulated
industry will be completely driven out of ﬁne regulating country. If ﬁne factor ﬁnat is used

intensively in ﬁne regulated sector is internationally mobile, it will migrate out of ﬁne regulating

22

 

in the l
beneﬁt
a facton

standar

mobile
capital f
than offs
a! subset
and the s
aWOprn'al
Swims ft

increase.

 

country and ﬁne overall economy will shrink, not only due to ﬁne decreased productivity entailed
in ﬁne regulation, but also due to ﬁne loss in ﬁne production factor. If, however, ﬁle mobile factor
beneﬁts ﬁom ﬁne regulation, because it is not used intensively, a regulation can actually induce
a factor inﬂow innto ﬁne regulating economy. Alﬁnough one would expect ﬁne ﬁrst case to be ﬁne

standard scenario, an economy could actually gain under a certain set of economic parameters.

Merriﬁeld (1988) also provides an example of a model of pollution abatement with
mobile capital. A tax on ﬁne polluting industries could actually increase pollutiorn, because
capital ﬂows into ﬁne oﬁner country, and ﬁne consequent increase in pollution ﬁnere may nnore
ﬁnan oﬂ‘set ﬁne reduction in errnissions at home. The effect depends crucially on ﬁne elasticities
of substitution among factor inputs, pollution and capital intensities in production furnctions,
arnd ﬁne sensitivity of ﬁne capital stock to pollution damage wiﬁnin each country. Given ﬁne
appropriate parameters, ﬁne model of Merriﬁeld is ﬁnus capable of producing ﬁne nightmare
scenario for rich countries: An increase in standards produces a loss of jobs while pollution
increases.

Worries of trade urnions and many environmentalists in wealﬁny countries about trade
liberalization wiﬁn poorer nations are based exactly on ﬁnis reasoning of ﬁne mixed commodity-
factor ﬂow nnodel. Of ﬁne ﬁnree factors of production ﬁnat we consider, poorer countries can be
assumed to have an abundance in ﬁne two ﬁnat are immobile (resources and labor), while ﬁney
have a scarcity in ﬁne mobile factor (capital). To equalize factor rewards, capital will ﬁnerefore
move ﬁom ﬁne rich country to ﬁne poor where it is scarce, and hence earns a larger return In
ﬁne extreme, ﬁne poorer economy grows and ﬁne wealﬁnier economy shrinks due to ﬁne capital

ﬂows.

23

In the
production:
loss through-
problem ﬁn:
country rm;
manic n
mobility lea

environmen

In ﬁne aseptic world of Heckscher-Ohlin models, ﬁnere is no tragedy in ﬁne loss of
production as ﬁne population of ﬁne country wiﬁn capital outﬂow gets overcompensated for ﬁneir
loss ﬁnrough ﬁne higher rent ﬁney obtain in ﬁne foreign rrnarket In real life ﬁnere is, of course, ﬁne
problen ﬁnat capital owners and workers are not identical. A move of capital outside of a
courntry implies direct job or earning loss and depresses ﬁne home country’s (Keynesian)
economic multiplier and its tax base. The ramiﬁcations of ﬁne standard model wiﬁn capital
nnobility leave policymakers only ﬁne choice of taking a wage loss or of harrnornizing ﬁne

environmental standards.

There are a number of reasons, however, why the capital mobility model need not lead to
an exodus of capital into ﬁne country that oﬁ‘ers low wages and environmental costs. One
important factor is ﬁnat a ﬁrm's decision to relocate depends on more parameters ﬁnan ﬁne ﬁrree
factors listed Notably, the model neglects ﬁnat labor is hardly homogenous. Know-how and
human capital are often more important for a production process ﬁnan ﬁne numbe of working
hands. While most poor countries are surely well-endowed wiﬁn unskilled labor, ﬁnis condition
is generally accomparnied by a relative scarcity of skilled workers. For many ﬁrms, ﬁnis scarcity
is ﬁne decisive constraint not to relocate. Oﬁner factors, such as cultural barriers, political
stability, quality of public inﬁastructure and commurnications ﬁrms, bureaucratic
idiosyncracies, or even ﬁne low level of environmental quality, may be important factors ﬁnat
combine to create an industrial inertia ﬁnat keeps companies from writing 05 ﬁne physical and

human capital of existing companies in ﬁne home country.

The value of low environmental regulations in ﬁne host country also may be overrmd as
a factor for industrial location, since companies plan ﬁneir pollution standards to meet standards

ﬁnat apply for ﬁne life span of ﬁne investment. As retroﬁtting of old equipment tends to be very

24

“pensive,

government:
environment
come 2
this context 1
than to dom-
felocate for
economic irr

barrierto cm

Pmductjvhy
0f know-hoe
”my, and
me and the
Simple mode
pmduCtix-tty
ﬂow, not le;

mmc ﬁn!

expensive, ﬁrms will mostly orient themselves to meet expected regulations." oaen
governmental rhetoric and anecdotal evidence point towards an increased stringency of
environmental regulatiorns. Even in ﬁne absence of regulatory enforcement, large international
connparnies generally try to meet global environmental standards. Leonard (1988) points out in
ﬁnis context ﬁnat many countries tend to apply stricter environmental standards to foreign raﬁner
ﬁnan to domestic ﬁrms. These general remarks do not imply ﬁnat ﬁnere are no companies ﬁnat
relocate for purely environmental reasons as ﬁne ﬁneory would predict, but raﬁner ﬁnat ﬁneir
economic importance tends to be limited. By ﬁne same token high investment costs can act as a

barrier to entry for new ﬁrms, which also cannot be measures directly.

The ﬁneoretical importance of capital ﬂows is also dependent on diﬁ‘erences in
productivity between ﬁne country of origin and ﬁne receiving country. Capital ﬂows and ﬂows
of know-how are usually tied to each oﬁner. If investment ﬂows aﬁ‘ect productivity in ﬁne poorer
country, and wiﬁn it ﬁne purchasing power, it may actually be increasing raﬁner ﬁnan decreasing
trade and ﬁne wage rate-even for unskilled laboruin the richer country. In ﬁne ﬁamework of a
simple model, Wong (1986) lists ﬁne necessary conditions for ﬁnis. The positive feedbacks ﬁom
productivity improvement may ﬁnus to a considerable extent beneﬁt ﬁne richer country's trade
ﬂow, not least because international transplants tend to have a larger import share ﬁnan

domestic ﬁrms.

 

7 For chenical ﬁrms, Monty states ﬁnat the capital investment necessary for pollution reduction on
existing plants is rouglnly ﬁve times as expensive as ﬁne equivalent equipment installation in a new
plant (Monty 1991, p.7).

25

critically ill
ofcapital f

lamented b

The ]
levels of en
be fornnnular
is a fundam
regulators.
depend on ii

1.43. Empi

Empir

Despite ﬁne acknowledgement in ﬁne theoretical literature that capital mobility can
critically alter ﬁne qualitative results of trade liberalization, an appropriate numerical modeling
of capital ﬂows is very diﬁcult. The omission of ﬁne problem in most applied models has been

lamented by several auﬁnors (Srinivasan and Whalley 1986, Goulder and Eichengreen 1992).

The precedirng review of ﬁne literature presents ﬁne traditional arguments of how diﬂ‘erent
levels of environmental regulation shape ﬁne pattern of trade specialization. This argument can
be formulated as ﬁne “industrial ﬂight hypoﬁnesis”. It maintains ﬁnat high pollution-control costs
is a fundamental factor in making ﬁrms leave nations which have a high level of environmental
regulations. Evidently, the link between pollution control costs and actual emissions will

depend on ﬁne type of environmental policy in place.

1.4.3. Empirical Findings on Industrial Flight Hypothesis
Empirical studies on industrial ﬂight hypoﬁnesis have to cope wiﬁn ﬁne intrinsic diﬁculty

of measuring levels of pollution and pollution control expenditures. Tacklirng ﬁlese severe data
linnitations has produced a wide array of empirical methods. Different approaches range from

ﬁne merely descriptive, to econometric tests and simulation models.

Kalt (1988) analyzes US trade ﬂows ﬁom 1967 to 1977 in a cross-country regression
His ﬁndings point to an insigniﬁcant impact of environmental regulation on all sectors.
However, if ﬁne analysis is limited to ﬁne manufacturing, a clear negative impact on exports due
to regulation is established. This impact becomes even more signiﬁcant, if ﬁne chemical sector

is excluded from ﬁne manufacturing aggregate.

In analyzing ﬁne pollution content of trade ﬂows, Robison (1988) ﬁnds ﬁnat increases in
pollution control have shifted ﬁne comparative advantage of ﬁne United States witln Canada
More high-abatement—cost goods are imported and more low-abatement cost goods are

26

Wong
discount

starts bet

turbulenc

even with
L’su

of a group
00¢ Changer

Calm}, l5 Sign

exported While ﬁnere is no doubt about ﬁnis trend, ﬁne value of ﬁne study needs to be
discounted on ﬁne grounds ﬁnat it has ﬁne implicit assumption ﬁnat standards remained
urnchanged in Canada Furﬁnermore, ﬁne analysis could be potentially biased by ﬁne timing of
ﬁne years for which the abatement content of trade was calculated. The time span analyzed
stars before ﬁne First Oil Crisis (1973) and shortly after ﬁre Second Oil Crisis (1982). The
turbulences of ﬁne world trade system at ﬁne time may have caused changing trade patterns,
even wiﬁnout changing environmental policies.

Using a similar meﬁnodology as Robison, Sorsa (1994) shows ﬁnat world market shares
of a group of countries with high industrial standards in environmentally sensitive goods have
not changed much over ﬁre last two decades. Wiﬁn ﬁne exception of a changing composition of
trade wiﬁn Eastern Europe, Scherp and Suardi (1997) ﬁnd also ﬁnat ﬁne relative pollution

intensity of EU trade has not changed and may have even increased since ﬁne 19705.

This result contrasts wiﬁn ﬁne study by Tobey (1990). He identiﬁes ”dirty" irndustries
according to ﬁne percentage of abatement expenditures per sector. From ﬁnis criterion he
derives ﬁne pollution content of a country‘s exports, which is regressed on is resource
endowmens. The inclusion of a dummy variable ﬁnat measures environmental stringency of ﬁne
courntny does not yield any statistically signiﬁcant impact of environmental regulation on trade

patterns.

Van Beers and van den Bergh (1996) develop ﬁne approach used by Tobey furtlner and
derive a rrnore differentiated result A broad indicator of environmental policy in ﬁne exporting
courntry is signiﬁcant, but has a positive sign. This positive sign means, environmental policy
irncreases ﬁne country’s export However, a narrower indicator of environmental policy

developed by ﬁne authors shows a signiﬁcant but negative sign on aggregate trade ﬂows. Most

27

nhztrnrc fo

Sim
Wigle 199
of trade. I
of: tax ﬁn:
US. He re
Low remain

linens.

importantly, they ﬁnd a signiﬁcant negative relationship for highly pollution intensive sectors

that are footloose.

Simulation models (Walter 1973, D'Arge 1974; OECD 1978; Pearson 1987; Perroni and
Wigle 1995) predict small but discernible eﬁ‘ects of pollution control measures on the balance
of trade. Tackling the problem in a simulation model, Low (1992) analyzes the consequences
of a tax that equates pollution abatement and control expenditures of Mexico with those of the
U.S. He reports that his simulations show only negligible effects on Mexican exports. Since
Low remains vague about the structural details of the simulation itself, it is diﬁicult to judge its
merits.

Location-of-industry studies also provide some insights. The literature is related to
studies measuring the locational impact of taxes. Newman and Sullivan (1988) provide a
literature review on this type of study. The existing consensus is that differences in taxes are of
importance in the intraregional location of ﬁrms, while its inﬂuence on location decisions
between regions is insigniﬁcant. Newman and Sullivan, however, consider the latter point to be
far from settled There are formidable econometric problems involved in estimating the tax
impacts. Mainly, these problems involve the fact that the celeris paribus condition does not
hold Businesses in general do not mind high taxes, if the local government uses the revenue to
provide for services such as a good infrastructure and a good local education level. Taxes that

are used for redistributional purposes will be regarded unfavorably.

In general, the ceten's paribus variables will be decisive in determining the location of a
ﬁrm, and this conclusion makes it diﬂicult to isolate the independent inﬂuence of taxes. This
diﬁculty is even more pronounced in the case of environmental regulations, which are usually

portrayed of having a small role compared to other factors (cp. Motta and Thisse 1993).

28

0n the receiving end, Birdsall and Wheeler (1992) state an increase in international
investment in pollution-intensive industries in Latin America because of stricter OECD rules.
Molina (1993) suggests a clear relationship between abatement costs and the growth of
Mexico's maquiladora industry. Instead of following other studies in regressing abatement
costs on the distribution of industries, he regresses abatement on the growth of diﬂ'erent
industry sectors in the Rio Grande area Molina ﬁnds that those sectors with the highest share
of abatement costs were the fastest to expand their activities in the Mexican maquila industry.
Indirectly, this may imply a certain degree of industrial ﬂight ﬁom the US or elsewhere,

although a correlation need not imply causality.

Xing and Kolstad (1997) also arrived at the conclusion that more lax environmental
regulations in a host country were signiﬁcantly correlated with US chemical industry
investments. For other industry this link could not be shown. However, they ﬁnd hints that
relaxed environmental regulations in the host country are correlated with higher overall

investments by US ﬁrms.

Bouman (1996) ﬁnds for Germany that compliance costs are slightly related to capital

outﬂows. However, these results are highly dependent on model speciﬁcations.

McConnell and Schwab (1990) indicate that diﬁ‘erences in environmental regulations
among counties in the United States do not appear to inﬂuence investment decisions
signiﬁcantly. The empirical evidence for the impact of pollution restrictions on location

corresponds to that of short-run tax incentives, a result that is not surprising in light of the

29

similar nature of environmental regulations and taxes as business incentives'. On an
international level, locational decisions are mostly driven by agglomeration economies, such as
inﬁ'astructure and other existing industries, with some level of importance attached to classical

parameters like market size and labor costs (Wheeler and Mody 1992).

No study seems to state conclusively whether there is a positive, negative, or zero
correlation between capital ﬂows and pollution abatement costs. This conclusion is due to the
low number of observations used in most studies, as well as a variety of estimation problems.
For the high-polluting sectors such as mineral processing, chemicals, pulp and paper, mid
petroleum, pollution control equipment can cost between roughly 10 and 24 %of new plant
equipment in OECD countries (Lucas er alii 1992). For these industries, a relocation response
to lower environmental standards would not be surprising. This, however, would only concern
new factories, not existing ones. Pollution abatement operating costs as a percentage of output
value lies in the United States at 0.54 % on average, with the highest value at 3.17 °/o (Low
1992, 113-4). The low level of these numbers do not point to a mass exodus of United States

industry due to diﬂ‘erences in environmental regulation.

It has been pointed out, however, by Chapman (1991) that regulation costs are highly
underestimated, because the ﬁgures do not include items such as workplace health and safety
protection costs. A possible counterargument is that these costs could equally be seen as

hidden labor costs. This seemingly academic statement points to the problem that if dirty

 

'Thereisanemergingconsensusintheliteraturethattaxesareamoreimportantissuein
intrametropolitan location decisions than in intermetropolitan decisions (McConnell and Schwab
1990).

30

industries are also labor intensive ones, it will be diﬁcult to separate that reason for the
relocation of an industry. A statistical regression thus encounters the problem of
multicollinearity, in addition to the unavoidable distortions of pressing the complex

decisionmaking process for a ﬁrm’s location into a simple mathematical model.

The argument by Chapman, however, ﬁnds support in the study of Gray and Shadbegian
(1993). Using a plant-level data set, they ﬁnd that, statistically, a one-dollar increase in
regulation costs is associated with a 3-to—4-dollar drop in productivity. Using these results, the
authors ﬁnd that environmental compliance costs have reduced the average total factor
productivity in the paper, oil, and steel industries by 5.3, 3.1, and 7.6 %, respectively. These
results appear to be at a higher level of plausibility than those quoted by Low, although they

surely will not be the last words written on the subject.

Staﬂ‘ord (1985) uses an approach that circumvents the problem of potentially unreliable
pollution cost ﬁgures by using personal interviews and questionnaires to identify the factors
that were most important for large U.S. corporations in locating their branch plants. The result
of the study is that diﬂ‘erences in environmental regulations have some inﬂuence on location
decisions, but rank behind other factors, like labor characteristics, markets, transportation,
materials, infrastructure, quality of life, business climate, community characteristics, and taxes.
Even for plant types that are qualiﬁed as "less clean”, the inﬂuence of environmental
regulations is outweighed by markets, labor, and materials. The inﬂuence of regulations seems
to be of slightly more importance for the choice of the exact plant site on a local level than on a
regional level. The inﬂuence of environmental regulations therefore mirrors the inﬂuence of
taxes on industrial regulation. Staﬂ‘ord's results converge with those of other econometric

studies.

31

However, Staﬁ‘ord's study may underestimate the relocation problem, because the ﬁrms
in the sample are all members of the Fortune 500. Large enterprises that run a large number of
factories will mually avoid the bad publicity of nrnning a hazardous plant The operation of a
plant like Union Carbide's Bhopal generally does not make good business sense for the mother
company. Large companies therefore have a tendency to use uniform standards at all
production facilities (Pearson 1987; Warhurst and Isnor 1996, Levy 1995, Leonard 1988).
Multinational enterprises generally seek consistent environmental enforcement rather than lax

enforcement

Jaﬂ‘e er a1. (1995) summarize intra-US locations studies. The studies summarized ﬁnd
either no signiﬁcant or very small effects in particular circumstances. There are even hints that

low environmental standards can even discourage investment.

A statistical problem that might lead to an understatement of the problem is that it
compares only locations within the United States with only a limited variation in environmental
relations. There is some reason to believe that the ﬁrms for which lax pollution standards are an
overwhelming factor are not part of the sample because they invest abroad In the framework
of the industrial ﬂight hypothesis, this approach means that ﬁrms are only surveyed if they did
not leave the country. Leonard's (1988) study must thus be seen as complementary to that of
Staﬂ‘ord, as he analyzes case studies of U.S. ﬁrms that left the country. He also ﬁnds that,
while lax environmental regulations may help to gain a locational advantage, they are usually

overwhelmed by other factors.

Staﬁ‘ord provides two important insights by disaggregating the general locational
inﬂuence of environmental regulation of the ﬁrm's decision into its component. The ﬁrst is that

it is not the allowable level of pollution emissions that deters companies, but the level of

32

uncertainty and delay that is involved with the bureaucratic process of obtaining an operating
license. The number of required permits are more important than the capital costs of pollution
control. This is related to the second irnsight that ﬁrms see environmental regulations as part of
a regulatory package. In other words, a helpful bureaucracy that is perceived as pro business
will not loose business through strict regulations, as long as it has a clear and quick permit-
granting process.

This harmonizes also with the ﬁnding of Duerksen and Leonard (1930) that most of the
relocation taking place due to regulatory diﬁ‘erences ﬂows into other industrialized countries,
and not into less-developed countries. Obviously, low emissions standards alorne do not suﬁce
in gainirng capital inﬂows.

It has been correctly pointed out by Pearson (1987) that it is not a priori clear to believe
that the increased output of an environmentally abundant country will be captured by
multinationals as opposed to domestic ﬁrms. An analysis of the locational patterns of
international ﬁrms may therefore be the wrong place to look for a solution of the industrial
relocation issue. The question of regulation-induced industrial relocation is therefore not yet
settled, although there is an indication that it plays some role for especially polluting sectors, as

Molina (1993) and Birdsall and Wheeler (1992) suggest.

In summary, it appears that, for the economy as a whole, the fears of industrial ﬂight are
largely exaggerated Comparative advantage in environmental regulatiorns appeals to play a
role for the location of only a limited set of industries, and is a minor factor for industry in
gerneral. Heckscher-Ohlin type trade models (at least in their naive form) are fournd warnting in
predicting the eﬂ‘ects of regulations on trade patterns. While of concern for trade tlneorists,

these empirical ﬁndings are reassuring for ecologically minded govemmernts. Due to the mirnor

33

inﬂuence of regulations on industrial location, it appears that trade and environmental goals can

be pursued largely independently.

1.4.4. Pollution Haven Hypothesis
Related to the industrial ﬂight hypotlnesis is the pollution haven hypotlnesis. It states tlnat

irn an open economy governments are willing to lower ernvrionmental standards to give a trade

advantage to domestic sectors.

In merging the ﬁndings of the environmental literature with trade tlneories, several papers
are careful to point out that, in an open economy, an optimal environmental tax is not simply a
matter of applying the Pigou theorem (i.e. imposing a marginal emissions charge equal to the
marginal extemality).9 the seminal paper was written by Markusen (1975), which addresses
the problem in a two-country, two-commodity general equilibrium framework with no
substitution possibilities for the production of the polluting good. A Pigouvian tax should be
equal to domestic external costs, while the optimal tariﬂ‘ combines the standard optimal tariﬂ‘
with an additional charge that reﬂects the extemality that results from the pollution imported
from foreigrn production. Clearly in this case, the transboundary pollution increases the optimal
tariﬂ' beyond the level that would prevail in its absence. The Pigouvian tax, however, remains

too low to produce a global social optimum.

Krutilla (1991) shows that there are at least two other factors that are to be included in

the determination of an optimal pollution tax, even without transboundary ﬂows of pollutants.

 

’Opﬁmalrefersheretotheopﬁnnalpohcyoftheirnposingcountryonly,notwlnatwouldbe
optimalunderaglobalwelfarefunction.

34

Theﬁrstistheeﬂ‘ectofanenvironmentaltaxonthetermsoftradeofacountrythatwas
already mentioned in the discussion of Baumol and Oates; the otlner is the eﬁ’ect on tariﬂ'
revenue. Both have opposing signs and depend on the position of a country as net exporter or
importer of the taxed good, as well as the question of whether the associated extemality occurs

during its production or consumption.

Taxing a production extemality in a country produces beneﬁts by reducirng tlne
extemality. Iftlne country is a net exporter of the polluting good, it also beneﬁts ﬁ'om improving
the terms of trade, thus the tax generates a monopolistic surplus gain on the reduced export
volume. An optimal tax tlnus needs to include the terms-of-trade eﬁ‘ects, and is higlner than the
Pigouvian tax for the net exporter. This result is a standard conclusion of trade and
environment modeling (see for example Markusen 1975; Rauscher,l993). The terms of trade
eﬁ‘ect is large, if the country's supply elasticity is. high and the export elasticity is low. If the
country is a net importer of the polluting good, the terms of trade eﬂ‘ect works to lower the
optimal tax below the Pigouvian level, as the country now suffers a terms-of-trade loss tlnrough

increased and more expensive imports.

There is a second eﬁ‘ect, however, which works in the opposite direction of the terms-of-
trade eﬂ‘ect In the case of a net exporter, a pollution tax reduces the volume of trade and with
it the country's tariﬂ~ revenues shrink. This eﬂ‘ect increases with the tariff rate and does not
exist, if the level of tariffs is zero. Krutilla thus hints at the importance of ﬁscal variables for the
analysis of trade and environment interactions. It should be pointed out here tlnat the analysis
remains partial and tlnus incomplete, in that it ignores how the tariff revenues are spent. (As

tariﬁ' revenues will shrink and pollution taxes increase, the overall direction of tlne public

35

budget is undetermined.) The argument for a general equilibrium analysis will be explored

later.

The analysis of Krutilla has been carried further by Kennedy (1993). Kenrnedy diﬁ'ers
from Krutilla in three crucial points. First and most importantly, Kennedy models strategic
interactions between two large trading countries in a game-ﬁneoretic framework. This approach
meanns that the analysis moves away from the somewhat urnrealistic assumption that the oﬁner
country does not react to the policy measures in the home country. Whether the assumption of a
given-and known—reaction curve by Kennedy is more realistic is another matter. However, it

points out the great importance of strategic interactions between countries.

The analysis deviates from Krutilla further in that it assumes imperfect competitiorn,
while Krutilla assumes a perfect-competition economy with the import or export status of a
country exogenously given. Thirdly, the inclusiorn of transbourndary pollution accentuates the
interaction between the two countries in a strategic sense, since the stakes for each country are
higher. The analysis is a modiﬁcation of the optimal tariﬁ‘ literature. Tlnree eﬂ'ects drive ﬁne
decision concerning the optimal tax on pollution away ﬁom the Pigouvian solution. First, there
is the rent-capture effect. This eﬂ‘ect denotes the change in the surplus generated ﬁom
foreigners, and includes changes in proﬁts from exports as well as changes in tax revenues

from exports. In Kennedy's model, this eﬁ‘ect is negative, since increased taxes reduce ﬁne level
of exports.

Most interestingly, while ﬁnis effect drives ﬁne tax level up in Krutilla's analysis, Kennedy
ﬁnds it to reduce ﬁne opﬁmal tax level. He attributes it to ﬁne fact ﬁnat, in Krutilla's model, trade

ﬂows are determined exogenously by traditional forces such as comparative advantage. Facirng

competitive buyers, ﬁne net exporting country is free to use a tax as a means to extract a

36

mornopoly rent from ﬁne buyers. In Kennedy's framework, ﬁne direction of trade is determined
exclusively by relative tax rates. The country (that is oﬁnerwise equal) which has ﬁne lower tax
rate will ﬁnerefore be an exporter, while ﬁne oﬁner will be an importer. The implications of ﬁnese
nnodelirng differences are quite fundamental, since Krutilla suggests ﬁnat free trade will not
provide an incentive to lower pollution standards, while Kennedy provides ammunition for ﬁne

side ﬁnat argues against free trade on ﬁne basis that it would erode environmental standards.

Certainly, ﬁnere are examples of industries ﬁnat support ﬁne arguments on eiﬁner side. In
ﬁne cases of an asymmetrical trade integration between poor and rich countries, Kennedy's
assumption that boﬁn countries have identical endowments is not tenable. Tlnere may ﬁnus be
room for ﬁne extraction of monopoly proﬁts from one country, at least in certain industries. On
ﬁre oﬁner hand, wiﬁn some likelihood, ﬁnere are industries where ﬁne competitive situation in ﬁne
diﬂ‘erent countries is quite similar. Differences in environmental regulations may therefore tilt
ﬁne balance in favor of one or ﬁne oﬁner country, ﬁnus lending plausibility to Kennedy's analysis.
Clearly, some analysis or educated guesswork of ﬁne compeﬁtive structure of key industrial
sectors is necessary to detennine ﬁne net beneﬁts of environmental policies in a free-trade
arrangement. In practice, ﬁne respective political strength of ﬁne potential winners and losers
will be decisive in determining ﬁne direction in which ﬁne rent capture eﬁ‘ect will point ﬁne

environmental regulations.

Two more shifters of environmental policy are identiﬁed by Kennedy. The
trarnsboundary eﬂ'ect keeps ﬁne optimal tax rate below Pigouvian levels, because a country’s
policy does not acconmt for ﬁne pollution ﬁnat causes damage in oﬁner countries. This effect

occurs wiﬁn or wiﬁnout trade. The last effect listed is ﬁne familiar pollute-ﬁny-neighbor-via-trade

37

eﬁ‘ect, which works to make ﬁne pollution policy more stringent ﬁnan warranted by Pigouvian

policy (Siebert 1935).

Using a dual general equilibrium approach to produce results comparable to that of
Kennedy, Ulph (1990) ﬁnds ﬁnat quantity irnstrument are Pareto superior over ﬁne tax
instrument The conclusion by Ulph is biased, however, through ﬁne fact that it is a partial
analysisﬁnatneglectsﬁnatﬁnemoneyeamedwithﬁnetaxinstrumentmaybeputintoauseoﬁner

than paying for an urnproductive state apparatus, and ﬁnus needs to enter welfare considerations.

Furﬁner models include dynamic interactions between countries. These models try to
overcome the assumption in a comparative static analysis that trade ﬂows are detemnined solely
on ﬁne base of factor endowments. Implicit in ﬁne traditional trade theory is ﬁnerefore ﬁne
assumption ﬁnat, once a comparative advantage in endowments disappears, trade ﬂows will
revert If ﬁnis assumption were true, it would be foolish for a government to subsidize ﬁre
location of a certain industry, because ﬁrms would only stay as long as ﬁne subsidy is grannted
In ﬁne economic system of ﬁne Heckscher-Ohlin paradign, history does not matter. Once ﬁne

initial parameters are replicated, exactly ﬁne same structure will be reproduced

Economic gowﬁn is, however, paﬁn dependent Through changes in price levels and ﬁne
structure of competitiorn, trade can lead to ﬁne formation of econonnies of size and technological
innovation. Many government planners ﬁnerefore believe that locational advantages are self-
perpetuating. Eﬂ‘ects, such as leaming-by-doing and agglomeration economies (i.e., ﬁre costs
and beneﬁts of geographical concentration) may change ﬁre economic structure of a courntry
permanenﬁy. Much of ﬁne difference between classical trade theory and recent ﬁneoretical

developments lies in ﬁne acknowledgement of ﬁne importance of ﬁne development paﬁn.

38

Porter (1991; Porter and van der Linde 1995) has turned ﬁne argument arournd arnd
fornnrulated ﬁne hypoﬁnesis ﬁnat countries can use ﬁne early introduction of environmental
policies strategically to give domestic environmental industries a head start compared to
foreign competitors. The idea behind ﬁne Porter hypoﬁnesis is ﬁnat irn countries ﬁnat regulate
early and well (1), companies can move down ﬁne leanring curve wiﬁnout large market losses to
non-regulated competitors. However, by ﬁne time competitors start to regulate ﬁney will have
developed a strong competitive edge. There are many caveats linked to ﬁne hypothesis. Most
rnotably, it fails to provide any ex ante information on what regulations will be beneﬁcial. For a
criticism of ﬁre Porter Hypoﬁnesis, see Palmer et al. (1995). Their critique relies basically on
ﬁne fact that ﬁrms could spot future business opportunities in ﬁne environmental ﬁeld even

wiﬁnout ﬁne government.

There are numerous extensiorns to ﬁne game ﬁneoretic literature ﬁnat analyze ﬁne problem
of organizing ﬁre world's countries to cope wiﬁn trarnsboundary pollution, especially global
warming However, ﬁne problem of global commons exceeds ﬁne scope of ﬁnis paper, whicln

focuses on domestic pollution only.

While dynamic and game-ﬁneoretic effects are of importance, ﬁney are intrinsically
diﬁcult to model, and have yielded limited insights in ﬁne sense of falsiﬁable predictiorns about
what governments actually do. Especially, game-ﬁneoretic models tend to be intellectually
stimulating mind games wiﬁn no attempt at corroborating ﬁneir insights wiﬁn empirical
observations. What ﬁnere is in empirical literature shows little evidence that governments
cornsciously use environmental regulations as irnstruments of trade-related policy goals in ﬁne
form of "ecological dumping", an irnsight which probably is not urnrelated to ﬁne limited eﬁ‘ect

such a policy seems to have on ﬁne location of industries.

39

Rauscher (1993) cauﬁons ﬁnat ecological dumping is not simply identical to having lower
environmental standards ﬁnan oﬁner countries. As has been pointed out, ﬁnere is no reason why
environmental regulations should be equal in all countries, since preferences. and national
endowments vary among regions. The normative statement ﬁnat regulations should be identical
around ﬁne world is to be rejected on ﬁrese grounds. Diﬂ‘erences in environmental regulations
(at least for local pollution) may be even desirable, as it leads to global welfare increases due to
the principles of comparative advantage. Ecological dumping is also not identical wiﬁr pricing
of pollution below marginal social damage. While ﬁnis pricing certainly produces economic
distortions it is not necessarily due to a conscious decision to change trade patterns, but can

have many other motivations.

on a practical level, Rauscher proposes a ﬁnird deﬁrnitiorn, which states ﬁnat ecological
dumping occurs wherever ﬁne (explicit or implicit) price of environmental resources is lower irn
ﬁne tradeables ﬁnan in ﬁne non-tradeables sector. Under ﬁnis deﬁnition, ﬁne level of infonnatiorn
needed to test for ﬁne existence of environmental policies as a means to gain a trade advantage
is considerably less ﬁnan ﬁnat for ﬁne previous definition. It is not necessary to urndertake ﬁne
near-impossible task of analyzing a correct resource price. Instead, one can simply focus on
price and regulatory differences. F urther, Rauscher's ﬁnird deﬁnition seems to be ﬁne most
realistic way policymakers would try to take strategic advantage of low regulation levels in a

trade setting.

To my knowledge, ﬁnere exists no study ﬁnat analyzes meﬁnodically, ﬁne question of
wheﬁrer states systematically follow a policy of ecological dumping in ﬁne sense of Rauscher,
alﬁrough anecdotal evidence exists. The most prominent example of ﬁnis kind is ﬁne exploitation

of tropical forests for export. In many cases, however, ﬁne policy is not part of a deliberate

40

long-term plan, but emerges from short-term necessity. Of special importance here, is ﬁne need
to serve huge amounts of foreign debts that might lead Third World courntries often to
underprice ﬁneir natural resources (T udini 1993). Anoﬁner important area where deliberate
discrimination applies is in ﬁne ﬁeld of energy/C02 taxation. Since energy can constitrrte a
considerable cost component for certain industries, this is a ﬁeld where eﬁ‘ective tax rates can
diﬁ'er substantially. For ﬁne global commons such a tax differentiation may even be beneﬁcial

as it reduces carbon leakage (Scherp and Suardi 1997).

It should be noted here ﬁnat, for ﬁne case of medium-income countries ﬁre supposition of
a pollution-haven strategy may not be ﬁne only relevant of ﬁne two hypotlneses for strategic
environmental policy, as ﬁrey may be squeezed on botln sides. Higher environmental standards
may decrease ﬁne country's attractiveness for capital from rich countries, while its own industry
moves towards courntries wiﬁr even lower regulations. An answer to ﬁne question of wheﬁner
trade liberalization improves or deteriorates ﬁne environment in medium-income countries,
leaves open ﬁre questiorn what takes place in oﬁner countries. A pollution reduction wiﬁnin ﬁne
free-trade area could mean ﬁnat ﬁne polluting sectors move to ﬁnird countries ﬁnat are more
willing to sell off ﬁneir environment On a global level, pollution may ﬁnerefore still rise. There
exists, however, to my krnowledge no ﬁneoretical literature dealing wiﬁn ﬁne trade and

environment complex in a ﬁnree-country ﬁarnework.

1.4.5. Empirical Evidence of the Pollution Haven Hypothesis

In light of ﬁne negligible eﬂ‘ect of environmental regulations on trade ﬂows it not
surprising that ﬁnere is no evidence that countries systematically use environmental policy as a
means of attracting business. Leonard (1988) screens numerous case studies of industrial

relocations of U.S. ﬁrms into four industrializing countries for evidence of conscious ecological

41

dumping. While ﬁne urnderpricing of environmental costs seems evident for ﬁre case of
Romania under Ceausescu, in oﬁner countries ﬁne evidence points largely to ﬁne contrary. After
attempts in ﬁne 19505 to use lax environmental regulations as a means of attracting foreign
investors, Ireland reversed ﬁnis policy, not least because it had only a small eﬁ'ect on investors.
For Mexico and Spain, Leonard ﬁnds ﬁre contrary policy ﬁnat environmental regulations are
mostly higher on foreign comparnies ﬁnan domestic ones. Historically, comparatively low
environmental standards are often more ﬁne result of ignorance ﬁnan of conscious decision
making Leonard provides evidence that ﬁre medium-income countries become increasingly
nnore adept at obtaining environmental concession ﬁom foreign ﬁrms, as ﬁne countries move

down a learning curve.

Murell and Rytennan (1991) analyze wheﬁner a comparative advantage in pollution-
intensive products could serve as a justiﬁcation for lax environmental standards. In particular,
ﬁney conclude ﬁnat ﬁre relatively lax environmental policy in Eastern Europe carnrnot be

explained by a tendency to export commodities intensive in pollution.

1.5. Poverty Attraction Hypothesis

The empirical evidence compiled above indicates that ﬁne two components of ﬁne
traditional pessimism hypoﬁresis have only a very limited backing in ﬁne empirical literature.
However, ﬁnis does not eliminate ﬁne possibility ﬁnat trade among countries wiﬁn urnequal level

of development results in increased pollution levels.

1.5.1. Conditions for the Hypothesis

While regulation-setting itself may not be important for industrial locationn, ﬁnere is a

strong possibility ﬁnat regulations are correlated to other important location factors. Therefore,

42

trade could lead to higher overall emissions, if countries with low environmental standards
specialize irn pollution intensive sectors, even if ﬁne relaxed regulations ﬁnemselves play a minor
role. Since low environmental standards can be found in developing countries and strict

starndards in industrialized countries, the nature of Norﬁn-Souﬁn trade becomes crucial.

This possibility leads directly to the formulation, of what could be labeled ﬁne “poverty
attraction hypoﬁnesis”: pollution-intensive sectors tend to be attracted to poor countries. Free
trade leads to environmental degradation in poor countries, because ﬁne relocatiorn is met wiﬁn
lax environmental regulation. This concern has been formulated early by Walter and Ugelow

(1979; see also Copeland and Taylor 1994 1995).

Specialization need not be driven by environmental standards but result from
exacerbating factors such labor and capital endowments. The ﬁneoretical trade literature is of
litﬁe help in determining ﬁne expected specialization. Depending on ﬁne correlatiorn of pollution-
intensity with oﬁner factors such as labor intensity and capital intensity, Norﬁn-Souﬁn
specialization could occur in eiﬁner way. Development ﬁneory oﬁ‘ers some assistance. It is well
established ﬁnat as countries move ﬁnrough stages of development, their econonnies become less
resource and labor based, and become increasingly capital intensive. However, again it remains
an empirical question wheﬁner the donninant sectors of early development stages are
intrinsically dirty or are polluting because of ﬁne coincidentally low pollution standards.

Furﬁnerrnore, it is an empirical question wheﬁner trade makes ﬁne situation worse.

1.5.2. Empirical Findings on Poverty Attraction Hypothesis
Empirical literature exists on boﬁn ﬁne trade aspect and ﬁne development aspect of ﬁne

poverty attraction argument The analysis of trade ﬂows indicates that environmentalist fears of

trade specialization are not completely unfounded. A number of empirical studies conﬁrm ﬁnat

43

developing countries tend to specialize in dirty industries. Low and Yeats (1992) investigate
ﬁne cmnection between ﬁne pollution content of trade and income level. They ﬁnd ﬁnat exports
of dirty products account for a growing share of developirng countries' exports. Oﬁner
econometric studies derive at similar results (Hettige et al. 1992; Birdsall and Wheeler 1992).
Desus and Bussolo (1995) achieve ﬁnis conclusion using a computable general equilibrium

model for Costa Rica

By contrast, Sorsa (1994) shows ﬁnat industrialized and developing countries roughly
maintained ﬁneir comparative advantage in environmentally sensitive goods. Similarly, Schep
arnd Suardi (1997) also ﬁnd ﬁnat EU-T‘lnird World trade specialization was mostly unclnanged

over 20 years.

The assembled evidence is weakened by ﬁne fact that all studies rely on the same
emissions data set compiled by ﬁre World Bank (Hettige et al. 1995) on which also this study
draws. However, ﬁne overall balance of ﬁne empirical trade literature appears to indicate ﬁnat
developing countries have a comparative advantage in pollution-intensive sectors. Potentially,
this conclusion could imply ﬁnat it is not commendable for a Third World country to follow an
open trade policy, because ﬁne removal of trade barriers will lead to a worsening of a poor

country's environmental and, in ﬁne longer run, economic situation.

The empirical literature of ﬁne connection between pollution and development hints that
ﬁne relationship between a country’s wealﬁn and pollution follows an inverted U (Selder arnd

Song 1994, 1995; World Bank 1992; Shaﬁk 1994; Grossman and Krueger 1995; de Bruyn et

44

al. 1995, Lucas at al. 1992; Rock 1996; Xapappadeas and Amri 1998)”. This phenomenon is
known also as environmental Kuzrnets curve. It denotes the observation that ﬁne least developed
courntries have relatively low levels of toxic release, countries undergoing industrialization are

highly polluted, and post-industrial countries are relatively clean.

Grossman and Krueger estimate ﬁnat ﬁne highest level of pollution occurs for countries
wiﬁn a per capita income near USS 5,000 (at purchasing power parity) which is about ﬁre
income level of Mexico. Beyond this ﬁnreshold, increased GDP is correlated wiﬁn a decrease in
pollution, at least in ﬁne cross-country data set. Radetzki (1992) notes additionally ﬁnat ﬁne
curve is moving down over time. A country today is cleaner than a country in a comparable
ecornorrnic stage of development ﬁnirty years ago. The shape and time trend of ﬁne curve is also
fonnrnd by Goldemberg (1992) for the consumption of energy per unit of GDP which is
ultimately ﬁne source of most pollutants. However, ﬁnese ﬁndings are not uncontested: Apart
ﬁom diﬁculties of comparing pollution levels across countries, it is neiﬁner clear where ﬁne
trnrning point rniglnt be located, nor does ﬁne absolute level of pollution decline in all cases (Esty

arnd Gentry 1998).

The observation of ﬁne inverted U curve does not allow to draw any direct inference on
ﬁne interaction between trade and environment, because it does not measure ﬁne composition of
the economy as a dependent variable. Rather, it looks directly at emissions which are obviously
also inﬂuenced by. regulation levels. Furthermore, ﬁnere is no hint at whether trade has any

impact on ﬁnis pattern. Therefore, ﬁne ﬁndings provide little direct evidence for or against ﬁne

 

'° Lopez (1994) derives the result from a theoretical model.

45

poverty attraction hypoﬁnesis. However, it points to ﬁne critical nature of assumirng constant

factor endowments and regulations.

1.6. Research Gaps and Purpose of this Paper

The existing body of literature leaves ﬁnree important lacunae that will be parﬁy ﬁlled
by ﬁnis dissertation. First, ﬁnis paper will add to ﬁne empirical literature on trade and
environment interactions. Second, it is one of only very few studies ﬁnat explicitly include ﬁne
environmental extemality in ﬁne analysis. Third, it treats integates ﬁne political process of

regulations in ﬁne analysis.

1.6.1. Contribution to Empirical Research
The literature on trade and environment has made substantial advances. Wiﬁn ﬁne notable

exception of ﬁne Porter hypoﬁnesis, most ﬁneoretical papers argue ﬁnat tighter regulations lead to
a comparative disadvantage of ﬁne regulated sectors. The important question is raﬁner how
important actually is ﬁne inﬂuence of regulatiorns. The emerging consensus of ﬁne empirical
literature provides good and bad news. On ﬁne one hand, industrial ﬂight of relatively little
importance. On ﬁne oﬁner hand, ﬁnere are some hints ﬁnat poor countries have a relative
advarntage in polluting industries. This paper will take a fresh look at ﬁne two hypoﬁnesis in ﬁne
context of NAFTA. In contrast to econometrical approaches ﬁnat focus naturally on statistical
signiﬁcance, ﬁne computable general equilibrium (CGE) approach allows a calculation of

absolute levels of importance.

1.6.2. Inclusion of Environmental Extemality

The empirical literature focuses on ﬁne impact of pollution abatement on trade

specialization. Remarkably, it neglects ﬁne extemality aspect of pollution. Potentially, ﬁne

46

integation of extemalities into ﬁne analysis can signiﬁcanﬁy effect results. Resource depletion
deprives a country of ﬁne opportunity to develop oﬁner industries such as tourism, which are
potentially big foreign-exchange earners. Pollution may harm people and materials or deter

industries from locating in a country.

There exists only a small body of descriptive literature ﬁnat emphasizes ﬁne negative
aspects of trade liberalization itself. This orrnission stems ﬁom ﬁne ﬁneory of ﬁne second best that
ﬁne removal of trade distortions can lead to a worsening of a courntry's situation--
environmentally or economically--if oﬁner distortions still exist. In an autarkic state it may not
be consequential ﬁnat a natural resource like tropical wood is underpriced. An opening of ﬁne
borders for exports worsens ﬁne effect of ﬁne distortion and leads to environmental
deterioration. " While the argument itself is straightforward, its analytical and empirical
examination is made difﬁcult by ﬁne complexity of ﬁne technical and economic relationships and
ﬁne oﬁen considerable time ﬁnat elapses between ﬁne emission and ﬁne time ﬁnat ﬁne full damage
occurs. Even if ﬁne country gains an advantage in ﬁne short-term, a policy-induced comparative

advantage in resource-intensive sectors disappears as ﬁne resource depletes. An analytical

 

" There are many examples of this sort. See for example Arden-Clarke (1992a). Sorrne ecological
econonnists take the thought even ﬁlrther and argue that trade generally should be minimized
(Morris 1990; Daly 1993; Daly and Cobb 1989). The envirorunental argument these authors make-
-there are other etlnical considerations not relevant for this paper—is that trade always entails
transportation and consequently energy consumption, with all its unwanted side eﬂ‘ects of resource
depletion, pollution, etc. More trade therefore leads to environmental deterioration. Cross-hauling
of near identical goods across borders can be readily accepted as an example of this point. Brande
and Krugrnan (1983) formulate a model where the waste of resources involved in the reciprocal
shipping of identical goods may outweigh the beneﬁt of increased competition. It is, however,
questionable, whether ﬁnis should be taken as an argument against trade itself. The real problem
lies obviously in ﬁne underpricing of ﬁne environmental resources. If ﬁne "correct" price for energy
issohigbtlnattradewouldfallasaconsequenceofhiglnertransportationcosts,thereisstilllittle
economic argument for the imposition of trade barriers after ﬁre price change.

47

integration of exterrnality may reveal ﬁnat lax environmental regulations lead to a deterioration
of a. country's trade position, as a country’s non-polluting export sector declines urnder ﬁne

burden of ﬁne oﬁner sector‘s pollution.

The static CGE model of ﬁris paper addresses ﬁne problem by integating ﬁne impact of
pollution on healﬁn into ﬁne analysis. This integration allows an analysis of ﬁne welfare impact of
policy changes when economic gowﬁn and pollution move in opposite direction Furﬁnermore,

it enables to assess ﬁne importance of ﬁne extemality on ﬁne industrial structure.

1.6.3. Endogenous Treatment of Pollution Factors

Boﬁn ﬁneoretical and empirical studies on trade and environment assume factor
endowments and institutions to be constant. In combination wiﬁn ﬁne poverty attraction
hypoﬁnesis, ﬁnese assumptions result in an easy detenninacy of ﬁne direction of trade-induced
change: Trade is bad for environment because it moves dirty industries to places where
regulatory enforcement is weak (even ﬁnough ﬁne enforcement itself may not be ﬁne driver).
However, it is well established that regulation stringency increases wiﬁn ecornonnic
development. The cererl‘s paribus assumption for regulatory stringency is ﬁnerefore not

legitimate, insofar as trade promotes development.

In many cases, ﬁne pollution result of ﬁne poverty attraction hypoﬁnesis reverts, if
regulation-setting is treated analytically as an endogenous process. As a complement, this
paper ﬁnerefore formulates a “institutional optinnism hypoﬁnesis”: ﬁne relocation of industries
cannot be separated ﬁom ﬁre creation of wealﬁn, which again is a key determinant of a
country’s regulatory stringency. Since free trade is ﬁnerefore closely associated wiﬁn ﬁne
application of pollution standards, it will generally lead to environmental improvements, even if

a courntry is attractive for pollution-intensive sectors. The institutional optimism hypoﬁnesis will

48

be developed formally in Chapter 2. This hypoﬁnesis will also be empirically analyzed in ﬁne

CGE model.

49

CHAPTER2

THE INSTITUTIONAL OPTIMISM HYPOTHESIS

The main body of empirical and ﬁneoretical literature takes ﬁne environmental regulation
level as externally given The present chapter will show ﬁne importance of ﬁnis assumption and
argue that it systematically leads to a rrnisjudgment of the environmental consequences of trade
liberalization. A ﬁrst section ﬁrst develop ﬁne economic and political mecharnisms justifying an
endogenous treatment of regulation levels in ﬁne analysis. Section two develops ﬁne ideas in a
ﬁneoretical Heckscher-Ohlin type model ﬁnat traces ﬁne consequences of such an endogenous
treatment. A ﬁnird section interprets ﬁne results and formulates ﬁne irnstitutional optimism
hypoﬁnesis. A fourth section will describe a disaggregation procedure for an empirical

examination of ﬁne hypoﬁnesis.

2.1. Economic Development as Explanation of Environmental Stringency

2.1.1. Development and Production Patterns

Trade contributes to ﬁne economic development of a country. The empirical evidence of
an environmental Kuznnets curve points to ﬁne fact ﬁnat economic development and pollution do
not form a linear relationship. The decomposition of environmental effects serves to disentarngle
wlnat might explain ﬁne relationship. The scale effect in isolation would have suggested ﬁnat
economic development entails a straightforward increase in emission levels. Evidenﬁy,
ﬁnerefore during ﬁne different stages of economic growﬁn, ﬁnere must be a distinct pattern ﬁnat
inﬂuences ﬁne two oﬁner important effects identiﬁed by Grossman and Krueger (1992), ﬁne
composition eﬂ‘ect and ﬁne technology effect. These will be addressed in turn. The stylized facts

of ﬁne econonnic development process are presented graphically in Figure 2-1.

50

machete:

Poor and medium income countries tend to have a high share of dirty sectors. (Figure 2-
1, parnel A). The argument presented here focuses on four factors ﬁnat explain why poor
countries might be prone to having dirty industries. First, poor countries tend to have a lnigh
demand for basic production which tends to be dirty, boﬁn for ﬁnal consumption goods, as well
as for investment. Consumption in wealﬁnier countries tends to be more service oriented
Secornd, labor endowment in poor country tends to consist of a pool of unskilled labor. This
endowment gives ﬁne country a comparative advantage in heavy industrial or agricultural
production. Third, poor countries are capital poor. It is not clear whether ﬁnis poverty should
move ﬁne sectoral composition of the industry. towards clean or dirty sector. However, it
contributes to pollution-intensive production technology, as will be elaborated below. Fourﬁn, irn

poor countries resource extraction tends to have a relatively high share in natiornal production

All ﬁnese factor give a comparative advantage to pollution-intensive industries irn poor
countries. If such countries open to trade, ﬁnis comparative advantage nnight be reinforced In
essence, ﬁnis conclusion is a restatement of ﬁne poverty attraction hypoﬁnesis. As a country gets
richer, ﬁne relative advantage nnight change, and ﬁne relative pollution intensity would decrease.
In itself, ﬁne composition eﬁ‘ect might ﬁnerefore explain part of ﬁne relative greening of richer
connrntries. However, it could not explain an absolute drop in pollution levels for rich countries,
because structural change is normally not accompanied by an absolute decline but a relative

decline of certain sectors (Figure 2-1, panel B).

51

Figure 2-1. Decomposition of the environmental Kuzrnets curve

A. Structural
change

 

 

 

 

Polution B. Unadjusted
pollution
curve

 

GDP

 

Unﬁt uni-ions

C. Institutional
and technical
change

 

GDP

 

Polution

D. Environmental
Kuznets curve

 

GDP

 

52

Icahnalansﬂest

Production technology in poor countries is also largely a ﬁmctiorn of resource
endowment, notably ﬁne lack of capital. Physical capital is often of an old vintage. Old vintage
capital stock is likely to be more polluting ﬁnan newer equipment Retroﬁtting is generally
expensive. Increased wealﬁn and, hence, capital stock tends to reduce emissions ﬁrst, because
environmental improvements are linked to ﬁne replacement of ﬁne capital stock. Second,
because low levels of capital endowment make environmental investments expensive in
foregone production. F irnally, new and environmentally friendly technologies are often capital
irntensive. This intensity is due especially to ﬁne fact that production processes are mosﬁy

developed. by rich countries for ﬁre need of rich countries. Wiﬁn increased capitalization of
productiorn, ﬁne likelilnood increases ﬁnat ﬁne technology has been developed by ﬁne ﬁrst world,
arnd ﬁnerefore tends to be environmentally cleaner. ﬁnan ﬁne existing technology of ﬁne
developing country. Irncreased capitalization of production may ﬁnerefore lead direcﬁy to lower

pollution per nnrnit of production, alﬁnough ﬁnere exist counter-examples.

Greener production technology is certainly ﬁne crucial reason why wealﬁnier countries can
be cleaner countries. However, it leaves ﬁne question why ﬁney actually are cleaner. The
inverted U-relationship of pollution appears to indicate an increasing importance of ﬁne
teclnnology eﬂ’ect from a certain income level onwards. (Figure 2-1, last two panels) This result
canbeexplainedonlybyalookatﬁne institutional aspectofregulation settingﬁnatwillbe
discussed more extensively.

2.1.2. Development and Institutions

Pollution control requires ﬁne existence of functioning regulatory institutiorns. The

endsternce of ﬁnese irnstitutions is intimately tied to a country’s wealﬁn, because ﬁne demand for

53

environmental quality is higlnly income elastic. (Esty 1994). Clean environment is a rnorrnal
good Its eﬁ‘ective demand rises wiﬁn ﬁne level of income. For very poor people, ﬁne basic
corncern is to earn a livelihood for ﬁnemselves and ﬁneir families. In such a situatiorn, ﬁne concern
for ﬁne environment tends is not expressed in ﬁne market and ﬁne political processes. As a
courntry gets richer and its population is increasingly able to bear a reduction in ﬁneir disposable
income, ﬁne demand for environmental service increases. If ﬁne political process permits it,

environmental regulations will become more stringent in such a case.

Furﬁnemnore, a clear link can be established between ﬁne income and education level of
ﬁne country and ﬁne level of public accountability of ﬁne administration (Hettige et al 1996,
1997).12 The difference in institutional capacity between poor and rich courntries is often
commented on (Chichilrnisky 1994; O’Connor 1994). Dasgupta et al. (1995) ﬁnd empirically

that ﬁne amount of regulation increases steadily with ﬁne gowﬁn of per capita incomes.

There are several arguments ﬁnat support a behavioral assumption of ﬁnis type. Forenost,
increased wealﬁn (approximated by ﬁne capital intensity) decreases ﬁre willingness to tolerate
pollution The desire for stricter standards may be ﬁne direct result of increased income itself,
since a clean environment is someﬁnirng ofa luxury good , or may be caused indirecﬁy ﬁnrougln
higher general education ﬁnat usually correlates wiﬁn increased wealﬁn. Irnasmuch as
environmental awareness and preferences are closely related to people's educational levels,
higlner income will result in stricter pollution standards. This argument will be elaborated

furﬁner below.

 

‘2 Sclden and Song (1994) provide similar arguments.

54

A transactions-cost eﬁ‘ect complements ﬁne income effect While ﬁne irncome eﬁ‘ect is
denarnd driven and relies on a positive income elasticity of a clean environment, ﬁne
transactions-cost eﬁ‘ect results from changes on ﬁne production side. Naturally, enterprises have
an incentive to cheat on environmental regulations, if ﬁnere is litﬁe likeliness in getting caught
Mornitoring is expensive, however, and almost certainly involves econonnies of scale. If an
ecornomy sets aside a certain percentage of its income for regulatory enforcement, its eﬁciency
is bound to rise as ﬁne value of production irncreases. There are considerable diﬁculties in
statistically verifying ﬁnis transactions-cost hypoﬁnesis. However, ﬁne capability of a state to
raise tax revenues may serve as a proxy for its ability to enforce regulations in general. Clearly,
ﬁnere is a trend for ﬁne share, ifnot ﬁne size, ofa country's irnforrnal economy to fall as its per-
capita income rises. This analogy lends some plausibility to ﬁne argument ﬁnat an increased
capital/labor ratio could result in a higher regulatory standard, even if ﬁne demand for

environmental quality is completely income inelastic.

Chiclnilrnisky (1994) stresses ﬁne importance of property rights in determining ﬁne relative
abundance of a country in natural resources ill a Norﬁn-Souﬁn trade model. Chiclnilnisky's
discussion shows that property rights by ﬁnemselves can detemnine a country's resource
aburndance. As ﬁne strengﬁn of ﬁne property rights is correlated to ﬁne income level of a country,
ﬁne argument made by Chiclnilrrisky can be seen as a variation of ﬁne transactions-cost argmnent
made above.

Despite ﬁneir seemingly similar implicatiorns, ﬁne income and ﬁne transactions-cost
argument diﬁ‘er qualitatively. The former assumes ﬁnat ﬁne regulatory policies are optimal for a
given income level, while ﬁne latter assumes ﬁne existence of distortions. Ifﬁnere exists only an

income effect, ﬁnere is no systematic change in ﬁne extemality costs, because ﬁne marginal costs

55

of pollution rise at ﬁne same time ﬁnat pollution levels decline. For ﬁne transactions-cost case, an
increase in capital endowment reduces ﬁne extemality, which is ﬁne gap between marginal
beneﬁts of production and marginal costs of pollution. (Since ﬁne model presented here does

not include any extemality effects, a distinction is not made in ﬁne model.)

The relationship between income and regulatory stringency conforms also wiﬁn ﬁne more
sophisticated approach used in ﬁne political science literature. One can separate ﬁne relationslnip
between income and environmental regulations into two components: preference formatiorn arnd
ﬁne translation of preferences into actual policies. It is argued here ﬁnat increased wealﬁn and
socioeconomic development is a contributing factor to boﬁn a value system ﬁnat assigns
irncreased importance to ﬁne environment, as well as to more democratic political institutions

that react to ﬁnese preferences.

The conditions for ﬁne development of democratic structures are among ﬁne oldest topies
studied by political scientists. Explanatory models stress ﬁne importance of cultural or of
socioeconomic factors (Arat 1988, p.21). For instance, Inglelnard (1990) describes how
economic development is accompanied by a complex change in ﬁne socioecornonnic and political

system. He identiﬁes several levels at which political changes take place.

First, a certain level of economic and technological development is a necessary conditiorn
for ﬁne increased importance of post-materialistic values, because it liberates people ﬁom
concern about basic economic security. Essentially, ﬁnis requirement means ﬁnat people move
up ﬁne Maslow pyramid of needs as more basic wants are satisﬁed Secondly, ﬁnis movement is
reinforced ﬁnrough rising levels of education of ﬁne general population. These ﬁrst two factors
were already identiﬁed earlier. A ﬁnird factor inﬂuencing values is what Inglelnard calls

distinctive cohort experiences. The history and culture of a country are important factors, since

56

ﬁney shape ﬁne ﬁninking of a cohort in ﬁneir formative years. Socioeconomic clnange usually has
litﬁe eﬂ‘ect on ﬁne values of cohorts whose way of ﬁninking is set, but irnﬂuences mainly ﬁne
yournger generations. Value change ﬁnerefore is usually associated wiﬁn generatiornal change. A
changing set of values would, however, be incornsequential if no political skills exist ﬁnat
trarnslate ﬁne values into politics. These skills are shaped ﬁnrough experiences arnd learning-by-
doing of ﬁne colnort, and are furﬁnered ﬁnrough ﬁne expansion of mass media, which enlarge ﬁne

pool of people who have access to information on ﬁne political process.

The combined changes in values and skills induced by economic progress exert pressure
ﬁnat makes environmental issues more relevant, and strengﬁnerns ﬁne channels of poliﬁcal
cornﬂict ﬁnat will translate ﬁnis pressure into practical politics, or rrnore corncretely into stricter
environmental regulation. Furﬁner factors omitted by Inglehard, such as income distribution are
likely to work in ﬁne same direction. There exists empirical evidence to support ﬁne argument
For example, Dahl (1971) and Arat (1988) establish a positive relationship between ecornomic

variables and political freedom and democracy.

One can establish from ﬁne accumulated economic and political evidence a direct lirnk
between irncreased income and stronger institutions to protect ﬁne environment A simpliﬁed
equation (e. g. as an income elasticity of ennission standards) can ﬁnerefore be direcﬁy used irn
economic modeling. Such an analytical representation will be central to ﬁne ﬁlrﬁner argument of

ﬁnis paper. However, a few interpretative caveats apply to such a simpliﬁed equation.

Most irnportanﬁy, ﬁne described socio-political changes do not occur wiﬁn necessity or

irnstantaneously. It would not difﬁcult to ﬁnd various reasons and cases ﬁnat would contradict

57

such an short-term interpretation of ﬁne relationship. 13 However, an income-elasticity of
regulation exists as a long-term trend wiﬁn an interpretation ﬁnat is similar to ﬁnat of a long-term
equilibrium of an economy: a useful simpliﬁcation of ﬁne real world In a comparative static
equilibrium analysis it can be simply understood as marking ﬁne pressure on ﬁne economy ﬁnat

is irnduced by a certain set of policy changes.

Furﬁnennore, a comparative static analysis leaves out ﬁne irnportarnt questiorns of ﬁne
trarnsitiorn process to ﬁne new equilibrium. Conceivably, an environmental resource could be
irretrievably lost in ﬁne transition period The movement to a diﬁ'erent equilibrium nniglnt
therefore be unattainable because, in ﬁne interirrr, ﬁne very conditions for ﬁne existence of ﬁne

oﬁner equilibrium are destroyed.

Finally, for purposes of modeling, a smooﬁn function serves as approximation of ﬁne
process towards stricter regulations. By contrast in real life, political and regulatory change
often takes place in a discrete raﬁner than a continuous fashion. However, it is not possible, ex

ante to know exacﬁy where, if at all, ﬁnere might be ﬁnresholds above which certain changes

take place.

2.1.3. Trade and Environmental Regulation

It is clear from ﬁne previous discussion ﬁnat environmental standards cannot simply be
taken as given On ﬁne one hand trade nnight improve environmental performance direcﬁy.

Trade itself, as opposed to autarky, increases ﬁne stock of krnowledge by giving a courntry

 

‘3 One may think of ﬁne example of the old Soviet Union as a state for which nnost socioeconomic
indicators would suggestﬁneexistenceofahighdcgreeofdenocraﬁzationandconcemfortbe
environnnent, but where boﬁn are conspicuously absent.

58

access to foreign innovations and knowledge (Grossman and Helpman 1995). Trade openness
itself might ﬁnerefore be associated wiﬁn a cleaner industrial base. Lucas at al. (1992) derived
ﬁnat open economies show a signiﬁcantly lesser growﬁn in pollution levels than closed
econorrnies. Birdsall and Wheeler's (1992) analysis of ﬁne situation in Latin America, shows ﬁnat
openness for trade leads to a lower level of environmental degradation, since trade involves a
transfer of technology. Wheeler and Martin (1992) present anecdotal evidence ﬁnat, in ﬁne case
of the paper and pulp industry in Latin America, investrnnent by foreign ﬁrms appears to be
followed by ﬁne import of pollution-control technology as well as industrial country pollution
standards. Openness of ﬁne economy is a major factor for ﬁne adoption of pollution-saving
technology, because it removes existing distortions. By contrast, ﬁne auﬁnors' ﬁnd no

independent eﬂ‘ect of a country's development level on ﬁne adoption of clean tedunology.

However, ﬁne evidence on outward orientation and decreasing pollution-intensity has
been questioned by Rock (1996). As a more political component of ﬁne direct eﬂ‘ect of trade on
regulation, one might also add ﬁne political pressure from trading partners, for instance, in ﬁne

context of NAFI' A.

Potentially as important as ﬁne eﬁ‘ect of trade liberalization of ﬁne poorer country's
economic structure may be ﬁne deregulation of its ﬁnancial markets. In ﬁne context of NAFTA,
some studies assume ﬁnat it would reduce ﬁne risk prennium on Mexican capital rates by 1
percentage point (CBC 1992). To ﬁnis one would need to add ﬁne effect of increased eﬁciency
in ﬁnancial services due to U.S. competition and ﬁne inﬂow of U.S. capital. Mexican
investment is likely to increase as a consequence, which by itself may lead to increased or
decreased pollutiorn, depending on ﬁne type of investment ﬁnat is induced In general, however,

a lower discount rate shifts ﬁne trade-off between resource conservation and depletion irn favor

59

of a lower rate of exploitation. The interest rate eﬁ‘ect may thus work as a factor ﬁnat pushes

Mexico irnto becoming a cleaner country.

Anoﬁner line of argument follows directly from ﬁne discussion of ﬁne previous section and
takes ﬁne link between wealﬁn and institutions as a starting point. There is no ﬁneoretical or
empirical trade literature ﬁnat treats environmental regulatiorn directly as a function of wealﬁn
However, Chichilnisky (1994) makes environmental stringency endogenous to ﬁne analysis
through a property-rights determined supply function. She assumes ﬁne property-rights
situation in ﬁne Norﬁn to be well deﬁned, so ﬁnat here ﬁne supply curve of ﬁne natural resource
follows ﬁne social optimum. In ﬁne Souﬁn, ﬁne lack of enforcement leads to a more outward-
lying private supply curve, which does not consider extemalities. In a general-equilibrium
framework, she derives ﬁnat ﬁne supply curve for ﬁne natural resource can be downward-
sloping.

The model assumes ﬁnat ﬁne private suppliers of ﬁne resource have no alternative
employment ﬁnan to bring ﬁneir labor into ﬁne production of ﬁne resource, while ﬁney consurnne a
second good which ﬁney purchase ﬁonn ﬁneir revenues. Under ﬁnese assumptions, their optimal
allocation problem is one between consumption of ﬁne good and leisure time. When ﬁne price of
ﬁne resource falls, two effects occur. The ﬁrst is ﬁne substitution eﬁ‘ect: Work decreases as ﬁne
reward for working declines. The second is ﬁne income effect: As wages fall low enough, nnore
eﬁ‘ort needs to be applied to earn ﬁne subsistence income. In ﬁnis case, resource exploitation

will increase as ﬁne terms of trade turn against ﬁne resource.

Raising ﬁne capital intensity will increase ﬁne factor reward for resource exploitation and
may ﬁnerefore lead to a decreased level of exploitation, if ﬁne economy operates on ﬁne

backward-bending part of ﬁne environmental supply curve. Raising a tax on ﬁne exploitation of

60

ﬁne resource, on ﬁne oﬁner hand, could produce an unintended rise in environmental destruction,
increase ﬁne comparative resource abundance of ﬁne Souﬁn, and lead to exports of resource—
intensive goods. The property rights determined resource abundance is ﬁnerefore similar in

result as ﬁne wealﬁn determined regulation setting.

Dome and Schulze (1996) provide anoﬁner attempt to ﬁne auﬁnor to internalize ﬁne
pollution stringency level into ﬁne trade analysis. In many respects ﬁneir ﬁneoretical model which
is also applied to ﬁne NAFI‘ A situation parallels ﬁne ideas ﬁnat will be developed in this elmpter.
However, ﬁre Bommer-Schulze political paradigm is substantially different ﬁorn ﬁne one that
will be developed further below. Following Stigler’s (1971) and Peltzman’s (1976) ﬁneory of
regulation, in ﬁne Bommer-Schulze model, ﬁne administration sets environmental standards to
maximize a political support function composed of net exporting sectors, net importing sectors,
workers and environmentalists. As trade liberalization changes ﬁne relative well-being of ﬁnese

four groups, environmental policies need to counterbalance ﬁne negative eﬁ‘ects on ﬁne losing
groups.

Bommer and Schulze establish that United States exports are relatively more pollution-
intensive ﬁnan imports. Taking ﬁne United States as a vantagepoint, ﬁney argue that trade
liberalization wiﬁn Mexico puts exporters and labor on ﬁne winning side, while importers arnd
environmental interests suﬁ‘er. They ﬁnen argue ﬁnat ﬁnis constellation automatically puts
pressure on ﬁne administration to increase ﬁne stringency of environmental legislation, which
serves ﬁne interests of ﬁne two losing actors. Environmental interests are helped for obvious
reasons; importers are helped because ﬁney are not pollution intensive and could ﬁnus improve
ﬁneir relative position The auﬁnors claim ﬁnat ﬁne environmental side agreements of NAFTA are

evidence of ﬁnis hypoﬁnesis.

61

However, several core assumptions of ﬁne Bommer-Schulze hypoﬁnesis are inaccurate.
Irrnportanﬁy, while it may be correct ﬁnat ﬁne United States exporting industries are relatively
pollution-intensive compared to importing industries, ﬁnis relationship is unlikely to be true for
actual embodied pollution, because US regulations are more stringent ﬁnan ﬁnose in ﬁne rest of
ﬁne world (see discussion in Chapter 4). The NAFTA-environment discussion in ﬁne US was
dominated by fear ﬁnat polluting industry would migrate to Mexico due to ﬁneir lower
environmental standards (ﬁne industrial ﬂight hypoﬁnesis in our terms). The assumption ﬁnat
trade is perceived by environmentalists as pollution-increasing is certainly correct However,
ﬁne line of argument was not that pollution would increase in ﬁne US but in Mexico. Home
and Schulze ﬁnerefore misjudge ﬁne US debate on Mexico as a pollution haven and ﬁne possible
erosion of US environmental standards as a consequence. As a result, ﬁne NAFTA
environmental side agreements were not directed at manufacturers in ﬁne US as implied by ﬁne

auﬁnors, but at manufacturers in Mexico.

Furﬁlermore, while it may be correct ﬁnat in ﬁne long-nln US workers might beneﬁt from
a trade agreement, ﬁnis fact does not translate politically into ﬁne direction pointed out by
Home and Schulze, because Labor perceived itself as a loser, not a winner of NAFTA
Possible reasons for this may be the resulting insecurity of structural change, the fact ﬁnat
(losing) incumbents are better organized ﬁnan ﬁne diffuse and uncertain winners of trade
liberalization, or simply ﬁne fact that certain segments wiﬁnin labor, like ﬁne unskilled, might

lose while oﬁners, like ﬁne university trained, might gain.

Therefore, ﬁne internalization approach of our paper follows a diﬁ‘erent. route of

intemalizatiorn, using ﬁne income level as ﬁne factor in determining stringency in environmental

regulation.

62

2.2 Trade Model with Endogenous Environmental Regulation

This section develops ﬁne arguments of ﬁne previous section in an analytical model. The

maﬁnematically disinclined reader might move on to section 2.3. wiﬁnout loss in ﬁne argument.

2.2.1. The Standard Model
Following ﬁne standard assumptions of trade modeling, a Heckscher-Ohlin world is

assumed wiﬁn two traded goods X and Y. The home country is small and takes ﬁne price levels
as really extemally given. The price of good Y is used as denominator for all prices. P denotes
ﬁne costs of a unit of X in units of Y, similarly, w and r denote ﬁne wage rate and ﬁne return on
capital. We assume ﬁnat all parameters are wiﬁnin a range ﬁnat prohibits a complete

specialization of ﬁne country.

The imported good Y is produced following a Cobb-Douglas function ﬁnat uses capital
(K) and labor (L) as inputs. For ﬁne production of the export good X an additional

environmental input (E) is needed, according to a ﬁne production function:

2.1 X =E'L‘K‘

S X X

where s,A,x>0, e+l+x=1.1hisequaﬁonmeansﬁnatﬁneproducﬁornfmcﬁonislinearly
inmgenlsinitshnpmwluchisﬁnesmndmdassumpﬁminHecksdne-Ohhnnndes.Irnﬁne
absmceofamgﬁaﬁetﬁnepmducemwoulduseaninﬁmemmmnofﬁneenvirmmemlinputE.In
ordetolimitﬁneuseofﬁneenvironmentalinput,itisnowassumedﬁnatthegovenmentiswillingto

accept pollution only ifit produces a certain level of output Maﬁlematically, ﬁnis msumption is

63

etpressedasﬁneconditionﬁnatﬁnemarginalproductivityofenvironmenthastobeatleast lt“'l'his
ﬁrst-order condition for the producers ochan then be written as:
2.2 p = cE"’L;K;
Solving ﬁnis for E produces
I
a I: .3.. _~_
2.3 X = - L1“ K3"
In

Ifﬁne factor reward is not taxed away, but stays wiﬁn ﬁne producers of good X, we can

substitute equation 2.3 back into ﬁne production function (equation 2.1) and obtain:
a 1%; _£_ _~_
2.. x = H L}:~K,‘*~
In

It can be easily seen ﬁnat ﬁne production flmction of X wiﬁn endogenous E is linearly

honnogernous in K and L. To avoid notational clutter, let us rewrite ﬁne production function as:

I
2.5 X = [i] L;K;'°‘
p

 

 

 

wherea= ’1 landﬂz a = ‘ .crmarksﬁneadjustednewfactorshareoflabor,
1+}: 1+): I-e

whﬂeﬁcmbeintepreedasﬁnereaﬁwineeaseinﬁneremnofﬁnemn-ewimnemlinputsthat
canbeascribedtoﬁneenvimnmentIfeisO.25,ﬁnenﬁneretunnstolaborandcapitalareaugnented

byoneﬁnirdltcanbeseenﬁnatpolluﬁornisasimplelinearﬁmcﬁonofX

 

“ This approach has been used by McGuire 1982.

2.6 E: X

f.
,u

The environmental intensity is related inversely to ﬁne minimum marginal productivity,
but rises wiﬁn ﬁle factor share 8 of ﬁne environmental input. The production of Y is assumed to

produce no environmental extemalities. Its production function is
2.7 . Y = L: Kﬁ'“

The labor intensity onis 6times ﬁnat ofgoodX. A value for ﬁsmallerﬁnan l mearns that
polluting good is also relatively labor intensive, which would approximate ﬁne relative position

of ﬁne poorer country. From ﬁnese assumptions, we can derive ﬁne ﬁrst-order conditions

ﬂ [-0 1““
K
p LJr Ly

and

2.9 r = p(1— 43111;: J = (1- M{%]"

The capital-labor ratio is a function of ﬁne wage-proﬁt ratio.

 

 

 

 

 

K
2.10 33: “ K*=—5‘3——’-
r I-aL, 1-6a Ly
Thiscanbetransformedinto
_ K K
2.11 1("=—‘5 6“-—’=¢—i
L, 1-6a Ly Ly

65

6+6a

where 50 = 1+6a

 

marksﬁnediﬂ‘eenceinﬁnecapital/laborratios.Iinsrelaﬁvelymore

labor intensive than Y, then 6<1,and l/I<1. Substitutiorn ofequatiorn 2.9 into 2.11 yields

equatian 2.12.

 

.V

1 5
7—5. - T -n ‘"
2.12 Ky :(g) ’ l (i) ‘ ¢a(J-1)L
[I

Ifﬁne total stock of labor and capital is limited by the equations
2.13a K = K" +Ky

2Bb L=g+g

ﬁne model is solvable and ﬁne following results are obtained:

41-54)

I
I a(a—i)
2.14a L =—‘/’— -—L+ K‘— ¢‘(""K
y 1_¢ all!

 

 

I
I tin-5) i
2.141) K =-—1——|:_[p£’] ¢a(l-J)K
¢

 

I
I m -(l—a)
2.14c L =—1—[L-[ﬂ;] ¢“""K

 

I .71?) LL
2.14d Kx=1¢¢[[p5’) ¢a(l-J)L_K
Furﬁner

66

 

 

"‘ (14.x: )
I a(l—:) ‘°
2.15a w=§a[pE ]_ ¢ 4")

 

 

r(l-e)
2.15b r = (14%”, )Hto (“’1

 

 

6p”
and
1 6, ﬁg” l-2oa+u’: ‘r’ ;—_ 311;.)
2.16a Y=——— - 13— ¢ “(”5 L+ p 36 H K
I-gb 6):” 6,11”
l-ad -d
5’ a(,_ 3) (I- Xm-a) , p ,_ 3 _—___5(1-.)
2.16b )(=—’—-1 [F J— p <’ ‘1 L— [1" ] ¢ 1-. K
1-¢P 5;: 6;:

These equations reproduce ﬁne standard Heckscher-Ohlin results. Equation 2.161) for
instance reveals ﬁnat an increase in ﬁne capital stock lowers ﬁne output of X, if X is relatively
labor-intensive, i.e. 6 is smaller than 1. This is ﬁne Rybczynski ﬁneorem. Similarly, it can be
veriﬁed that ﬁne Stolper-Samuelson ﬁneorem holds in ﬁne model. If ﬁne relative price of X
increases, ﬁne relative wage rate will rise, if labor is ﬁne factor ﬁnat is used intensively irn ﬁne

production of X.

67

Figure 2-2. Trade liberalization with constant environmental regulations

Include... '

M‘ ¥
Clean good

 

 

Since ﬁne country is assumed to have a comparative advantage in ﬁne production of X,
trade liberalization would result in an increase in its relative price. A higher P results in an
increased production of X for ﬁne export market, while ﬁne production of Y drops and is partially
replaced ﬁnrough imports. In Figure 2-2, production moves from ﬁne autarky production poirnt
A on ﬁne production possibility frontier to point B under open trade. Consumption now takes
place at point B. The improved terms of trade for ﬁle polluting sector result in an increased
production. Because resource use is a simple multiple of ﬁne production of X as deﬁned by

equation 2.5, pollution will increase in parallel.

The model presents ﬁne standard arguments of ﬁne consequences of trade liberalization
For a courntry witln low pollution standards, trade liberalization leads to an increased production
of ﬁne pollution intensive good and, consequently, to an environmental deterioration in ﬁne home

conmtry. Trade liberalization can potentially be welfare reducing, if ﬁne increased consumption

68

in ﬁne country, which moves ﬁom A in Figure 2-2 to B, does not compensate for ﬁne increased
pollution ﬁnat ﬁne population now suffers. A low ennissions standard it serves as a substitute for
a high price level P and exacerbates ﬁne situation. In graphical terms, lax pollution

requirements move ﬁne production possibility frontier inward.

2.2.2. The Modiﬁed Model
Several mechanisms could make it , which denotes ﬁne trade-off between production and

environment ﬁnat ﬁne population is willing to accept, model endogenous. In ﬁnis paper, we

propose a dependence of p on ﬁne capital-labor ratio of X according to ﬁne functional form:

2.17 p=[f’)

This means ﬁne required marginal productivity of T increases exponentially wiﬁn ﬁne

 

capital intensity. This is a useful proxy for what would more precisely be represented as an
income elasticity of regulation. However, setting I) as a function of U would extremely
complicate ﬁne analysis wiﬁnout adding anyﬁning to ﬁne argument developed here. Wiﬁn ﬁnese

preliminaries, ﬁne model can now be solved. Using ﬁne equation

 

 

I
_— [-05
2.18 —K‘= pr” “(l-”WM
L dp’

X

and substituting equation 2.17) yields ﬁle following formula for p:

 

 

q
‘ C(I-Jyrﬁ ”(I‘d)
“(’3‘ J—

69

Ifwe substitute equation 2.19 irnto equations 2.14 and 2.16 of ﬁne previous chapter, ﬁne

results change into

2.20a

 

 

 

 

 

F «(I-6w H‘
2.2% K, = 7—1—[-[p 6‘ J p 4H“ L +K
1 pa” «(I-51M: (’ ""3)
2.20c L1: =—- L-[ J (’ "WK
1- 6
¢ p 5.! 41.15),” 7’1",—
2.20d K, = ¢°"‘WL_K
1- 511 6
and
1 5.! ﬁg "245*‘425MH 8, ﬂ; «HI-re!)
2.21a r =_ _ P ¢——«u-w L, P ¢WK
1-¢ 6
[’4'”! -a-rﬂ
, , —a(l-J)+¢ I-e-erU-r) I m -.-.,g
2.21b X: e I" p “(NH L- .125— W 1-. eK
1 - ¢ 6 6
The behavior of pollution is now

2.22

l-¢-v(l-ﬁ) -a-r(l+;)

 

‘¢"1(I*”d)

 

1+! I “(1")”, l-c-r,+.r(l-a+r,) , “(14)”,
E: a [pa ¢ «(l-5)"! L- P; ¢ 41-3)»; K

1-¢ a

70

Ifnisequalto0,noincome eﬁ‘ectexistsandﬁleoutcomeisidenticaltoﬁneprevious
results from equations 2.14 and 2.15. However, as 17 increases, ﬁne model results change
qualitatively. There exist ﬁnree value ranges for ﬁne pollution elasticity. If r) is low, ﬁne standard
result Occurs: An increase in ﬁne price of ﬁne polluting good increases boﬁn ﬁne output and ﬁne
pollution level. If n is at a medium level, X will be stricﬁy increasing, but ﬁne pollution level
willstarttodropbeyondacertainlevel,asﬁneincreaseinﬁneoutputofﬁnepollutinggoodis
overcompensated ﬁnrough increasingly stricter regulations. At high levels of n, ﬁnally, boﬁn ﬁne
productiorn of X and ﬁne level of pollution begin to fall beyond a certain level. These results are

summarized in Table 2.1.

Figure 2-3: Trade liberalization with endogenous environmental regulation setting

Pelhthggeed

 

 

 

Clea-good

71

Table 2-1: Summary of Model Results

 

 

 

Rangeofq XasfunctionofP EasflmctionofP
< 1 - a Increasing Irncreasing

I] 1 + ﬂ

1 - a 1 - 0. Increasing Inverted U

l + B B

1_-_(_1_ < 7l Inverted U Inverted U
B

 

The model demonstrates how ﬁne existence of an income effect can fundamentally alter
ﬁne environmental eﬁ‘ect of trade liberalization. Trade liberalization can potentially reduce ﬁne
pollution even in ﬁne country wiﬁn a comparative advantage in ﬁne pollution-intensive good
Figure 2-3 depicts ﬁne mechanism graphically: A again denotes ﬁne production and
consumption level in ﬁne state of autarky. It is ﬁne tangency point of ﬁne indifference curve
nmde ﬁne pollution constraint level A, which reﬂects ﬁne price level under autarky (shovwn as
ﬁne dotted line). Wiﬁn constant regulations, consumption would move to point B and
consumption to point E. However, ﬁlese points are not compatible wiﬁn ﬁne eﬂ‘ect ﬁnat ﬁne price
level has on ﬁne stringency of ﬁne pollution standards. Since it increases as a result of trade
opening, ﬁne production frontier moves inward (ﬁne solid line). This means ﬁnat production
moves now to point F while consumption takes place at point G. Therefore, an unadjusted
calculatidn of ﬁne trade eﬁ‘ect will overestimate ﬁle increase in ﬁne polluting good Even more

so will it overestimate ﬁne induced pollution effect.

2.3. The Institutional Optimism Hypothesis

2.3.1. Formulation of the Hypothesis
For a country ﬁnat has a comparative advantage in pollution-intensive industries, ﬁne

impact of- trade liberalizatiorn on pollution is a priori ambivalent. One can identify two eﬂ‘ects

72

working in opposite directions. First, ﬁne country will specialize in ﬁne pollution intensive
industry, which results boﬁn in an increased scale of ﬁne economy and in an altered composition
Thisresultisatﬁneheartofﬁneﬁaditional hypoﬁnesis and, inannodiﬁedfornnofﬁnepoverty
attraction hypoﬁlesis. A second often-neglected effect of trade is on ﬁne environmental
institutions ﬁnrough wealﬁn creation. Section 2.1. discussed ﬁne mechanisms ﬁnrough which

trade liberalization tends to strengﬁnen ﬁne functioning of regulatory institutions.

Section 2.2 presented an analytical model ﬁnat discusses ﬁne interaction of ﬁne
specialization and regulation effects of trade. Which one of ﬁne two dominates, is an empirical
question. Its answer is at ﬁne heart of ﬁne trade and environment debate. It can be formulated as
a ﬁnird big empirical hypoﬁnesis on trade and environment, ﬁne institutional optimism
hypoﬁlesis. Since free trade is closely associated wiﬁn ﬁne application of pollution standards
(mainly ﬁnrough wealﬁn creation), it will generally lead to environmental improvements, even if

a country is attractive for pollution-intensive sectors.

On ﬁne empirical answer to ﬁne hypoﬁnesis ultimately hinges ﬁne question wheﬁner trade
as such is good or bad for ﬁne environment Indirectly, it is also of fundamental importance
concerning ﬁne strategy environmental interests should pursue vis-a-vis trade issues. In moving
ﬁnis issue forward, ﬁne remainder of this section will address ﬁne question what enpirical
evidence might corroborate ﬁne institutional optinnism hypoﬁnesis. Section 2.4. will develop

some meﬁnodological preliminaries.

2.3.2. Empirical Evidence
There is no empirical evidence that tests ﬁne institutional optimism hypoﬁnesis direcﬁy. A

full econometric analysis of the issue would require the statistically difﬁcult separation at is

two counteracting eﬂ‘ects. Even ﬁne separate analysis of ﬁle specialization and ﬁne institutiornal

73

eﬁ‘ect is lacking. In ﬁne context of industrial ﬂight hypoﬁnesis, ﬁne previous chapter showed ﬁnat
few of ﬁne regressions of trade specialization on explanatory variables yielded statistically
signiﬁcant results. On ﬁne impact of wealﬁn on regulatory stringency, ﬁne discussion above
pointed to substantive anecdotal evidence. Diﬁiculties of having a good yardstick for
environmental stringency is a major obstacle to a more detailed statistical analysis. Mucln
analysis is ﬁnerefore based on measuring pollution levels irnstead of environmental regulation,

for irnstance ﬁne literature on ﬁne environmental Kuznets curve.

Neverﬁneless, ﬁne environmental Kumets curve can be taken as indirect evidence for ﬁne
institutional optinnism hypoﬁnesis. It is clear on ﬁne one hand, ﬁnat ﬁne curve is also compatible
wiﬁn oﬁner explarnatory models, such as ﬁne standard paﬁn of economic development and ﬁne
associated changes in economic composition. In decomposing ﬁne pollution-income eﬁ‘ect,
Lucas et al. (1992) have found supporting evidence for ﬁnis hypoﬁlesis ﬁnat pollution reduction
is due mainly to a composition eﬂ‘ect. High pollution may thus be just a fnmction of early
industrialization, which relies heavily on mineral processing and oﬁner relatively dirty industry,
while ﬁne income eﬂ‘ect on regulations may be of only secondary importance. On ﬁne oﬁne
hand, it cannot be excluded ﬁnat ﬁne changing industrial structure is not to some extent caused

by changes in environmental legislation.

However, it is unlikely ﬁnat ﬁne composition eﬁ‘ect alone would suﬁce to generate a
downward trend in absolute pollution levels. Principally, only ﬁne regulation eﬁ‘ect could
achieve ﬁnis alone. However, this effect would need to be fairly high. to compensate boﬁn for
scale and composition effect. If ﬁne composition effect were zero, ﬁne regulation eﬂ‘ect would
have to be larger ﬁnan one. The analytical model in ﬁne previous section shows ﬁnat ﬁne

introduction of a regulation eﬁ‘ect can reproduce ﬁne inverted U-shape. However, ﬁne analytical

74

result relies not just on ﬁne regulation effect, but also on ﬁne composition eﬂ‘ect (ﬁlrough a lower

output of ﬁne polluting good) and ﬁne scale effect (low overall output).

The diﬁculty in interpreting ﬁne results of ﬁne environmental Kuznets curve is ﬁnat ﬁne
analysis is results-based. The statistical relationship between income and pollution need not
imply a causal relationship. This means it considers ﬁne development of environmental
indicators wiﬁnout ﬁne decomposing wheﬁner it is due to changing econonnic compositiorn, more

stringent regulation or technical progress.

A separate problem in ﬁnis context is ﬁnat not only might higher income lead to stricter
regulation but also environmental regulations determine ﬁne potential for economic growﬁn. On
ﬁne one hand, strict regulations nnight make an area unattractive for a number of enterprises. On
ﬁne oﬁler hand, a clean environment and low extemaliﬁes might make ﬁne area rrnore attractive

for oﬁner sectors.

To answer ﬁnis question, it is necessary to statistically separate ﬁne bi-directional causal
relationship between income and regulation. This is inherently impossible to do wiﬁn simple
cross-country data sets, but time-series data are necessary. Alﬁnougln he does not analyze
exactly ﬁle question at hand, ﬁne study by Schimmelpfennig (1992) is worﬁn noticing as a ﬁrst
attempt at statistically separating ﬁne bi-directional relationship between income and pollution
levels. Using time-series county data of ﬁne U.S., he ﬁnds ﬁnat an increase in the level of
income causes a higher level of pollution, wlnile ﬁnere is some, ﬁnough not signiﬁcant, evidence
ﬁnat lower pollution improves economic productivity. While cross-country studies are often a
means of necessity, because ﬁnere exist few reliable time series on pollution data, ﬁney do not
necessarily allow ﬁne conclusion ﬁnat ﬁne functional relatiornslnips established here pertain also in

a time paﬁn.

75

2.4. An Illustrative Application of the Institutional Optimism Hypothesis: A
decomposition procedure

2.4.1. Introduction and Case Description
The discussion of ﬁne previous section shows ﬁnat ﬁne empirical information on ﬁne

ove'all pollution level of a country does not suﬁce to provide strong evidence about ﬁre causes
of ﬁne overall effect Much less is ﬁnere any hint m to how trade might inﬂuence ﬁne result,
because of the interplay of scale, composition and regulation effect More ﬁnan ﬁne industrial
ﬂight arnd ﬁne poverty attraction hypoﬁnesis, ﬁne institutional optimism requires a disaggregation
of ﬁle overall pollution impact into components. This section will develop such decomposition
wiﬁn an illustrative example. We consider a simple Ricardian case of trade liberalization. The
example reﬂects very closely ﬁne mechanisms at work in a CGE model, it also illustrates ﬁne

taxonomy ﬁnat will be used in ﬁne rest ofﬁne text.

Table 2.2 lists outputs, inputs, consumption, and emissions for two countries A and B,
where A is more eﬁcient at producing X, while B is better at producing Y. For illustrative

purposes we assume a Cobb«Douglas utility function wiﬁn equal weights for boﬁn goods.

Table 2.2: The effect of trade on two fictive economies

 

Scenario Region Output Consumption Emissions Welfare
X Y X Y X Y Total

0. Autarky Country A 20 10 20 10 40 30 70 14.1

(Emission fac- Country B 10 20 10 20 20 60 80 14.1

 

 

 

tor x=2;y=3) World 30 3O 30 30 60 90 150 914.1
1. Trade Country A 20 10 15 15 40 30 7O 15
without produc- Country B 10 20 15 15 20 60 80 15
tion changes World 30 3O 30 30 60 90 150 $15
2. Trade with Country A 40 - 20 2O 8O - 80 20
production Country B - 4O 20 20 - 120 120 20
changes World 40 40 40 40 80 120 200 $20
3. Regulations: Country A 36 - 18 18 S4 - 54 18
Emissions -25% Country B - 36 18 18 - 81 81 18
Output -10%; World 36 36 36 36 54 81 135 018

 

Note: Utility U - x °-‘ Y °-‘. This excludes any extemalities

76

In ﬁne autarky case boﬁn countries consume ﬁneir output in a ratio of 2 to 1 depending on
ﬁne relative advantage. They achieve a utility level of 14.1, while pollution lies at 70 arid 80

units, respectively. The aspect of trade liberalization can now be disaggregated into three steps.

W In ﬁnis case, ﬁne only adjustment would take
place irn ﬁne consumption pattern. This increases welfare to a level of 15, but does not use a
country’s comparative advantage. It has no consequence for pollution. This step shows ﬁne
barter eﬁ'ect of trade. However, furﬁner below, ﬁne broade term allocation eﬁ‘ect is used, which
includes two further components. The ﬁrst additional component is ﬁne gain transaction
eﬁciency implied by reduced rent-seeking when non-tariﬁ‘ barriers are removed The secornd
component is ﬁne scale economy ﬁnat is made possible by ﬁne increased trade. The inclusion of
ﬁle transaction and scale emciency also explains why ﬁne allocation effect is relatively large in

ﬁne model than would be suggested by an inspection based on ﬁnis simple example.
W: In adjusting Production. welfare increases in both
countries to a level of 20. Pollution, which is linked to ﬁne output, rises to 80 or 120. This step

shows ﬁne structural or specialization effect of trade liberalization.

W: Here it is assumed ﬁnat induced by ﬁne trade, boﬁn countries
adopt stricter regulations, lowering emissions by 25 percent and output by 10 percent The
change in output’is introduced here for didactic purposes. Insofar as reduced emissions lead to

lower extemalities, ﬁne output level might even increase.

2.4.2. Decomposition with Constant Regulation Level
From ﬁne values in ﬁne table, ﬁne calculations for disaggregating ﬁne pollution eﬂ‘ect can

be made. First, we ignore ﬁne step of increased regulations. This yields ﬁne summary Table 2.3:

77

Table 2.3: Pollution effect of trade liberalization with constant abatement

 

 

Country A Colmtry B
Pollution Eﬁ‘ect +14.3°/o . +50.0°/o
Scale effect +41.0°/o +41.0°/o
Allocation eﬁ'ect -6.4% -6.4%
Composition eﬂ‘ect -l4.3°/o +12.5%

 

The values for ﬁne constant abatement case result from ﬁne following calculations:
1. Total pollution effect: A) +14.3%; B) + 50 %; Calculation:

m_1= Aﬂqﬁﬂﬁq
Emrssronso 70 80

2. Scale effect: +41%;

Calculation: yi—l=£-l
U0 14.1

3. Output effect: + 33.3 %; (This is an intermediate step for calculating allocation and

composition effect).
Calculation: M24424
0:4er 30

4. Allocation (barter) effect: 64%;

Calculation: l--U—' =1-—1-5—
U0 14.1

The relationship between ﬁne ﬁnree effects is:
1 + Output eﬂect = (1+ Scale eﬂectXl-l-Allocarr'on eﬂ'ecr).

5. Composition effect: A) -l4.3°/o; B) + 12.5 %;

78

Cal culation' 1+TotalPoIlutr’onEﬂect _1 ___ A)l' 143 ,8) 1.5
l + OutputEﬂect 1.33 1.33
The various effects (for country B) can also decomposed graphically (Figure 2-4).

Figure 2-4. Environmental effect of trade liberalization: Decomposition into scale,
allocation and composition effect

ﬂuvial-hale-

Pelhﬁea change of

 

 

 

 

Clea-good

 

2.4.3. Decomposition with Endogenous regulation level
When changing regulations are incorporated, ﬁne calculations are slighﬁy altered (Table 2.4).

Table 2.4: Pollution effect of trade liberalization with endogenous abatement

 

 

Country A Country B
Pollution Effect -22.8% +1.25%
Scale eﬁ‘ect +27. 6% +27.6°/o
Allocation eﬁ’ect o6.4% -6.4°/o
Composition eﬂ‘ect -l4.3% +12.5°/o
Mulation eﬁ‘ect -25.0°/o 425.0%

 

79

The adjusted calculations are:
1. Total pollution effect: A) -22.8%; B) + 1.25 %;

Calculation: EEO—"5.2. — 1 = .4151 - 1;B)§1 - 1
Emissrons, 7O 8O

2. Scale effect: + 27.6%;

Calculation: 5 -1 = i -1
U, 14.1
3. Output effect". + 20 %;
Calculation: m-l =E—l
Output, 30

4. Allocation effect: -6.4%; remains constant.

5. Composition effect: A) ~14.3%; B) + 12.5 % remains constant.

 

 

1 + TotaIPoIIutionEﬂect 1 A‘ 0.772 '3‘ 1.0125

Calculati I — = ,
m (1 + OutpurEﬂeCIXI + RegulationEffect) ’ 1. 2 0.75 ’ 1.2 0.75

6. Regulation effect: -25%; by assumption

Despite ﬁne changing output levels, ﬁne 10 efﬁciency effect as well as ﬁne composition
remain unchanged by ﬁne inclusion of an income effect. However, ﬁnis would not hold, if

sectors are hit asymmetrically by production losses.

2.5. Preliminary Conclusions
The ﬁneoretical considerations in ﬁnis Chapter showed ﬁnat ﬁne overall eﬂ‘ect of trade on

ﬁne environment depends on a number of mechanisms ﬁnat often work in opposite direction A

80

fnnll understanding requires a general equilibrium analysis. This is important irn particular for
four lessens ﬁnat can be drawn from the discussion.

First, ﬁne political process of regulation setting is an important factor in the trade and
environment complex. It can be shown in an analytical model ﬁnat ﬁne income eﬂ‘ect on
regulatory stringency can fundamentally alter ﬁne environmental outcome of trade liberalization.

This leads to ﬁle formulation of ﬁne institutional optimism hypoﬁnesis. Clearly, an empirical test

of ﬁne hypoﬁnesis requires an explicit modeling of ﬁne political mecharnism.

Second, boﬁn ﬁne industrial ﬂight and ﬁne poverty attraction hypoﬁnesis require a
concentration on ﬁne composition effect. An empirical analysis of ﬁnese hypoﬁneses needs to be

able to ﬁlter out ﬁnis eﬂ‘ect from ﬁne oﬁner emission-relevant factors, such as scale and
regulation eﬁ‘ect.

Third, ﬁne previous section showed ﬁnat ﬁne scale effect and ﬁne output of ﬁne ecornorrny
are not identical. Therefore, a focus solely on ﬁne scale effect overestimates ﬁne pollution impact
of pollution Instead, an input based indicator of pollution intensity is needed. In particular, in
ﬁne context of trade ﬁne allocation efﬁciency effect ﬁnat determines ﬁne diﬂ‘erence between scale

and output eﬂ'ect can be substantial.

Fourﬁn, interactions between increased requirements for abatement are complex. On ﬁne
one hand, higher production costs can reduce output, and might cause ﬁrms to relocate. On ﬁne
oﬁner hand, ﬁne reduced extemalities increase ﬁne potential total output of an economy. They
also might have a feedback on ﬁne composition of ﬁne economy. An explicit modeling of ﬁnese

mechanisms is also desirable.

81

A full understanding of ﬁnese interactions requires a complex model. It will be shown in
ﬁne next Chapter ﬁnat a CGE model is best suited for ﬁnis purpose. The model developed irn ﬁne

next Chapter will address ﬁnese four important issues.

82

CHAPTER 3
MODELING TRADE AND ENVIRONMENT IN A GENERAL EQUILIBRIUM

FRAMEWORK

3.1. Empirical Modeling Approaches

The previous clmpters have presented a considerable complexity concerning trade and
environment irnteractiorns. The ﬁrst part of ﬁnis chapter describes and evaluates diﬂ‘erent
meﬁnodological approaches ﬁnat are available for an empirical analysis of ﬁne various trade and
environment hypoﬁneses. It will justify ﬁne choice of a computable general equilibrium analysis

for ﬁne present study. The model itself is developed in ﬁne second part of ﬁnis chapter.

Ideally, an empirical analysis ought to integrate ﬁne important feedback mechanisms to
ﬁne largest possible extent No empirical meﬁlod takes account of all such mechanisnns.
However, a few approaches could provide fruitful insights in understanding and quantifying ﬁne
various relationships. One can organize ﬁnese approaches into ﬁnree major groups. A ﬁrst way
of exploring ﬁne trade and environment relationship is ﬁne case-study approach; ﬁle second
approach is to econometrically estimate ﬁne pertinent relationships; ﬁnirdly, one can apply
econorrnic simulation models, especially computable general equilibrium (CGE) models. The
distinction among ﬁnese ﬁnree approaches is in practice not quite as sharp as ﬁne taxonomy
might suggest. Simulation models, for instance, rely on econometric estimates or use estimates
derived from case studies. Depending on ﬁne case at hand, it is possible or even advisable to
adopt hybrid approaches. Neverﬁneless, for a full appreciation of ﬁle choices irn empirical

modeling it is useful to examine brieﬂy ﬁne ﬁnree basic approaches.

83

3.1.1. Econometric Approaches
Some econometric studies of ﬁne tradeenvironment relationship were discussed in

previous chapters. They focus eiﬁner on trade ﬂows or on foreign direct investment, and relate
ﬁnem to indicators of environmental stringency. As discussed previously, despite some progress
in understanding ﬁne problems, ﬁnese studies fail to fnrrnly establish a conclusive link between
environment and trade. Alﬁnough ﬁne econometric approaches have a rigorous ﬁneoretical
ﬁ'amework, ﬁne available data are generally too weak to allow a conclusive estimation

Statistical diﬁiculties appear at numerous levels.

1, 195m g Q; Hgﬁgher-Ohlin ﬁlegry

The Heckscher-Ohlin ﬁneory of comparative advantage, on which much of ﬁne argument
in ﬁle previous two chapters rests, is diﬁcult to prove empirically, alﬁnough it remains ﬁne nnost
important ﬁneoretical framework in international econonnics. Notably, it took several decades to
solve ﬁle sorcalled Leontief paradox. In his senninal article, Leontief (1954) showed ﬁnat ﬁne
capital-redundant United States apparently exported labor-intensive goods. The article sparked
an abundant literature that eiﬁner developed ﬁneoretical modiﬁcations to ﬁne simple Heckscher-
Ohlin model (e.g., ﬁne inclusion of product cycles) or pointed out biases in ﬁne data construction
(e. g., ﬁne assumption ﬁnat imports use ﬁne same production technology ﬁnat is used in ﬁne U.S.).

Also it is difﬁcult to get pre- and post-trade prices.

Naturally, an analysis of ﬁne signiﬁcance of ﬁne environmental stringency in determining
trade ﬂows will be even more difﬁcult ﬁlan ﬁne analysis of labor and capital endowment
Furthermore, a time series analysis of one country would need to include environmental

policies in ﬁne main trading partners. An increasing regulatory stringency of a country does not

84

imply a decreasing attractiveness for pollution-intensive industry, if environmental policies in

oﬁner countries evolve faster.

We:

For cross-country comparisons, no clearly identiﬁed yardstick for environmental
stringency is available. The various possibilities for such an indicator include government
ouﬁays on environmental policy; participation in international agreenents; abatement
expenditure ﬁgures; or ﬁne number and value of environmental taxes and levies. However, ﬁne
choice of one indicator over anoﬁler will skew the result, because preferences vary among
countries for certain type of instruments (e.g., taxes or regulatiorns). Similarly, ﬁne oﬁcial
regulatory ﬁamework may not be supported by actual enforcement, key industries may be
exempted from regulation or taxation, or inefﬁciencies in ﬁne environmental policies may make

ﬁne same pollution reduction much more costly in one country ﬁnan in anoﬁne.

 

Also at ﬁle ﬁrm or sector level, a numbe of potential indicators of regulatory costs
exists, such as abatement expenditures, ﬁne number ’of inspections, ﬁne amount of
environmental taxes paid, and ﬁne number of regulations. These measurements, too, can only
be a proxy of ﬁne actual importance of environmental policy for a ﬁnn's operation First, ﬁnere
maybealargegapbetweenﬁneletterofﬁnelawandwhatisactuallyenforced Secondﬁne
cost-eﬁ‘ectiveness of an environmental policy can vary substantially. In ﬁne extreme case, ﬁne
actual cost of ﬁne abatement itself could be nearly zero while ﬁne administrative burden to prove
ﬁnat ﬁne abatement took place could be quite high. Also, if one country achieves ﬁne abatement
reduction via a regulation but another via an ecotara the regulated company is likely to have a

competitive advantage over ﬁne taxed one, which in addition to its abatement costs has to pay

85

taxes for ﬁne non-abated emissions. The taxed enterprise would react nnore sensitively to
environmental policy ﬁnan ﬁne non-taxed one.

LMmurirlalem

On ﬁne output side, ﬁnat is, concernirng ﬁne pollution level itself, dimculties lie not only in
measuring pollution levels but also in deﬁning meaningful ways of aggregating a multitude of
diﬂ‘erent pollutants. Solutions to ﬁnese problems often need to be found on a case by case basis.
For instance, various indicators of environmental stringency could be compared using
sensitivity analysis. An alternative could consist in aggregate indicators based on ad hoc
weighting meﬁnods, toxicity weights, hedonic values, or principal-component arnalysis.
Unfortunately, often even ﬁne basic elements of such an index construction are hard to come by,
as data collections of environmental factors exist only fairly recenﬁy. A full time-series analysis

is ﬁnerefore often impossible.
5 ri ' ment

A furﬁner statistical difﬁculty lies in deriving an abatement function. General data
problems are exacerbated by ﬁne fact ﬁnat environmental regulations are rarely relaxed but only
increase in stringency. Therefore, regulations follow a common trend wiﬁn technological
process. This common trend means it is often not clear wheﬁne a change in ﬁne emissions is
due to increased environmental stringency or to nmobserved technological processes, because

multicollirnearity is likely to plague ﬁne analysis.

65'] .

As was discussed in Chapter 2, environmental stringency cannot be taken as

exogenously given. This relationship requires ﬁne estimation of a system of simultaneous

86

equations to establish cause and eﬁ’ect Pitfalls in establishing causality also exist in oﬁner areas.
For instance, one could falsely interpret low abatement expenditures (in dollar terms) as having
lax environmental standards in country. In reality ﬁney might be ﬁne result of a very cost-
eﬁ‘ective environmental policy, or in ﬁre extreme, ﬁne result of a policy ﬁnat leads to an exodus
of pollution-intensive industries. Similarly, ﬁne opening of a country to trade might increase ﬁne
relative importance of diﬁ'erences in environmental regulatiorns, but improve technology

dissemination.

If one adds to ﬁnese issues just discussed, problems of imperfecﬁy operating rrnarkets,
erogenous shocks, or rigid prices, it is clear ﬁrst an econometric analysis of trade arnd
environment relationships is diﬁcult In practice, it is likely to remain limited to testing simple
relationslnips, for instance, ﬁne direction of trade and investment as a fnmction of an index of
regulatory stringency. Many more complex interactions are beyond ﬁne reach of ecornometric

meﬁnods urntil ﬁne data situation improves substantially.

3.1.2. Case Studies
The division line between econometric approaches and case-study approaches is not

sharp, because ﬁne data of an econometric study also ultimately derived ﬁom individual cases.
However, a change in focus warrants a distinction. Econometric analysis concentrates on ﬁne
formulation and testing of falsiﬁable hypoﬁneses, and applies standard statistical criteria to do
so. Evidenﬁy, ﬁnis approach can also be followed wiﬁnin a case study. However, for ﬁne case-
study approach, as it is understood here, it is possible to remain purely descriptive or operate
wiﬁn simple inspection of data For ﬁre issue at hand, sectoral or historical conmtry studies could

provide suggestive insights.

87

W

The advantage of ﬁle sectoral case-study approach is ﬁnat it allows us to look intensively
at ﬁne obvious candidates where environmental factors might play a role (one could think here
of chemicals, metal production, etc.) and which are of great concenn ﬁom a policy point of
view. For ﬁnese, it would be necessary to identify ﬁne various technological options arnd collect
data on ﬁneir respective cost structure and environmental impact One would ﬁner need to
detect to what extent regulations or oﬁner factors detemnine ﬁne sector’s size and techrnological
development One could place ﬁne study by Wheeler and Martin (1992) into ﬁnis category. The
auﬁnors arnalyzed ﬁne dissemination of pulp production technology as a flmction of a country’s
openness to trade. They could show ﬁnat economies ﬁnat are more open generally have ﬁne nnore
advanced (and clean) technology.

However, it is questionable wheﬁner ﬁne experience in one sector is anecdotal or can be
generalized, because there is a risk of a selection bias when choosing ﬁne sector. Furﬁre
drawbacks are ﬁne potential need of considerable data, in particular at ﬁne ﬁrm level, that might
make many potentially interesting cases impossible to conduct in ﬁne ﬁrst place. In addition, ﬁne
approach risks leaving important factors out of ﬁne analysis, due to ﬁne partial nature of ﬁne

analysis (in particular, ﬁnose ﬁnat affect ﬁne policy process).

3 l 2 2 II ri ! 1

Historical studies of whole countries are one way to avoid ﬁne problem of having only a
partial (and ﬁnerefore possibly biased) look at ﬁne trade and environment problem. The result of
ﬁne historical changes ﬁnat occurred in ﬁnese countries is ﬁnen extrapolated arnd qualiﬁed to

provide an estimate of ﬁne expected impact of a similar change. Hufoauer and Schott (1992)

88

applied ﬁnis approach for ﬁne case of NAFTA The auﬁnors assume an arnalogy of ﬁne Norﬁn
American case wiﬁn 31 similar countries ﬁnat have liberalized economically in ﬁne past They
derived ﬁom ﬁnese data an approximation for ﬁle economic changes induced ﬁnrough ﬁne trade
liberalization of NAFTA. In ﬁneory, it might be possible to collect ﬁne corresponding
information on environmental factors for at least some of ﬁne cases. However, it has not been
until fairly recent ﬁnat organizations, such as ﬁne World Bank (especially since the World
Development Report 1992), ﬁne OECD (1995) and ﬁne World Resources Institute (1986), have
begun to compile international statistics of environmental indicators. In practice, ﬁneefore, one
would have to rely to a signiﬁCant extent on ex post construction of data sets, usirng external
information on pollution intensities. Alternatively, one could choose a more descriptive

approach based, for instance, on people’s perception of ﬁne development.

If ﬁne diﬁ'lculties in constructing useful environmental data sets can be overcome, ﬁne
historical approach could provide useful ﬁrst-order approximations of ﬁne expected impact of
trade liberalization on growﬁn and environmental variables. However, problems renain For
instance, ﬁne case of NAFTA is fairly urnique, because it constitutes a free trade area between a
higlnly industrialized and a fairly poor country. The case ﬁnat may come closest to ﬁne NAFTA
is ﬁnat of ﬁne 1986 accession of Spain into ﬁne European Community (now European Uniorn). rs
Still, Spain's EC membership differs ﬁom Mexico's membership in NAFTA in at least four
respects. First, NAFTA does not provide for ﬁscal support for its poorer member. Second,

NAFTA does not allow free movement of labor. Third, ﬁne income diﬁ‘erences between ﬁne

89

 

 

US

3.1

35%:

U.S. arnd Mexico are a multiple of ﬁnat between ﬁne European natiorns. Fourﬁn, ﬁne European
Commurnity has an active policy aimed at hannonizing environmental minimum standards

wiﬁnin ﬁne Community.

Arnoﬁner critical factor ﬁnat speaks against using ﬁne historical approach to analyze ﬁre
question of NAFT A's environmental consequences is that it provides little guidance on a
disaggregated level, since ﬁne composition of any economy is unique. Therefore ﬁne historical
approaclncouldsuccessfullyattainonlyagoodestimateofﬁnescaleeﬂ'ectbutnotﬁne

composition effect of trade liberalization on pollution.

3.1.3. Simulation Approaches

Simulation approaches are distinct from boﬁn econometric approaches arnd case studies irn
that ﬁney principally do not need original data Instead, ﬁley rely on constructing ecornomic
nnodels wiﬁn parameter values ﬁrst are derived from literature reviews of econometric studies,
case studies, engineering data, or even educated guesses. Wiﬁn ﬁlese data ﬁne modeler can

analyze ﬁne impact of counterfactual policy scenarios.

Simulation analyses have ﬁre clear disadvantage ﬁrat ﬁney are irnherenﬁy incapable of
hypoﬁnesis testing according to scientiﬁc criteria Their reliance on secondary data means ﬁnat
ﬁne modeling assumptions already contain ﬁne outcome of ﬁne analysis. For instance, if a trade
nnodel contains an equation ﬁnat speciﬁes environment as an important production factor, a

simulated regulatory change will automatically lead to a change in ﬁne trade pattern The

 

'5 The other countries, Greece and Portugal, ﬁnatjoined ﬁne EU in ﬁne Southern enlargenent (1981
and 1986) are qualitatively different. Both already had largely ﬁes-market access, due to an
association treaty and EFTA menbership, respectively (Shelbume 1993).

90

scientiﬁc argument about ﬁre importance of regulation remains limited to a discussion, wheﬁler
ﬁne original assumption is plausible. The discussion is complicated by ﬁne fact ﬁnat a correct
speciﬁcation of one policy aspect can be overwhelmed by an incorrect speciﬁcation of anoﬁne'
essential relationship. This problem is ﬁne reason for ﬁne unease of many ecornonnists wiﬁn
economic simulation models. It is often not immediately clear, which particular equation
speciﬁcation is ﬁne driving force of a simulation result Consequenﬁy, simulation models often
remain black boxes to ﬁne reader, unless a signiﬁcant amount of time is invested irn exploring
ﬁne modeling details. Unfortunately, ﬁnerefore, model validation ﬁnrough peer review is often

While suﬁ‘ering from a severely limited model validation, simulation models are often ﬁne
only meﬁnod of deriving at least an approximate economic analysis. As discussed data
problems are likely to be overwhelming for an econometric approach, if a minimum arnournt of
complexity is required Simulation models allow a complex analysis while avoiding ﬁne data
problem by using best available estimates. The importance of individual parameters can be
tested using sensitivity analysis. Three types of simulation approaches are available. These are

macromodels, input-output analysis, and ﬁnally CGE modeling.

Masmmadels

Macroeconomic models are based on observed statistical correlation among aggregate
variables in ﬁne past They are applications of econometric models, and as such shares some of
ﬁneir problems for ﬁne estimation ﬁne economy-environment interaction Therefore,
macroeconomic models of trade and environment relationships are forced eiﬁne to make
simpliﬁcations in ﬁne modeling structure or to impose external parameters into ﬁne model
structure ﬁnat are not derived wiﬁnin ﬁne same framework as ﬁne econometric estimates.

91

For instance, in ﬁne context of analyzing NAFTA, Adams et al. (1992) and Clopper
Almon/Inforum (1992) applied macronnodels wiﬁn fairly detailed sectoral disaggregation
However, ﬁney do not provide any disaggregated information on ﬁne factors of production. An
extension of ﬁne models to include environment as a production factor is ﬁnerefore not
straightforward In addition, most environmental data do not exist in suﬁcienﬁy detailed time
series, but are at best available as simple point estimates.“ While macro-models have been
medsmcessﬁrﬂymmewmsmncesmesﬁmeemonﬁceﬁmofﬁadewhemmmﬂydng

ﬁne ﬁeld of economy-environment interactions, its use is limited.

- M l

Envirornrnent can be integrated in a straightforward way by extending an input-output
matrix On ﬁne input side, ﬁne environment appears as a source of extraction and provider of
recreation for industry and ﬁnal demand. On ﬁne output side, ﬁne environment receives
discharges of residuals ﬁnat occur during ﬁne production or consumption of a good Like all
oﬁrer sectors of ﬁne [-0 matrix, the environmental sector can be furﬁner disaggregated, eg into

air, land, and water. ‘7

The ﬁrst generation of simulation studies are Leontief models ﬁnat used ﬁnis type of

extended input-output matrix to analyze policy changes (e.g. Rhee and Mirarnowski 1984).

 

mOnanaggregatelevelﬁncreexists,however,agoupofottenhighlysophisticatedKLEMnnodels
named after the four included input factors capital (K), labor (L), energy (E) and materials (M).
These studies analyzed the possibility of an economy to substitute away from energy dependency
aﬁerﬁneoilshocksinthe l970s.Thesemodels,however,areparﬁalatbest,andareof1imited
valucinanalyzingﬁnenwmmulﬁfaceedproblencenplexthatweamdealmgwhh.

92

Victor (1972) provides a comprehensive model of ﬁnis type for ﬁne whole economy. Most oﬁner
enpirical models such as Cumberland and Stram (1976) are restricted to an industry-by-

irndustry format A survey is presented in Forsund (1985).

The usefulness of traditional input-output modeling is, however, limited by ﬁne
assumption ﬁnat all coefﬁcients are ﬁxed This means ﬁnat I-O models are generally not useful
tools when it is assumed ﬁnat an economy undergoes structural change, as is ﬁne case for trade
liberalization. To a lesse extent, ﬁle implicit assumption ﬁnat statistically established structural
relationships will continue to hold in ﬁne future, vexes also oﬁner approaches such as
macroeconomic and CGE modeling. However, macroeconomic models allow mitigating ﬁnis
problem ﬁnrough ﬁne inclusion of trend variables. By contrast, in input-output analysis ﬁne level
of pollution only changes through alterations in the composition and magnitude of
cornsumptiorr, or some arbitrary change in ﬁne pollution coeﬁcients over time. Input-output
analysis ﬁnerefore usually overestimates ﬁne eﬂ‘ects of policy measures, since it does not allow
for substitutions ﬁnat may nnitigate ﬁne impact of ﬁne parameter changes. Input-output
calculations ﬁnerefore could only serve as an upper bound of plausible values. Any conclusions

resulting ﬁom an extrapolation of ﬁnese results would have to be qualiﬁed.

m l r E uilibri M ls

Computable general equilibrium (CGE) models are hybrids of macronnodels and input-

output models, combining ﬁne advantages of boﬁn. The CGE approach involves ﬁne construction

 

"’ Ahmad, E1 Serafy, and Lutz (1989) and Costanza (1991) contain papers on the issues involved
in producing environmental accounts.

93

of a model ﬁnat expliciﬁy incorporates ﬁneoretical assumptions about ﬁre behavior of individual
actors. Most ofﬁne assumptions used in standard models are ﬁne usual and widely accepted
staple of economic ﬁreory. CGE models generally postulate ﬁnat ﬁrms maximize proﬁts subject
to cornstraints set by technology, prices, interest rates, and so forﬁn, and ﬁnat ﬁne behavior of
cornsumers is determined by utility maximization subject to price and income constraints. These
basic assumptiorns are usually extended to serve ﬁne intention of ﬁne modeler. Modeling
economy-environment interactions, for instance, requires some explicit assumptions about ﬁne
form in which ﬁnis interaction takes place. Many CGE models use statistical estinnates for ﬁne
flmdamental ﬁneoretical parameters. The missing parameters are obtained ﬁnrougln calibration
(cp. Shoven and Whalley 1992). This approach means ﬁley are chosen in sucln a fashion ﬁnat
ﬁne model reproduces a historical data set, called a Social Accounting Matrix (SAM),
constructed for ﬁne purpose of ﬁne model. Therefore, CGE models use boﬁn point arnd tinne-
seies estimates to derive behavioral parameters. However, ﬁle difference between
macronnodels should not be overestimated (cp. CBO 1992, p. 68). Econometric models can be
regarded as analogous to a reduced form of ﬁne more expliciﬁy modeled CGE models, alﬁnough

some diﬁ'erences remain.

The ﬂexibility ﬁnat CGE models provide in analyzing complicated economic interactions
has led to ﬁreir wide application in ﬁne ﬁelds of trade and public ﬁnance wiﬁl a special interest
in ﬁne distributional impact of macroeconomic policy (Robinson 1989; Shoven arnd Whalley
1992). Some CGE models analyze ﬁne economic costs of environmental regulations at ﬁne
regional level, and at ﬁne national and international level, mainly wiﬁn a focus on ﬁne economic
eﬂ‘ects of reducing C02 emissions. Hoeller, Dean, and Nicolaison (1990), arnd Nordhaus

(1991) provide surveys of ﬁnis kind of modeling. Some more recent examples are given by

94

Hazilla and Kopp (1990), Jorgenson and Wilcoxen (1990), Bergman (1991), Boyd and Uri
(1991), Conrad and Schroeder (1993), Ballard and Medema (1993), Nestor and Pasurka
(1993), and Perroni and Wigle (1995), Beghin et al. (1995), Copeland and Taylor 1995; Smith

and Espirnoza 1996), Dessus and Bussolo (1998).

The advarntages of ﬁne CGE approach made it also ﬁne prime choice for modeling ﬁne
eﬁ'ects of NAFTA (CBC 1992). At least two dozen CGE models deal wiﬁn various aspects of
trade liberalization on ﬁne Mexican economy, none of which focuses on ﬁne environment.

Reviews are provided in Shiells and Francois (1994), Brown (1992), and CBC (1993).

Table 3-1 summarizes ﬁne pros and cons of ﬁne ﬁnree main empirical approaches. The
overwhelming arguments in favor of a CGE model are its manageable data requirements and
its analytical ﬂexibility.

Table 3-1. Comparison of different empirical approaches to assess trade and
environment interactions

 

 

Econometric Studies Case Studies Simulation /CGE models
Data 0 high, problems of 0 medium 0 low
Requirements multicollinearity 0 selection problem 0 use of best
0 diﬂicultiesin o useofmicro-and econometricestimates
constructing proper macro-data possible
indices
Complexity of 0 simple, partial I complete analysis 0 high
analysis analysis possible 0 allows experimental
- could include policy forms
Hypothesis 0 yes 0 focus on obvious I not tnnly possible,
testing 0 estimation of candidates results driven by
conﬁdence intervals 0 descriptive assumptions
0 low generalizability 0 can ﬁlter out key
relationships
0 sensitivity analysis
Required . o mainlydata o needsdetailedﬁr'm o high,ifmodelisbuilt
work load of construction level or institutional ﬁ'om scratch
analysis knowledge
Existence of o few, inconclusive 0 some 0 plenty concerning
literature trade relationships and
environmental
relationships

 

95

3.2. Non-Technical Model Description

For ﬁne purpose at hand, ﬁne arguments overwhelmingly favor ﬁne employment of a CGE
model for ﬁne analysis. However, even after deciding to use a CGE approach, ﬁnere are an
inﬁnite number of variants possible. These concern especially ﬁne representation of ﬁne
environmental component, ﬁne details of ﬁne tax system, ﬁne labor market, ﬁne government
sector, ﬁne level of sectoral disaggregatiorn, and ﬁne supply of production factors. Ideally, one
would want to have a model ﬁnat is as complete and accurate as possible. In practice, a cost-
beneﬁt calculus guides model construction. While ﬁne skill of ﬁne modeler, ﬁne existence of
oﬁner models, and data availability inﬂuence ﬁnis calculus, it is primarily driven by ﬁne analytical
focus. In the case at hand, it is evidently important ﬁnat ﬁne environmental aspects of ﬁne model
are included in a careful manner. Clearly, however, in some cases diﬁcult choices have to be
made. In ﬁne case hand, geographical differentiation and ﬁne aspect of income distribution
(which is important for its inﬂuence on regulation setting) had to be omitted ﬁom ﬁne analysis.
The description of ﬁne model utilized in ﬁnis paper is separated into a technical and a non-

teclnrnical part, which principally can be read wiﬁnout ﬁne other.

3.2.1. Overview

To assess ﬁne environmental consequences of trade liberalization empirically, a purpose-
built computable general Equilibrium model of ﬁne Trade Environment Relationships in Norﬁn
America (ETERNA) will be employed. The newly developed model is comparative-static; it
models a single period ornly. The model distinguishes four regions, namely ﬁne ﬁnree NAFTA

conmtries, Mexico, ﬁne United States and Canada, as well as ﬁne Rest of ﬁne World. Wiﬁnin each

96

NAFI‘ A country, ﬁnere exist four agents: ﬁrms, consumers, importers, and ﬁne government.

Output is based on ﬁnree primary production factors: labor, capital and air pollution

ETERNA has 26 production sectors, most of which trade products wiﬁn oﬁner regiorns
‘ (Table 3-2). All sectors share a common production structure ﬁnat is depicted in Figure 3-1. As
usual in ﬁnis type of model, producers choose ﬁne optimal combirnation of inputs to mirnimize
production costs, given ﬁne level of sectoral demand and relative after-tax prices. Production in
some sectors shows econonnies of scale. However, ETERNA maintains ﬁne assumption of

mornopolistic competition. This assumption means ﬁnat all sectors earn zero proﬁts.

Technology is assumed to be such ﬁnat ﬁne decision-making process can be separated into
several stages. " First, demand for ﬁnal and intermediate inputs is allocated between imported
arnd domestic supply. This allocation is the so-called Armington assumption, which etplaim
cross-hauling of identical goods (Armington 1969). Second, domestic production results ﬁorn a
combination of value added and intermediate inputs. Third, value added is a composite of labor
arnd production capital. Fourﬁn, value added is associated wiﬁl ﬁne use of an envirornmerntal sink
Fiﬁh, ﬁne environmental sink is a function of abatement capital and environmental pollutiorn,

which in ﬁne model includes only air emissions.

The demand for ﬁne sectoral outputs has ﬁnree components: ﬁney are used as intermediate
inputs to production, they are exported, and they serve for ﬁne ﬁnal consumption of each
country’s houselnolds, which are modeled as representative agents. Households act as utility

maximizes ﬁnat choose ﬁneir Optimal. consumption bundles. ETERNA does not distinguish, as

97

is oﬁen done, between consumption and production sectors. Raﬁner, ﬁne ﬁnal consumption of

ﬁne produced good enters ﬁne utility function directly.

 

" All production steps are hornothetic with a constant elasticity of substitution, which implies
separability among subsets of different input bundles.

98

Table 3-2. Definition of Production Sectors for North American Social Accounting

 

 

Matrix
Sector Description
1. Agriculture Agriculture; Livestock; Forestry; Fishing & Hunting
2. Mining Coal products; Metal ore mining; Other mirning; Quarrying; Oﬁner
metal ore nnining
3. Petroleum Petroleun extraction & natural gas; Petroleum prodnncts; Basic
petrochemical

4. Food Processing

5. Beverages

6. Tobacco

7. Textiles

8. Wearing Apparel
9. Leather

10. Paper
11. Chemicals

12. Rubber

13. Non-Metallic Mineral
Products

14. Iron arnd Steel

15. Non-Ferrous Metals

16. Wood & Metal
Products

17. Non-Electrical
Machinery

18. Electrical Machinery

19. Transport Equipment

20. Other Manufactures

21. Construction '

22. Electricity

23. Commerce,
Restaurants & Hotels

24. Transport &
Communication

25. Financial & Insurance
Services

26. Other Services

Meat & dairy products; Processed ﬁuits & vegetables; Milling of
wheat & their products; Milling of corn & their products; Processing
of coﬁ‘ee; Sugar & products; Oils & fats; Food for animals; Oﬁner
processed food

Alcoholic beverages; Beer, malt; Soft beverages & syrups

Tobacco & products

Soft ﬁber textiles; Hard ﬁber textiles; Other textiles

Wearing apparel; Hosiery; Knitted wear

Leather & products

Pulp; Paper products; Printing & publishing

Basic chenicals; Fertilizers; Synﬁnetic ﬁbers; Drugs & nnedicine;
Soaps & detergents; Other chenical industries

Rubber products; Plastic products

Glass products; Cenent; Oﬁner non-metallic mineral products

Steel mills

Non-ferrous basic industries

Manufactnnring wood; Other wood industries; Furniture; Metallic
structures; Metal forging; Other metallic products

Machinery & non-electrical equipment

Electrical machinery; Electrical appliances; Electronic equipment;
Other electrical products

Motor vehicles; Motor parts; Missiles & tanks; Oﬁner transportation
equipment

Other manufacturing industries

Construction

Electricity, gas & water

Commerce (wholesale & retail trade); Restaurants & hotels;

Transport; Communications
Financial services; Dwellings, real estate

Professional services; Educational services; Medical services;
Recreational & cultural services; Other services

99

Figure 3-1. Structure of the production function in ETERNA

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Households Indirect Exports
Consumption El.
CONS [oi
Total Goods
Supply
xi
CBS (Armlngton)
Domestic
Production mam”
XDi la
Leontief
Indirect Inputs
IO- .
I
Laontlat
Value Added ENVirgs‘Tental
VA, 5.
CBS Exponential funeﬁon
- Labor = .
ProductnonCapltal . Abatement Capital Pollution
L e, llutlon
KPI (W39 [:0 ) KA' POLL.

 

 

 

 

 

 

 

 

 

 

100

 

Trade relationships are modeled such ﬁnat ﬁne balance of payments of ﬁne different
regiorns does not change. Included here are also ﬁne ﬂows from cross-country capital
ownership. Demand for exports to a NAFTA country results from an Armirngton-type demand
structure. Exports to ﬁne rest of ﬁne world follow a constant demand elasticity function, while
supply ﬁom ﬁne rest of ﬁne world is perfectly elastic. Trade ﬂows are subject to import duties,
which are collected by ﬁne government, which recycles ﬁnem back to the economy in a lump-
sum fashion Non-tariﬁ‘ barriers are a sigrniﬁcant obstacle to ﬂee trade, which results in rents
for ﬁne importers. However, it is assumed that ﬁnese rents do not produce any beneﬁt to ﬁne

representative agent, and are ﬁnerefore counted as net welfare losses.

3.2.2 Economy-Environment Nexus in the Model

The important feature of ETERNA is ﬁne economy-environment nexus. Five diﬁ‘erent
relatiornships can be identiﬁed:

1. Calculation of emissions

2. Extemality in ﬁle production function

3. Extemality in ﬁne utility furnction

4. Abatement cost ﬁmction
5. Determination of abatement level

These relationships are shown in Figure 3-2. The numbers in ﬁne Figure correspond to
each identiﬁed relationship. There exists no model ﬁlat incorporates all 5 aspects. The simplest
arnalysis integrates only ﬁne ﬁrst relatiornship. This integration can be achieved by use of a
standard CGE model of trade liberalization and inclusion of an environmental input-output
table as a simple add-on This approach has been taken by Grossman and Krueger (1995) who

use ﬁne existing model by Brown, Deardorﬁ‘ and Stern (1992) and calculate ﬁne envirorunental

101

consequences through imputation of U.S. pollution intensity data into ﬁne volume of trade.

Tlneir results suggest ﬁnat ﬁne environmental consequences of NAFTA will be negligible.

Figure 3-2. Economy and Environment Interaction in ETERNA

 

 

Welfare
Utility EW '\
Health Consumption
Production
A externnality /
Production Regulation
atnuns
Vat
Emission V
calculation .
Pollution < Regulatron

 

Lee and Roland-Holst (1997) analyzed ﬁle economic relationship between Japan arnd
Indonesia by irnputing U.S. pollution intensities into ﬁneir mutual trade. Even under ﬁne
arguable assumption ﬁnat ﬁne pollution intensity of a sector in Japan is not lower ﬁnarn ﬁnat irn
Indonesia, ﬁne auﬁnors ﬁnd a considerable asymmetry in ﬁne pollution content embodied in ﬁne
exports of ﬁne two countries. Indonesia exports pollution-intensive goods arnd irrnports goocb
ﬁrst are relatively clean. A CGE analysis of ﬁne trade relationslnip points to considerable scope

for policy instruments to reach environmental improvement at low costs in terms of GDP. In

102

many respects ﬁne econonnic relationship between ﬁne U.S. and Mexico is similar to ﬁnal
between Japan and Indonesia. However, in ﬁne North American case, it is not evident ﬁnat
embodied pollution ﬂows from ﬁne poorer to ﬁne richer country. Bommer and Schulze (1996)
who used a similar approach too Lee and Roland-Holst for NAFTA show ﬁrst irn this case ﬁne
U.S. is a net exporter of relatively pollution intensive goods and becomes nnore so due ﬁne

irntroduction of NAFTA.

The add-on approach provides a straightforward way to orgarnize data for a historical
ecornonnic situation However, for ﬁne analysis ofa counterfactual situatiorn, ﬁne approach is too
parsimonious. Changes irn ﬁne pollution level are calculated out of ﬁne resulting change irn
sectoral composition ﬁom a model that oﬁnerwise completely igrnores envirornmental
interactions. This approach is a special case of ﬁne more general nnodel ﬁnat includes

envirornmental feedbacks on production.

Several CGE models consider ﬁne eﬁ'ects of regulatiorns on production costs arnd ﬁne
consequent clnarnges in output and trade. Alﬁnougln hampered by sketchy data, ﬁnere exist some
interesting approaches for single country models ﬁnat include representations of emissiorns
abatement ﬁmctions, for instance, Dessus and Bussolo (1998). A direct applicatiorn to Mexico

can be fonrrnd irn Beghin et al. (1995).

Most of these models are, however, of a partial equilibrium nature in ﬁnat ﬁney mly
considerﬁnepotentialcostsbutnotﬁnebeneﬁtsofenvirenmentalresﬁicﬁonsandstandardson
ﬁnenaticnalproductThisconsiderationisbecausebeneﬁtsandcostsofchengesinﬁnelevelof
polluticnarediﬁculttoobtain.Perroni and Wigle (1995) useanadhocflmctionalformthat
measures ﬁne welfare increase from a reduced pollutiorn level. Their analysis relies on a

separability of pollution damage and cornsumption in ﬁne utility ﬁmctiorn The welfare eﬂ'ect ﬁnus

103

has no impact on ﬁne behavior of ﬁne model itself. This outcome means ﬁnat, eﬁ‘ectively, ﬁne

modelisrmLandﬁnewelfareeﬁ‘ectiscalculatedlater.

Ballard and Medema (1993) integrate producer-producer and producer-consumer
extemalities into a CGE model of ﬁne United States. The auﬁnors incorporate material damage
irnto ﬁne analysis tlnrough variable input-output coeﬁcients. This approacln allows ﬁne
researchers to approximate ﬁne costs of damaged output due to changes in ﬁne polluticrn level
ﬁnrough increases in ﬁne demand for intermediate inputs of that aﬁ‘ected sector. In addition
cornsumer welfare is affected ﬁnrough a parameter aﬁ‘ecting ﬁne healﬁn of ﬁne population. Similar
approaches are followed by Copeland and Taylor (1995) and, in a trade, context by Snniﬁn and

Espinoza (1996)

Pireddu (1996) developed a closed-economy model that includes ﬁne ﬁrst four important
envirornment economy relationships. This approach allows him to test a variety of
environmental tax options. His model so far is calibrated only to a primitive “toy” ecornomy.

However, in principle, the model could serve as a shell ﬁnat could be calibrated to actual data.

There are two attempts ﬁnat are in spirit close to ﬁne modeling assumptions described
furﬁner below. Cole er a! (1997) add emissions ﬁgures to an existing model simulation A
pseudo-regulation ﬁrnction is imposed on their trade model by imposing a U-shasped emision
function on top of ﬁne results. However, since ﬁne environmental Kuznets curve is ﬁne result of
boﬁn structural and regulatory changes, ﬁnis meﬁnod inherently leads to a double counting of ﬁne
structural clnange. By contrast Strutt and Anderson (1998) add a unit ennissiorns curve ﬁnat is
estimated from surveys While ﬁnis work provides good detailed technical information, ﬁne
projected techrnological progress is not linked to trade, and could ﬁnerefore be deenned

autonomous.

104

ETERNA ﬁlls a gap in ﬁne literature by incorporating all ﬁve identiﬁed economy-
envirornment relationships: The environment is modeled as an input factor. Production ﬁnat uses
ﬁnis factor results in pollution ﬁnat damages ﬁne healﬁn of ﬁne population The use of ﬁle
environment ﬁnerefore aﬂ’ects direcﬁy ﬁne supply of labor in ﬁne nnodel. This eﬁ‘ect leads to
lower production as a result of pollution due to sick days, reduced physical healﬁl, etc. The
snnpply of labor is ﬁnerefore modeled not only as function of the real wage rate but also of ﬁne

general level of pollution.

The use of ﬁne environmental input depends on two factors. First, it is a direct function of
ﬁne output in ﬁne various sectors. If a polluting sector grows wiﬁnout any change in ﬁne
composition of ﬁne inputs, ﬁne pollution output increases. (Because ETERNA allows for
economies of scale, ﬁnis increase will not necessarily be in proportion.) The second factor that
determines ﬁne pollution output is ﬁne pollution intensity of production ﬁrst is allowed by ﬁne

government.

The government regulates ﬁne amount of pollution each sector is allowed to emit pe nrrnit
of production. Eﬁ‘ectively ﬁne use of ﬁne environmental output also ﬁxes ﬁne amount of
abatement capital per unit of production. In a ﬁrrﬁner important step, ﬁne level of ﬁne abatement
expenditure has been made endogenous to ﬁne model, namely as a ﬁrnction of ﬁne real income
of ﬁne representative agent. The motivation behind ﬁnis follows ﬁne argument outlined in
previous chapters ﬁnat a wealﬁnier population calls for a stricter level of environmental
regulation. Therefore, insofar as ﬁne policy of a country increases ﬁne material well-being of its
population, ﬁnere exists a direct feed-back to ﬁne stringency of its environmental regulation It is

ﬁnerefore not a priori clear what direction environmental changes will have in ﬁne diﬁ‘erent

105

countries, because ﬁne composition of ﬁne economy changes at ﬁne same time as ﬁne eﬁ'ective

supply of ﬁne environmental input.

To irnpute ﬁne eﬁ'ect of pollution on well-being (which is not linearly related to increased
material welfare), overall welfare ﬁnerefore takes account of boﬁn changes in ﬁne material well-
being and of healﬁn. For ﬁnis feedback mechanism macro-epidemiological data are enployed
ﬁrst show ﬁne effects of pollutants on healﬁn, sick days, and hence labor supply. However, three

oﬁner aspects ﬁnat are not addressed should be mentioned here for completeness sake.

First, ﬁne mecharnisms of economy-environment interaction, such as teclnrnology adoptiorn
and are intrinsically dynamic in nature. A comparative static ﬁ'amework glosses over ﬁnis
aspect.

Second, a focus on ﬁne income elasticity of regulation neglects ﬁne demand side eﬁ'ect
and consumption production patterns of higher income. A high demand elasticity for clearn
product would have an impact on a country’s econorrnic composition and reinforce ﬁne courntry
transformation. However, many higlnly income elastic products, such as cars, are also pollutiorn
intensive. The analysis furﬁner below will however be based on a unitary income elasticity.

Third,evenifﬁneanalysis showsﬁnatcountrytransfonnationhypoﬁnesis holdsinagroup
of countries that liberalize their trade, it cannot be excluded ﬁnat pollution in ﬁnird courntries
irncreases. As ﬁne country wiﬁn ﬁne previously lax regulation level improves its enforcennent, ﬁne
vey polluting industry might simply move on to oﬁner places to satisfy ﬁne large overall

denand

Next, a nnore detailed techrnical descriptiorn of ﬁne equatiorns will be given.

106

3.3. Model Equations: Technical Specification

In ﬁnis sectiorn, a nnore detailed and complete description is given of ﬁne structure of
ETERNA The calibration process and ﬁne data used for ﬁne numerical speciﬁcatiorn of ﬁne

modelwillbedescribed furﬁnerinsection 3.

The description of ﬁne model equations observes ﬁne following notational conventions.
Ouantities are capitalized (e. g. H) for domestic production); prices are in lower case letters
(e.g. pxd for ﬁne price of domestic output); parameters are denoted inn Greek letters (e.g. afor
an elasticity) or spelled out completely (e. g. scale for ﬁne ecornomies of scale parameter). To
avoid notational clutter, country indexes are generally omitted, except where ﬁney are necessary

to describe bilateral relationslnips.
Irndices used in ﬁne description are

production sectors (subscript)
countries (subscript) ,
foreign countries (subscript)
world (subscript)

net of taxes (superscript)
gross of taxes (superscript).

magma-w

3.3.1. Production
A diﬁcult problem for CGE models is to specify ﬁne production function. Like nnost

models, ETERNA assumes a functional forrn wiﬁn convenient maﬁnematical properties, irn
particular constant elasticities of substitution. As described in ﬁne introductory secticrn, in each
country, production technology in ﬁne 26 sectors follows a nested structure. In all irndustries, a
ﬁxed-coeﬁcient matrix (Leontief fnmction) is used in ﬁne top nest for intermediate values and
ﬁne value-added composite. The relationship ﬁxes ﬁne relative proportions of ﬁne irnputs. For
total output, however, ETERNA allows for scale ecornonnies, as outlined in ﬁne following
equation:

107

“hi
3.1 m, =[min(2ionj,VA,)]
I

where

XI); = domestic production of good i,

ioij = intermediate input parameter of good Xj into production of good i,
VA: = value added for production of good, and

scale: = elasticity expressing econonnies of scale associated wiﬁn sector i.

In ﬁne second nest, value added is produced in a constant-elasticity-of-substitution (CES)
production function, using labor and a capital-environmental sink composite.

'l

3-2 VAt = CES(KSi nit): (pi[ﬂtKIJi—'J";l +(1— ﬂiyi'i—lljn-lv

 

where

KP: = production capital,

Li = labor used in production sector i,

4); = scaling parameter,

,6: = share parameter, and

or = elasticity of substitution between labor and capital-sink composite.

The ﬁnird nest is deﬁned as a ﬁxed-coefﬁcient relationship between ﬁne use of direcﬁy
productive capital in ﬁne sector and ﬁne environmental sink fnmction. The rationale for ﬁnis
ﬁmction is ﬁnat every production process not only consumes material irnputs but also produces
undesired byproducts ﬁnat need to be removed from ﬁne production process by a sink.
Technically, ﬁnis is a production output. Maﬁnematically, however, ﬁnis component to ﬁne

production function can be deﬁned as an input.
3.3 S , = 5, VA,
where

108

S5 = sink function, and
5': = proportionality parameter.

The sink again is a combination of two factors. The sink furnction can be fulﬁlled eiﬁner
by ernnitting ﬁne by-products of ﬁne production process direcﬁy into ﬁne environment, or by
installing abatement equipment (e.g., scrubbers). The sink follows a constant elasticity

ftmction:
3.4 S, = 21,164,;
where

A1 = emission of air pollutants
1011' = pollution abatement capital employed in sector i
4' = positive parameter between 0 and l.

Abatement expenditure ﬁnerefore yields decreasing returrns to scale. An increase in

abatement expenditures by 1 percent leads to a reduction in emissions by 4 percent

The total capital employed in production can be deﬁned as ﬁne sum of its components,

productive and abatement capital:

3.5 KT, =KA, +KP,

The usual proﬁt maximizing conditiorns apply. At each production level, ﬁnerefore, ﬁne
costs of ﬁne inputs equal ﬁne value of ﬁne outputs, which translates into ﬁne followirng two
demarnd fnmctions for labor and capital:

‘r

3.6 L, = -1—[p[(L"l-6-?—':]H + (1 e my" VA,

 

lot

109

'r

I-"

_ 1 ﬂax H
3.7 KT, -;[(1- 4W] +(1- 5)] VA,

In equilibriunn, proﬁts will be zero. At ﬁle top nest of ﬁne production furnctiorn, ﬁnerefore,

3.8 pxd,”)ﬂ), = 2pr101. +wL, +r‘KI}
1'
where

= gross price for intermediate inputs (a composite of domestic productiorn
and imports);
= wage rate; and
r3 = gross return on capital.

P14” = net price of domestic production in sector i;
mi
w

It slnouldbenotedhereﬁnatﬁne production input ofemissionsdoesnotappearinﬁne
equaﬁatbecauseitisaﬁeegoodﬁnatcanbeusedbyﬁneﬁnnwiﬁnoutcharge.Howeve,as
will be explained later, ﬁne use of the environmental resources is not unlimited For value

added, analogously, ﬁne formula can be derived:

3.9 pvafVA, = wL, +r‘KT,

3.3.2. Households
Households are assumed to have homoﬁnetic utility furnctions and are ﬁnerefore modeled

as a single representative agent The consumer’s decision problem is simpliﬁed in ﬁlis model
due to ﬁne absence of intertenporal decisiorns. No saving takes place. All ﬁne consumer’s
irncome is spent. Total welfare results ﬁom two components, namely material well-being, arnd a
parameter reﬂecting ﬁne healﬁn of ﬁne population. Neiﬁner leisure nor savirng enter ﬁne consumer

welfare directly, as is often assumed in CGE models. This simpliﬁcation has some irrnplicatiorns

110

for ﬁne factor supply, as will be elaborated below. The relationship assumed here between

healﬁn and material welfare is of a simple multiplicative nature.

 

3.10 T OTU = MATU(
BASEHEALTH

HEALTH J“

where

TOTU = total welfare of representative agent;

MATU = well-being due to consumption and leisure;

HEALTH = healﬁn of ﬁne population due to ﬁne quality of ﬁne environment;
BASEHEALTH = base healﬁn of ﬁne population due to ﬁne quality of ﬁne environment; and
Ir = valuation of healﬁn.

This relationship means ﬁnat ﬁne valuation of healﬁn increases wiﬁn ﬁne general welfare of
ﬁne population. The demand elasticity of healﬁn wiﬁn respect to total welfare is one. In principle,
ﬁne ﬁmctiornal form could be chosen such ﬁnat it contains a lnigher elasticity. The simple form
has been chosen here for ﬁnree reasons. First, ﬁne expected changes in total welfare are not
enough to make a major diﬂ'erence between a linear or non-linear ﬁmctional form Secondly,
and more important, healﬁn is a multifaceted concept, ﬁnat is represented here irn a simple linear
relationship, namely, ﬁne number of days an average citizen is not ill. At an aggregated level,
ﬁne data situation is not adequate to justify choosing a more complicated fnmctional form
Thirdly, in ETERNA, healﬁn cannot be chosen direcﬁy by ﬁne agent. Tlnis restriction means ﬁnat
total welfare is only a reporting variable, raﬁner ﬁnan a decision variable. Therefore, even wiﬁn a

diﬂ'erent functional fornn, ﬁne equilibrium outcome of ﬁne model would not change.

The valuation parameter 1: allows a calibration of ﬁne welfare function ﬁnat provides
direcﬁy ﬁne monetary equivalent of any change in ﬁne healﬁn of ﬁne population. Henlﬁn is

affected by ﬁne total pollution output of ﬁne country’s economy.

111

3.11 HEALIH=I—qZA,
l

where
17 = positive pMeter.

In oﬁner words, healﬁn decreases as pollution increases, and it does so in a linear fashion.
ETERNA assumes ﬁnat ﬁnis relationship is not affected by sector speciﬁc increases in
expenditures, irn particular in healﬁn care (which is not contained in ﬁne model as a sector), ﬁnat
might mitigate ﬁne impact pollution has on healﬁn It is, however, possible to irnterpret Equation
3.10 to include implicitly ﬁne welfare-decreasing aspect of increased healﬁn-care expenditures.
Furﬁnermore, equation 3.11 implies ﬁnat ﬁnere are no cross-country pollution eﬂ‘ects. All

pollution is ﬁnerefore assumed to be local.

Consumer behavior is deﬁned as welfare maximization of U, which is deﬁned as

:1 :1. it
3.12 MATU = CES(CONSU, 112150125) = [pcomu . (1 - ¢)LEISURE . J
where

LEISURE = Leisure

CONSU = utility derived ﬁom consumption

w = share paranneter

r = elasticity of substitution between leisure and consumption of goods.

The welfare component due to pure consumption is deﬁned as

t-_I i
3.13 CONSU = CES(Z CONS, ) = [Z a,CONS, . J
where

112

CONS: = consumption of good i,
a: = share parameter, and
p = elasticity of substitution between ﬁne various consumption goods.

Consumers behave as welfare maxinnizers. Consequently, ﬁne demand for cornsumptiorn

goodsis

l
3.14 CONS, = “"INCOW

 

ill-o)

I
p -.
px.‘ Z a; pr.
1'
where

INCOME = national income.

Incorntrasttomarnymodelsofﬁnissort,ﬁnereexistsnodistinctioninwe1fareterms
between private consumption and government consumption. Boﬁn are assumed to contribute
equally to ﬁne welfare of ﬁne representative agent. Consumption is bournd by a budgetary

cornstraint.
3.15 2 px,‘ CONS, = INCOME
Income of ﬁne representative agent itself stems from factor income and public transfers.

3.16 INCOME = w"L +r"KH + 25%, + TRANSFERS,
q

where

101 = domestic capital owned by ﬁne home country
= capital owned by domestic agents in foreign countries
TRANSFERS = government transfers.

113

The factor income is separated into wages as well as capital income. To incorporate
information on cross-country capital ownership, an explicit distinction is nnade here between

capital owned by a country, and capital employed in a country.

3.3.3. Regulation Setting and Supply of Productive and Abatement Capital
The total supply of capital is assumed to be constant. As was touched upon brieﬂy when

discussing ﬁne welfare ﬁmction, saving is not part of ﬁne utility function. Capital formation is
ﬁnerefore not endogenous to ETERNA, but is assumed to be ﬁxed Capital can be used eiﬁner
direcﬁy for production or can be used for abatement. It is assumed to be connpletely mobile
between sectors. At least in ﬁne base model, however, it is not mobile between conmtries. The

pre-existing cross-country capital ownership patterns persist

3.17 Z(KA,+KP,)=K

1
where

K=totalcapitalinﬁneeconomy.

Total capital'is owned eiﬁner by domestic agents or foreigners:

3.18 2K1 +KH =K
4

where
K.q = capital owned by foreigners in ﬁne domestic country

In principle, ﬁne supply of pollution is unlimited, wiﬁn no direct constraint applying to it
However, two components limit its use. The ﬁrst one was already elaborated upon in ﬁne

production ﬁmction in equations 3.3 and 3.4. These two equatiorns ouﬁine ﬁnat ﬁne total demand

114

for ﬁne sink furnctiorn is related to ﬁne capital intensity of production. Furﬁnermore, ﬁnere is a
substitution relationship between pollution and ﬁne amount of capital spent on abatement
Without imposing any costs on ﬁne environment or constraining its use oﬁnerwise, pollutiorn
would be driven to inﬁnity. Therefore, ﬁne model needs a mechanism to limit its usage. In
. practice, in most cases, environmental pollution is limited via regulation that prescribes the use
of certain pollution abatement equipment. More rarely is its use limited via a price mechanism.
Whichever of ﬁne two meﬁnods is applied, in maﬁnematical terms ﬁne result can be expressed irn
terms of a tax equivalent ﬁnat leads to an identical allocation of abatement and productive
capital. In parallel to ﬁne discussions in earlier chapters, ﬁne allowed pollution intensity is seen
as a fnmctien of the material well-being of ﬁne country. Therefore ﬁne use of abatement capital is

determined by ﬁne following equation

 

3.19 KA‘ = KAO‘ MATU‘
KTi KTOi

where

K210, = abatement capital in base case,

KTO, = total capital in base case, and

s = positive number (income elasticity of regulatory stringency as a fnrrnction of
per capital utility).

This relationslnip could also be interpreted as an implicit tax on ﬁne productive capital ﬁnat
is used for ﬁne abatement of ﬁne environmental pollution. The institutional arrangement is sucln
ﬁnat ﬁne government does not attempt to equalize ﬁne marginal abatement costs across sectors,
but changes ﬁne stringency of regulation across ﬁne board. This unequal regulating of various

sectors may be ﬁne result of limited information on side of ﬁne government or political pressure.

115

3.3.4. Labor Supply
Labor input to ﬁne individual sectors is limited by ﬁne overall supply of labor in ﬁne

economy.

in ZL=L
i

This equation means ﬁnat ETERNA employs ﬁne full-employment assumption All
unemployment in ﬁne model is ﬁnerefore voluntary. The supply of labor is derived from utility

maximization ﬁnat derives ﬁne demand for leisure. If we take ﬁne total endowment wiﬁn time as:

3.21 7M=LABOR+LEISURE

3.22 LEISURE: '. (1—¢)n:MTU -
w" (0—31))“ +pmatu’")

where
pmam = marginal utility of income

F urﬁnerrnore, labor supply increases wiﬁn ﬁne real wage rate ﬁnat is reﬂected irn ﬁne

parenﬁnesis of ﬁne equation pmatu denotes ﬁne true cost of living index, and is deﬁned as

I

3.23 pmatu = (Z a,PX,"' J H

LABOR is to be understood here as ﬁne time spent working. Its productivity is assumed
to be also a fnmction of ﬁne healﬁn of ﬁne population, according to ﬁne following functiornal form:

3.24 L = LABOUR- HEALTH

It is ﬁnerefore assumed ﬁnat ﬁne healﬁn of ﬁne population has an effect not ornly on ﬁne well-

being, but also direcﬁy on ﬁne productivity of its labor.

116

3.3.5. Trade
Final consumptiorn, exports, and intermediate inputs are a composite of domestic arnd

imported products. Maﬁnematically, ﬁnis ﬁne composite good is be described as an Armington
aggregation, which means ﬁnat a CBS function combirnes imports and domestic productiorn:

J

t.-. a: 7537
3.25 x,=CES(.m,,zM,,)= p,.rD,T+z,.,,M,,‘t]
9 9

where

Xi = Armington composite of good i in country k,

Miq = Imports of good i into country k from country q,
A = shift parameter,

pi = shares of domestic production,

pig, = share of irnnports, and

(5' = elasticity of substitution.

An Armington flmction is chosen because, oﬁnerwise, ﬁne model may provide ﬁne
unrealistic result ofa complete production concentration of a certain sector in just one courntry.
The derivation of ﬁne Armington aggregate can be treated completely analogous to ﬁne CES
production functions described above. Demand for domestic production arnd imports,

respectively, can be derived as:

 

ml
3.26 M, =—’- (I—p,, ””p ‘9 8 “1,, X,
’1! Pipxdr' +Znuttpmlk
k
’1
[-6, 7:}:
3.27 XD,=—1-(1-p, Jpri; +p, X,
1'1 ztuigpmtq

117

Zero-proﬁt conditions result similarly in ﬁne following price deﬁnition:

3.28 pxinXi = ZPMiquiq + Mimi ’
q

where

px,” = net price of Armington composite,
pmiqg = gross price of imports ﬁom comntry q, and
pxdi = price of domestically produced goods.

In ﬁne ﬁeld of trade, a set of identities needs to hold for ﬁne bilateral relatiorslnips.
Exports ﬁom country k to country q must equal imports of country q ﬁ'om courntry k

Therefore,
3.29 E,” = Mm,
where

E11“, 8 exports of good i ﬁom country k irnto country q; and
Migk = imports of good i by courntry q from conmtry k.

Equally, export prices of country k must equal net import prices of country q:
3.30 pew = ping,
where

peikq = price of exports of good i from country k into country q, and
pm"iqk = net price of irnnports of good i by country q from country k

The goods supply ﬁom ﬁne rest of ﬁne world is assumed to be perfecﬁy elastic. Sirrnilarly,

ﬁne exchange rates of all countries are ﬁxed in irntemational currency, leading to ﬁne equation:

3.31 pm; = m

118

where
m = exchange rate of domestic currency expressed in terms of intematiornal currency.

On ﬁne oﬁner hand, demand of domestic products by ﬁne rest of ﬁne world follows a

constant elasticity function ﬁnat is driven by ﬁne real export price.

3.32 5,, = E0,,[-pi'—)
Em

where
v = demand elasticity of ﬁne rest of ﬁne world.

The balance of payments of each country is deﬁned as:
3.33 BOP, = 2298.45.14 - PmLMm)+Z(’q"e "We: ).
r q 9

where

BOP]; = balance of payment of country k, and
qu = capital in country q owned by country k.

The ﬁrst component lists ﬁne real trade ﬂows, while ﬁne second component denotes ﬁne
capital balance between ﬁne countries. In equilibrium, ﬁne sum of ﬁne external balances will be

zero.

3.34 ZBOP, =0
k

3.3.6. Taxes and Government

The government fulﬁlls ﬁnree functions. It collects various taxes and duties, it purchases

goods, and redistributes revenues in ﬁne form of transfers to households. Taxes included in

119

ETERNA are value-added taxes, sales taxes, taxes on capital, and labor taxes, resulting in ﬁne

following four equations:

3.35 pm,‘ =pva,"(1+tva,)
3.36 px,‘ =px,"(1+tx,)
3.37 r‘ =r"(1+tk,)

3.38 w‘ =w"(1+tl,)

Imports are subject to ad valorem tariffs, wiﬁn tmiq denoting ﬁne tariﬁ‘ on product type i
from country q. Furﬁner, non-tariﬁ‘ barriers are also taken into account. They are similarly
expressed irn ﬁneir ad valorem equivalents, as miq- Using ﬁnese values, ﬁne prices paid by ﬁne

consume for imports are:
3.39 pm; = pm;(1+tm,q +171”)

The practical diﬁ‘erence between rm and tn is ﬁnat ﬁne revenues generated by on are
recycled back to ﬁne economy as goverrnment consumption (beneﬁting also ﬁne consume). By

corntrast, In is modeled as complete welfare loss due to rent-seeking behavior, following Arnne
Krueger’s argument (Krueger 1974).

3.40 MORT LOSS, = m,,M,,

Government provides a public good according to ﬁne forrnala:

8

s-r —
3.41 PUBGOOD + CES(Z GOVCONS,) = [Zw,GOVC0NS,T)H
i n'

where

120

PUBGOOD = public good,
GOVCONS,‘ = government consumption of good i,

an = share parameter, and
t9. = elasticity of substitution between ﬁne various government
consumptiorn goods.

The provision of ﬁne public good is assumed to stay constant for all scenarios.

 

3.42 PUBGOOD = PUBGOOD

Because of ﬁnis condition, ﬁne supply of ﬁne public good does not enter ﬁne welfare
furnctiorn of households. The tax revenues ﬁnat are not consumed to produce ﬁne public good are

recycled back into ﬁne economy via transfers.

TRANSFERS: ZZthM +Ztva,,VA +Zor,,X
+rkK+tIL+BOP- PUBGOOD

3.43

 

where

BOP = balance of payment in base year

The government transfers include also ﬁne balance of payments in ﬁne base year, which is
assumed to be unchanged. This assumption has implications for ﬁne closure of ﬁne nnodel.
Cornsistent wiﬁn ﬁne assumption of no household saving, ﬁne government deﬁcits are netted out

in ﬁne rrnodel.

3.3.7. Closure
A ﬁnal set of equations is needed in order for Walras's Law to hold In oﬁne words, in

equilibrium, ﬁne system is not allowed to have any excess supplies. Therefore ﬁne supply of ﬁne

Armington aggregate must equal its demand:

3.44 X, = 216,210), + CONS, + GOVCONS, + 2E" + MORT LOSS,
r q

121

The supply can be used eiﬁner domestically (as ﬁnal consumption and as intermediate
irnput) or for export This ﬂexibility implies ﬁnat ﬁne system is balanced via trade, or, more

precisely, wiﬁn a ﬁxed balance of payments via ﬁne export prices.

Since all supply and demand functions in ﬁne model are homogenous of degree zero wiﬁn
respect to prices, only relative prices are important for ﬁne determination of quarntities of goocb
supplied and demanded All prices ﬁnerefore need to be deﬂated by a numéraire. In ETERNA,

ﬁnis was chosen to be ﬁne international price level of goods.
3.45 E20? = 1

This ﬁnal equatiorn completes a full description of ﬁne maﬁnematical relatiornships ﬁnat
deﬁne ﬁne model. However, ﬁne behavior of ﬁne model depends crucially on ﬁne parameter
values ﬁnat are used for ﬁne numerical analysis. Chapter 4 will discuss ﬁne data on whicln

ETERNA was calibrated.

122

CHAPTER4

DATA DESCRIPTION AND MODEL CALIBRATION

This chapter describes ﬁne calibration of ﬁne ETERNA model described in Chapter 3. A
ﬁrst part presents ﬁne social accounting matrix employed. It also presents some stylized facts of
ﬁne NAFTA econorrnies. The data presented in ﬁnis part are of little originality and overlap
signiﬁcanﬁy wiﬁn ﬁnose used by Roland-Holst et al (1994).19 These data are suﬁcient for
constructing a standard CGE model. Since ﬁne contribution of ﬁnis paper consists mainly irn
adding an environmental modeling component, ﬁne construction of ﬁne environmental data
needs to be described more extensively in a second part This part also serves to ouﬁine ﬁne

rationale for ﬁnose modeling choices ﬁnat are inherenﬁy data driven.

4.1 Stylized facts of the North American Free Trade Area

4.1.1. Social Accounting Matrix
As ﬁne most important data source, ETERNA uses ﬁne social accounting matrix (SAM)

ﬁnat was compiled by Reinert, Roland-Holst and Shiells (1993). The SAM is a statistical
compilation of ﬁne ﬂow of funds situation for ﬁne ﬁlree NAFTA conmtries. Unless stated

oﬁnerwise, ﬁne discussion below refers to ﬁne data in ﬁnis SAM, which reﬂects ﬁne situatiorn irn

 

”Deviationsﬁ'omtheirapproachhavebeenchosenonly formodelingconvenicnce,anddonot
represent a substantive criticism of ﬁneir paper. However, they are responsible for sornne divergence
in the sectoral composition of the modeling results reported in Chapter 5.

123

1988, which is ﬁne base year for ﬁne arnalysis. The year is chosen because it lies before ﬁne

implementation of CAFT A.

Sinceﬁnennodel followsﬁnecreedﬁnatﬁnebenchmarkdatareﬂectaneconomyin
equilibrium, evey dollar of ﬁne ﬂows of ﬁmds is interpreted as an eﬁciency nmit wiﬁn a price of
1. This interpretatiorn is diﬁ‘eent ﬁom observed physical urnits, but reﬂects various qualiﬁes of
ﬁneinputs.Forinstance, ifﬁne wagesinonesectororornecountryarehigheﬁnarnirnanoﬁner,it
is assumed ﬁnat ﬁnis diﬁ‘erence represents lnighe productivity. Irnpliciﬁy ﬁnis means ﬁnat ﬁnere is
a pefect substitution between 10 workers canning 1 dollar an hour and one worke earning 10

dollars.

The SAM provides infornnation on ﬁne money ﬂows in ﬁne base year for a numbe of
variables, namely domestic production (m), consumption (CONS), input-output relationslnips
(to), imports (M), exports (E), balance of payments (BOP), sectoral (KT) and total proﬁts (K),
cross-country capital ownership (KD and K9), wages (L), and transfes (TRANSFERS).
Furﬁnermore, ﬁne flmds received by ﬁne govennrnernt can be used to derive eﬂ’ective collection
rates for tariffs (rm), sales tax (Ix), value-added tax (tva), and capital (tit) and labor taxatiorn (II).
It should be emphasized here ﬁnat all tax rates in ﬁne model are eﬁ‘ective net rates. This
deﬁnition mearns, on ﬁle one hand, ﬁnat taxes and subsidies to ﬁle same sector are netted out
On ﬁne oﬁner hand, ﬁne rates used here may deviate substantially ﬁonn oﬁcial rates, because ﬁne
government (for one reason or ﬁne oﬁner) does not collect ﬁne amount of rrnoney ﬁnat would
' follow ﬁom simply multiplying oﬁcial rates wiﬁn ﬁne quantities reported This adjustment is
particularly important in ﬁne case of tariﬁ‘s, where, due to exemptions, ﬁne eﬁ‘ective collection

rates are often substantially below ﬁne omcial tariﬁ‘ rates.

124

m 'v A
A special problem for ﬁne CGE model is ﬁnat ﬁne SAM reports a loss for ﬁne United
States automotive sector in 1988. The standard meﬁnodology ﬁnat equalizes capital endowment
wiﬁn proﬁts would produce ﬁne meaningless result ﬁnat ﬁne capital endowment in ﬁne sector is
negative. In its place, we have taken ﬁne average proﬁt rate in ﬁne sector for ﬁne next 5 years
(1989-1993), which is 5.7 percent of turnover. This value for proﬁtability has been multiplied

by ﬁne sectoral turnover. The difference is carried along in ﬁne model in form of a constant
W
A sectoral disaggregation of ﬁne government consumption (i.e., of ﬁnose government
revenues ﬁnat are not used for transfers) is not available ﬁom ﬁne SAM They had to be taken
from anoﬁner source. The sectoral breakdown of government consumption shares is taken ﬁom
Ballard et al.(1985) and applied ﬁne 26 sectors of ﬁne SAM. These values are listed in Table 4-

1. Since a similar sectoral breakdown was difﬁcult to obtain for Mexico and Cenada, ﬁne same

government consumption shares were used for ﬁnese countries.

125

Table 4-1. Disaggregation of government consumption shares

 

 

Sector Percent of Sector Pecent of
' Government Government
Consumption Consumption

Agriculture 0.36 Iron and Steel 0.01
Mining 0.10 Non-Ferrous Metals 0.01
Petroleum 3.63 Wood & Metals 0.64
Food Processing 1.26 Non-Electr. Machines 2.30
Beverages 0.25 Electrical Machines 6.33
Tobacco 0.14 Transport Equipment 13.45
Textiles 0.09 Oﬁner Manufactures 2.42
Wearing Apparel 0.39 Construction 27.96
Leaﬁne 0.08 Electricity 4.18
Paper 2.76 Commerce 3.04
Chenicals 2.10 Transport & Commurn. 4.89
Rubber 0.73 Finance & Insurance 1.97
Non-Metal Minerals 0.05 Oﬁner Services 20.85

 

4.1.2. Asymmetric Structure of NAFTA
The United States’ economy clearly dominates ﬁne Norﬁn Americarn Free Trade

Agreement. In 1988 ﬁne U.S. economy had a GDP of 4504 bn U.S. dollar. Those of Canada
and Mexico were 438 and 163 bn U.S. dollars, respectively. These ﬁgures mean ﬁnat ﬁne GDP
of ﬁne USA makes up over 88 percent of ﬁne total NAFTA econonnies, while ﬁnat of Canada is

8.6 percent. Mexico’s economy is only 3.2 percent of ﬁne total NAFTA economy.

The U.S. also dominates ﬁne trade of ﬁne area Between 50 and 60 percent of Canadian
and Mexican exports and imports are directed at ﬁne United States. By contrast, ﬁnese two
conmtries combined absorb only 20 percent of ﬁne U.S. trade. Table 4-2 shows ﬁnat trade
between Mexico arnd Carnada is small. These ﬁgures even underestimate ﬁne one-sidedness of
ﬁne trade depmdency, because barer 5 percent of ﬁne U.S. production is exported This share

is much higher for ﬁne oﬁner two countries, wiﬁn 12 percent for Mexico, respectively 15 percent

126

for Canada Unsurprisingly, ﬁnerefore NAFTA will aﬁ'ect ﬁne USA less ﬁnarn ﬁne oﬁne two

countries in relative, ﬁnough not in absolute terms.

Table 4-2: Trade in billion U.S. dollars (1988)

 

 

Importers
Exporters USA Mexico Canada World
USA - 16.840 69.802 340.262
Mexico 19.730 - 1.078 15.053
Canada 79.172 0.397 - 49.359
World 434.741 14.668 54.350 -

 

4.1.3. Differences in Economic Development of NAFTA States

W

Mexico’s economic development lags substantially belnind that of the two northern
members of NAFTA In ﬁne base year 1988, Mexico’s pe capita income is a nnere $2,000,
while ﬁnat of ﬁne Canada and ﬁne USA are 316,500 and $18,000, respectively. However,
Mexico looks nnore prosperous, when GDP is calculated based on purchasing power parity.
Summers and Heston (1991) list 1988 per capita GDP of $19,851 (USA), $17,681 (Canada),

and $5,323 (Mexico).

The income distribution is Mexico is more unequal ﬁnan in ﬁne oﬁner two courntries. The
wealﬁniest 10 % of ﬁne population in Mexico control about 40 % of ﬁne income, while ﬁne
equivalent ﬁgure for Canada and ﬁne U.S. is 25%. The aspect of income inequality is certainly
innportant in explaining ﬁne political mecharnism of regulation setting. Howeve, inﬂuence of
income inequality on ﬁne simulation results cannot be arnalyzed wiﬁn ﬁne ETERNA nnodelirng

tool, which employs ﬁne assumption of a representative consumer.

127

Wit
Naturally, ﬁne diﬁ'erent levels of development are also reﬂected irn ﬁne ecornonnic structure
of ﬁne countries. Tables 3a-c break down ﬁne ﬁnree Norﬁn American ecornorrnies into 26

SOCTOI'S.20

Compared to ﬁne developed NAFTA countries, Mexico has a fairly high share of primary
sectors. The combined share of agriculture, mining, and petroleum productiorn is nearly 18
percent of is output, while ﬁneir values for ﬁne USA and Canada are only 5, respectively 8
percent By contrast, ﬁne norﬁnem countries have a more developed tertiary sector. Trarnsport,
commece, ﬁnancial, insurance, and oﬁner services combine to about a ﬁnird of ﬁne U.S. and
Carnadian econonnies. Their importance for Mexico is less ﬁnan one fourﬁn These facs rouglnly

match ﬁne standard patterns observed in developed and developirng nations.

However, ﬁne interpretation of ﬁne statistical information ﬁnerefore requires some caution
First, every sector is an aggregation of ﬁrms of various sizes and trades. These are treated as
homogeneous alﬁnough ﬁney do not necessarily react ﬁne same way to ecornonnic policies.
Second, and more problematic may be ﬁne application of ﬁne same sectoral deﬁnitiorn across
courntries wiﬁn a diﬂ‘erent state of development, such as Mexico on ﬁne one hand, and Carnada
arnd ﬁne USA on ﬁne oﬁner. This deﬁnition will be discussed in more detail for ﬁne calculatiorn of

errnissions factors in Secﬁon 4.2.

The greate dependence on expors of Canada and Mexico ﬁnan for ﬁne U.S. was already

mentioned Sectoral ﬁgures for ﬁne U.S. export shares never exceed 20 percent while in the

128

oﬁne two countries, up to 70 percent of a sector can go to foreign markes, mainly ﬁne USA
One can distinguish to some extent ﬁne inﬂuence of natural endowmens-on ﬁne natiornal
ecornomy and consequently ﬁneir exports. For instance, sparsely populated Canada is rrnore
intensive ﬁnan ﬁne USA in ﬁne production of primary goods. More extreme is ﬁne situation in
Mexico. Petroleum constitutes over 40 percent of Mexico’s expors. This trade gives ﬁnis
sector a level in importance ﬁnat is well in excess of what is share in total GDP would suggest
The dependency on a single product group is anoﬁner characteristic ﬁnat Mexico has irn common

wiﬁn many developing countries.

However, even before ﬁne implementation of ﬁne NAFTA treaty, Mexico was moving to
a nnore diversiﬁed export base. In particular, ﬁne large export and irrnport ﬁgures for transport
equipment arnd machinery hint at ﬁne great importance of ﬁne maqur’ladora industry.
Maquiladoras are export-processing zones located along ﬁne Mexican side of ﬁne US-Mexican
border. In ﬁnese zones, companies enjoy exemptions ﬁom duties on impors innto Mexico when
ﬁney re-export ﬁne producs back to ﬁne United States (Hufoauer and Schott 1992). However,
ﬁne relative importance of ﬁne special zones is likely to decrease, because ﬁne NAFTA treaty

reduces tariffs for all of Mexico.

 

3° Government services are not listed separately, but are integrated into ﬁne sectors.

129

Table 4-3a: Key sectoral data for the United States

 

 

Sector Produc- Value Denand Exports Imports Export Import
tion (%) Added (%) (%) (%) share (%) share (%)
(%)

Agriculture 2.4 2.0 2.2 5.1 1.4 10.6 4.2
Mining 0.3 0.4 0.3 1.2 0.4 19.6 10.2
Petroleum 2.4 1.8 2.8 2.5 8.0 5.2 18.3
Food Processing 3.5 1.6 3.4 3.0 2.3 4.2 4.2
Beverages 0.6 0.2 0.6 0.1 0.7 1.1 7.2
Tobacco 0.4 0.3 0.4 0.7 0.1 9.0 2.4
Textiles 1.0 0.7 1.0 0.8 1.3 3.9 7.6
Wearing Apparel 0.7 0.4 1.0 0.3 5.0 1.9 30.9
Leather 0.1 0.1 0.2 0.1 2.1 6.8 58.6
Paper 2.5 1.8 2.5 2.8 2.5 5.7 6.4
Chenicals 2.4 1.5 2.2 7.7 3.4 16.2 10.0
Rubber 1.5 1.0 1.4 4.4 2.3 15.0 10.7
Non-Metal Minerals 0.8 0.7 0.8 0.6 1.3 3.7 10.1
Iron and Steel 0.9 0.4 0.9 3.2 2.5 18.5 18.5
Non-Ferrous Metals 0.8 0.4 0.9 0.6 1.8 3.8 12.8
Wood & Metals 3.2 2.5 3.2 3.4 4.3 5.4 8.4
Non-Electr. Machines 1.9 1.3 1.9 6.3 6.0 16.8 19.9
Electrical Machines 3.4 2.7 3.8 10.3 15.0 15.0 24.8
Transport Equiprrnent 3.7 2.4 4.0 16.1 17.2 21.6 27.5
Oﬁner Manufactures 1.1 0.9 1.3 2.3 6.2. 10.7 29.1
Construction 7.0 5.1 6.9 0.0 0.0 0.0 0.0
Electricity 3.3 3.5 3.8 0.1 8.5 0.2 14.0
Commerce 11.7 12.7 11.0 10.0 0.0 4.3 0.0

Transport & Cornmun. 4.8 5.9 4.8 5.9 5.1 6.1 6.8
Finance & Insurance 14.3 16.3 14.0 5.8 2.1 2.0 1.0
Oﬁne Services 25.3 33.5 24.7 6.4 0.4 1.3 0.1
Total 100.0 100.0 100.0 100.0 100.0 5.0 6.3

130

Table 4-3b: Key Sectoral Data for Mexico

 

 

Sectors Produc- Value Denand Exports Imports Export Import
tion (%) Added (%) (%) (%) share (%) share (%)
(%)

Agiculture 7.9 7.9 8.5 3.7 8.4 5.8 11.5
Mining 1.4 1.6 1.1 3.1 1.5 29.1 14.8
Petroleum 8.3 3.4 3.4 41.5 2.5 63.2 8.8
Food Processing 8.8 5.6 9.1 3.1 5.7 4.4 7.3
We 1.6 1.0 1.6 0.9 0.5 7.3 3.3
Tobacco 0.3 0.1 0.3 0.1 0.0 4.8 0.1
Textiles 1.5 1.2 1.5 0.9 1.5 7.9 11.2
Wearing Apparel 1.3 0.8 1.2 1.6 1.2 15.7 11.3
Leather 0.8 0.7 0.8 0.7 0.7 10.0 9.4
Paper 1.8 1.6 2.1 1.4 4.3 9.9 23.9
Chenicals 3.6 2.4 4.0 4.9 9.1 17.6 26.3
Rubber 1.0 0.8 1.3 1.3 4.2 16.2 36.5
Non-Metal Minerals 1.6 1.9 1.6 0.3 0.7 2.7 5.4
Iron and Steel 1.4 1.1 2.2 1.3 8.0 11.6 42.4
Non-Ferrous Metals 0.8 0.7 0.7 2.2 1.7 36.5 29.2
Wood & Metals 2.5 1.3 2.5 3.7 4.6 19.3 21.0
Non-Electra Machirnes 0.9 1.0 2.6 2.9 17.7 39.5 78.2
Electrical Machines 1.8 1.4 1.4 10.1 7.9 71.5 64.2
Transport Equipment 3.3 2.6 3.6 12.9 16.9 50.2 54.7
Other Manufactures 0.9 0.6 0.8 3.3 3.0 47.6 42.7
Construction 6.7 3.9 6.7 0.0 0.0 0.0 0.0
Electricity 1.2 1.4 1.2 0.0 0.0 0.0 0.0
Commerce 17.4 26.6 17.6 0.0 0.0 0.0 0.0
Transp. &Connmun. 6.1 7.7 6.2 0.0 0.0 0.0 0.0
Finance & Insurance 5.8 7.8 5.9 0.0 0.0 0.0 0.0
Oﬁner Services 11.6 15.1 11.7 0.0 0.0 0.0 0.0
Total 100.0 100.0 100.0 100.0 100.0 12.7 11.6

 

131

Table 4-3c: Key Sectoral Data for the Canada

 

 

Sector Produc- Value Denand Exports Imports Export
tion (%) Added (%) - (%) (%) share (%) share (%)
(%)

Agriculture 3.6 3.4 3.1 5.0 1.4 20.8 7.1
Mining 1.5 2.7 1.5 2.5 2.6 25.7 26.2
Petroleum 3.3 2.0 2.7 7.0 3.1 31.6 16.8
Food Processing 4.1 2.4 4.1 2.3 2.8 8.6 10.2
Beverages 0.7 0.6 0.7 0.4 0.6 8.8 12.7
Tobacco 0.2 0.2 0.2 0.1 0.0 4.3 1.6
Textiles 0.7 0.6 0.9 0.7 2.1 16.2 36.2
Wearing Apparel 0.8 0.7 1.1 0.4 2.0 6.7 27.8
Leather 0.2 0.1 0.3 0.1 1.0 12.8 53.4
Paper 4.1 3.8 2.7 11.7 2.4 42.6 13.3
Chennieals 1.9 1.9 2.6 0.7 4.9 5.2 28.3
Rubber 0.8 0.8 0.9 1.3 2.0 22.6 31.1
Non-Metal Minerals 0.8 0.8 0.9 0.9 1.2 15.8 21.5
Iron and Steel 1.2 1.0 1.3 1.5 1.7 18.6 20.0
Non-Ferrous Metals 1.0 1.0 0.9 2.8 1.8 40.4 30.8
Wood & Metals 3.9 3.4 3.5 7.5 4.5 28.3 19.3
Non-Electr. Machines 1.8 1.0 2.7 5.8 12.0 49.4 66.9
Electrical Machirnes 2.0 1.7 2.5 4.1 7.9 31.1 46.8
Transport Equipment 6.7 3.1 5.9 30.3 24.9 67.8 63.4
Other Manufactures 1.0 0.7 1.3 2.2 4.6 34.2 52.0
Construction 10.5 8.6 10.5 0.0 0.0 0.0 0.0
Electricity 2.2 3.6 2.1 0.5 0.1 3.7 0.6
Cornrrnerce 12.8 17.9 12.5 3.2 0.9 3.7 1.0
Transp. & Cornmun. 7.6 8.0 7.1 5.6 2.2 10.9 4.6
Finance & Insurance 8.4 10.2 9.1 0.8 5.4 1.5 9.0
Other Services 18.2 19.8 19.0 2.7 7.8 2.2 6.1
Total 100.0 100.0 100.0 100.0 100.0 15.0 15.0

 

132

I l . .

Table 4-4 shows ﬁne capital to labor ratios of ﬁne various sectors. The values are
calculated ﬁorn ﬁne factor rewards, where capital is deﬁned as ﬁne sum of proﬁs arnd irnterest
payments, and labor denotes ﬁne gross wage bill. It is remarkable ﬁnat ﬁne ratio of capital to
labor irnpus in ﬁne economy is ﬁve times higher for Mexico ﬁnan for ﬁne USA and Canada (ﬁrst
ﬁnree columns of ﬁne Table 4-4). This value appears to be in stark contrast to ﬁne common
peception of Mexico as being labor-abundant and ﬁne USA and Canada as being capital
abundant However, ﬁne capital-labor ratios reﬂect degrees of eﬁciency in ﬁne two econonnies.
The capital-labor ratio in ﬁne U.S. is lower ﬁnan ﬁnat of Mexico because American wages are
higlner ﬁnarn Mexicarn wages reﬂecting higher U.S. labor productivity. Considering ﬁnis aspect of
labor eﬁciency, ﬁne United States and Canada end up being actually more labor-abundant ﬁnan
Mexico, alﬁnough one unit of production requires a larger number of hours worked in Mexico

ﬁnarn irn ﬁne oﬁne two countries.

Barring large differences in ﬁne elasticity of substitution between labor and capital, one
would expect ﬁnat across countries ﬁne capital-labor ratios of ﬁne individual sectors would vary
nnore or less in parallel. To analyze ﬁnis aspect, ﬁne last ﬁnree columns of ﬁle table present ﬁne
ratios of ﬁne ﬁrst ﬁnree columns nonnalized by dividing ﬁnem by ﬁne average capital-labor ratio.
Clearly, ﬁne diﬁ’erence between Mexico and ﬁne oﬁner two states is decreased. Even so, ﬁne U.S.
and Canada remain more similar in ﬁle relative labor-capital abundance of ﬁneir input structure

ﬁnan Mexico wiﬁn eiﬁner of ﬁne two.

A part of ﬁne variation in ﬁne labor-capital intensities is likely to be a statistical artifact.
Among countries ﬁnee are diﬁ'erences in ﬁne composition of production wiﬁnin ﬁne irndividual

sectors is likely to vary systematically among courntries. Furﬁnermore, ﬁne statistical deﬁrnitiorn

133

of ﬁne sectors nnight be artiﬁcially inﬂuenced by ﬁne industrial organizaﬁon of a sector. If a
company out-sources part of is activities, ﬁney will be registered as production of ﬁne sector in
which ﬁne supplier is categorized. Anoﬁner explanation lies in actual teclnrnological diﬁ‘erences.
These will be more prevalent between Mexico and ﬁne oﬁner two countries ﬁnan between
Canada and ﬁne US. Furﬁnennore, ﬁne interpretation of Mexico as labor-scarce is a
simpliﬁcation Mexico is probably scarce in skilled workers, while ﬁnere is no lack of unskilled
labor. The productivity of unskilled labor is, however, highly dependent on ﬁne existence of a
trained middle marnagement to put ﬁnem to ﬁneir best use. The degree to which ﬁne lack of
highly skilled labor aﬁ‘ecs productivity will be diﬁ‘erent across sectors. For irnstance, ﬁne
production of electricity is likely to have little use of unskilled workers, which would explain
ﬁnat ﬁneir production structure is nearly ﬁne same everywhere. By contrast, in ﬁne sectors whee
one would most likely suspect sweashop conditions, ﬁne diffeences in labor intensity are ﬁne
higlnest, e.g. for textiles, apparel and leaﬁner, arnd also in food processirng and certain
rrnanufacturing sectors. It is ﬁnese sectoral differences in input intensities across courntries ﬁnat

are important in explaining why sectors react diﬁ‘erently to changes in ﬁne trade regime.

134

Table 4-4

 

Table 44. Sectoral capital-labor ratios

 

 

Sector Ratio of Capital to Labor shares Ratio of Capital to Labor shares
(absolute values) (Country averages = 1)
USA Mexico Canada USA Mexico Canada
Agriculture 1.4 4.1 1.5 2.3 1.3 2.4
Mirnirng 0.4 2.1 0.9 0.7 0.7 1.4
Petroleum 2.8 7.6 1.3 4.6 2.5 2.1
Food Processirng 0.6 5.0 0.5 1.0 1.6 0.7
Beverages 0.5 3.1 0.7 0.9 1.0 1.1
Tobacco 1.9 3.0 1.2 3.1 1.0 1.9
Textiles 0.3 2.2 0.3 0.4 0.7 0.5
Wearing Apparel 0.2 2.7 0.2 0.4 0.9 0.3
Leaﬁner 0.6 1.8 0.1 0.9 0.6 0.2
Paper 0.4 3.4 0.5 0.6 1.1 0.7
Chenicals 0.7 3.3 0.8 1.2 1.0 1.3
Rubber 0.3 2.5 0.2 0.5 0.8 0.3
Non-Metal Minerals 0.3 3.7 0.5 0.4 1.2 0.8
Iron and Steel 0.1 2.5 0.3 0.1 0.8 0.4
Non-Ferrous Metals 0.2 3.4 0.7 0.3 1.1 1.0
Wood & Metals 0.2 2.8 0.2 0.3 0.9 0.3
Non-Elect. Machines 0.2 2.3 0.3 0.4 0.7 0.5
Electrical Machines 0.2 1.9 0.3 0.4 0.6 0.5
Transport Equipment 0.1 2.3 0.3 0.2 0.7 0.4
Other Manufactures 0.5 4.1 0.2 0.8 1.3 0.4
Construction 0.1 0.5 0.2 0.2 0.2 0.4
Electricity 1.8 1.9 2.0 3.1 0.6 3.1
Commerce 0.3 4.0 0.2 0.5 1.3 0.4
Transp. & Commun 0.4 2.4 0.4 0.7 0.8 0.7
Finance & Insurance 1.8 3.3 0.5 3.0 1.0 0.8
Oﬁner Services 0.2 0.8 1.1 0.4 0.3 1.8
AVERAGE 0.6 3.1 0.6 1.0 1.0 1.0

 

135

.4
£32
(I)

\ _

the taxes in
instance, gr
businesses
and capital
indirect tax

Fir
United St:
govcmma
i“Stance t
°V€fWhelr

Schott 19.

13.5mm

Mexico is also set apart by ﬁne structure of its taxes. Table 4-5 lists ﬁne composition of
ﬁne taxes in a simpliﬁed structure that is also adopted in ﬁne general equilibrium model. For
irnstarnce, government subsidies to enterprises are netted out; property taxes and taxes on
businesses are treated as taxes on capital; taxes on households are allocated to taxes on labor
and capital; government transfers reduce ﬁne labor taxes; sales and “sin” taxes are listed as

irndirect taxes. Neverﬁneless, ﬁne stylized structure of ﬁne tax is in some aspects quite revealing.

First, ﬁne effective tax collection of Mexico is only half of ﬁnat of Canada and the
United States. However, ﬁnis tax collection rate does not necessarily mean ﬁnat ﬁne Mexican
government has a comparatively lesser inﬂuence on its economy than ﬁne other countries. For,
imtance ﬁne government still controls PEMEX, ﬁne petrol monopoly, which has such an
overwhelming importance on Mexico’s exports and, hence, ﬁne overall economy (Hufoauer and

Schott 1992 ). However, ﬁnis control does not show in ﬁne tax statistics.

Second, while ﬁne most important taxes are labor-related for ﬁne United States arnd
Canada, ﬁnis share is raﬁner small for Mexico. Instead, ﬁne country relies primarily on indirect
taxation and value added taxation. It is likely ﬁnat ﬁnese shares are simply ﬁne result of greater

ease in collecting ﬁnenn, raﬁner ﬁnan a strategic choice on part of ﬁne Mexican government.

136

Table 4-5.

 

Taxes

Capital in:
Indirect ta
Value add
Duties
Effective t:
collection
Note: Figt
taxes, etc.

 

4.1.4. Tra

Table 4-5. Structure of tax collection in the NAFTA countries

 

 

USA Mexico Canada

Taxes bn S % of taxes bn S % of taxes bn S % of taxes
Labor tax 800 51.2 5 19.0 64 41.8
Capital tax 369 23.6 7 25.1 35 23.3
Indirect tax 376 24.1 9 31.9 49 32.2
Value added tax 0 0.0 6 21.3 0 0.0
Duties 16 1.1 1 2.9 4 2.4
Eﬁective tax 1562 34.7% 28 17.2% 153 34.8%
collectiorn of GDP of GDP of GDP

 

Note: Figures are net of subsidies and consolidated, e. g., excises are integrated irnto indirect
taxes, etc.

4.1.4. Trade Protection before NAFTA
Mate:

The eﬁ‘ect of ﬁne trade liberalization implied by NAFTA depends crucially on ﬁne pre-
existing trade barrier. Table 4-6 lists ﬁne tariff levels (variable In: of ﬁne model) of ﬁne ﬁnree
NAFTA members applied in 1988. The numbers in the table do not report omcial tariﬂ‘ rates
but effective collection tariﬂ‘ rates. Maﬁnematically ﬁnis is ﬁne value of customs revenues
divided by ﬁne value of imports. There are some marked diﬁ‘erences among ﬁne sectors. Tariff
collection rates are high for textile and apparel imports in Canada and ﬁne US, but for other
sectors no simple system emerges ﬁnat explains ﬁne various levels of tariﬁ' collection. Overall,
ﬁne eﬁ'ective tariﬁ‘ collection in all ﬁnree countries is surprisingly low, being on average between
1 and 5 percent among ﬁne ﬁnree NAFTA partners. Reasons are, ﬁrst, ﬁnat large arnournts of
imports ﬁnat are not covered by tariffs, for instance ﬁne maqur’ladora industry. Second, ﬁne
collection rates are likely to under-report ﬁne actual protection ﬁnese tariﬂ‘s exert: ﬁne average
rate is not identical wiﬁn ﬁne marginal tariﬁ‘ rate. In ﬁne extreme case, a tariﬁ‘ may be so high
that it is prohibitive for any trade. This extreme would result in an eﬁ‘ective tariﬂ‘ collection of

zero, which might give ﬁne false impressiOn ﬁnat ﬁnere is no trade barrier at all.

137

Table 4—

 

 

Rol
barriers,
Paperwor]
(Table 4-7
smom ta
and the Con
"Mel,
the Value
Ofﬁne 1055

Table 4-6: Etfective Tariff Collection of North America (in percent of import value)

 

 

 

USA Mexico Canada
ROW Can- Mexico ROW USA Can- ROW USA Mexico
ada ada
Agriculture 1 2 6 0 l 0 l l 2
Mining 0 O l 0 2 0 0 0 0
Petroleum 1 0 0 l 4 0 0 0 0
Food Processing 4 2 6 l 3 2 4 4 5
Beveages 3 3 2 0 0 0 35 35 35
Tobacco 10 17 8 0 0 0 8 8 0
Textiles 10 6 7 3 2 0 12 12 12
Wearing Apparel 19 9 l6 5 2 O 18 18 20
Leather 9 22 5 0 l 0 l3 l3 0
Paper 1 0 2 2 2 3 4 4 0
Chenicals 5 l7 2 2 3 0 5 5 8
Rubber 6 10 4 4 l 0 7 7 0
Non-Metal Mineals 6 l 0 4 8 0 5 5 8
Iron and Steel 4 3 3 l 4 0 4 4 5
Non-Ferrous Metals l l 0 2 4 O 2 2 0
Wood & Metals 4 l 2 4 3 0 6 6 6
Non-Elect. Mach 3 l l 5 3 5 2 2 2
Electrical Machines 3 2 3 7 l 5 4 4 4
Transport Equip. 3 O 2 l 2 1 7 0 7
Othe' Manufactures 4 l 3 2 10 0 4 4 5
All 5 l 3 3 2 2 7 3 5
1 i - El .

Roland-Holst et al. (1994) provide important supplementary information on non-tariﬁ'
barriers, such as quotas, voluntary export restraints, rules of origirn, and burdensome
paperwork This effective trade protection is trarnslated into an ad valorem tariff equivalent
(Table 4-7). The auﬁnors calculated ﬁne ﬁgures from a composite of three sources: ﬁne observed
sectoral tariﬁ' collection rates in ﬁne SAM; independent sectoral estimates by oﬁner researchers;
and ﬁne combined UNCTAD-GATT database of four-digit SlTC trade control measures. In ﬁne
model, non-tariﬁ‘ barriers (tn), are calculated simply as ﬁne diﬁ‘erences between ﬁne tariffs and
ﬁne value of ﬁne table. A multiplication of ﬁne ﬁgures wiﬁn actual imports allows ﬁne calculatiorn

of ﬁne loss ﬁnrough rent seeking (MORTLOSS).

138

particu

hadﬁne

lowest

complen

apparel.

where it

 

 

Non-tariﬁ‘ barriers in Norﬁn America were quite substantial in 1988. They were
particularly high against Canadian exports. Boﬁn Mexico and ﬁne United States tend to be more
protectionist against Canada ﬁnan against ﬁne rest of ﬁne world or each oﬁner. The United States
had ﬁne highest average import barriers against its neighbors, and Canada maintained ﬁne
lowest Mexico and ﬁne USA were highly protectionist in primary exports.21 Mexico and
Canada focus nnost of ﬁneir protection on agricultural imports. There is also a certain
complementarity at work. Where barriers are high in ﬁne two norﬁnem countries (e. g., textiles,
apparel, and leaﬁner), ﬁney are low in Mexico. Conversely, Mexico applies high trade barriers,
where it is not competitive (e.g., paper). Here ﬁne oﬁner two countries apply low protection

rates.

 

2“Ihereare,lnoweveranumberofzerost‘orMexicanbarrier'sagainstCanada.However,thismay
beeithcrastatisticalartifacteithcrbecauselowtradevolumesﬁnatdonotallowforbctter
estimates,orthattheMexicangovemmentdidnotneedtoboﬁnertoimpedethealreadysmalltrade
ﬂowsbetweenthetwocountnies.

139

Table 4—7

 

 

Table 4-7: Ad valorem estimates for North American import protection (tariff and
non-tariff barriers in percent of pre-tariff import value)

 

 

USA Mexico Canada
ROW Can. Mex. ROW USA Can. ROW USA Mexo
Agriculture 24 14 42 84 84 100 81 83 99
Mining 4 6 37 O 2 0 1 O 0
Petroleum 92 65 98 86 89 0 25 48 7
Food Processing 27 23 22 95 101 82 58 58 78
Beverages 97 97 92 100 100 0 35 35 35
Tobacco 21 81 23 100 100 0 8 8 0
Textiles 51 6 85 3 2 0 85 79 103
Wearing Apparel 19 9 l6 5 2 0 18 18 20
leather 9 22 5 2 3 0 105 103 39
Paper 1 o 2 64 66 87 s 4 0
Chemicals 7 18 9 9 7 9 l4 l2 8
Rubber 1 1 17 5 4 1 0 9 9 0
Non-Metal Mineral 9 1 57 7 1 1 O 19 14 l 1
Iron and Steel 83 48 75 47 43 0 86 74 95
Non-Ferrous Metal 2 l 0 2 4 0 2 2 0
Wood & Metals 13 5 10 4 3 O 16 14 9
Non-Electr. Machin l 1 2 1 7 4 5 3 2 2
Electrical Machines 13 7 3 13 8 l 5 5 6 4
Transport Equipme 71 65 6 13 19 1 68 57 83
Oﬁner Manufactures 28 3 24 3 11 O 30 17 17
Economy-wide 28 38 10 25 15 26 36 31 32

 

Source: Roland-Holst, Reine" and Shiells 1994

140

4.1.5. £1
Tl

elasticitil
al (1994
demand
The ﬁgu
output b:

In
value of
The leisn
of the ut
SubStitutj
demand I

1.4 and]

4.1.5. Elasticities
The responsiveness of an economy to policy changes depends on various economic

elasticities. Table 4-8 lists ﬁne most important elasticities. They are taken from Roland-Holst et
al. (1994). The labor-capital elasticity of substitution (0), ﬁne Amnington elasticities (6), and ﬁne
demand elasticity of ﬁne rest of ﬁne world (v) are deﬁned according to standard conventions.
The ﬁgures for elasticity of scale (scale) imply ﬁnat an increase in irnputs by X % increases

outputby(1+X%)l+'"'°-l.

In addition, ﬁne uncompensated wage elasticity of labor supply is assumed to lie at a
value of 0.10, ﬁne compensated value is at 0.15. This is ﬁne value derived by Burﬁess (1987).
The leisure endowment and ﬁne leisure-consumption elasticity of substitution (1’) in ﬁne top nest
of ﬁne utility function are calibrated to reproduce ﬁnese values. Furﬁnermore, ﬁne elasticity of
substitution for private demand (p) is set to a value 1.5. The equivalent value for government
demand (.9) is set to be equal to one. This value translates irnto own price elasticities between

1.4 and 1.5.22

 

2“InaCES function,uncompensatedpriccelasticityequals -a'- (1-0) a, whereoistbe
substitutionelasticity,andaisﬁneconsumptionshareofasector.Sincevaluesforaarelowdueto
high disaggregation, theprice elasticities renain closeto a, whichis setat 1.5.

141

Table 4-8

 

Food Prom

 

 

 

Table 4-8: Various elasticities by sector for all regions

 

 

Elasticity of Scale Labor-Capital Elasticity of Armington Elasticities Dem-

(in %) Substitution and

- Enact

Sector USA Mex Can USA Mexico Canada USA Mexico Canada ROW
Agriculture 0 0 0 0.680 0.768 0.680 1.500 1.500 2.250 4
Mining 5 5 5 0.900 0.950 0.900 1.062 1.062 0.781 5
Petrolelm 10 10 8 0.861 0.861 0.861 0.660 0.660 0.580 20
FoodProsessing 18 18 12 0.710 1.100 0.710 0.889 0.889 1.007 4
Beverages 13 13 18 0.710 1.100 0.710 0.326 0.326 0.726 3
Tobacco 7 7 24 0.708 1.100 0.708 1.008 1.008 1.008 3
Textiles 9 9 14 0.900 1.100 0.900 0.918 0.918 1.022 3
Wearing Apparel 6 6 13 0.900 1.100 0.900 0.479 0.479 0.802 3
Leather 2 2 14 0.900 1.100 0.900 1.007 1.007 1.066 3
Paper 16 16 22 0.900 1.100 0.900 0.967 0.967 0.734 3
Chemicals 12 12 19 0.960 1.100 0.960 0.903 0.903 0.702 3
Rubber 13 13 18 0.960 1.100 0.960 1.026 1.026 0.763 3
Non-MetalMinera 25 25 16 0.901 1.100 0.901 1.152 1.152 0.826 3
Imnand Steel 14 14 13 0.740 1.100 0.740 0.931 0.931 0.716 3
Non-FerrousMeL 14 14 20 0.740 1.100 0.740 0.825 0.825 0.663 3
Wocd&Metals 9 9 14 0.811 0.811 0.811 0.888 0.888 0.594 3
Non-Electr. Mach. 8 8 9 0.740 0.740 0.740 1.012 1.012 0.694 3
ElectricalMachin 8 8 28 0.740 0.740 0.740 1.035 1.035 0.705 3
Transp. Equip. 10 10 27 0.867 0.867 0.867 0.982 0.982 0.679 3
Other Manufacture 9 9 12 0.740 0.740 0.740 0.550 0.550 0.463 3
Constnrction 0 0 0 0.900 0.500 0.900 1.500 1.500 1.200 3
Electricity 0 0 0 0.521 0.300 0.521 1.200 1.500 1.300 0.5
Commerce 0 0 0 0.800 0.300 0.800 1.500 1.300 1.200 3
Trans.& Comm. 0 0 0 0.502 0.300 0.502 1.100 1.200 1.400 3
Financc&lnsur. 0 0 0 0.800 0.800 0.800 1.500 1.200 1.100 3
OtherServices 0 0 0 0.800 0.800 0.800 1.300 1.100 1.200 3

 

Source: Roland-Holst, Reinert, and Shiells (1994, p. 67); last column adapted from GREEN
(Bumiaux er a1. 1992).

142

4.2. Em

place bc
accompl
available
evaluatic
This is c
Third, ﬁ
constitutl
0f consur
comm
intemahz

the GMT]

“I“ The

avﬁilabilil

(1)
(2)
(3)
(4)
(5)
(6‘)

(7)

 

 

4.2. Environmental Components

The integration of an environmental component into economic modeling needs to take
place boﬁn on ﬁne production side as well as on ﬁne side of ﬁne environmental extemality. To
accomplish such integration, ideally ﬁlree (quantitative) information components should be
available. First, emissions of each sector need to be krnown. This information allows ﬁne
evaluation of sectoral changes on emission levels. Second, an abatement function is needed
This is crucial for evaluating ﬁne impact of regulations on ﬁne cost structure of various sectors.
Third, ﬁne emissions extemalities should be included In is simplest fornn, an extemality
constitutes a pure welfare reduction. In ﬁnis case, ﬁne extemality does not affect ﬁne production
orconsumptiornpattems ofﬁne economy and remains externaltoﬁneecononnicrrnodel itself. By
contrast, if emissiorns affect certain production or consumption factors, ﬁnis impact needs to be
intemalized into ﬁne model. Unfortunately, ﬁne data situation is not such ﬁnat ﬁne relationslnips of
ﬁne environmental component can be easily constructed Ten steps are necessary for
establishing ﬁne full economy-environment relationship for ﬁne Norﬁn American Free Trade
area. These steps follow a combination of logical and practical reasons, especially limited data
availability.

(1) Derivation of ﬁne sectoral emission coefﬁciens (available only for ﬁne U.S.).

(2) Derivation of sectoral abatement coss (available only for ﬁne U.S.).

(3) Construction of ﬁne abatement function.

(4) Extrapolation of U.S. relationships to ﬁnose of ﬁne oﬁner two NAFTA countries.

(5) Calculation of total emissions for each country.

(6) Association of emission values wiﬁn ambient pollution levels.

(7) Establishing ﬁne effect of pollution on human healﬁn.

143

additio
criteria

ernviror

4.2.1. 5

States.

ﬁne Wo
work i]
Agency
the the,
Well re:
Frommc
Donutam

by POUu

 

(8) Calculation of ﬁne degree to which healﬁn limis labor as a production factor.

(9) Quantiﬁcation of total welfare effect. '

(10) Political income elasticity of pollution abatement

In ﬁne following sections each of ﬁnese eight individual steps will be addressed in turn Irn
addition, one could list ﬁne choice of ﬁne pollutant(s) included in ﬁne analysis as an important
criterion It will become clear ﬁnat a whole set of uncertainties is involved in constructing ﬁne

environmental data These uncertainties stress ﬁne experimental nature of ﬁnis paper.

4.2.1. Sectoral Emission Coefﬁcients in the United States
The ﬁrst task involves taking stock of ﬁne sectoral information that exists for ﬁne United

States. Sectoral emission values draw heavily on ﬁne work undertaken wiﬁnin ﬁne framework of
ﬁne World Bank’s Industrial Pollution Projection System (IPPS; see Hettige et al. 1995). This
work, in turn, is indebted to ﬁne Toxic Release Inventory of ﬁne U. S. Environmental Protection
Agency. The IPPS liss various air, land and water pollution emissions for industrial sectors at
ﬁne ﬁnree-digit level. The main interest of ﬁnis paper is in air pollutans, because ﬁney have fairly
well researched damage functions. Air pollution tends to spread over large areas, and
protection from is hazardous eﬁ‘ecs is diﬁicult and cosﬁy. By contrast, land and water
pollutans are generally of a local nature. This concentration means also ﬁnat damages caused
by pollution of ﬁnese two media cannot be generalized because ﬁney are highly location

dependent and can often be avoided or abated. In ﬁne extreme, a polluted area could simply be
roped off.

Major air pollutans included in ﬁne IPPS are 802, N02, CO, total particulate matter
(TP), particles smaller ﬁnan 10 microns (PMlO), and volatile organic compounds (V 0C). Table

4-9 liss ﬁne toxic release coeﬁiciens as a function of sectoral value added. Data are adjusted to

144

other sen
For elec
OECD 1
source 6

emission

 

match ﬁne disaggregation into 26 sectors used so far. Since ﬁne IPPS database only contains
dasmmmufactunngsecmw,itisnecesseymconsﬁuedasforﬁneoﬁnesectos.The
followirng adjustmens are made: Emissions for agriculture are set to zero. Mining is assumed
to have halfﬁne emission intensity of non-metal minerals. Construction is given equal values to
ﬁnose of ﬁne wood and metal sector. Ennission values for commerce, ﬁnance and insurance, and
other services are set equal to ﬁne lowest values assigrned to any of ﬁne manufacturirng sectors.
For electricity production and transport, ﬁne values are calibrated such ﬁnat ﬁney replicated
OECD (1995) emission ﬁgures.23 Because ﬁne United States constitutes ﬁne original data
sonnce for ﬁne constructing ﬁne IPPS data, ﬁne assumption ﬁnat ﬁnese values reﬂect sectoral

enissicrn averages for ﬁne United States is unproblematic.

 

’3 Values for electricity are calibrated to constitute for 802 69% oftotal enissions; for N02 22%;
CO 5%; VOC 20%, and particles 20%. The analogous enission allocation for transport is for $02
4% , for N02 31%, for CO 80%, VOC 40 "/6, and for particles 25%. It is assumed that 40 percent
of transport is commercial transport. Emissions for private transport and household ernissicns are
not incorporated into these ﬁgures.

145

Table

Sector

 

Table 4-9: Pollution intensity of the production sectors (pounds per USD million value

 

 

added)

Sector 802 N02 CO Volatile Fine Total Toxicity

Organic Particul- Sus- Weigh-

Com- ates pended ted Index
pounds (PM10) Particu-
(V OC) lates
([811

Agriculture 0 0 0 0 0 0 0
Mirning 26259 177 3015 855 21555 17024 619
Petroleum 82270 48716 41302 32495 1441 16012 751
Food Processing 61 15 4548 1653 1406 2328 . 5563 202
Beverages 3893 1881 212 7588 97 294 29
Tobacco 1840 1113 145 366 14 34 5
Textiles 1948 1637 495 3000 29 736 35
Wearing Apparel 1 105 289 94 2602 31 370 18
Leaﬁner l 105 289 94 2602 31 370 18
Paper 13290 7801 15060 3018 740 2583 123
Chemicals 7443 8115 15628 7318 529 1535 94
Rubber 2412 831 104 3083 42 275 18
Non-Metal Minerals 52518 35517 6030 1711 43110 34049 1239
Iron and Steel 41044 17829 63961 5494 11344 9510 425
Non-Ferrous Metals 123489 4022 57444 4492 1135 10371 460
Wood & Metals 1 199 1702 3454 4704 487 2303 92
Non-Electr. Mach 1894 801 1876 1499 2 356 18
Electrical Machines 1158 551 684 815 5 122 8
Trarnsport Equipment 3082 1301 410 6427 129 913 47
Oﬁner Manufactures 1 12 200 42 737 25 77 4
Cornstruction 1 199 1702 3454 4704 487 2303 92
Electricity 362087 343 75 30440 3 1647 6929 14727 797
Commerce 1 12 200 42 366 3 34 2
Trarnsp. & Comm. 6712 15490 155758 20241 2770 5887 377
Finance & Insurance 112 200 42 366 3 34 2
Oﬁner Services 1 12 200 42 366 3 34 2

 

Source: Adapted from IPPS, March 1995; Based on OECD ﬁgures (Environmental
Data 1995). For ﬁne toxicity weight ﬁne shares are assumed to be 70 % for TSP, and 7.5 % for
all oﬁner except PM10, which is set to zero to avoid double counting.

146

thecross<
TSPconst

N02 form

choice Of ;

and VOC

reportton

The model will focus on TSP, as will be explained furﬁner below. Table 4-10 presents
the cross correlation of various sectoral emission indicators to provide a simple test whether
TSP constitutes a good approximation of a larger pollution problem: TSP, toxicity, mm and
N02 fornn a close cluster. This close clustering is particularly true for ﬁne correlation of the
logarithmic values, which assignns less weight to ﬁne extreme values. Wiﬁnin this group, the
choice of an indicator is relatively easy. By contrast, the correlation of ﬁne ﬁrst cluster wiﬁn C0
and VOC emission factors is relatively low. SO; takes an intermediate position Chapter 5 will

report to what degree the results depend on the choice of ﬁne pollutant.

Table 4-10: Correlation matrix of various sectoral emission parameters (logarithmic

 

 

in italics)
TSP TOX PM10 N02 S02 C0 VOC
TSP 1.000 0.982 0.890 0.832 0.474 0.233 0.346
TOX 0.994 1.000 0.809 0.896 0.594 0.348 0.504
PMIO 0.939 0.947 1.000 0.574 0.194 0.044 -0.027
N02 0.902 0.934 0. 900 1.000 0.596 0.373 0.746
SO; 0.877 0.910 0. 824 0.906 1.000 0.225 0.682
CO 0.853 0.874 0. 776 0.874 0.824 1.000 0.534
VOC 0. 6 74 0. 705 0. 5 73 0. 660 0.678 0. 706 1.000

 

4.2.2. Sectoral Abatement Costs in the United States

Information on abatement expenditures of manufacturing sectors in ﬁne U.S. is available
from Low (1992) who compiled data of ﬁne U.S. Department of Commerce (1988a; 1988b).
The ﬁrst column of Table 4-11 lists sectoral abatement values. Similarly to ﬁne situatiorn for
emissions, values are set to zero for agriculture. For commerce, ﬁnance and insurance, and
other services, values are assumed to be a ﬁnird lower ﬁnan ﬁnose of ﬁne next lowest

manufacturing sector, paper. They are set to 0.1 percent of production value. Following an

147

arcsettc

of total ;
than one
hardly ju
to under:

Fir
upendin
drag on I
dealing v

losses in

proﬁs d;

Sec
expmdm
Control is
Therefme

pmducﬁon

 

 

estimate by ﬁne European Commission (1994), abatement costs of electricity production zero

are set to 9 percent of production costs.

The data result in relatively small costs of environmental abatement of only 0.6 percent
of total production costs on average. Most manufacturing sectors face abatement costs of less
ﬁnarn one ﬁnird of one percent of production costs. The ﬁgures appear implausibly low and could
hardly justify a discussion on ﬁne trade impact of environmental regulation The data are certain

to underestimate actual regulatory costs by one half.

First, even if it were possible to determine wiﬁn precision ﬁne level of physical
expenditures on environmental abatement, ﬁney would neglect ﬁne fact ﬁnat ﬁne environmental
drag on businesses includes a large number of intangible factors. These are resources spent
dealing wiﬁn administrative procedures, costs of government inspections, uncertainty arnd time
losses in waiting for permits, risks of litigation, etc. For instance, Gray and Shadbegian (1993)
estimate that, for every dollar ﬁnat appears in a company’s books on emission reduction, actual

proﬁts drop by roughly 3 to 4 dollars, wiﬁn some variation among sectors.

Second, ﬁne data listed in ﬁne ﬁrst column of ﬁne Table are only based on ﬁnose
expenditures ﬁnat serve exclusively ﬁne purpose of pollution abatement. However, ennissicns
control is increasingly integrated into production equipment and production processes.
Therefore, it is difﬁcult to separate statistically what is purely productive expenditure arnd what

production component serves environmental purposes.

148

Table 4-11: Derivation of abatement expenditures for United States in 1988

 

 

Sector abatement total adjusted Adjusted total
Domestic costs (% of abatement abatement abate ent
production production)!» costs n costs (% of costs6
(bn USD)” USD) production)d)

Agriculture 195.49 0.00 0.00 0.00 0.00

Mining 24.97 1.50 0.37 3.33 0.83

Petroleum 187.68 1.53 2.87 3.40 6.37

Food Processirng 298.41 0.33 0.98 0.73 2.19

Beverages 49.45 0.33 0.16 0.73 0.36

Tobacco 31.06 0.16 0.05 0.36 0.11

Textiles 86.59 0.27 0.23 0.60 0.52

Wearing Apparel 62. 58 0.27 0.17 0.60 0.38

Leaﬁner 8.55 0.24 0.02 0.53 0.05

Paper 210.67 0.14 0.29 0.31 0.65

Chemicals 199.16 1.18 2.35 2.62 5.22

Rubber 122.34 0.30 0.37 0.67 0.81

Non-Metal Mineral 64.92 0.70 0.45 1.55 1.01

Iron and Steel 73.67 1.21 0.89 2.69 1.98

Non-Ferrous Metal 69.92 0.48 0.34 1.07 0.75

Wood & Metals 268.40 0.32 0.86 0.71 1.91

Non-Electr. Mach. 157.25 0.18 0.28 0.40 0.63

Electrical Machines 291.74 0.35 1.02 0.78 2.27

Transport Equip. 312.24 0.28 0.87 0.62 1.94

Oﬁrer Marnufactures 91.91 0.22 0.20 0.49 0.45

Construction 594.58 0.30 1.78 0.67 3.96

Electricity 272.89 9.00 24.56 19.98 54.52

Commerce 869.94 0.10 0. 87 0.22 1.93

Trarnsp. & Comm. 391.82 1.48 5.80 3.29 12.88

Finance & Insur. 1114.47 0.10 1.11 0.22 2.47

Other Services 2143.40 0.10 2.14 0.22 4.76

TOTAL 8194.09 0.60 49.07 1.33 108.94

 

Source: a) Social accounting matrix of Reinert et al. (1992); b) Low (1992), Electric
derived ﬁom European Commission (1994); costs for services are adapted from Rutledge arnd
Vegan (1994): It is assumed ﬁnat business abatement of mobile ennissions can be attributed to
transport and commurricatiorns. Services, transport and communications, ﬁnance arnd insurance,
and oﬁners are assumed to have abatement expenditures of 0.1 percent in raw expenditures,
which is somewhat lower ﬁnan ﬁne lowest manufacturing sector. c) = column a) times colurrnrn
b); d) and e) own calculations as described in text. See also Footnote 9.

149

En!
provided

the regul

of ﬁnese t

An
embodie
data sou
(Rutledg
(camam
over 50‘]
ﬁle Sartre
mm,

PTOducu"

Environmental drag and ﬁne statistical underestimation justify ﬁnat ﬁne raw ﬁgures
provided by Low should be adjusted upwards. In particular, in light of ﬁne purpose of assessing
ﬁne regulatory impact of diﬁ‘ering regulations on trade determination, an urncritical acceptance

of ﬁnese data would prejudge ﬁne analytical outcome.

An' ad hoc assessment of ﬁne order of magnitude to which environmental costs are
embodied in production costs is possible by going back to original Departrrnent of Commerce
data source ﬁnat was used by Low and are summarized in ﬁne Survey of Current Business
(Rutledge arnd Vogan 1994). Between 1975 and 1992, total annual pollutiorn abatenent irn
(constant 1987 dollars) increased from USD billion 57 to 87, denoting an irncrease of slighﬁy
over 50 percentThe data report an increase in capital expenditures by only 20 percent during
ﬁne same time span“ This small increase reﬂects ﬁne statistical phenomenon of an irncreasirng
integration of pollution control into ﬁne equipment, which ﬁner can no longer be separated ﬁ'om

productive investment.

Therefore, ﬁne reported data on current expenditure are likely to be a better
approximation for ﬁne time trend of pollution abatement, because ﬁne technological integratiorn
of abatement aﬁ‘ects ﬁnem less. From 1975 until 1992, ﬁnese ﬁgures increased from $17.1
billion to 38.7 billion, marking an increase by 126 percent” Ifone applies ﬁris growﬁn rate to
capital expenditures in ﬁne 1975 (to net out statistical shtinkttge) one yields an adjusted 1992

ﬁgure for total abatement expenditures of S 131 billion instead of ﬁne $87 billion reported by

 

2‘ The more relevant ﬁgure for our purposes would have been the depreciation of capital equipment
torcﬂectthecxisting stock, ratherthantheﬁgurcs fornew investment.

150

percent t

expendit

abatemei

business

 

Rutledge and Vogan. For ﬁne base year of ﬁne NAFTA calculations 1988, ﬁre value is $109
billion. This ﬁgure represents 6.3 percent of ﬁne United States proﬁts in ﬁnat year, or 1.33
percent of GDP. The values for abatement expenditures ﬁnat are reported by Low are ﬁrerefore
annualized to yield costs of that level (ﬁnird column of Table 4.11)."5 In ﬁne model, ﬁnese
expenditures are assumed to burden only production factor capital and are used to calculate
abatement capital (164).” They are unlikely to overestimate ﬁne gross costs imposed on

businesses.”

In addition, ﬁne ﬁgures leave out ﬁne signiﬁcant share of abatement costs ﬁnat accrue to
households and govemment directly. This onnission needs to be borne in mind when
interpreting ﬁne simulation results. However, ﬁne trade incidence of private arnd public
abatement costs would be less pronounced ﬁnan ﬁnOse of producer abatement costs. Only ﬁnose
costs ﬁnat are linked directly to ﬁne production process will substantially aﬁ‘ect ﬁne locatiorn of
industries. This impact on sectoral competitiveness does not exist if abatement costs are borne

by oﬁner econonnic actors. However, evidenﬁy ﬁne ﬁnancial extemality aﬁ‘ects ﬁne overall

 

2‘ Expenditures on motor vehicle enission abatencnt are subtracted, because of an interruption of
the series.

3‘ The values by Low (1992) present only pollution abatennent operating costs, which excludes
investment. Therefore, the adjustments in ﬁre table are higher ﬁnan the calculation would suggest.
Raw expenditures data are adjusted to yield total expenditures of 109 billion, i.e., multiplied by
2.22. This ﬁgure excludes about 1/3 of enission abatement, because it occurs within private
consumption, i.e., private transport, heating, etc.

’7 In economic terms, this exclusive burdening of capital takes place, even ifthe abatenerrt itself
usesonlylaborasaninput.lnﬁniscasc,theassociatedwagccostsreducethcfactorrewardof
capiml.Cmcepmaﬂy,hdoenamaﬁewhethewemEgimthepmcesasomofamduccdme
ofretumforaconstantcapitalstock,orasoneofaconstantrateofreturnforarcduccdcapital
stock.

2'Howevcr,theyovcrestimatethenetcosts,i.e.whenthebeneﬁtofrcduccdexternalitiesis
considered.

151

economy: Costs that are borne by ﬁne consumers of certain products will aﬁ'ect consumption
patterns. Pollution abatement undertaken by ﬁne government also affects ﬁne competitiveness of

ﬁrms indirecﬁy via an increased tax burden to ﬁnance ﬁne expenditure.

4.2.3. Abatement Functions

Information on abatement expenditure and ﬁne amount of ennissions in each sector does
not establish a relationship between ﬁne two parameters. The construction of an abatement
function deals wiﬁn two dimculties. First, little systematic information is available ﬁnat could be
used to construct sectoral abatement functions. Estimations by Hartrnran et a1. (1997) are
statistically not robust enough to be a base for sectorally differentiated abatement fnrrnctions.
Since ﬁne expenditure data do not allow a sectoral differentiation of ﬁne abatement cost furnction
it must be assumed ﬁnat a macroeconorrnically established relationship holds for each irndividual

SOCIDI'.

Second, it is not evident which part of ﬁre abatement costs should be attributed to which
pollutant, because. cleaner technology often reduces emissions for multiple pollutarnts. For
instance, a technology that reduces fuel consumption reduces CO; emissions as well as
emissions in particles, sulfur oxides, etc. Therefore a large component of joint costs make it
practical to look at abatement costs and emissions in ﬁreir entirety. A practical approach is to
use a pollution index to reﬂect ﬁne cumulative beneﬁts of all abatement eﬂ‘orts. The nnodel uses
two diﬂ‘erent indices. One is to only trace ﬁne development in particles, which already irncludes
a variety of molecules, so ﬁnat it correlates fairly well wiﬁn oﬁner air pollutants. In addition, ﬁne
impact of particles on healﬁn is statistically well established. For a sensitivity arnalysis, a

pollution index based on toxicity weights will be used.

152

1n 1i;
dawn
U.S. time
air emiss:
Emission:
reporting

ﬁmwm

period 1

C02 em

Thel

In liglnt of ﬁne poor data quality, ﬁnis paper applies a simple approach for ﬁne construction
of an abatement function based on aggregate ennissions and abatement ﬁgures. To ﬁnis end,
U.S. time-series data on abatement expenditure from 1975 to 199229 are set into relation wiﬁn
air ennission data during ﬁne same period (OECD 1989, and 1995-Environmental Data).
Ennissions of particulates (PM10) for all sources inn ﬁne United States sank by one ﬁnird for ﬁne
reporting period ﬁ'om 1975 until 1992 (Table 4-12). Emissions of oﬁner pollutants sank during
ﬁne same time by similar orders of magnitude, alﬁnough ﬁnere is some variation in ﬁne trend
across pollutants. CO and 80;: and VOC emissions decrease by 17 to 36 percent during ﬁne
period However, NOx emissions actually increase during this time period, in parallel wiﬁn

C02 emissions.

Table 4-12: Pollution abatement expenditures and air emissions in the United States

 

 

. , . 1975 1992 Change (%)
Abatement expending?" $58.1 bn $131.6 bn 126.18
C02-Emissions (1%? 4800 ' 5035 4.90
PM10 (1000 ton)? 10600 7080 -3321
CO (1000 tons) 124731 79092 -36.59
NOx (1000 tons)? 20100 21001 4.48
sox (1000 tons) ) 26000 20622 -20.68
voc (1000 tons)” 25000 20617 .1753
Average pollutants (excl. C02)? . -20.71
Avegge (gdjusted for growﬁn) ) -25.60

 

Source: 8) Adjusted from Rudlege and Vogan (1994); b) OECD-Environmental Data
(1989 1995); c) ariﬁnmetic average of change for CO, PM10, NOx, 80K and VOC; d) previous
row minus growﬁn in C02.

 

'9 The longest time span for which boﬁn enission arnd abatement ﬁgures are available.

153

Ho»-
neural ab:
factors 11:
economic
intensive
technolog
a more c
these ﬁnr
emission
0f fuel c1

Fn
emission
by 4.9 p
the net e
by 25.6
90111160,
in the (
1992), ,

undena]

Pine .3

Econo

However, ﬁnese trends in abatement expenditures and in ennissions do not establish an
actual abatement relationship. In parallel to ﬁne decomposition of ﬁne pollution eﬂ‘ects, ﬁnree
factors need to be taken into account when assessing ﬁne importance of abatement. ﬁrst,
economic growth (scale effect); second, a shift in ﬁne industrial structure away from emission-
intersive industry towards generally cleaner services (composition effect); and ﬁnally,
technological progress, reducing ﬁne need for material ﬁnrouglnput (techrnology eﬂ‘ect). Short of
a nrore complicated analysis, ﬁne consumption of hydrocarbons can be taken as a proxy for
ﬁnese ﬁnree combined factors. This approach is also likely to be consistent wiﬁn ﬁne way
ennissions data tend to be constructed in practice, wiﬁn total ennissions output set as a multiple

of fuel cornsumption.

From 1975 to 1992, C02 emissions rose by 4.9 percent (OECD 1995). Therefore, had
emission technology stayed ﬁre same, one could have expected oﬁrer emissions to rise similarly
by 4.9 percent Instead, ﬁney fell on average by 20.7 percent One might ﬁnerefore assume ﬁnat
ﬁne net eﬁ‘ect of ﬁne 126 percent increase in abatement expenditure30 is a decrease irn emissions
by 25.6 percent (20.7 % direct reduction plus 4.9% C02 trend). This value translates into a
pollution-abatement substitution elasticity of 0.36. The value lies within ﬁne range ﬁnat is given
in ﬁne OECD literature review for energy-capital elasticity of substitution (Bunniaux et al.
1992), and is taken as a central estimate for ﬁne model simulations. A sensitivity nun will be
undertaken wiﬁn a value of 0.6 which results ﬁom making an analogous calculation based on

PM10 ennissions.

 

3oEconornicgowthandtechnicalprogressinabatementappeartoberoughlyinbalancc.

154

speciﬁcini
concernsﬁ

model 8551

However,

expenditu

4.2.4. Ex

Iti

not GXist
adjusted
mung-yr:

light of 1

An important implicit assumption of this approach is ﬁnat ﬁnis relationship holds across all
sectors. There is no particular rationale for ﬁnis assumption; however, given ﬁne lack of nnore
speciﬁc informatien, ﬁne described meﬁnodology needs to serve as a proxy. A special problen
concerns ﬁne treatment of ﬁne abatement elasticity in ﬁne presence of scale elasticity. Here ﬁne
nnodel assumes ﬁnat scale economies apply only to production inputs labor and capital.31 This
means ﬁnat pollution output will rise more ﬁnan proportional to ﬁne irnputs of capital and labor.
However, as a consequence, ﬁrere are econonnies of scale wiﬁn respect to abatement

expenditures.

4.2.4. Extension of Environmental Relationships to Canada and Mexico

It is not possible to estimate parameters for the oﬁner two countries analogous to ﬁne
environmental sink function of ﬁne U. S., because independent and consistent data sources do
not exist in particular for Mexico (arnd to a lesser extent for Canada). Irnstead, ﬁne U.S. data are
adjusted to ﬁne situation in ﬁne oﬁner countries. For Canada, ﬁne hypoﬁnesis is simply ﬁnat ﬁne
country’s emissions factors and abatement expenditures are identical to those of ﬁne US. In

light of Mexico’s completely diﬂ‘erent developmental status, ﬁnis hypoﬁnesis is not defensible.

Following ﬁne argument made in ﬁne previous section, wiﬁn identical emission techrnology
per nrrnit of capital employed, pollution output in Mexico should be proportional to ﬁne
consumptiorn of energy. Because energy cornsumption in ﬁne U.S. is 16.8 times higher ﬁnan that

of Mexico in ﬁne base year (OECD 1998), emissions in ﬁne U.S. would be higher ﬁnan Mexican

 

3' Pollution follows ﬁre formula:
pouutiona ﬁ, 2 abate, 2 Z, 2 76) = 2““ pollutionCKF, abate, Z, '15) .

 

155

emissions by exactly that factor. However, actual emissions for ﬁne U.S. are only between 2
and 10 times higher ﬁnan ﬁnose for Mexico.32 If one takes a simple average of ﬁne ﬁgures for
802, NOx, CO, and VOC, Mexican production is 3 times as polluting per output value as ﬁne
US. Assuming a constant abatement elasticity of 0.36, we can conclude ﬁnat abatement
expenditure in Mexico is 5 percent of ﬁnat in ﬁne United States per unit of production If one
assumes an elasticity of 0.6, Mexican abatement would be 15.5 percent ﬁnose of ﬁne U.S. per

unit of production

Table 4-13: Pollution output in United States, Mexico, and Canada

 

US Mexico Canada Ratios US/MX

 

Value Add 566.2 43.3 78.4 13.08
Gross production 391.8 17.7 64.8 22.16
802 842 403 95 2.09
NOx 9718 955 1223 10.18
CO 81025 17152 7164 4.72
VOC/HC 10650 1753 908 6.08

 

Source: OECD-Environmental Data (1989 1995)

Alternatively, a set of ennissiorns data for 14 sectors in Mexico would be available (varn
Torngeren et al. 1991). This is not used due to an apparent gap in ﬁre data quality and a limited
sectoral breakdown of ﬁne emission ﬁgures. In any case, for ﬁnis study ﬁne relative change in ﬁne

level of ennissions is more important ﬁnan ﬁne absolute level of pollution.

Table 4—14 correlates ﬁne TSP per value added and abatement costs per unit of output wiﬁn ﬁre
capital-labor ratios and net export positions of each country. As a ﬁrst impression nnost

correlations are raﬁner low. The highest positive correlation consists between pollution and

 

3’ Values for PM have not been used, because of differences in measurement techniques.

156

abatement. However, there are some hints that the relationship ﬁts less for sectors with extreme
values, as can be derived from the fact that the logarithmic correlation is substantially better

thanthelinearone.

Table 4-14: Correlation matrix of various sectoral parameters (logarithmic in Italics)

 

 

TSP Abate- K/L- KIL- K/L- Net Net Net

ment ratio ratio ratio exports exports exports

USA Canada Mexico US Canada Mexico
TSP 1.000 0.305 0.149 0.284 0.264 0.078 0.092 0.083
Abatement 0.789 1.000 -0.069 0.052 -0.117 -0.042 0.121 0.017
K/L-ratio USA -0. 039 -0. 237 1.000 0.710 0.549 -0.280 0.295 0.131
K/L-ratio Canada 0.246 0.101 0. 601 1.000 0.218 -0.080 0.190 0.106
K/L-ratio Mexico 0.161 -0. 058 0.460 0.147 1.000 -0.425 0.404 0.173
Net exports US 0.002 0. 015 -0.102 -0. 069 -0. 286 1.000 -0.861 -0.490
Net exports Canada 0.177 0.051 0.120 0.197 0.260 -0.861 1.000 0.601
Net exports Mexico 0.023 0.071 0.098 0.109 0.111 -0. 490 0. 601 1.000

 

Note: a) Since for net exports no logarithms could be calculated, their original values are used
also in tlne logarithmic correlation. b) For net trade an index is constructed by forming tlne ratio
of net intra-NAFI' A trade and domestic production

Pollution intensity tends to be positively correlated with capital intensity, although tlne
logaritlnnnic correlation for the U.S. is slightly negative. By contrast, tlne sign of tlne relationship
between abatement expenditure and capital intensity is mixed, with a negative sign for the U.S.
and Canada, and a positive one for Mexico. The relationslnip of abatement and pollution

intensity to net export positions is practically zero.33

 

33’Itmayappenrinconsistentthatalltlnreecor'relations forthetradeindexarepositivealthough
intra-NAFI‘ A net exports cancel out by deﬁnition. However, the use of a trade index (net exports
divided by output) enn result in a statistical paradox, if countries diﬁ‘er in size. For instance, if
Mexico has a trade surplus of 10 with the US, the index values for Mexico would be 0.2 and for
the U.S. -0.001, ifproduction in Mexico is 50 and in the U.S. is 1000.

157

The table also shows another example of ﬁne Leontief-Paradox, as it shows that ﬁne U.S. is
importing capital-intensive goods. However, as was explained furﬁner up, ﬁnis ﬁnding is
consistent wiﬁn ﬁne statistical results ﬁnat establish ﬁne U.S. as a relatively labor-intesive
country. By contrast, boﬁn Mexico and Canada are exporters of goods that are relatively

capital-intensive. This fact, again, is in line wiﬁn ﬁne ﬁndings of ﬁneir relative endewtnents.

4.2.5. Calculation of Total Emissions
Technically, the calculation of total emissions is straightforward It consists simply of

multiplying ﬁne sectoral ennission values just discussed by ﬁne sectoral estimates of value
added These ﬁgures are ﬁnen summed over all sectors. However, for electricity and trarnsport
no emission factors per nnnit of output are available. Instead, these ennission factors are
calibrated for the U.S. to reﬂect total emission estimates for ﬁne respective shares of road
trarnsport arnd electricity production. This meﬁnod implies that for ﬁnese cases total annd sectoral
enissions had to be calculated simultaneously. The values ﬁnus calculated for the United States

are used directly for ﬁne oﬁner two countries without making any furtlner adjustments.

4.2.6. Relationship of Total Emissions to Air Quality

I

Of ﬁne multitude of air pollutants, ﬁnis paper imputes only ﬁne consequences of srrnall
particles. Despite considerable remaining uncertainties, small particles are ﬁne air pollutant for
which ﬁne eﬁ‘ect on healﬁn is best researched due to broadly available statistics. Furﬁnermore,
ﬁne relationship between particulate emissions, air quality and healﬁn ﬁts very well a linear
fnmction, which is not ﬁne case for more reactive pollutants such as NOx or ozone. This means
ﬁnat a doubling irn emissionns has a doubling of particle concentrations as a consequence. A
linear relationship also holds for ﬁne effect of air quality on human healﬁn. For many oﬁne

pollutants, one can discern a threshold effect: a concentration in ﬁne air below a certain value

158

does not entail any measurable impact on human healﬁn, while higher concentratiorns can have
cornsiderable consequences. These non-linearities would not allow a simple aggregation, as it is

possible for particles.

However, even particles are not wiﬁnout measurement problems. Notably, ﬁney do not
constitute a single molecule, but are composed by a group of molecules, ranging from simple
dust to 80x. It is now well established ﬁnat ﬁne damaging eﬂ‘ect of particles on respiratory
fnnnctions is ﬁne greater ﬁne smaller ﬁne individual particles are, because smaller particles enter
ﬁne lungs rrnore deeply ﬁnan bigger ones. This insight leads to a variety of measurements
diﬂ‘ering by ﬁne size of particles included. They range from total suspended particles (TSP) to
particles ﬁne size of 10 microns (PM10) to particles ﬁne size of 2.5 rrnicrons (PM2.5) or even
smaller. A generally accepted relationship is to assume ﬁnat PM2.5 constitutes half of PM10,

which in turn constitutes half of TSP.

For ﬁne United States, using ﬁne average exposure, PM 2.5 lies roughly at 18ug/m3
(Dockery er al. 1993; American Lung Association 1995). The same concentration is assumed
for Canada. For Mexico, ﬁne derivation of concentration levels of total suspended particles
follows Ronnieu, Weitzenfeld and Finkelman (1990). Average exposure of . total suspended
particles lies at 141 ug/m3. In applying ﬁne approximation ﬁnat one quarter of ﬁne TSP is
PM2.5,34 ﬁne average population in Mexico is exposed to a PM2.5 level 35.3 ug/m3. Deﬁnite
extremely high levels of exposure in some districts of Mexico city (reaching average TSP

exposure of up to 500 pig/m3) cautious calculations result in an average exposure to air

 

”Thislatioisacautiousestimate,asinﬁneUnitedStatestheratioisnearlyoneinthree.

159

pollutantsﬁnatisonlytwiceashighasﬁnatofﬁneUS.”Aonepercentreductioninennissiorns

reduces PM2.5 concentration in the U.S. by 0.018ug/m3 and in Mexico by 0.0353 rig/m3.

However, it is likely ﬁnat ﬁne values for Mexico err at ﬁne side of cautiorn, and ﬁnere is
evidence ﬁnat ﬁne actual risk of exposure to PM2.5 may be higher ﬁnan ﬁne numbers suggest.
FirstﬁneratioofPMthoTSPinﬁneUS. sarnplesiscloserto3ﬁnanto4.Thereisno
evidence ﬁnat ﬁne ratio in Mexico should be higher. Collins and Scott (1993) cite evidence ﬁnat
ﬁne geographical situation of Mexico City is very conducive to ﬁne formation of vey ﬁne
particles. Despite considerable diﬁculties in ﬁne reliability of measurements particle exposure
appears to be at least eight times ﬁne levels detected in Chicago. Secornd, due to substantial
diﬁ'erencesinwealﬁnbetweenﬁneNorﬁn andﬁne SouﬁnofﬁneNAFTAareeitisliltelyﬁnat
Mexicans are less able to protect ﬁnemselves against particle exposure ﬁnan Canadians or U.S.

4.2.7. Health Effect of Air Quality
There exist a substantial number of epidemiological studies measuring ﬁne impact of particles

on various indices of human healﬁn. These concern inter alia premature mortality; chronic
bronclnitis in adults; respiratory hospital adrnissiorns; emergency room visits; asﬁnnna symptom
days; days wiﬁn respiratory symptoms; acute bronchitis in children; restricted activity days, etc.
(American Lung Association 1995) These are diﬁcult to aggregate, since they contain

substantial double counting. Most interesting and straightforward to interpret for purposes of

 

3’ The average level of total suspended particles in Mexico city (38 °/o of population) lies at around
250 mg/m’, those for other cities (38 percent) is assumed to be 125 mym3, and for rural areas 25

160

economic modeling are restricted activity days or work loss. Ostro (1987) estimates ﬁnat an
increase in ambient concentrations of ﬁne particles (PM2.5) by 1 mg/m3 leads to 0.403

additional annual restricted activity days per worker.

The estimate might overestimate ﬁne isolated eﬁ’ect ﬁnat particulates have on humarn
healﬁn, because ﬁne econometric estimate by Ostro is likely to have captured also ﬁne eﬁ‘ect of
oﬁner pollutants, which are probably closely related to particulate pollution However, ﬁne
estimate will underestirrnate ﬁne healﬁn eﬂ‘ect of total air pollutiorn. In additiorn, ﬁne air pollution
damage function neglects non-healﬁn-related extemalities, such as ﬁne pollution of
environmental media like soil and water, and omits damages to plants and materials. Wiﬁn
certain caveats attached, ﬁne functional form can be used as an approximation of ﬁne healﬁn
eﬁ‘ects of pollution. Ronnieu, Weitzenfeld, and Finkelman (1990) have applied ﬁnis meﬁnod to

pollution in Mexico city.

4.2.8. Effect of Health on Labor Productivity

TheworklossestimatesofOsﬁocanbeusedinastraightforwardfashiontomeasure
reduced labor output due to particulate emissions. This implies ﬁnat a reduction in pollution by
10 percent would reduce annually sick days in ﬁne U.S. by 0.725 days, and would increase
labor supply by 0.29 percent”. Identical ﬁgures are assumed for Canada For Mexico, a ten
percent reduction in air pollution leads to an increase in activity days by 1.42 days or 0.57

percent. It could be argued in particular for ﬁne case of Mexico ﬁnat not all sick workers stay

 

mg/m’. If one quarter of these values consists ﬁne particles (<2.5 mg/m3), ﬁne average population
in Mexico is exposed to a PM 2.5 level 31.5 mg/m’.

3‘ This is the equivalent of 0.725 sick days/250 work days per annum.

161

away from work However, in any case, ﬁneir productivity will be lower, and it can be argued

ﬁnat lack of treatment probably leads to a more drawn-out disease.

For purposes of a sensitivity analysis, ﬁne emission values of ﬁne toxicity-weighted index
will be used Following ﬁne calculations of the European Comnnission, total particulates cause
only 70 percent of ﬁne total healﬁn damage of air pollution Therefore, in ﬁnis case, ﬁne healﬁn
eﬁ‘ects are increased accordingly by 43 percent” over ﬁnose of ﬁne case taking into acconnnt only

particulates.

4.2.9. Welfare Effect or Pollution
While the use of ﬁne equation for work loss is likely to be a suﬂ'rcient proxy for

measuring ﬁne eﬁ‘ect of ﬁne air pollution extemality on labor productivity, ﬁnis factor
underestimates ﬁne total welfare impact of pollution. Most notably it omits ﬁne impact of
pollution on premature mortality. According ﬁne American Lung Association (1995) ﬁre cost
of ﬁnis factor is at least as high as ﬁne costs of morbidity. Therefore, a cautious adjustment is to
assume ﬁnat ﬁne welfare costs due to air pollution are double those for ﬁne work loss. This

welfare component does not affect any oﬁner component of ﬁne model.

4.2.10. Political Income Elasticity for Pollution Abatement

The income elasticity for pollution abatement (s) is not ﬁxed Variations in ﬁnis
parameter will be used to determine ﬁne sensitivity of ﬁne model simulations to ﬁne inclusiorn of

ﬁnis parameter. However, a central rate of 0.75 is assumed. This is based on two plausibility

 

3’ 43% = (l-70%)/70%.

162

considerations. First, based on purchasing power parity, ﬁne U.S. is 3.73 times as rich as
Mexico ($19,851/35,323). Ifﬁne assumption is correct ﬁnat Mexico allows roughly ﬁnree times
ﬁne amournt of pollution per unit of output, ﬁnis implies an income elasticity of regulation 0. 83

(3.73”'“=o.33).

Second, if ﬁne value were one or larger, it would mean ﬁnat, in practice, pollution would
be nnnlikely to ever become a problem in any country over its whole development paﬁn This
cannot be squared wiﬁn the empirical observation of the inverted U-shaped pollution cnnrve. By
contrast, a somewhat lower value is compatible wiﬁn ﬁne observed curve, if it is accompanied
by ﬁne typical structural changes ﬁnat occur during a country’s development process. During an
early development phase, a rising pollution level will accompany ﬁne economic specialization inn
ﬁne relatively dirty secondary sector. During a later development phase, a falling pollution level
will accompany ﬁne growﬁn of ﬁne relatively clean tertiary sector. Ifﬁne elasticity were too low,
only a steady increase in pollution would be observed, except in ﬁne case where dirty

production shrinks not only in relative but also in absolute terms.

163

CHAPTERS

SIMULATION RESULTS

This chapter presents ﬁne results of simulations wiﬁn ETERNA A ﬁrst section proceeds
by building up ﬁne full model in several steps. It starts by describing ﬁne sirnnulation results of
ﬁne trade liberalization scenario wiﬁn nationally ﬁxed capital stock excluding any environmental
interactions. The basic model is presented in two variants. Tlne model is ﬁner extended to
include ﬁne environmental extemality. A second extension incorporates in addition induced
regulation effects. Section 2 modiﬁes ﬁne policy scenario of ﬁne ﬁrst section by allowing intra-
NAFTA capital mobility. Togeﬁner wiﬁn ﬁne ﬁrst scenario, ﬁris scenario serves as reference case
to assess ﬁne importance of various assumptions. Section 3 shows ﬁne importance of ﬁne
petroleum sector in determining ﬁne results. Section 4 presents sensitivity nnns on a numbe of
calibration parameters. A ﬁfth section analyzes different formulations of ﬁne country
trarnsforrnation equation. Section 6 illustrates ﬁne impact of unilateral actions inn NAFTA

countries. A ﬁnal section presents a synopsis of ﬁne results and provides indicative cornclusions.

5.1. Building up the Model Structure of the Central Case

5.1.1. Simple Trade Scenario with Internationally Immobile Capital
mm

To allow an understanding of ﬁne model mechanism it is useful to start wiﬁn a simulation

for which ﬁne environmental component is completely switched 03. The underlyirng policy

164

assumption is that trade barriers disappear for all intro-NAFTA trade.” The eﬁ‘ects of reducing
tariﬂ‘ arnd non-tariff barriers are quite distinct. Tariﬂ‘s cornstitute boﬁn costs for irnportes and
revenues for governments. To compensate for clnanges in revenues governments adjust ﬁne
transfers to households. By contrast, ﬁne production of ﬁne public good and all tax rates, apart
from tariﬁ's remain constant For non-tariﬁ‘ barriers, no compensation mecharnism exists. By
assumption, non-tariﬂ' barriers cornstitnrte a waste of resources ﬁnat are used for rent seeking A
reduction in non-tariff barriers makes ﬁnese resources available for ﬁnal consumption or
immediate production. Therefore, even wiﬁrout any changes in import volumes, ﬁne ecornonnies
beneﬁt from ﬁne increase in net output. By contrast, a tariﬁ‘ reduction leads to economic growﬁn

and irncreased welfare only because trade patterns adjust to reduced distortions.

M mi im

The macroeconomic impact of ﬁne trade liberalization is listed in Table 5-1. All ﬁgures
express percentage changes from the pre-NAFI‘ A baseline. An evident eﬂ‘ect is ﬁnat boﬁn ﬁne
absolute and relative trade integration of Norﬁn America increases, as ﬁne strong rise in trade
volume attests.39 In terms of aggregate economic indicators, NAFTA has a positive impact on
ﬁne North American econorrnies. In relative terms, ﬁne greatest winners of ﬁne free trade

agreement are Canada and Mexico, which realize GDP gains by roughly 2.5 % each The

irncrease in ﬁne USA is 0.67 °/o. This relative distribution of gains results ﬁom ﬁne diﬁ‘erences in

 

3' In ﬁne following the term NAFTA will be used, although ﬁne trade liberalimtion modeled
propely also includes the earlier Canadian American Free Trade Agreenent (CAFT A).

165

size and dependency of ﬁne ﬁnree courntries. However, in absolute terms, ﬁne U.S. is ﬁne main
beneﬁciary. Out of a total gain of S41 bn, slightly less ﬁnan two-ﬁnirds ($25.7 bn) takes place in

ﬁne U.S., Canada enjoys a quarter of ﬁne beneﬁts ($11.2 bn), and Mexico one-tenﬁl (84.0 bn).

Table 5-1. Macroeconomic effects of trade liberalization (immobile capital; no

 

 

extemalities)

USA Mexico Canada
GDP 0.67 2.45 2.55
Material product 0.21 1.23 1.94
Capital return (real) 0.60 2.54 2.23
Wages real (net) 0.69 2.02 2.48
Labor supply 0.05 0.19 0.26
Private consumption 1.03 2.50 2.78
Exports 4.68 11.78 14.81
Imports 3.60 13.41 15.08
Terms of trade -0.84 -2.66 -7.38

 

The change in private consumption is generally higher ﬁnan ﬁnat of GDP. The diﬂ‘erence
is explained mostly by ﬁne assumption of budget neutrality, which acts as leverage of GDP
eﬁ‘ects. For instance, if government consumption is 20 "/o and GDP increases by 1%, ﬁner ﬁne
consumption eﬁ'ect would be expected to be of the order of 1.25 °/..‘° Clearly, the leverage is
smallest in Mexico due to a small government sector. Reduced government trarnsfers resulting

from tariﬁ‘ losses also have an inﬂuence.

The increase in real consumption is accomparnied by higher factor rewards. As ﬁne

relative increase in the economic pie is highest in Canada and Mexico, ﬁne largest relative

 

3’Diﬁ‘crencesinthechangesofexportsandinnportsareduetotherelativetr'adeandcapital
positionofthecountriesinthebaseyearwiththeU.S.runningabalanceofpaymentdeﬁcitand
Mexico and Canada having a surplus. To preserve a constant external balance, exports and
importschangeasomewhatdiﬁ‘erentrate.

”1.25 °/o=l%/(l-20%)

166

increases can be found here. While in ﬁne U.S. arnd Canada beneﬁts are relatively neutrally
distributed between capital and labor, capital is ﬁne main beneﬁciary of trade liberalization inn
Mexico. This is consistent wiﬁn ﬁne Stolper-Samuelson ﬁneorem, Mexico is a relatively capital-

abnnrndant country since, as was noted in Chapter 4.

A secondary effect of ﬁne increased purchasirng power of wages is ﬁnat labor supply arnd
hence employment increases slighﬁy in all ﬁnree conmtries, between 0.05 and 0.26 "/o. Next to
ﬁre allocation effect of trade, ﬁnis provides additional economic gowﬁn as ﬁne absolute resource
endowment rises. The mecharnism also explains why wages increase less ﬁnan might be

expected (e.g. in ﬁne U.S. which is relatively labor-abundant).

mm

A value-based deﬁnition of output (such as GDP) is misleading for capturing
environmental eﬁ‘ects of trade liberalization, because only material ﬂows are remd to
pollution. Instead, one needs an indicator ﬁnat captures changes in ﬁne material ﬁnroughput
Therefore, ﬁnis paper makes ﬁne important distinction between GDP and material product,

where ﬁne latter is calculated as goss output wiﬁn constant output prices.

The substantive difference between ﬁne increase in ﬁne value of production and physical
production is explained by ﬁne fact ﬁnat even wiﬁnout actually producing much nnore (in
physical nnnnits) inn each individual country, ﬁne better allocation across countries allows a
substantially lniglner consumption (in value terms). Several mechanisms can be identiﬁed to
explain ﬁne magnitude of ﬁne diﬁ‘erences between ﬁne values: First, ﬁne removal of trade barriers
increases ﬁne purchasirng power of consumers. It simply allows cornsumers to allocate bette
ﬁneir consumption bundles. This leads to a higher increase in ﬁne value of consumption ﬁnan ﬁne

pure quantity of goods would suggest. Second, ﬁne removal of trade barriers allows for

167

reallocation in ﬁne production process. This increases ﬁne eﬁciency in ﬁne production process,
even wiﬁnout inncreasing ﬁne material ﬁnroughput. These two factors simply reﬂect ﬁne ﬁneory of
comparative advantage. A ﬁnird factor is ﬁrst a part ofﬁne trade distortion consists in norn-tariﬂ‘
barriers. By assumptiorn, non-taniﬁ‘ barriers lead simply to a waste of resources. These
resources are now available for consumption (net output), which increases welfare even if
production (gross output) were to remain unchanged‘1 While increasing GDP, all ﬁnese

mechanisms aﬁ‘ect pollution only insofar as ﬁney might induce sectoral changes.

mm

The sectoral changes undemeaﬁn ﬁne macro-economic aggregates are listed in Table 5-2.
Despite an overall induced gowﬁn in all ﬁnree econonnies, ﬁne 26 sectors are aﬂ‘ected unevenly,
wiﬁn all states showing net winners and losers. The table reports material product, because of
its importance for ﬁne calculation of ennissions ﬁgures. Changes in production values are
qualitatively very similar, because physical output follows relative price changes. However, in
some irnstances, sectors will see ﬁreir output decrease in material terms but increase in value

terms.

Several sectors deserve particular mentioning. The ﬁrst columns of each country in Table
5-2 show ﬁnat agricultural production clearly moves away ﬁom Canada and Mexico to ﬁne
United States. By contrast, petroleum production in ﬁne United States shrinks slighﬁy, giving a

boost to production in Mexico and Canada Anoﬁler important sector is transport equipment,

 

‘" While this assumption concerning non-tariﬁ barriers has some signiﬁcance on the calculation of
thewelfareeﬁ‘ectofﬁadehberalinﬁontheimpactonsectoral sizeandcompositionofthe

168

where production increases substantially in ﬁne United States and Canada. Alﬁnough each
country has a few shrinking sectors, ﬁnere is a general increase in manufacturing at ﬁne expense
of services. This shiﬁ results from ﬁne fact ﬁnat ﬁne removal of trade barriers practically only
aﬂ‘ects manufacturing sectors. In ﬁne data set a number of services are not even traded at all.
The associated eﬁiciency gain ﬁnerefore moves ﬁne relative advantage towards manufactured
products. In terms of ﬁne pollution eﬂ‘ect of NAFTA, ﬁnis may entail an upward bias, as

services are relatively clean wiﬁn ﬁne important exception of transport

The second set of columns in Table 5-2 shows how ﬁne relative changes translate inn
absolute shifts in production. The values are calculated by multiplying ﬁne values of ﬁne ﬁrst
column wiﬁr ﬁne output values of ﬁne base case. A monetary indicator for channges in material
ﬁnroughput may be a contradiction in terms. However, it presents ﬁne order of magnitude annd
importance of ﬁne sectoral changes in constant prices. Clearly, for boﬁn ﬁne United States and
Canada, ﬁne effect of NAFT A is dominated by ﬁne transport equipment sectors. For ﬁnese
countries, ﬁne shrinking of services also play an important role. By contrast, ﬁne agicultnn'al and
ﬁre petroleum sectors, ﬁne two biggest in ﬁne economy, dominate charnge in ﬁne Mexican

ecornomy.

 

econonny is small, as the composition of resource waste is identical to consumption. Changes in the
economy occur only insofar, as the increased real income aﬁ‘ects the labor supply ofan econornny.

169

 

 

 

Table 5-2. Sectoral calculation of emissions impact of trade liberalization (immobile
capital; no extemalities)
USA Mexico Canada

Out- Out- Emissi Outpu Out- Emissi Out- Out- Ennissi

put put ons t (%) put ons put put orns

(%1 (bn 3) (bn 5) (%) (bn 3)
Agriculture 1.66 3.25 0.000 -3.27 -0.73 0.000 -2.38 -0.79 0.000
Mining 0.18 0.04 0.007 1.70 0.07 0.161 1.16 0.14 0.205
Petroleum -0.75 -1.42 -0.114 14.11 3.05 2.688 9.36 2.49 1.139
Food Processing 0.88 2.61 0.039 2.41 0.62 0.260 0.40 0.14 0.020
Beverages 0.80 0.39 0.000 3.01 0.12 0.003 0.84 0.05 0.001
Tobacco -0.60 -0. 19 0.000 1.47 0.01 0.000 -1.62 -0.03 0.000
Textiles 1.33 1.15 0.003 3.15 0.12 0.010 -0.06 0.00 0.000
Wearing Apparel 0.72 0.45 0.001 2.29 0.08 0.002 -0.06 0.00 0.000
Leather 3.34 0.29 0.001 -0.14 0.00 0.000 2.79 0.04 0.000
Paper 0.21 0.45 0.005 -0.82 -0.04 -0.012 -0.82 -0.28 -0.032
Chemicals 0.51 1.02 0.006 1.35 0.14 0.017 1.38 0.22 0.016
Rubber 0.52 0.64 0.001 0.12 0.00 0.000 6.40 0.45 0.005
Non-Metal Minerals 0.26 0.17 0.031 -0.57 -0.02 0127 0. 84 0.06 0.093
Iron and Steel 0.93 0.68 0.019 3.75 0.15 0.139 10.33 1.07 0.377
Non-Ferrous Metals 0.74 0.52 0.016 -0.42 -0.01 -0.011 6.33 0.53 0.255
Wood & Metals 0.52 1.39 0.015 2.15 0.14 0.022 1.93 0.64 0.058
Non-Electr. Mach. 0.61 0.96 0.001 0.77 0.02 0.001 1.54 0.23 0.002
Electrical Machines 0.21 0.62 0.000 2.58 0.13 0.001 2.49 0.41 0.002
Trarnsport Equip. 3.61 11.27 0.041 1.87 0.16 0.015 33.43 19.01 0.370
Oﬁner Manufactures 0.37 0.34 0.000 5.16 0.12 0.001 0.42 0.03 0.000
Construction 0.01 0.06 0.001 -0.34 -0.06 -0.011 -2.10 -l.69 -0.162
Electricity 0.37 1.00 0.099 3.76 0.15 0.268 -0.39 -0.07 -0.039
Connmerce -0.19 -1.67 0.000 -1.24 -0.55 -0.004 -2.70 -2.82 -0.006
Transp. & Comm. 0.02 0.07 0.003 0.15 0.03 0.024 -0.78 -0.50 -0.141
Finance & Insurance -0.33 -3.69 -0.001 -1.55 -0.25 -0.001 -2.77 -1.69 -0.004
Oﬁner Services -0. 16 -3.38 -0.001 -0.25 -0.08 0.000 -1.26 -1.82 -0.003

 

Note: Ennission ﬁgures are normalized such total emissions before trade liberalizatiorn in each

country are 100.

170

mum

Irnportanﬁy, material ﬁnroughput also constitutes an intermediate step for ﬁne calculation
of changes in ﬁne pollution levels. The ﬁnal columns in Table 2 illuminate ﬁne environmental
aspect of NAFTA It is calculated by multiplying ﬁne sectoral changes wiﬁn ﬁne pollutionn
coeﬁcielts discussed in Chapter 4. Since ﬁre absolute level of pollutiorn is not direcﬁy
comparable between countries, numbers are calculated to set pre-NAFTA base ennissiorns of

TSP to 100.

Clearly, ﬁne change in ﬁne petroleum sector dominates ﬁne picture. The productiorn shift
away ﬁom ﬁne U.S. towards its neighbors has in its wake a substantial shift in pollution
Petroleum overwhelms all oﬁner changes in Mexico, wiﬁn some additional impact from mining,
food processing and electricity. This can be seen even better in Figure 5-1 where ﬁne size of ﬁne
circles reﬂects ﬁne contribution of individual sectors to ﬁne overall emission charnge. If
petroleum had an emission factor of zero, NAFTA’s net result on pollutionn inn Mexico would

actually be negative. This aspect will be discussed furﬁner below.

In Canada, important contributions to ﬁne overall pollution eﬁ'ect are made by expansions
in ﬁne nrnirning and transport equipment sectors. Expansions in food processing, non-metal
manufacturing, and electricity production, and contractions in petroleum inﬂuence ﬁne result for

ﬁne U.S.

I71

Figure 5-1: Contribution of Individual Sectors to Overall Emission Changes (ignoring
regulation effect)

 

USA

Change in output (56)

 

 

 

 

 

 

 

 

Emission factor
Mexico
20
2‘, 15
g 10
5
.5 A , ° C G.
E I V ‘ A ' ﬁ 1 G 1
o -10 _5 f 10 20 30 40
8
0
~10
Emission factor
Canada
E
‘5
e
'5
o
.5
2 T . I
0 30 40

 

Emission factor

 

 

 

Note: Size of bubble represents overall errnission change (Table 5-2). White bubbles represent decreases.
Emission factor = index for TSP cnnissions per dollar of output value (Table 4-9).

172

The sectoral ennissions changes sum up to ﬁne total pollution eﬂ‘ect of ﬁne trade
liberalization scenario (Table 5-3). Pollution in Mexico increases signiﬁcannﬁy (by 3.4 °/o),
while ﬁnat ofCanada rises by 2.2 % and ﬁrst ofﬁle U.S. rises only by 0.2 °/o. Table 5-3 ﬁnntlne
disaggregates ﬁne total emission impact into three components. The scale eﬁ‘ect is equivalent to
ﬁne change in GDP. Pollution would change by ﬁne same amournt as GDP, if no oﬁner changes
took place at ﬁne sanne time. This eﬁ‘ect constitutes an important driver of ﬁne overall pollution

eﬂ'ect Values for Canada and Mexico are evidenﬁy higher than U.S. values.

Table 5-3. Emissions impact of trade liberalization (immobile capital; no

 

 

extemalities)
USA Mexico Canada
Emissions 0.17 ' 3.44 2.16
1. Scale effect 0.67 2.45 2.55
2. Allocation eﬁ‘ect -0.46 -1.19 -0.59
3. Common eﬁ‘ect -0.04 2.19 0.21

 

Clearly, however, material product increases less ﬁnan ﬁne production value. This meanns
that GDP per unit of material product increases.” This increased allocation emciotcy earn be
calculated as ﬁne diﬁ‘erence between changes in GDP and physical product In all ﬁnree cases,
ﬁnis second eﬁ‘ect reduces ﬁne impact of ﬁne scale eﬁ‘ect substantially. However, ﬁnere is no case

where it overcompensates for ﬁne scale effect, because material product gows eveywhere.

The composition eﬁ‘ect constitutes a residual value, and is calculated as ﬁne change in
pollution ﬁrst is neiﬁner explained by the scale eﬁ'ect or ﬁne allocation eﬁciency effect This

eﬂ‘ect provides a differentiated view. The production structure inn ﬁre U.S. moves sliglnﬁy

 

42T‘hisissinnilarinresulttoadematerialiaationoftheeconorny,whichcouldoccurdnneto
technicalprogress. -

173

towards less polluting sectors. In Mexico, ﬁne compositiorn change is substantial. It contributes
to an overall pollution increase of 2.2 °/o. The effect on Canada is also to increase pollutiorn,
alﬁnough only by 0.2 %. However, as can be seen from Figure 5-1, ﬁne correlation between

tradeinduced sectoral specialization and emissions factors is far ﬁom systematic.

The ETERNA model setup leaves ﬁnree possible factors to explain ﬁnis composition
effect First, it could be the result of the relative factor abundance of the countries involved As
mentioned above, Mexico needs to be considered as capital abundant This mearns ﬁrst it tends
to specialize in capital—intensive irndustries, of which ﬁne dominant petroleum sector is certairnly
a part Second, since trade barriers were highest for ﬁne manufacturing sectors and low for
services, a relative shift towards manufacturing could be expected at ﬁne expense of se'vices.
Third, diﬁ'erences in ﬁne regulatory standards among countries (and hence diﬂ‘erences inn capital
costs) might reirnforce a specialization of Mexico inn pollution-intensive (or more precisely high-
abatement cost) goods. However, abatement costs alone are inconsequential for trade patterns
due to ﬁne calibration process. In ﬁne pre-NAFI‘ A case, sectoral diﬂ'erences in ﬁne abatement
costs are exactly balanced by diﬂ‘erences inn ﬁne productivity of capital. Otherwise, ﬁnere would
have been a diﬁ‘erence in ﬁne net return of ﬁne sectors, implying ﬁnat ﬁne ecornomy could not

have been in equilibrium.

5.1.2. Introducing the Extemality
The simulations just presented calculate emissiorns wiﬁn a simple add-on approacln,

wiﬁnout incorporating its associated extemalities. Table 5-7 presents main eﬁ‘ects of including
extemalities into ﬁne model. Compared to ﬁne case wiﬁnout extemalities, four more reporting
categories are introduced. First, ﬁle variable “healﬁn” denotes ﬁne change in ﬁne extennality.

Second, it is now useﬁnl to distinguish welfare and private consumption, because ﬁne two now

174

deviate. Welfare is a composite of private consumption and healﬁn Third, as additiornal
information, ﬁne share of ﬁne extemality in driving ﬁne overall welfare eﬁ‘ect is reported This
ﬁgure includes production and hedonic eﬁ‘ects. Finally, nominal and eﬁ‘ective labor supplies are

disﬁnguished, because healﬁn has a direct impact on labor productivity.

Table 5-4. Trade Liberalization when Extemalities are included: Welfare Change

 

 

(immobile capital)
USA Mexico Canada
Total welfare 0.94 2.23 2.41
Private consumption 1.02 2.45 2.74
Healﬁn 0.00 -0.19 -0.06
Extemality (% welfare) -0.94 -7 . 73 -4.56
Eﬁ‘ective labor supply 0.05 0.01 0.20
Nominal labor supply 0.05 0.21 0.27

 

Eﬁ‘ective labor supply consists of ﬁne nominal labor supply adjusted for ﬁne healﬁn aﬁect
Changes in healﬁn affect ﬁne number of actual work hours only inn a simple multiplicative way.
The increase in ﬁne wage sum ﬁnat occurs, because people are less sick does not act as a wage
increase to which people adjust their labor supply. This is because boﬁn sides of the labor

supply curve (leisure and labor) are affected equally by improving or worsening healﬁn.

The impact of including extemalities on ﬁne economic structure itself is not vey
substantial, and ﬁnereforc not reported. Neverﬁneless, ﬁne ﬁgures denoting ﬁne relative
contribution of healﬁn to ﬁne overall welfare change show ﬁnat ﬁne impact is not altogeﬁner
negligible. In ﬁne case of constant pollution technologies, lower healﬁn reduces ﬁne welfare gain
of NAFTA for Mexico by nearly 8 %. Even for ﬁne U.S. and Canada, healﬁn reduces ﬁne total

beneﬁts of liberalized trade by 0.9 and 4.6 %, respectively.

175

5.1.3. Introducing the Regulation Effect
A next, step introduces a numerical formulation of ﬁne country transformation hypoﬁnesis.

Abatement efforts are no longer constant. Instead, it is assumed that an increase in private
consumption by 1 % is accompanied by regulations ﬁnat decrease ﬁne permissible emissions per

unit of output by 0.75 %.

Numbers reveal ﬁnat ﬁne impact of introducirng ﬁne regulation eﬂ’ect on environmental
regulatiorn on macro-economic aggregates are small (Table 5-8). The increased abatement
enmenditure acts to reduce overall production by 0.02 % in ﬁne case of ﬁne United States, while
ﬁne reduction Canada’s output is 0.06 %, and Mexico’s production is unchanged. Alﬁnougln ﬁne
gowﬁn impact of ﬁne regulation on ﬁne U.S. and Mexico are eiﬁner small or non-existent, ﬁne
reasorns for contrast with Canada ﬁnis are diﬂ’erent. In ﬁne case of ﬁne U.S., ﬁle explanatiorn is
simply ﬁnat ﬁne income gowﬁn induced by trade liberalization is smaller ﬁnarn Canada’s.
Consequenﬁy, ﬁne induced change in environmental stringency is also small. Inn ﬁnis case,
emissions per unit of output must be reduced by 0.74 %, while emission stringency in Mexico

and Canada increases by 1.8 and 1.95 %, respectively.

By contrast, ﬁne reason for ﬁne small economic impact in ﬁne case of Mexico lies inn ﬁne
small level of pollution abatement in ﬁne country on ﬁne one hand, and ﬁne larger beneﬁts of
pollution abatement on workers’ healﬁn on ﬁne oﬁner hand. Healﬁn improves by more ﬁnan 0.1 °/o
compared to a case ﬁnat ignores ﬁne income effect. This increases effective labor supply by ﬁnis

amount, and ﬁnerefore counteracts ﬁne resource loss implied by risirng abatement costs.

176

Table 5-5. Central case simulation with immobile capital

 

 

USA Mexico Canada
GDP 0.64 2.40 2.46
Materialproduct 0.18 1.18 1.84
Capital return (real) 0.65 2.50 2.36
Wages real (net) 0.63 2.05 2.31
Eﬁ'ective labor supply 0.06 0.10 0.24
Nominal labor supply 0.04 0.19 0.24
Exports 4.68 11.73 14.75
Innports 3.60 13.37 15.00
Terms of trade -0.86 -2.63 -7.32
Total welfare 0.95 2.30 2.43
Private consumption 0.99 2.45 2.66
Healﬁn 0.02 -0.09 0.00
Extemality (°/o welfare) 3.58 -3.36 0.00
Emissions change -0.65 1.52 0.00
1. Scale eﬁ'ect 0.64 2.40 2.46
2. Allocation eﬁ’ect -0.46 -1.19 -0.61
3. Composition eﬁ'ect -0.09 2.17 0.15
4. Regulation eﬁ'ect -0.74 -1.80 -1.95

 

The introduction of ﬁne regulation eﬁ‘ect changes ﬁne net pollution eﬂ’ect of ﬁne NAFTA
scenario ﬁrndamentally. The U.S. registers now a noticable net reduction in pollution by 0.65
°/o. The emission eﬁ‘ect for Canada disappears from an uncorrected value of over 2 °/o. Only
Mexico continues to have a net increase in emissions. However, ﬁne values drop by more ﬁnan

halfto 1.5 °/o.

An interesting aspect of ﬁne increased abatement effort is also ﬁnat ﬁnere are sliglnt
secondary cﬁ’ects on pollution. First, irnsofar as economic growﬁn may be reduced, so is ﬁne
scale eﬁ’ect on pollution. Second, ﬁnere is a slight shift in ﬁne composition eﬂ’ect In ﬁnis case, it

induces all ﬁnree countries to move slighﬁy towards less polluting industries.

The two welfare components are affected in opposing direction by ﬁne regulation eﬂect

Gains in healﬁn counteract ﬁne decrease in consumption. Despite reduced private cornsumptiorn

177

in Carnada and ﬁne U.S., overall welfare increases slighﬁy. By contrast, Mexico realizes a healﬁn

improvement while maintaining an unchanged consumption level.

The interpretation of ﬁne welfare results requires considerable caution because ﬁney
obviously depend crucially on ﬁne extemality estimates ﬁnat are used These are notoriously
subject to uncertainties. As ﬁne parameters used in ﬁne simulatiorns regard only a sinngle aspect
of ﬁne extemality (ﬁne healﬁn effect of particulate air pollution), it is sure to underestimate ﬁne

beneﬁts of environmental regulation.

5.2. Introducing Factor Mobility
The model is now modiﬁed by making capital mobile across countries. The mechanisms

at large are ﬁne same as described in ﬁne previous case. However, in ﬁnis case capital moves to
ﬁne place of highest nominal after-tax return across countries. This is not ﬁre case for real retnun
to capital, which factors in ﬁne consumption deﬂator. In ﬁne simulation at hand, capital moves
ﬁom ﬁne U.S. to Mexico, while Canada’s position remains practically uncharged Accordirngly,
ﬁne output of ﬁne latter two countries rises more ﬁnan under ﬁre scenario wiﬁn immobile capital.
By contrast, production in ﬁne U.S. even contracts. Obviously, ﬁnis shift in productiorn has

cornsequernces for ﬁne pollution levels in ﬁne NAFTA countries.

178

Table 5-6. Central case simulation with mobile capital

 

 

Indicators USA Mexico Canada
GDP 0.61 3.30 2.47
Material product 0.13 2.51 1.86
Capital return (real) 0.75 1.95 2.31

Wages real (net) 0.59 3.06 2.33

Eﬂ’ective labor supply 0.06 0.13 0.24
Nominal labor supply 0.03 0.35 0.24
Exports 4.27 16.94 14.84
Imports 3.46 14.72 15.05
Tems of trade 2.11 -3.25 -5.92
Total welfare 0.95 2.21 2.42
Private cornsumption 0.99 2.48 2.66
Healﬁn 0.02 -0.22 0.00
Extemality (% welfare) 3.93 -8.71 -0.06
Emissions change -0.71 3.79 0.03

1. Scale eﬂ'ect 0.61 3.30 2.47
2. Allocation eﬁ’ect -0.48 -0.80 -0.61

3. Composition eﬁ’ect -0.11 3.13 0.15
4. Regulation eﬂ‘ect -0.73 -l.82 -1.95

 

At ﬁrst glance, ﬁne movement of capital appears to be conmterintuitive. In particular, it
contrasts wiﬁn ﬁne previously established notion ﬁnat ﬁne U.S. ecornorrny is relatively labor-
abundant Therefore, one could have expected ﬁnat capital ﬂows into ﬁne relatively capital
scarce country. However, due to a larger relative importance of NAFTA, capital returns inn
Mexico and Canada rise substantially more ﬁnan returns in ﬁne U.S. However, Carnada’s

increase capital return is near exactly matched by a substantial worsenirng of its ternns of trade,

179

and hence, depreciation. Consequently, U.S. capital follows ﬁne higlner return in Mexico. The

diﬂ’erences in economic gowﬁn among ﬁne countries are ﬁnerefore ampliﬁed“

Compared to a scenario wiﬁn immobile capital, ﬁne real return of American capital rises
(by 0.1 %), while that of Mexico drops (by 0.55 %). As secondary eﬁ‘ects, ﬁle capital
nnovement causes wages in Mexico to rise 1 % more and ﬁnose of ﬁne U.S. to rise 0.04 % less
ﬁnan inn ﬁne case of immobile capital. Consequelt changes in labor supply reinforce ﬁne shift
toward productiorn in Mexico. The production eﬁ’ect is a nearly full percentage poirnt higher
than wiﬁn immobile capital.

While substantive in terms of production changes and trade, ﬁne difference between ﬁne
scenarios wiﬁn and wiﬁnout capital mobility is insigniﬁcant for ﬁne welfare eﬁ'ect This is
because ﬁne income loss or gain ﬁnat results from ﬁne relocation of capital is compensated by

proﬁts ﬁnat are transferred across borders.“

Capital mobility also affects ﬁne trade impact of liberalization. Two irnportarnt diﬁ'erences
to the case without mobility are worth mentioning. First, in the U.S. trade rises less than inn the
case of immobile capital, because capital ﬂows act as a substitute for trade. Second, despite

constant balance of payment requirement, exports and imports develop diﬁ’erently. This is

 

‘3 Barriers to eapital movenents are not explicitly modeled. The equilibrium assumption of
ETERNA (or most CGE model) automatically presumed that an autonomous rrnigration of capital
has already equalized national rates of return before trade liberalization.

“ Because in the ease at hand, capital ﬂows out of the labor-intensive economy (U.S.) into the
capital-intensive economy (Mexico), the result could even be a decreased overall welfare. This
paradox result can occur, because capital transfer entails an extemality in the labor supply
function. With identical labor supply elasticities in two econornnies, a dollar in a labor-intensive
economy induces a higher increase in ﬁne labor pool ﬁnan a dollar in ﬁne capital-intensive economy.
Inthc case, whereinaddition health extemalitiesexist, iteanbedenonstratedthatcapital mobility
is actually welfare decreasing.

180

actually corresponds to ﬁne outﬂow of capital. The U.S. trade balance turns (nnore) negative,
because of proﬁt transfers ﬁom abroad. Correspondingly, Mexico’s, balance of trade turns

positive to ﬁnance ﬁnese proﬁt transfers.

It should be noted ﬁnat ﬁne case of mobile capital only constitutes a long-term
equilibrium. This does not mean ﬁnat the paﬁn to ﬁnis equilibrium would be straightforward In
particular, one would have to expect a J-curve eﬁ‘ect, if ﬁne modeling predicts large capital
transfers. If, for irnstarnce, ﬁne U.S. runs a trade deﬁcit and ﬁnances it via proﬁt transfes from
investment in Mexico or Canada, ﬁne U.S. ﬁrst would have to run a surplus to ﬁnance ﬁnese
investments, or has to borrow from elsewhere. If return on capital is 10 "/o, for every dollar
deﬁcit in ﬁne steady state, ﬁne country ﬁrst would have to nor a cumulative surplus of rouglnly
10 dollars to ﬁnance ﬁne necessary investnnents. A dynamic model might ﬁnerefore arrive at

substantially diﬁ’erent results than ﬁne static one presented here.

The sectoral impact of ﬁne liberalization scenario reveals a picture that is qualitatively
similar to ﬁne one for immobile capital (Table 5-7). Sectoral gowﬁn and contractions take place
in more or less ﬁne same sectors as in ﬁne case for immobile capital (agicultnnre; petroleunn;
non-metal manufacturing; ferrous metals; and transport equipment). The obvious rnodiﬁcatiorn
to ﬁne previous scenario is ﬁnat in general sectoral values for ﬁne U.S. are smaller or nnore

negative, while ﬁnose for Mexico are larger, wiﬁn Canada practically unaﬂ'ected.

181

Table 5-7. Sectoral calculation of emissions impact of trade liberalization (mobile
capital; no extemalities)

 

USA Mexico Canada

 

Out- Out- Emissi Outpu Out- Ennissi Out- Out- Ennissi
put put ons t(°/o) put ons put put ons

 

(%) (bn 3) (bn 3) (%) (bn 3)
Agriculture 1.41 2.76 0.000 -2.08 -047 0.000 -244 -0.81 0.000
Mining 0.04 0.01 0.001 4.71 0.18 0.444 1.14 0.14 0.200
Petroleum -0.89 -1.67 -0134 22.32 4.83 4.253 9.34 2.48 1.136
FoodProcessing 0.81 2.42 0.036 2.77 0.71 0.298 0.37 0.13 0.019
Beverages 0.81 0.40 0.000 3.20 0.13 0.003 0.85 0.05 0.001
Tobacco -0.76 -024 0.000 1.86 0.01 0.000 -1.63 -0.03 0.000
Textiles 1.30 1.12 0.003 3.79 0.15 0.012 .004 0.00 0.000
Wearing Apparel 0.79 0.50 0.001 2.97 0.10 0.003 .003 0.00 0.000
Leather 3.30 0.28 0.001 0.38 0.01 0.000 2.79 0.04 0.000
Paper 0.17 0.35 0.004 0.23 0.01 0.003 -0.81 -0.28 -o.031
Chemicals 0.41 0.83 0.005 2.80 0.28 0.036 1.39 0.22 0.016
Rubber 0.42 0.52 0.001 1.23 0.03 0.001 6.43 0.45 0.005
Non-Metal Mineral 0.22 0.14 0.026 -019 -0.01 -0042 0.84 0.06 0.093
IronandSteel 0.80 0.59 0.016 5.02 0.21 0.186 10.35 1.07 0.378

Non-Fern. Metals 0.65 0.45 0.014 1.04 0.02 0.028 6.35 0.54 0.256
Wood & Metals 0.47 1.26 0.014 2.85 0.19 0.029 1.94 0.65 0.059
Non-Elect. Mach. 0.50 0.79 0.001 2.31 0.06 0.003 1.52 0.23 0.002
Electrical Machines 0. 13 0.38 0.000 4.84 0.24 0.003 2.51 0.42 0.002
Transport Equip. 3.52 10.99 0.040 3.39 0.30 0.028 33.50 19.05 0.370
Other Manufacture 0.35 0.32 0.000 5.94 0.14 0.001 ' 0.44 0.04 0.000
Construction 0.01 0.04 0.000 -0.62 -0. 12 -0.020 -2.1 1 -1.69 -0. 162

Electricity 0.32 0.86 0.085 6.44 0.25 0.458 -0.40 -0.07 -0.040
Commerce -0.23 -l.98 -0.001 -0.40 -0.18 -0.001 -2.71 -2.83 -0006

Transp. & Comm. -0.04 -0. 15 -0.007 1. 13 0.20 0.177 -0. 80 -0.52 -0. 145
Finance & Insuranc -0.41 -4.56 -0.001 -0.96 -0. 16 -0.001 -2.78 -l .70 -0.004
Other Services -0. 17 -3.60 -0.001 0.32 0.10 0.001 -l.27 -1.84 -0.003

182

Since changes in ﬁne pollution level are driven by changes in sectoral productiorn, it is not
surprising ﬁnat pollution in ﬁne U.S. should rise less ﬁnan in ﬁne case of irnnnobile capital, while
pollution in Mexico rises furﬁner. However, in ﬁnis case ﬁne order of magnitude of ﬁne charnge in
pollution levels has increased. Main factor is a much larger importance of ﬁne compositiorn

eﬁ’ect (driven by relocation of ﬁne petroleum industry).

In Mexico, ﬁne composition effect contributes over 3 percentage points of pollutiorn
growth, out of nearly 3.8 % in total. While loosing some of its industrial base, in terms of
pollutiorn, ﬁre U.S. is ﬁne winner, wiﬁn a net reduction of 0.7 %. While in many aspects for ﬁne
simulations ﬁne question of capital mobility is relatively unimportant, clearly for ﬁne
environmental assessment of ﬁne trade liberalization, ﬁne question of capital mobility is crucial.
In ﬁnis case, NAFTA would not only lead to a relocation of pollutiorn, but could potentially
entail a net increase in pollution despite a large regulation effect. This would be ﬁne case in
particular under the assumption ﬁnat production in Mexico is substantially nrnore polluting ﬁnan
in ﬁne U.S., However, it should be cautioned ﬁnat to a substantial degee ﬁne changes discussed

are due to a single sector, petroleum production.

5.3. Importance of the Oil Sector

5.3.1. Leaving out the Emission Effect
The simplest way to analyze ﬁne importance of ﬁne petroleum sector is by setting the

emission coeﬂ'rcients of ﬁne sector to zero, while keeping ﬁne remaining scenario assumptions
constant This limits ﬁne scenario changes to ﬁne pollution compositiorn eﬁ’ect Table 5-8
compares ﬁne composition effect of ﬁne two central cases (for mobile and immobile captial) to

one wiﬁnout ﬁne inclusion of ﬁne petroleum sector.

183

Table 5-8. Influence of the petrol sector on the overall emissions impact

 

 

 

Immobile Capital Mobile Capital
USA Mexico Canada USA Mexico Canada
Compos. Eﬁ’ect incl. oil -0.09 2.17 0.15 -0.11 3.13 0.16
Compos. Eﬁ‘ect wiﬁnout oil 0.07 ~0.31 -0.84 0.07 -0.59 -0.83
Total emissions incl. oil -0.65 1.52 0.00 -0.66 3.90 0.21
Total emissions wiﬁrout oil -0.49 -0. 93 -0.98 -0.49 0.17 -0.77

 

Clearly, ﬁne omission of ﬁne sector causes important sign reversals across ﬁne board for
ﬁne composition eﬁ‘ect. While ﬁne composition eﬁ‘ect for ﬁne U.S. changes from slighﬁy
negative to slightly positive, changes for ﬁne oﬁner two countries are nnore massive. Wiﬁnout
petroleum, Mexico registers a composition effect ﬁrst is reduced by arournd 2.5 % for immobile
capital and even 3.7 % for internationally mobile capital. The composition eﬁ'ect of Canada
dropsroughly 1 %. InboﬁnMexico andCanada, overall ennissiornsnowdropasaresultoftrade
liberalization There is little diﬂ’erence between ﬁne mobile and immobile capital scenario irn ﬁnis
aspect It is also important to note ﬁnat wiﬁnout ﬁre petroleum sector, ﬁne central scenario
delivers pollution improvements everywhere, with ﬁne exception of a negligible irncrease in

Mexico, when capital is mobile.

5.3.2. Exclusion of Mexican Oil Sector from NAFTA

As a second way to examine the implication of exempting ﬁne Mexican oil sector ﬁom
trade liberalization, ﬁne model was run leaving all bilateral trade barriers between Mexico and
ﬁne oﬁner two states constant. To some extent, ﬁnis reﬂects ﬁne actual situatiorn ﬁnat was
negotiated in ﬁne NAFTA treaty, where a number of restrictions for investnnent in ﬁne Mexican
oil sector remain in order to protect PEMEX (cp. Huﬂnauer and Schott 1993, p. 33-36). Table

5-9 reports ﬁne results under ﬁne assumption of intematiornally immobile and mobile capital.

184

Table 5-9. Exclusion of Mexican petroleum sector from NAFTA

 

 

 

Innmobile capital Mobile capital

USA Mex. Can. USA Mex Can.
GDP 0.59 1.94 2.46 0.62 1.11 2.57
Material product 0.17 0.85 1.84 0.19 -0.24 1.98
Capital return (real) 0.60 2.02 2.36 0.55 2.47 2.07
Wages real (net) 0.59 1.56 2.31 0.61 0.73 2.45
Eﬁ’ective labor supply 0.06 0.11 0.24 0.06 0.08 0.26
Nominal labor supply 0.04 0.15 0.24 0.04 0.02 ' 0.26
Exports 4.34 12.18 14.74 4.56 7.84 15.14
Imports 3.32 13.53 14.99 3.39 12.40 15.11
Total welfare 0.90 1.66 2.43 0.89 1.72 2.44
Private consumption 0.94 1.75 2.67 0.94 1.72 2.69
Healﬁn 0.02 -0.04 0.00 0.02 0.07 -0.01
Extemality (% welfare) 3.76 -2.10 -0.04 3.58 3.34 -0.42
Ennissions -0.65 0.69 0.02 -0.61 -1.14 0.20
1. Scale eﬁ'ect 0.59 1.94 2.46 0.62 1.16 2.57
2. Allocation eﬁ’ect -0.42 -1.07 -0.51 -0.43 -1.35 -0.59
3. Composition eﬁ'ect -0.12 1.15 0.17 -0.11 0.37 0.23
4. Regulation eﬁ’ect -0.70 -1.29 -1.95 -0.70 -1.27 -1.97

 

Unsurprisingly, on a macroeconomic level ﬁne beneﬁts of trade liberalizatiorn for Mexico
are now about one half-percentage point less ﬁnan in ﬁne base case. There is also a rnoticeable
reduction in ﬁne trade beneﬁts for ﬁne U.S. The reduced welfare gains are borne sliglnﬁy nnore
by capital owners ﬁnan workers. Owing to ﬁne capital intensity of ﬁne sector, ﬁnis could be
expected. As trade between Mexico and Canada is minimal, Canada remains unaﬂ'ected by ﬁne

exclusion of the oil sector.

The limited NAFTA changes ﬁne overall pollution eﬁ‘ect substantially less ﬁnan ﬁne earlier
sensitivity case ﬁnat exempts ﬁne oil sector ﬁom ﬁne calculation of ﬁne pollution eﬁ’ect None of

ﬁne signs of ﬁne individual eﬁ’ects changes, alﬁnough ﬁne net impact on Mexico’s pollutiorn level

185

is only about one ﬁnird of ﬁre central case. Important contributors are a lower scale eﬁ’ect,

which is dampened by a reduced income eﬁ’ect, and a lower composition effect

In ﬁne case of immobile capital, .ﬁre drop in ﬁne composition eﬁ’ect could have been
expected to be more substantial in light of ﬁne earlier discussion on ﬁne sector’s innportarnce.
However, despite restrictions on trade, ﬁne oil sector in Mexico still expands by a substantial 6

% (compared to 14 °/o in ﬁne base case). This is due to growtln in energy arnd oil-intensive

sectors in Mexico and has obvious consequences for emissions.

For mobile capital, ﬁne effect of ﬁne change in ﬁne scenario is identical in directiorn, but
substantially larger in magnitude. Mexico’s GDP gains drop to a ﬁnird of ﬁne central case.
Capital ﬂows to Canada and ﬁne United States irnstead, causing even ﬁne oil sector to shrink
slightly. The production shift is accompanied by a shift in ﬁne pollution pattenn Mexican
emissions drop by more ﬁnan 1 %, instead of increasing by nearly 4 %. The sharply reduced

scale effect and a substantially reduced composition effect domirnate ﬁnis change.

5.4. Sensitivity to Calibration Parameters

Chapter 4 described extensively ﬁnat ﬁne construction of ﬁne model parameters had to rely
on numerous assumptions and educated guesswork. Therefore, it is important to urndetake a
systematic sensitivity analysis to test ﬁne robustness and to explore ﬁne parameters ﬁrst drive ﬁne
results. The scenario assumptions will be ﬁnose of ﬁne central cases (wiﬁn and wiﬁnout

international capital mobility) wiﬁn individual assumptions varied one at a time.

5.4.1. Using a toxicity weighted emission factor

In ﬁnis scenario, ﬁne use of TSP as an indicator for pollution is replaced by toxicity

weights, i.e. an aggregate of TSP, S02, N02, CO, VOC (Table 5-10). The macro-ecenornic

186

impact of introducing toxicity weiglnts is small (less ﬁnan 0.02 “/11 overall). This was to be
expected ﬁom ﬁne discussion in section 5.1.2, which revealed a relatively limited macro—
ecornonnic impact of ﬁne environmental component Since ﬁne use of toxicity weights is
simultaneously linked to an increase in ﬁne estimate for extemalities it is evident ﬁnat ﬁne trade
beneﬁts for countries ﬁnat increase ﬁneir pollution level (Mexico) become slightly less, while ﬁne
trade beneﬁts of pollution exporters (U.S.) become sliglnﬁy higher. This is reﬂected in a higher
share of healﬁn beneﬁts in ﬁne overall result The use of toxicity weights has also litﬁe
noticeable impact on ﬁne direction of pollution ﬂows. However, it should be mentioned ﬁrst

TSP makes up a signiﬁcant component of ﬁne toxicity weiglnts used

Table 5-10. Replacing TSP in base case (immobile capital) with toxicity weights:
Macroeconomic impact

 

 

 

Immobile capital Mobile capital
USA Mex Can USA Mex Can
Total welfare 0.96 2.26 2.43 0.96 2.12 2.42
Private consumptiorn 1.00 2.44 2.67 0.99 2.45 2.67
Healﬁn 0.03 -O.13 0.00 0.03 -0.33 0.00
Extemality (% welfare) 5.14 -5.14 0.28 5.21 -13.85 -0.35
Ennissiorns -0.67 1.60 -0.09 -0.67 4.03 0.1 1
1. Scale eﬁ’ect 0.64 2.39 2.46 0.61 3.29 2.47
2. Allocation eﬁ'ect -0.46 -1. 19 -0.61 -0.48 -0.80 -0.61
3. Compositiorn eﬂ’ect -O.11 2.26 0.06 -0. 12 3.27 0.06
4. Income effect -0.74 -1.79 -1.95 -0.69 -1.70 -1.78

 

5.4.2. Various Pollution Indicators
Table 5-11 analyzes wheﬁner ﬁne robustrness between TSP as pollution indicator annd

toxicity weights is equally solid for its composite pollutants. The compositiorn eﬁect of ﬁne
previous scenario wiﬁn different pollutants largely supports ﬁne hypoﬁnesis ﬁnat ﬁne connposition

eﬁ‘ect is robust. Most values for ﬁne U.S. show a slight negative trend, while ﬁnose for Mexico

187

are strongly positive, while values for Canada are slighﬁy positive. However, clearly carbon
nnornoxides (CO) and small particles (PM10) do not ﬁt ﬁne picture. CO causes sign reversals
for Canada and signiﬁcanﬁy lower values for Mexico. PM10 even reverses signs for all
counntries. This is surprising in particular, because PM10 is an important cornstituent of TSP.
One explanation for ﬁnis may lie in ﬁne quality ofﬁre original data set, as we have hinted earlier
at some sectoral anomalies in ﬁne relationship between PM10 and TSP". A furﬁner explanation
lies in ﬁne dependence of ﬁne results on only a few crucial sectors. Most notably, ﬁnere is a

major diﬁ’erence in emission values for PM10 and TSP in ﬁne petroleum sector.

Table 5-11. Comparison of the Composition effect for various pollutants

 

 

 

 

Immobile Capital Mobile Capital

USA Mexico Canada USA Mexico Canada
802 -0.07 3.74 0.18 -0.07 5.55 0.20
N02 -0.22 3.77 0.46 -0.24 5.57 0.46
CO -0.18 0.40 -1.46 -0. 19 0.65 -1.47
VOC -0.08 3.05 0.68 -0.09 4.46 0.68
PM10 0.02 -0. 15 -0.54 0.01 -0.21 -0.53
TSP -0.09 2.17 0.15 -0.11 3.13 0.16
Toxicity -0.1 1 2.26 0.06 -0. 12 3 .27 0.06
5.4.3. Abatement Elasticity

As central case assumption serves an abatement elasticity (ﬁne percentage reductiorn in
pollution caused by a one % decrease in abatement expenditures) of 0.6. Howeve, in Chapter
4 it was argued ﬁnat ﬁne elasticity might be as low as 0.36. This would make increased
abatement eﬁ'orts more costly. For instance, a regulation effect of one % will increase

abatement costs by 2.8 "/6 instead of 1.6 %. However, ﬁre impact of ﬁnis change results in ornly

 

‘5 For sornne sectors, the reported value for PM10 was higher than for TSP, which is by deﬁnition
not possible, because clearly small particles (PM10) are a subgroup of total suspended particles.

188

a small reduction of trade-induced growth, because the overall costs of abatement are less than

1.5 °/o ofGDP (Table 5-12).

Table 5-12. Simulations with a low abatement elasticity

 

 

 

Immobile capital Mobile capital
USA Mex. Can. USA Mex Can
Total welfare 0.92 2.31 2.36 0.92 2.22 2.36
Private consumption 0.97 2.45 2.59 0.96 2.49 2.59
Health 0.02 -0.09 0.00 0.02 -0.22 -0.00
Extemality (% welfare) 3.88 -3.40 0.10 4.23 -8.67 -0.00
Emissions change -0.69 1.54 -0.05 -0.75 3.79 0.00
1. Scale effect 0.61 2.41 2.42 0.58 3.30 2.43
2. Allocation eﬂ‘ect -0.45 -l.19 -0.60 -0.48 -0. 80 -0.61
3. Composition eﬁ‘ect -0.13 2.19 0.11 .015 3.13 0.12
4. Regulation eﬂ'ect -0.72 -1.80 -l.90 -0.7l -l.83 -1.90

 

5.4.4. Abatement Function
Another potential source of bias may be that only capital is used for emission

abatement Alternatively, abatement efforts could reduce the value added of a sector. In other
words, irn each sector pollution abatement uses labor and capital in proportion. This has evident
impacts on the incidence of pollution control. While in the central case the burden of pollution
control is mostly borne by labor, in the alternative formulation it is more even It will not be
completely neutral, if abatement intensive industries are more capital-intensive. From the
evidence provided in Chapter 4, we know that there is some, thougln not strong, correlation
between the two. Results from the sensitivity run show that the impact of the assumption is so

small that it can be safely neglected.

189

5.4.5. Labor Supply Elasticity
Of far greater importance is the sensitivity of the results to variatiorns irn the labor

supply elasticity. To this end two extreme cases are considered: ﬁrst, a completely inelastic,

second, an inﬁnitely elastic labor supply.

Z 1..

In ﬁne case of an inelastic labor supply, the scale eﬁ‘ect of NAFI' A is sliglnﬁy reduced
(Table 5-13). This affects most macroeconomic indicators by the same order of magnitude.
However, ﬁnereisasmallshiﬁinﬁnestructureofﬁneeconomy. Sincelaborismorescarce
compared to ﬁne base case, wages increase everywhere slighﬁy, while rents fall. This leads all
ﬁnree econonnies to become more capital-intensive ﬁnan in ﬁne central case. Since capital-
intensive industries tend to be more pollution-intensive, ﬁnere is a small compositiorn eﬂ‘ect
towards pollution intensive production. However, a reduced scale eﬁ'ect and a reduced

regulation eﬁ’ect lead ﬁne overall result on emissions to cancel out.

190

Table 5-13. Central case with labor supply elasticity of zero

 

 

 

Irrnmobile capital Mobile capital
USA Mexico Can USA Mexico Can
GDP 0.61 2.43 2.33 0.53 3.28 2.20
Material product 0.16 1.13 1.70 0.06 2.36 1.58
Capital return (real) 0.60 2.43 2.14 0.63 1.76 1.96
Wages real (net) 0.65 2.24 2.48 0.65 3.58 2.61
Eﬁ'ective labor supply 0.02 -0.09 0.00 -0.07 -0.39 -0.21
Nomirnal labor supply 0.00 0.00 0.00 -0.09 -0. 18 -0.21
Exports 4.66 11.68 14.62 4.24 16.76 14.51
Imports ‘ 3.58 13.31 14.86 3.42 14.55 14.75
Total welfare 0.98 2.34 2.51 0.91 2.19 2.35
Private consumption 0.96 2.39 2.51 0.89 2.31 2.35
Healﬁn 0.02 -0.09 0.00 0. 02 -0.21 0.00
Extemality (% welfare) 3.41 -3.30 0.00 3.91 -8.75 0.01
Emissions -0.64 1.52 0.00 -0.68 3.77 0.00
1. Scale eﬁ‘ect 0.61 2.35 2.33 0.53 3.15 2.20
2. Allocation eﬁee -0.45 -1.19 -0.61 -0.47 -0.79 062
3. Composition eﬁ'ect -0.08 2.18 0.17 -0.08 3.13 0.18
4. Regulation eﬂ‘ect -0.71 -l.75 -1.84 -0.66 -l.70 -1.73

 

IE I ‘i

The oﬁner extreme assumption is a perfectly elastic labor supply function, or,
alternatively, ﬁne ﬁxing of wage levels. Such an assumption increases signiﬁcanﬁy ﬁne net eﬂ‘ect
of NAFTA (three quarter of a % for ﬁne U.S. and Mexico, and 2 % for Canada). The

econonnies become more labor-intensive wiﬁn a relative trend towards less pollution-intensive

production. In addition to increasing ﬁne regulation effect, this mitigates or even over-

compensates ﬁne gowtln of pollution ﬁnat is entailed by ﬁne increased labor supply. No

diﬂ'erence is noticeable between ﬁne cases of mobile and immobile capital. Apart ﬁom ﬁneir
obvious impacts on labor supply and, hence, absolute scale effect of NAFI‘ A, changes in ﬁne

supply elasticity of labor have no impact ﬁnat in any qualitative way changes ﬁne outcome of ﬁne

model.

191

Table 5-14. Central case with inﬁnite labor supply elasticity

 

 

 

 

Immobile capital Mobile capital

USA Mex. Can. USA Mex. Can
GDP 1.40 3.07 4.48 1.30 4.28 4.84
Material product 0.92 1.79 3.84 0.79 3.30 4.31
Capital return (real) 1.75 3.37 5.59 1.81 3.17 5.35
Wages real (net) 0.00 0.00 0.00 0.00 0.00 0.00
Eﬁ'ective labor supply 1.27 2.32 3.80 1.16 3.30 4.19
Nominal labor supply 1.25 2.40 3.80 1.13 3.52 4.20
Exports 5.19 12.30 16.66 4.55 17.52 17.64
Imports 7.12 15.19 18.87 3.92 15.57 17.56
Total welfare 1.28 2.50 2.97 1.26 2.43 2.99
Private consumption 1.98 3.21 5.05 1.89 3.50 5.30
Healﬁn 0.03 -0.08 0.00 0.03 -0.21 O -0.01
Extemality (°/o welfare) 3.62 -3.05 0.08 4.00 -7.78 -0.52
Emissions -0.89 1.50 -0.05 -0.97 3.70 0.30
1. Scale eﬁ'ect 1.40 3.09 4.48 1.30 4.15 4.84
2. Allocation eﬁ‘ect -0.48 -1.26 -0.62 -0.51 --0.81 -0.50
3. Composition eﬂ’ect -0.34 2.11 -0. 12 -0.35 3.01 -0.05
4. Regulation effect -1.46 -2.34 -3.63 -1.39 -2.55 -3.80
5.4.6. Demand Elasticities

resulting in own price demand elasticities of roughly 1.4 for all sectors. A sensitivity simulation

In ﬁne central scenario, a consumption elasticity of substitution of 1.5 is assumed,

reduces ﬁne substitution elasticity to 0.9. The results of ﬁne scenario are presented in Table 5-

15. As should be expected, lower demand elasticity reduces ﬁne overall eﬁ‘ect, alﬁnougln one

might be surprised ﬁnat ﬁne impact of changing this parameter is so small. However, even wiﬁn

a zero elasticity of substitution for private consumption, a positive trade impact would result

This is one ﬁne one hand, because ﬁne import (or Arnnirngton) elasticity allows improvements in

ﬁne allocation of production even if consumption is unchanged Furﬁnermore, ﬁne model

contains a substitution elasticity of government consumption (set to 1) which would remain In

addition, ﬁne resource waste of non-tariﬂ‘ barriers plays a strong role. The beneﬁt of reducing

these barriers will be present, independent of ﬁne size of macroeconomic change.

192

Table 5-15. Simulations with reduced demand elasticity (0.9)

 

 

 

Immobile capital Mobile capital

USA Mex. Can. USA Mex Can
GDP 0.59 2.39 2.37 0.56 3.33 2.67
Material product 0.10 0.93 1.56 0.03 2.19 1.82
Capital return 0.67 2.41 2.39 0.81 1.86 1.86
Wages real (net) 0.55 2.16 2.34 0.49 3.12 2.58
Eﬂecﬁve labor supply 0.05 0.14 0.25 0.04 0.16 0.28
Nominal labor supply 0.03 0.21 0.23 0.02 0.36 0.28
Exports 4.24 10.93 12.76 3.66 15.96 13.53
Imports 3.23 12.43 12.80 3.02 13.88 13.12
Total welfare 0.90 2.28 2.56 0.90 2.15 2.55
Private cornsumption 0.93 2.42 2.78 0.92 2.41 2.81
Health 0.02 -0.07 0.02 0.02 -0.20 0.00
Extemality (°/o welfare) 4.21 -2.67 1.08 4.53 ~8.20 0.05
Emissions -0.73 1.20 -0.54 -0.82 3.37 -O.22
1. Scale eﬂ'ect 0.59 2.39 2.37 0.66 3.20 2.67
2. Allocation effect -0.49 -1.42 -0.79 -0.53 -l.01 -0.85
3. Composition eﬂ‘ect -0.13 2.07 -0.03 -0. 16 2.98 0.06
4. Regulation eﬂ'ect -0.69 -1.78 -2.04 -0.69 -1.77 -2.06

 

The most important and obvious impact of a reduced elasticity of substitution is ﬁnat
most numbers are simply smaller ﬁnan in ﬁne central scenario. In particular, ﬁne clnarnge in trade
volume is reduced However, at ﬁne same time some structural diﬁ‘erences occur. Material
product is relatively reduced, leading to lower pollution increases. This increases eﬁecﬁw
labor supply despite relatively sinking wages. The economy becomes more labor-intensive,
becausewagesareaﬁ‘ectedmoreﬁnanrents.Itcanbenotedalsoﬁnatﬁneallocaﬁoneﬁectis
higher ﬁnan inn ﬁne central case, leading even to a slighﬁy lnigher overall welfare irn Canada
Considering ﬁne lower substitution elasticity ﬁnis is somewhat conunterintuitive. However, ﬁnis
eﬂ'ect is ﬁne result of an improvement in ﬁne terms of trade with ﬁne rest of world by 1 %, as ﬁne
lower demand elasticity compared to ﬁne central case leads to a relative appreciation of ﬁne

NAFTA currencies.

193

5.4.7. Elasticity of Scale

The inclusion of scale elasticities into ﬁne simulation also has a relatively small eﬂ'ect on
ﬁne overall results. The results of setting scale elasticity to zero can be summarized in very
simple terms. For all ﬁnree countries, ﬁne macroeconomic impact of trade liberalization would
be reduced by 10 to 15 %. There is also a slight, yet unsystematic impact on ﬁne pollution eﬂ‘ect
of trade liberalization. Capital mobility makes scale elasticity more important for ﬁne recipients

of capital (Mexico), but does not alter ﬁne results much compared to immobile capital.

5.4.8. Revenue Recycling
A furﬁner set of sensitivity runs replaced ﬁne assumption ﬁnat changes in government

budgets are balanced through government transfers wit ﬁne assumption that budgets are
balanced ﬁnrough changes in labor taxes. This mechanism reduces labor taxes, because ﬁne loss
in tariﬂ‘ revenues is more ﬁnan compensated by increased government revenues induced by
overall economic gowﬁn. Therefore, labor supply and GDP increase. However, ﬁne net
amournts of taxes ﬁnat could be redistributed are small. Consequently, ﬁne impact of a switch to
reducirng labor taxes compared to lump sum transfer is very tiny. Even wages would be

aﬂ‘ectedby less ﬁnan 0.01 %.

5.5. Variations of the Regulation Equation

5.5.1. Various Regulation Elasticities

Clearly; ﬁne level of regulation elasticity is crucial in determining ﬁne net pollution eﬂ‘ect
of trade liberalization. Figure 5-2 shows ﬁne impact of increasing ﬁne irncome elasticity on ﬁne
ﬁnree NAFTA countries for internationally immobile and mobile capital. The gaphs are

normalized such ﬁnat ﬁne trade impact with zero income elasticity is set to l.

194

In ﬁne U.S. and Canada, ﬁne simulations indicate ﬁnat ﬁne GDP impact of an increase in
regulatory stringency is negative. For instance, in ﬁne U.S., a regulation elasticity of 2 would
reduce ﬁne GDP gain by 10 %. By contrast, welfare increases slighﬁy due to reduced pollution
extemalities.

For immobile capital, ﬁne cost of regulation and ﬁne increase in labor productivity
appear to balance out exacﬁy in Mexico. By contrast, overall welfare in ﬁne country increases
substantially, due to ﬁne hedonic component of improved healﬁn Capital rrnobility has little
inﬂuence on ﬁnis pattern, except ﬁnat it widens slighﬁy ﬁne discrepancy between GDP and

consumption.

It should also be remarked upon ﬁrst in a conﬁguration wiﬁn toxicity weights (implying
higher extemality values), ﬁne evaluation of various income elasticities of regulation changes.
Now, for Mexico not just welfare, but also GDP rises wiﬁn income elasticity, because ﬁne
country has high extemalities and low abatement costs. In ﬁne oﬁner two countries, GDP still
drops, as stringency increases. However, in boﬁn cases ﬁne welfare eﬁ‘ect is nnore positive. Of
course, ultimately, ﬁne welfare effects are largely a ﬁnnction of ﬁne starting assurnnptions. The
exact values are also not relevant for ﬁne discussion of ﬁnis paper, which does not focus on ﬁne
question of an Optimal regulation level but on ﬁne consequences of Figure 5-3 shows ﬁne
pollution effects of increased regulation elasticity. In all cases ﬁne curve for total emissions
drops somewhat steeper ﬁnan ﬁnat for ﬁne regulation effect. However, the additiornal impact by
output and composition effects are negligible in practice. For each country, one can derive ﬁne
ﬁnreshold value above which NAFI‘ A will be pollution reducing. (Evidenﬁy, ﬁnis will diﬁ‘er by

type of pollutant). For ﬁne U.S., the value is very low at about 0.2; for Canada ﬁne value is

195

Figure 5.2: The impact of various levels of regulation elasticity on GDP and welfare
(Zero elasticity case set to l)

a) USA (immobile capital)

1.“
1.02
1
O.“
O...
0.84
0.02
0..

00.5

1

1.3

 

2.8

b) Mexico (immobile capital)

1.1
1.0.
1.00
1.04
1.02

1
0.“

e) Canada (immobile capital)

1.02
1.01

1
O.”
0.08
0.01
0.0.
0.“
O.“
0.83

 

 

 

+°°'l

+W¢lhn

 

 

i-o—ooP

+Woltare

l

 

+60?
+Wellare

b) USA (mobile capital)

1.04
1.02
1
I.”
0...
0.“
0.02
0..
0.88

 

 

 

O 0.. 1 1.8 2 2.5

d) Mexico (mobile capital)

1.1
1.08
1.0.
1.04
1.02

1
0.08

 

 

 

00511.52”

1‘) Canada (mobile capital)

1.02
1.01

1
0.”
0.88
0.07
0.”

 

 

 

110.611.5225

196

Figure 5.3. The impact of regulation elasticity on total pollution, growth and
composition effect (percentage changes from pre NAFTA base case)

 

 

 

 

 

 

   

 

 

 

 

 

 

 

 

a) USA (immobile capital) b) USA (mobile capital)
as 0.5
e o
4.6 +roun «0.3 +11“
.1 +6rowﬁn .1 +Growtln
4.. +Connpoa. 4“ +Colnpoa.
4 -2
4.6 4.6
0 0.5 1 1.0 2 2.3 o 0.5 1 1.3 1 u
c) Mexico (immobile capital) (1) Mexico (mobile capital)
7
s
+roun ‘ l-e-roun
+Orowth ‘ +M
+Compos. ; +Cornpoa.
1
o
e) Canada (immobile capital) 1) Canada (mobile capital)
3 s
z 2
‘ +Total ' i-e—rou
° +Growtln o +m
'1 +Compos. '1 +Compos.

 

 

 

sun

00.011.022.‘

 

lob

 

00.011.0210

197

aronmd 0.75. Mexico, by contrast, would need values between 1.4 and 2.2. However, ﬁnere
may be good reasons to believe ﬁnat ﬁne elasticity in Mexico is higher ﬁnan in ﬁne oﬁner two
courntries, due to external and internal pressures, and ﬁne simple fact ﬁnat ﬁne country appears

under-regulated.

5.5.2. Policy Function Connected to Wages
The paper of Rome and Schulze (1996) is based on ﬁne assumption ﬁnat ﬁne

goverrunent balances the interests of labor against ﬁnose of ﬁne environment To assess ﬁnis
hypoﬁnesis, sensitivity runs link ﬁne regulation stringency to real hourly wages instead of private
consumption. Table 5-16 shows ﬁne pollution result when a regulatory elasticity of 0. 75 is
applied The inﬂuence on oﬁner macroeconomic variables is so small ﬁnat it is not worﬁn

reporting on.

Table 5-16. Regulation effect as function of wages

 

 

 

Immobile capital Mobile capital
USA Mex. Can. USA Mex Can.
Emissions -0.37 1.80 0.25 -0.40 3.38 0.27
1. Scale eﬂ‘ect 0.64 2.40 2.46 0.62 3.31 2.48
2. Allocation eﬂ‘ect -0.47 -1.19 -0.60 -0.48 -0.79 -0.61
3. Composition eﬂ‘ect -0.07 2.18 0.16 -0.09 3.13 0.16
4. Regulation effect -0.48 -1.53 -1.72 -0.46 -2.22 -l.73

 

A priori ﬁne simulations will be diﬂ'erent from ﬁne central case only irnsofar as wages
and private consumption diﬁ‘er. As in all cases wage increases are somewhat less ﬁnan welfare
increases, ﬁne regulation effect under ﬁne Bommer-Schulze assumption would be accordingly

smaller. Notably, Canada new reports a pollution increase by 0.25 %.

However, small as ﬁney may be ﬁne difference between ﬁne assumptions applied in ﬁne
central case and ﬁne one applied here overestimate ﬁne true importance of ﬁne hypoﬁnesis. More

important is actually ﬁne assumption of keeping government consumption ﬁxed The policy

198

ﬁnrnctiorn is based on ﬁne development of private consumption If government consurnptiorn is
ﬁxed, for a given GDP increase private consumption must increase at a higher percentage rate
ﬁnarn GDP. Wiﬁn government consumption share at arournd one fourﬁn (ﬁnis excludes transfers),
ﬁne leverage eﬁ‘ect for Canada and ﬁne U.S. is about one ﬁnird For Mexico, ﬁnis is somewhat
smaller. For ﬁnisreason, ﬁne difference between ﬁne Bommer-Schulze assumption and ﬁne one
applied here should not be exaggerated. The results would be very similar, if the same innplicit

elasticities were used in boﬁn cases.

5.5.3. Quantitative Restrictions
An alternative presentation of ﬁne regulation problem could be in ﬁne form of

quantitative restrictions of emission by sector. The government would set ﬁne permissible
emission per unit ofoutput such ﬁnat each sector would achieve exactly ﬁne same percentage
reduction in total emissions independenﬁy of wheﬁner it might be expanding or contracting as a
result of ﬁne regulation. Sectors ﬁnat increase ﬁneir output would ﬁnerefore face relatively
tougher constraints, while emission limits for contracting sectors are relaxed The eﬂ‘ect of such

a regulatory mechanism is reported in Table 5-17.

Table 5-17. Deﬁnition of restriction target in quantities of each sector

 

 

 

Immobile capital Mobile capital
USA Mex. Can. USA Mex Can
Emissions -0.73 -1.81 -1.93 -0.72 -1.85 -1.94
1. Scale effect 0.63 2.43 2.45 0.59 3.32 2.51
2. Allocation eﬂ‘ect -0.46 -1.21 -0.70 -0.47 -0.80 -0.67
3. Composition eﬂ‘ect N/A N/A N/A N/A N/A N/A
4. Modiﬁed Regulation eﬁ'ect -0.90 -2.99 -3.63 -0.84 -4.28 -3.73

 

The values shown here are quite diﬁ‘erent from ﬁnose of ﬁne central case, which is
essentially ﬁne result of a higher de facto regulatory stringency as well as a diﬂ‘erent

irnterpretation of ﬁne results. Most importanﬁy, ﬁne scenario assures ﬁnat ﬁne ennissions

199

reductions desired by a country ex ante will actually occur ex post. In oﬁner words, ﬁne
emissions impact of trade liberalization has a guaranteed negative sign. This is ﬁne result of two
clnarnges compared to ﬁne regulatory setup in ﬁne central case. First, ﬁne composition eﬂ’ect must
be zero. By deﬁnition, relative differences in gowﬁn across sectors are exacﬁy cournteracted by
changes in regulatory stringency. Second, ﬁne implicit regulation impact is substantially
stronger ﬁnan irn ﬁne central scenario. In ﬁne central case, ﬁne regulation effect is ﬁxed, making
ﬁne emissions effect a residual variable. In ﬁne case of quantitative restrictions, ﬁne emission
eﬁ‘ect is ﬁxed, leaving ﬁne regulation effect to be determined. Sirnce for ﬁnis inherenﬁy diﬁ'erent
mecharnism ﬁne same elasticity of 0.75 is applied, ﬁne eﬂ'ective stringency is higher ﬁnan in ﬁne
central case, which prohibits a direct comparison of ﬁne eﬂ‘ectiveness of ﬁne different regulatory
regimes.“ As a secondary effect of ﬁnis increased stringency, ﬁnere is a slight reduction in

gowth, as could be expected ﬁom ﬁne discussion in ﬁne previous section.

Therefore, a quantitative regulation setting is not very interesting and would not need
ﬁne arnalytical tool of an integated CGE model, because ﬁne eﬁ‘ect could simply be calculated
externally. Noneﬁneless, such a scheme nnight conceivably be employed to mitigate ﬁne impact
of trade liberalization, as losers are treated more lenienﬁy ﬁnan winners. However, ﬁnis would
leave open a number of questions concerning ﬁne implicit formulation of environmental

policies.

 

‘6 Comparable stringencies would require ﬁxing identical joint impacts of income on regulation
nninus gowth. However, this would not solve the fundamental dilenma that the overall emissions
eﬂ‘ect is a foregone conclusion.

200

5.6. Unilateral Actions

5.6.1. Unilateral Changes in Abatement Intensity

A potential diﬁculty in interpreting impact of regulation elasticities consists inn ﬁne
assumption that changes occur in all ﬁnree countries at ﬁne same time. This assunnptiorn leaves
two open ends. First, since ﬁne regulation level for Mexico is substantially lower ﬁnarn irn ﬁne
United States or Canada, even an increase ﬁnat is relatively higher in Mexico ﬁnan in ﬁne oﬁner
countries might still increase the absolute attractiveness of ﬁne country for polluters. Second,
simultaneous changes irn abatement eﬁ’ort do not allow an analysis of a unilateral increue irn
regulations.

Simulations of a unilateral reduction irn unit emissions by one ﬁnird illumirnate ﬁnis
aspect. This increase in the stringency is ex ante only. To ﬁne extent ﬁnat ﬁne scenarios might
change private consumption, ﬁne ex post ﬁgure might deviate ﬁom ﬁnis. There is no discernible
diﬂ‘erence between ﬁne impact of a unilateral increase in regulation wiﬁn an wiﬁnout NAFTA
For ﬁnis reason, only ﬁne pre-NAFI‘ A set is reported Therefore, in practice, NAFTA does not

limit ﬁne possibility to set environmental standards in any of ﬁne countries.

The direct impact of ﬁne increase in U.S. regulatory stringency is forGDP to sirnk by
2.3 °/o (Table 5-18). The incidence of ﬁne regulation falls exclusively on wages (-4.76 %),
because effective labor supply increases by 0.35 % do to a large improvement irn healﬁn By
corntrast, capital actually beneﬁts due to ﬁne demand for abatement equipment and ﬁne irncreased

labor supply (+3.17 %). The U.S. economy becomes more labor-intensive.

The pollution eﬂ'ect of ﬁne regulation is noticeably higher ﬁnan what would be expected
by ﬁne regulation effect only. Next to ﬁne contracting GDP, ﬁne composition effect plays a

substantial role, as production moves away from abatement and pollution-intensive goods.

201

I‘ll.

Most of ﬁnis reﬂects actual changes in consumption, only relatively little of ﬁne composition
eﬂ‘ect is conmterbalanced by concomitant increases in pollution-intensity irn Mexico arnd
Canada For ﬁnese two countries, ﬁne effect of production relocation is much too small to
compensate ﬁnem for ﬁne loss ﬁney suﬂ‘er as a result of ﬁne changes in ﬁne U.S. Due to a
simultaneous increase in import prices for U.S. products and a contraction irn their largest

export markets, Mexico and Canada suffer GDP losses of more than 0.3 %.

Table 5-18. Unilateral reduction in unit emissions by one third in the United States

 

 

 

Immobile capital Mobile capital
USA Mex. Can USA Mex Can
GDP -2.28 -0.29 -O.29 -2.20 -1.01 -0.83
Material product -2.22 -0.02 -0.08 -2. 10 -1.20 -0.80
Capital return (real) 3.17 -0.31 -0.28 2.93 0.22 1.17
Wages real (net) -4.76 -0.27 -0.27 -4.67 -1.13 -0.94
Effective labor supply 0.35 -0.05 -0.04 0.36 -0.09 -0.14
Nominal labor supply -0.71 -0.03 -0.02 -0.69 -0. 18 -0.16
Exports -0.50 0.3 1 -0.08 0.43 -4.54 -2.06
Imports -0.59 0.33 0.02 -0.30 -1.03 -0.62
Total welfare -1.06 -0.36 -0.35 -1.06 -0.24 -0.34
Private consumption -2.84 -0.35 -0.36 -2.83 -0.35 -0.46
Healﬁn 1.07 -0.03 -0.01 1.06 0.09 0.01
Extemality (°/o welfare) -174.94 6.67 6.14 -174.70 -32.59 -7.35
Emissions -36.80 0.48 0.42 -36.69 -l.59 -0.50
1. Scale eﬁ'ect -2.28 -0.29 -0.29 -2.20 -l.01 -0.83
2. Allocation eﬁ‘ect 0.06 0.27 0.21 0.09 0.01 0.03
3. Composition eﬁ‘ect -4.42 0.23 0.23 -4.37 -0.65 -0.05
4. Regulation eﬁ'ect 32.37 0.27 0.27 -32.37 0.26 0.34

 

The diﬂ‘erence between simulations wiﬁn internationally mobile and irnnnobile capital is
surprisingly small for ﬁne United States. The U.S. is actually better oﬁ‘ wiﬁn mobile ﬁnarn wiﬁn
immobile capital, because it attract capital ﬁ'om neighboring countries. This might be contrary
to intuition, as one could expect ﬁnat ﬁne increased abatement costs leads capital to ﬂee ﬁne

country. However, since capital returns in ﬁne U.S. actually increase due to a higher eﬁ‘ective

202

labor supply and lower wages. (It can be demonstrated ﬁnat ﬁne two eﬁ'ects cancel out, when

ﬁne healﬁn eﬂ‘ect of reduced emissions is forced to zero.)

The net capital migration to ﬁne U.S. because of ﬁne regulation causes ﬁne composition
eﬁ‘ect in all ﬁnree countries to turn negative. This is a crucial diﬂ'erence. In ﬁne case of
immobile capital, trading partnners counteract ﬁne composition eﬂ‘ect in ﬁne regulating country.
In ﬁne case of mobile capital, ﬁne allocation eﬁ‘ect is exported to ﬁne trading partrners. For ﬁnis
reason, ﬁne welfare and income effect in Canada is substantially rrnore negative ﬁnan for

immobile capital. However, Mexico beneﬁts due to lower pollution levels.

Table 5-19 shows ﬁne effect of a unilateral regulatory increase in Mexico. Given ﬁne
appropriate adjustment for ﬁne size of ﬁne economy, ﬁne eﬂ‘ect of increased regulation inn Mexico
islargelyﬁnesameasﬁnatofaunilateral actionbyﬁneUnited States. GDP dropsinallﬁnree
courntries. However, in ﬁne case of Mexico, low abatement costs and high externnalities actually
lead to an increase irn overall welfare in ﬁne country. Again, owners of capital become better off
ﬁnan wiﬁnout ﬁne regulation. Due to its small size, ﬁne inﬂuence Mexico has on ﬁne other two
countries is minor but slighﬁy negative. The composition effect induced in all ﬁnree countries
has ﬁne expected sign, but is small. Capital mobility reinforces ﬁne eﬁ‘ects ﬁnat occur in ﬁne case
of immobile capital. In ﬁne case at hand, ﬁne favorable effect of regulation on capital return
leadsto a noticeable inﬂow of capital to Mexico. Finally, Table 5-20 reports ﬁne Canadiarn case,

which is mutatis mutandis ﬁne same as ﬁnat of ﬁne United States.

203

Table 5-19. Unilateral reduction in unit emissions by one third in Mexico

 

GDP

Material product
Capital return (real)
Wages real (net)
Effective labor supply
Nominal labor supply

Exports
Imports

Total welfare

Private consumption
Healﬁn

Extemality (% welfare)

Emissions

1. Scale effect

2. Allocation eﬂ‘ect

3. Composition eﬂ‘ect
4. Regulation eﬂ‘ect

 

 

Immobile capital Mobile cmital
USA Mex. Can. USA Mex. Can
-0.004 -0.l88 -0.002 -0.006 -0.135 -0.002
-0.001 -0.363 -0.001 -0.003 -0.288 0.000
-0.004 0.359 -0.001 0.002 0.328 -0.002
-0.004 -2.860 -0.001 -0.006 -2.809 -0.001
-0.001 1.539 0.000 -0.001 1.544 0.000
0.000 -0.383 0.000 o0.001 -0.374 0.000
0.010 -0.125 -0.002 -0.013 0.176 0.000
0.014 -0.214 -0.001 0.007 -0.131 0.000
-0.005 1.012 -0.002 -0.005 1.009 -0.002
-0.005 -0.238 -0.002 -0.005 -0.236 -0.002
0.000 1.930 0.000 0.000 1.925 0.000
5.822 165.272 8.759 2.053 165.466 7.907
0.006 -33.855 0.003 0.002 -33.769 0.003
-0.004 -0.188 -0.002 -0.006 -0.135 -0.002
0.004 -0.225 0.001 0.003 -0.153 0.001
0.002 -0.539 0.002 0.001 -0.483 0.002
0.004 -33.254 0.001 0.004 -33.254 0.002

 

Table 5—20. Unilateral reduction in unit emissions by one third in Canada

 

GDP

Material product
Capital return (real)
Wages real (net)
Eﬂ‘ective labor supply
Nominal labor supply
Exports

Imports

Total welfare

Private consumption
Healﬁn

Extemality (°/o welfare)

Emissions

1. Scale eﬂ‘ect

2. Allocation effect

3. Composition eﬁ‘ect
4. R5gulation eﬂ'ect

 

 

Immobile capital Mobile capital
USA Mex Can. USA Mex Can.
-0.04 -0.01 -1.76 -0.11 -0.13 -1.05
-0.01 0.00 -2.21 -0. 10 -0. 15 -l.28
-0.04 -0.01 3.99 0.15 0.03 2.11
-0.04 -0.01 -4.87 -0.12 -0.14 -4.04
-0.01 0.00 0.25 -0.02 -0.01 0.41
0.00 0.00 -0.76 -0.02 -0.02 -0.58
0.04 0.00 -0.81 -0.64 -0.58 1.83
0.13 0.00 -1.41 -0.08 -0.14 -0.58
-0.04 -0.01 -0.76 -0.05 -0.02 -0.76
-0.05 -0.01 -2.44 -0.07 -0.04 -2.32
0.00 0.00 1.02 0.00 0.01 1.00
6.57 13.38 -228.64 -6.20 -52.31 -224.72
0.06 0.04 -35.17 -0.06 -0.23 -34.36
-0.04 -0.01 -1.76 -0.11 -0.13 -l.05
0.03 0.01 -0.45 0.01 -0.02 -0.22
0.03 0.03 -1.78 -0.01 -0.11 -1.43
0.04 0.01 -32.51 0.05 0.03 -32.55

 

204

5.6.2. Sectorally Optimal Regulation
A fnnrﬁner interesting simulation run is to test what would happen, if countries

introduced an optimal regulation ﬁnat equalizes ﬁne marginal abatement costs across sectors.
Table 521 shows ﬁne result of such a regulatory change. The abatement values are calculated
to meet ﬁne same emissions level as in ﬁne pre-NAFTA scenario for a constant production
structure. The level of stringency iswnot adjusted to account for sectoral changes ﬁnat are
introduced by ﬁne improved regulation. For ﬁnis teaser, ﬁne overall pollution eﬂ‘ect diﬂ‘es from

2610.

Table 5-21. Optimal sectoral regulation level

 

 

 

Immobile capital Mobile capital

USA Mex. Can USA Mex Can
GDP 0.59 0.26 0.52 0.68 0.51 0.59
Material product 0.63 0.25 0.69 0.62 0.58 0.62
Capital return (real) -0.54 0.15 -0.72 -0.53 0.01 -0.59
Wages real (net) 1.05 0.47 1.15 1.04 0.72 1.08
Eﬂ‘ective labor supply 0.09 0.07 0.16 0.09 0.08 0.15
Nominal labor supply 0.14 0.06 0.16 0.14 0.10 0.15
Exports 0.36 0.18 0.50 0.32 1.50 0.31
Imports 0.39 0.21 0.63 . 0.37 0.57 0.57
Total welfare 0.63 0.31 0. 75 0.63 0.30 0.75
Private consumption 0.80 0.33 0.87 0.81 0.34 0.85
Healﬁn -0.05 0.00 0.00 -0.05 -0.03 0.00
Extemality (°/o welfare) -14.34 0.84 -0.34 -14.26 -7.50 0.22
Errnissiorns 1.73 -0.05 0.05 1.73 0.44 -0.03
1. Scale eﬁ'ect 0.59 0.26 0.52 0.68 0.51 0.59
2. Allocation eﬁ‘ect 0.03 -0.01 0.17 -0.06 0.07 0.03
3. Composition eﬂ'ect 1.71 -0.06 0.01 1.71 0.12 -0.02
4. Rggplation eﬂ‘ect -0.60 -0.25 -0.65 -0.60 -0.26 -0.64

 

Since sectoral diﬁ‘erences in ﬁne marginal abatement costs are quite large, induced

gowth is substantial and reaches 0.6 to 0.7 °/o of GDP in ﬁne U.S. The gain for Mexico is only

205

0.26 to 0.5 % due to a smaller level of abatement expenditures. The improved regulation also
induces signiﬁcant composition changes, which, in ﬁne United States, irncreases pollution
compared to ﬁne base case. This could mean ﬁnat ﬁne more polluting sectors are relatively over-
regulated, and beneﬁt ﬁom ﬁne lower burden ﬁnat is now imposed on ﬁnem. An alterrnative
explanation could lie in ﬁne incidence of ﬁne regulatory change. It can clearly be seen that ﬁne
capital rents drops because of reduced demand for abatement capital. (The only country where
capital does not suffer is Mexico, where beneﬁts from trade wiﬁn ﬁne United States are more
important ﬁnan reduced capital demand). By contrast, labor beneﬁts ﬁ'orn ﬁne better regulation
ﬁnrough higher wages. Consequenﬁy, ﬁne NAFTA econonnies move into ﬁne direction of

increased capital intensity, which inﬂuences ﬁne sectoral emissions eﬂ‘ect.

5.6.3. Some Considerations on the Optimal Emissions Level
In ﬁnis context, one could also calculate an optimum optimorum, for which not just ﬁne

relative level of regulation would have to be ﬁxed, but also ﬁne absolute emissions. While an
analytical solution is raﬁner complex, ﬁnis could be done in a simple search procedure by
increasing ﬁne stringency levels until ﬁne maximum welfare level is attained. However, in light
of ﬁne great uncertainties attached to ﬁne values of extemalities, such a calculation itself does

not provide useful insights. Instead, we limit ourselves here to some ﬁneoretical consideratiorns.

For ﬁne functional form chosen for ﬁne overall utility level", it can be demonstrated that

ﬁne optimal share of abatement expenditures in ﬁne total economy is constant. This is shown in

 

"Utility(U)isacompositeofmaterialwell-beingMandhealth(inaccordingtothecquation
U=W.

206

ﬁne Appendix This optimal share of abatement expenditure rises when ﬁne extemality is high
and abatement costs are low. The utility function implies a unitary elasticity of pollution
abatement expenditures wiﬁn respect to income increases. This mearns ﬁnat ﬁne optimal
regulatory elasticity of income would be zero. The reason is ﬁnat ﬁne for ﬁne selected fnmctiornal
form, boﬁn marginal costs and beneﬁts increase in proportion to income, leaving ﬁne beneﬁt-

cost ratio of unit emissions unchanged

However, for several reasons, ﬁne functional form should not let one presume that ﬁne
income elasticity of regulation is zero. First and importanﬁy, ﬁne functional form is arbitrarily
chosen for illustrative purposes. It could be changed into a linear expenditure function wiﬁn
minimum consumption levels to change ﬁne income elasticity of healﬁn such ﬁnat a cetairn
income elasticity of regulation is implied. Preference is given to ﬁne present fnrrnctiornal form,
because it is simple and has no inﬂuence on actual behavior. Furﬁnermore, precise information
is unavailable on which to base a diﬁ‘erent ﬁmctional form. Second, ﬁne furnction shows ﬁne
importance of good regulation. A move towards a better type of regulation (e. g ﬁne sectoral
adjustment simulated furﬁner up) leads boﬁn to a lower pollution level and an increase irn overall
abatement expenditures. Third, ﬁne zero elasticity result only holds for an optimum paﬁn of
regulation. It is highly doubtful ﬁnat any country has achieved ﬁnis. To ﬁne extent ﬁnat regulation
levels are below ﬁne optimum, one would expect a higher increase irn regulation. Fourﬁn, ﬁne
functional form assumes irnpliciﬁy ﬁnat no structural change occurs irn ﬁne economy, which
would alter ﬁne beneﬁt cost relationship of abatement However, ﬁne main eﬁect of trade
liberalization lies exacﬁy in a change in ﬁne economy. Fifth, ﬁne formulation reﬂects preferences
and not a political furnction, which rrnight be different Sixth, teclnrnical progess in abatement

wchnology is not irncluded in ﬁne calculus of ﬁne equatiorn, which would lead to a higlner level of

207

abatement and lower emissions. Wiﬁn ﬁnese limitations in rrnind, a tentative resume of ﬁne

simulation results is drawn in ﬁne next section.

5.7. Tentative Conclusions

This chapter presented model simulations of trade liberalization under a large variety of
diﬂ'erent assumptions. Before coming to an overall assessment on ﬁne ﬁnree empirical
hypoﬁneses on trade and environment, a brief synopsis is presented here. Conclusions can be
drawmﬁrstenﬁneuseﬁﬁnessofﬁneanalyticaltool itself; secondonﬁne concretecaseofﬁne
environmental impact of NAFTA; ﬁnird, on ﬁne importance of various factors for determining
ﬁne overall results; arnd fourth, on recommendations for environmental policy in an open

economy. These four will be brieﬂy addressed here.

LEW

The simulations have demonstrated that ﬁne issue of trade and environment can be
successfully addressed in a in a CGE model. Important limitations to ﬁnis approach can be
found less in ﬁne modeling itself ﬁnan in ﬁne lack of reliable data However, ﬁne possibility of

data construction in ﬁne CGE approach makes ﬁne data problem much less constraining ﬁnan in

alternative meﬁnods.

A particular advantage of ﬁne modeling approach chosen is ﬁnat it allows a decompositiorn
of the underlying processes ﬁnat determine ﬁne overall environmental result. The disaggegation
into an effect on gowﬁn, allocation efﬁciency, composition, and regulatory stringency is also of

geat assistance in identifying important data and policy parameters.

208

' n i f NAFTA
The simulations allow robust ﬁndings for ﬁne analysis of trade liberalizatiorn. Of
particular importance in ﬁnis context is ﬁne model-endogenous regulation-setting. The model
runs indicate ﬁnat concerns that trade liberalization might lead to an environmental erosion are

largely misplaced for two reasons.

First, ﬁne correlation between trade liberalization and specialization in polluting industry
is weak. The paper ﬁnds ﬁnat, as a result of NAFTA, Mexico specializes relatively in polluting
sectors, ﬁne United States in less polluting ones, wiﬁn mixed results for Canada However, ﬁnis
specialization is far ﬁom systematic and is dominated by ﬁne trade impact on ﬁne location of just
one sector (oil and petrochemical industry). For ﬁnis trade specializatiorn, ﬁne importance of
diﬁ‘erences in environmental stringency among countries is small. Instead ﬁne trade
specialization is strongly dominated by differences in ﬁne relative capital-labor endownnents of
ﬁne courntries. The ﬁndings mean in practice, ﬁnat trade and environmental policies can be

pursued relatively independent ﬁom each oﬁner.

Second, it is demonstrated ﬁnat even in the country ﬁnat ends up specializing irn ﬁne
relatively polluting sectors (in this case Mexico), trade liberalization results in at nrost a small
deterioration of ﬁne environment, if reasonable assumptions are employed for an income—
induced demand for abatement effort. In many cases, it would ﬁnerefore be counteproductive

to erect trade barriers, if one wanted to preserve ﬁne environment at home and abroad.
W
The analysis allows to identify ﬁne factors ﬁnat are important in driving ﬁne results. Table

5-22 summarizes ﬁne ﬁndings of ﬁne various sensitivity runs. In terms of ﬁneir importance,

issues concerrning model structure and data can be sorted into a group of important factors and

209

 

a goup wiﬁn low or predictable effects. To ﬁne goup of important factors belong capital
rrnobility, ﬁne importance of ﬁne oil sector, ﬁne choice of pollutant, and, evidenﬁy, ﬁne regulatiorn
elasticity. The impact of ﬁne ﬁrst ﬁnree factors on overall pollution is mainly ﬁnrougln ﬁneir

inﬂuence on ﬁne composition effect, while regulations obviously reduce emissions direcﬁy.

Oﬁner factors, such as ﬁne value of ﬁne extemality, ﬁne abatement elasticity or functional
form, labor supply elasticity, and econonnies of scale, have a small impact on ﬁne modeling

results. Demand elasticities can have a substantive impact on ﬁne overall magnitude of ﬁne trade

 

impact, but leave ﬁne structure of ﬁne emissions impact unaffected.
4 li r

The analysis of policy variables allows three important conclusions. First, ﬁne regulatiorn
elasticity is of essential importance for ﬁne determination of net results. In ﬁne central case, ﬁne
inclusion of ﬁnis parameter results in a ﬁmnly positive environmental impact in ﬁne U.S. instead
of trade leading to a deterioration of ﬁne environment. Despite substantive gowth, ﬁne polhrtion
impact on Canada is zero. In Mexico, ﬁne trade impact remains negative. However, it is
substantially reduced If it were not for ﬁne special case of ﬁne petroleum sector, ﬁne trade
ageement would lead to an overall environmental improvement It can ﬁnerefore be said that it
is not possible to assume a ﬁrm link between trade liberalization and environmental
degadation. On ﬁne contrary, insofar as wealﬁn is a precondition for regulation setting, trade
opening is likely to be an essential ingredient for achieving a clean environment Furﬁnermore,
ﬁne impact of gowﬁn is more benign, ﬁne higher ﬁne regulation elasticity is. This means ﬁnat
from an environmental point of view ﬁne key leverage should be at supporting political

institutions in poorer countries rather ﬁnan in blocking trade.

210

i

Table 5-22. Analysis of different factors on their influence on modeling results

 

Factors Explanation of Macroeconomic Environmental Remarks
simulation ' impact

1. Extemality Inclusion of a Lowers effective Small (less gowth Deﬁnition aﬂ'ects
health extemality, labor supply, balanced by less welfare assessment
reducing also slighﬁy lower stringent
effective labor regulation)

2. Capital Allows capital to be Capital ﬂows to Relocates pollution Important for

mobility mobile intra- MX, CN due to across countries oveall analysis
NAFTA economic growth

3.1mportance Allirnpactofoil Canrevertsignfor Sectorisextrernely

of oil sector sector on emission structural and important for
calcnnlation is left overall eﬂ‘ect overall analysis of
out pollution eﬂ'ect

4. Exclusion of Trade barriers for Reduction in Lesser impact of Mitigates overall

petroleum petroleum trade NAFTA beneﬁts; NAFTA, but no effects, but results

sector from between Mexico large changes in oil sign reversals are qualitatively

trade and other countries actor still occur robust

libe'alimtion remain in place due to intermediate

dennand expansion

5. Variation in Use of toxicity Same as above Same as above. Results are robnrst,

extemality index increases however, largely
extemality by 40% due to high weight

of TSP.

6. Pollution Use of alternative Possibility of sign Fairly robust results

indicators indicators such as reversal but net effect for
TSP, PM10, 802, individual pollutant
N02, CO, VOC, is driven by fairly
and Toxicity few sectors

7. Abatement Lower elasticity Lower gowth as Practically Negligble impact,

elasticity makes pollution result of reduced unchanged but aﬂ'ects
reduction more regulatory cost-
expensive beneﬁt calculus

8. Abatement Labor enters Alters incidence of Not systematic No inﬂnrernce on

fnnnctiorn abatement function regulation on labor aggegate values,
nexttocapital andcapital,and butaﬂ’ectssectoral

individual sectors. structure

9. Labor supply Variation of labor Higher labor supply Pollution increases, Can be neglected

elasticity supply elasticity ‘ elasticity increases but scale eﬁ‘ect is within realistic
from 0 to inﬁnite GDP gowth mitigated by stricter range of elasticity

regulation

 

211

continued

Table 22 (continued): Analysis of different factors on their inﬂuence on

 

 

modeling results
Factors Explanation of Macroeconomic Environmental Remarks
simulation impact impae
10. Demand Reduction of Reduces trade Less total impact Marked inﬂuence
elasticities demand elasticities beneﬁts (less than across the board; no on magnitude of
’ proportional) sign reversals trade impact, but
inconsequential for
qualitative results
11. Economies Set scale elasticities Gains of trade Slighﬁy reduced Practically no
of scale to zero specialization are scale eﬂ'ect inﬂuence
diminished by a
small amount
12.Revenue Recyclingof Reduced labortaxes Noneinpractice Canbeneglectedin
recycling government induce a tiny scale case at hand
revenues via labor effect
taxes or transfers
13. Regulation Income elasticity of Higher elasticity The higher the Extremely
elasticity regulation varies reduces gowth elasticity ﬁne lower important in oveall
between 0 and 2 slighﬁy; could be overall pollution. pollution impact of
even positive in trade h’beralintion
case of MX
14. Policy Instead of total Deviation of wages Not systematic and Can be ignored
function income, wages from income is not very srrnall
connectedto determineregulato- sogeatastomake
wages ry stringency a difference
15. Quantita- Emissions are Sets lnigher Redeﬁnes structural No noticeable
tive restrict- restricted by sector, restrictions for trade ennission eﬂ‘ect impact on aggegate
ions instead of per unit winners; slightly reenlts; difﬁcult
of output more balanced interpretation of
sectoral distribution pollution change
of effects decomposition
l6. Unilateral Increase in Reduced or Large reductions Countries can set
action regulatory unchanged growth possible in home regulation
stringency by just in home country country; pollution unilaterally even in
one country and trading leakage rrnininnal an open economy
partners
1?. Optimal Sets marginal Lower abatement Knock-on effects Regulamry
sectoral abatement costs of costs; higher beyond emission elasticity might
regulation allsectors equal growthandwelfare neutrality dnreto increaseasresnnltof
gains; composition sectoral changes better regulation;
of economy moves however, this is not
towards less analyzed here
polluting sectors.

 

212

 

Second, regulations can be set independenﬁy of ﬁne trade regime. The simulations have
shown ﬁnat even when regulatory stringency is increased by 50 % nmilaterally, there will be
only small increases or even decreases in pollution in ﬁne trading partners. This does not change
as a result of trade liberalization. It should be pointed out, however, ﬁnat ﬁne model could only
accournt for changes ﬁnat are made on top of existing regulations. It cannot disprove ﬁnat

sensitive industries might have already nnigated to pollution havens.

Third, good regulation setting can yield a double premium. Foremost, it frees resources
ﬁnrougln a better allocation of abatement expenditures and results in economic gowﬁn and
increased welfare. Second, it improves ﬁne beneﬁt-cost ratio of regulation of regulations,
makirng stricter abatement more attractive. The most can be gained by ﬁne most regulated
ecornorrnies. The induced composition effect is ambivalent. It appears ﬁnat ﬁne rrnost polluting are
at ﬁne same time ﬁne relatively most over regulated industries. However, ﬁnis is subject to ﬁne
caveat of statistical limitations. It does not emerge ﬁom ﬁne simulations ﬁnat trade inﬂuences in
any (signiﬁcant) way ﬁne optimal structure of regulation, as ﬁne structural trade impacts are

relatively small and unsystematic.

The ﬁnal chapter will summarize ﬁne main ﬁndings of ﬁnis paper and put ﬁnem into ﬁne

analytical context

213

CHAPTER 6

SUMMARY AND CONCLUSIONS

6.1. Research Question

6.1.1. Introduction

Much of ﬁne economic literature signiﬁcanﬁy nnisjudges ﬁne net impact of trade on ﬁne
environment, because it takes sectoral emission factors as constant However, ﬁnis assumption
conﬂicts wiﬁn ﬁne common observation ﬁnat wealﬁnier countries apply stricter errnission
standards. The paper shows ﬁnat ﬁne inclusion of an endogenous regulation-setting in ﬁne
analysis substantially alters ﬁne environmental results of trade liberalization The endogenous
treatment of regulation-setting in a CGE model applied on a NAFTA data set indicates ﬁnat irn
various simulations, stricter standards eiﬁner reduce net pollution eﬁ‘ects to a fraction of their
uncorrected values or, in most cases, lead trade to reduce pollution levels. This outcome
provides evidence to what can be formulated as institutional optimism in ﬁne trade arnd
environment debate: pollution reduction from trade-induced institutional change compensates
for ﬁne pollution increase caused by gowth and compositionchanges ﬁrst result ﬁom trade.
Institutional change is a necessary condition for trade to have ﬁne eﬂ'ect of beirng
environmentally beneﬁcial. Policies to improve ﬁne environment in oﬁner courntries should,

therefore, focus on institution building rather ﬁnan on trade.

The remainder of ﬁnis section brieﬂy recapitulates ﬁne literature on trade arnd environment
and develops ﬁne ﬁneoretical base for the analysis. Section 2 describes ﬁne CGE model

constructed. Section 3 deﬁnes ﬁne policy scenarios applied to ﬁne model. Section 4 focuses on

214

ﬁne nnacroecornonnic aspects of ﬁne simulations, while Section 5 traces ﬁne environmental

consequences. Section 6 concludes.

6.1.2. Literature Review: Traditional Pessimism

Chapter 1 shows ﬁnat ﬁne question of wheﬁner trade liberalization is harmful to ﬁne
environment has generated a substantial body of empirical and ﬁneoretical literature (cf. surveys
by Dean 1992; Beghin et al 1995; Ulph 1994). The ﬁneoretical and empirical literature has
advanced in a number of ways. The discussion can be divided into two important empirical
hypotheses: (1) ﬁne traditional pessimism and (2) ﬁne poverty attraction hypoﬁnesis. These are

complemented by (3) ﬁne institutional optimism hypoﬁnesis developed in ﬁnis paper.

The traditional pessimism hypoﬁnesis on trade and environment derived ﬁ'om a

straightforward extensiorn of ﬁne Heckscher-Ohlin model of comparative advantage:

Traditional gssimism hmthesis: diﬁerences in environmental regulations are an
important factor in industrial location (industrial ﬂight hypothesis). Since companies can
avoid regulations by locating abroad, ﬂee trade erodes the independence of a country to set

environmental policies and exerts a strong pressure towards lax regulation (pollution haven
hypothesis).

A broad consensus has emerged in ﬁne literature ﬁnat regulatory diﬂ'erences(wiﬁn some
exceptions) have, at best, a negligible impact on industrial location largely due to ﬁneir small
cost share. This result emerges boﬁn from studies looking at foreign direct investment (Leonard

1988; Xing arnd Kolstad 1996; Bouman 1996; Birdsall and Wheeler 1992) arnd trade ﬂow

215

analysis (Walter 1973 ; Kalt 1988; Jaﬂ‘e et al. 1995; Robison 1988; Sorsa 1994; Low and
Yeats 1992; Tobey 1990; van Beers and van den Bergh 1996, Scherp and Suardi 1997).“ In
its wake, ﬁne empirical consensus has substantially reduced ﬁne weight trade considerations
have on regulation setting. There is also litﬁe evidence to suggest that countries (at least

consciously) lure businesses wiﬁn low environmental standards (Leonard 198 8).

However, ﬁne consensus ﬁnat regulation setting is not of geat importance in industrial
location still leaves ﬁne problem ﬁnat trade between countries wiﬁn vastly diﬂ‘erent regulations
might have a quite damaging environmental impact This is particularly important irn ﬁne
context of North-South trade, where econorrnic specialization in polluting sectors can meet low
environmental standards (Walter arnd Ugelow 1979; Copeland and Taylor 1994 1995;

Chichilrnisky 1994). A modiﬁed empirical hypoﬁnesis can be formulated.

Rover-Lu mgg‘on Mthesis: pollution-intensive sectors tend to be attracted to poor

countries. Free trade leads to environmental degradation in poor countries, because the

trade specialization is met with lax environmental regulation.

The poverty attraction hypoﬁnesis differs from ﬁne traditional pessimism hypoﬁnesis irn
two aspects. First, while ﬁne traditional pessinnism hypoﬁnesis applies also to countries wiﬁn
equal levels of development, ﬁne poverty attraction hypoﬁnesis expressly centers on courntries at
differing levels of economic development Second, while regulatory diﬂ‘erences drive ﬁne
traditional pessimism hypoﬁnesis, ﬁnis factor is incidental for ﬁne poverty attraction hypoﬁnesis.

Specialization results from oﬁner factors such as relative capital endowments or diﬂ‘erences irn

 

“Howeve,theassenbledevidencenmybeweakenedbythefactthatmostnudiesrelyonthe

216

human capital. The evidence lends some support to environmentalist fears. A number of
enpirical studies conﬁrm ﬁnat developing countries tend to specialize in dirty industries
(Hettige et al. 1992; Low and Yeats 1992; Birdsall and Wheeler 1992, Dessus arnd Bussolo

1998).

6.1.3. The Environmental Kuznets Curve
Anoﬁner branch of empirical research hints ﬁnat ﬁne relatiornship between a country’s

wealﬁn and pollution follows an inverted U (Selder and Song 1994; World Bank 1992; Shaﬁk
1994; Grossman and Krueger 1995; Lucas at al. 1992; Rock 1996)". This phenomenon is
known also as environmental Kuznets curve. It denotes ﬁne observation ﬁnat ﬁne least developed
countries have relatively low levels of toxic release, countries undergoing industrialization are
highly polluted, and post-industrial countries are relatively clean. However, ﬁnese ﬁndirngs are
contested. Neiﬁner is it clear where ﬁne turning point nnight be located, nor does ﬁne absolute
level of pollution decline in all cases (Esty and Gentry 1998). Furﬁnennore, some resource

degadation in early development phases might not be reversible.

A part of ﬁne observed environmental Kuznets curve can be explained by ﬁne typical
economic development pattern. Durirng an early development phase, a risirng pollutiorn level
accompannies ﬁne economic specialization in ﬁne relatively dirty secondary sector. During a later
development phase, a falling pollution level follows the gowﬁn of ﬁne relatively clean tertiary

sector. This development results from ﬁne interaction of factor endowment wiﬁn ﬁne structure of

 

same data set compiled by ﬁne World Bank (Hettige et al. 1995) on which this study also draws.
‘9 Lopez (1994) derives the result ﬁom a theoretical model.

217

denand Poor countries tend to have a high demand for basic productiorn, which tends to be
dirty, boﬁn for ﬁnal consumption goods, as well as for investment Cornsurrnption irn wealthier
countries tends to be more directed towards durable, semi-durable and perishable goods and
services. At ﬁrst glance, ﬁnis observation supports ﬁne poverty attraction hypoﬁnesis. However,
ﬁnis hypothesis alone cannot explain ﬁne reduction in pollution, because in practice dirty sectors

shrinks only in relative but not in absolute terms.

6.1.4. Decomposition of Pollution

The mecharnisms that could explain ﬁne downward sloping part of ﬁne envirorunental
Kuznets curve can best be explained by disaggegating pollution causation into four

components”, all of which are affected by ﬁne trade regime (Figure 6-1).

Figure 6-1. Decomposition of Pollution Causation

 

 

Pollution = GDP ‘ Production * 2c, * Pollution ,

/ GDP / Production,

1. Scale 2. Allocation Efﬁciency 3. Composition 4. Emission factor
(Regulation) -

 

5° Grossman and Krueger (1995) and the World Bank (1992) use a similar decomposition of
pollution causation.

218

 

 

1mm ceteris paribus pollution should increase in proportion to GDP. Beglnin
arnd Potier (1997) show in a survey ﬁnat in many cases oftrade liberalization ﬁne scale eﬁ‘ect is

substantially more important ﬁnan induced changes in ﬁne ecornorrnic composition.

W to ﬁne extent ﬁnat GDP can be produced wiﬁn fewer resources, ﬁne
scale eﬂ'ect needs to be corrected downwards. Generally, ﬁnis allocation eﬁ‘ect (denoting
increased factor efﬁciency) is driven by factor neutral technological progess.’l However, irn
additiorn, trade liberalization aﬁ‘ects ﬁnis factor ﬁnrough (a) nrore eﬁcient production pattens;
(b) a welfare improving redistribution of output, even if production did not change at all (barter
effect); and (c) ﬁne reduction in non-tariff barriers means ﬁnat fewer resources are wasted in

rent seeking, but increase are directed to net output.

W: ﬁne composition eﬁ‘ect denomirnates ﬁne change irn emissions ﬁnat
would take place iftotal output and technology stayed ﬁne same, arnd only sectoral slnares

changed The composition eﬂ‘ect of trade is at ﬁne heart of classical arnd ﬁne povety attraction
hypoﬁneses.

4 ' mi ion r ff :emissionsperunitofoutputareaﬂ‘ectedbytnm
factors. First, emissions could decrease as a result of non-neutral technological progess, which
reduces ﬁne productivity of ﬁne environment as a sink for production wastes. Secornd,
regulations reduce ﬁne amount of permissible emissions and force industries to enploy

pollution abatement technologies. The downward sloping Kuznets curve can only take place, if

errnissions per nrrnit of output decrease during ﬁne course of economic development The

219

necessity of a drop in ennissiorn factors points to a very important gap in ﬁne literature on ﬁne
trade-environment link. It will be shown below ﬁnat ﬁre omission of ﬁnis eﬁ'ect substantially

nnisjudges ﬁne net effect of trade liberalization on pollution.

6.1.5. Institutional Optimism Hypothesis

The unilateral focus of ﬁne literature on ﬁne demand side aspects of trade biases ﬁne
analytical results because it takes factor endowments and institutions as cornstant These
assumptions result in an easy detenninacy of ﬁne direction of trade-induced change: Trade is
bad for environment, because it moves dirty industries to places where regulatory enforcement
is weak (alﬁnough ﬁne enforcement itself may not be ﬁne driver). However, as Chapter 2 argued,
ﬁnere is ample evidence that ﬁne trade-induced wealth should lead to a reduced pollution
intensity per writ of output across ﬁne economy. Three causal chains can be identiﬁed ﬁnat

nrnight contribute to institutional change.

First, pollution control requires ﬁne existence of furnctiorning regulatory irnstitutions. The
existence of ﬁnese institutions is intimately tied to a country’s wealﬁn, because ﬁne demand for
environmental quality is highly income elastic.Clean environment is not simply a consumption
amenity. It also reduces production costs due toreduced costs for clean-ups or its importance
for healﬁn and, hence, productivity of ﬁne workforce. In certain high tech sectors, a clean

environment even ranks as a precondition for attracting high skilled labor.

 

5' The World Bank (1992) calls this factor neutral technical change increased input-output
eﬁciency.

220

The diﬁ‘erence in institutional capacity between poor and rich countries is often
remarked (Chichilnisky,1994; O’Connor 1994). Dasgupta et al. (1995) ﬁnd empirically that ﬁne
amount of regulation increases steadily wiﬁn ﬁne gowﬁn of per capita incomes. A clear link can
be established between ﬁne income and education level of ﬁne country and ﬁne level of public
accountability of ﬁne administration (Hettige et al. 1996).” Therefore, at a conceptual level, a
number of auﬁnors have argued ﬁnat trade opening should be accompanied by institutional

reform (Copeland 1996; Beghin et al. 1997; Runge 1994).

Second, it can be argued ﬁnat trade itself, as opposed to autarky, increases ﬁne stock of
knowledge by giving a country access to foreign innovations and knowledge (Grossmarn and
Helpman 1995). Trade openness itself might ﬁnerefore be associated wiﬁn a cleaner industrial
base (Birdsall and Wheeler 1992; Lucas at al. 1992). One component is ﬁnat multirnationals
tend to apply similar standards to ﬁneir operations globally (Pearson 1987; Warhurst and Isrnor
1996, Levy 1995). However, ﬁne evidence on outward orientation and decreasing pollution-

intensity has been questioned by Rock (1996).

Third, changes in ﬁne quality of factor endowments reinforce ﬁne trend toward lower
emission intensities. In poor countries, capital stock is likely to be of old vintage and nnore
polluting ﬁnan newer equipment Retroﬁtting is generally expensive. Therefore, environmental
improvements are linked to ﬁne replacement of ﬁne capital stock Low levels of capital
endowment make environmental investrrnents expensive in foregone production Furtlnermore, a

pool of unskilled labor gives a comparative advantage to traditional smokestack industries.

 

’2 Selden and Song (1994) provide similar arguments.

221

However, ﬁne literature has largely ignored that environmental policy is endogenous to
wealﬁn creation. One exception is Bommer and Schulze (1996) who link regulation to labor
income. A higher level of wealﬁn can create ﬁne regulations ﬁnat reduce ﬁne pollution resulting
from ﬁne industrial expansion ﬁnat accompanies trade. The importance of ﬁne trade-induced
greening of production can be formulated as an alternative empirical hypoﬁnesis on trade and

environment:

Institutional optimism hmthesis: trade-induced wealth creates demand jbr stricter
environmental regulations. This wealth eﬂect on regulations can annul the pollution-
increasing ejects of trade-induced economic expansion and specialization in pollution-

intensive sectors.

Alﬁnough ﬁne arguments for ﬁne institutional optimism hypoﬁnesis are not new, so far it
has not been explicitly formulated or subjected to an empirical test This paper ﬁlls ﬁne gap by
applying a CGE model ﬁnattreats regulation setting as an endogenous function of wealﬁn The
model allows testing the institutional optimismhypothesis by comparing the pollution.
increasing effects of econonnic growﬁn and trade specialization wiﬁn ﬁne pollution-reducing
effect of wealﬁn creation. The hypoﬁnesis is applied to various trade policy scenarios among
NAFI‘ A participants, which serves as a nnicrocosm of North-Souﬁn trade relationships. It is
shown ﬁnat ﬁne perceived conﬂict between trade and environmental interests is largely ﬁne result
of a misunderstanding in ﬁne full impact of trade openness. In many cases, ﬁne regulation eﬂ'ect

is strong enough for trade liberalization to result in globally reduced pollution levels.

6.2. Model Description and Calibration
Thanks to ﬁneir versatility, CGE models have been ﬁequenﬁy used in ﬁne context of trade

and environment interactions. These aspects are discussed in Chapter 3. However, no model

222

has incorporated all of ﬁne ﬁnree aspects ﬁnat set pollution apart from oﬁner production factors.
First, pollution depends not just on sectoral output, but on policies. This fact requires ﬁne
inclusion of an abatement function in ﬁne model, as, for irnstance, in Dessus and Bussolo (1998)
or Beghin et al. (1995), wiﬁn an application to Mexico. Second, ﬁne economic evaluation
requires ﬁne imputation of environmental extemalities (e. g. provided by Ballard and Medema
1995; Copeland and Taylor 1995; and Srrniﬁn and Espinoza 1996). Third, ﬁne assumption of
constant regulations, and hence constant emission factors, needs to be relaxed (of. Home arnd

Schulze 1996).

6.2.1. Social Accounting Matrix
The model used in ﬁnis paper is comparative-static and calibrated on ﬁne data contained irn

ﬁne Social Accounting Matrix (SAM) of Reinert et al. (1993). The SAM includes 26 sectors inn
ﬁne ﬁnree NAFTA countries (USA, Canada, and Mexico) and is based on 1988 data. This
mearns ﬁnat any trade liberalization effects will also include ﬁne impact of ﬁne Canadian
American Free Trade Agreement (CAFT A). The SAM does not include any information on
environmental aspects of production. Notably, capital used in each sector needs to be split

intocapital used for abatement and directly productive purposes.

6.2.2. Production

Producers areassumed to be proﬁt maximizers. Production follows a nested constant
elasticity of substitution (CBS) structure. The top nest combines value added and intermediate
goods. The model allows for econonnies of scale at ﬁnis level. The intermediate aggregate is
obtained by combining products in ﬁxed proportion. Value added is decomposed into a labor
and a capital component. Capital can be moved between sectors and employed for production

itself and pollution abatement It belongs to boﬁn domestic and foreign owners. The overall

223

stock of capital in ﬁne economy is ﬁxed. In ﬁne model, an increase in wealﬁn is ﬁlerefore not

accompanied by a higher capital stock.

6.2.3. Households

Private demand is obtained by maximizing ﬁne nested utility fnmction of a representative
household. In ﬁne top nest, ﬁne household chooses between leisure and consumption. This
function also determines labor supply. Labor supply is expressed in eﬁciency urnits,i.e. value
added, not in hours worked. In addition to wages, households get revenues ﬁom government
transfers and proﬁts. Consumption e demand for individual products is ﬁle result of a CBS
function ﬁnat combines ﬁne product of ﬁne individual sectors. Because ﬁne CBS dernnand
function has unitary income elasticities, ﬁne model does not capturewealﬁl-induced changes irn
ﬁne structure of demand. Smiﬁn and Espinoza (1996) have analyzed ﬁlis aspect, but ﬁneir results

suggest that ﬁnese demand effects are relatively unimportant.

6.2.4. Government

The model includes a number of taxes, such as VAT, sales taxes, income taxes, capital
taxes and customs duties. These revenues are used for transfers to households and ﬁne
provision of public goods. The public good is a CBS composite of various types of government

consumption goods.

6.2.5. Trade
The model follows ﬁne standard Armington (1969) procedure of combining foreign and

domestic goods to an aggregate, which can ﬁnen be used for private or government

consumption or. as intermediate input. In parallel to imports, export supply is modeled as a

224

cornstant elasticity of transformation function. The assurrnption that ﬁne balance of

paymentalways remains ﬁne same as in ﬁne base year yields model closure.

Tariﬁ‘ rates are calculated from ﬁne SAM and are deﬁned as actual collectiorn rates.
Additionally to tariffs, non-tariff barriers are included Values are taken from Roland-Holst et
al. (1993). It is assumed here ﬁnat ﬁne value of ﬁne non-tariﬁ barriers does not accrue to any
economic actor as rent, but constitutes waste of economic resources used for rent-seeking. In
ﬁne case of trade liberalization, ﬁle reduction in non-tariﬁ' barriers leads to an increase in

resources for import consumption.

6.2.6. Emissions and Abatement

Physically, pollution is a joint output of production. However, in ﬁne production function,
emissiorns are treated as input in addition to labor and capital, because higher permissible
emissions reduce sectoral production costs. This is ﬁne standard approach of ﬁne trade and
environment literature. For manufacturing, ﬁne sectoral emission factors per productiorn nmit of
ﬁne model are derived from ﬁne International Pollution Projection System (IPPS) database
(Hettige et al. 1995).’3 As is elaborated in Chapter 4, emission factorsfor non-manufacturing
sectors are added ﬁom oﬁner sources (Jansen 1998). This paper concentrates on airenissions.
Data are available for sulfur dioxide (802), nitrogen dioxide (N02), volatile organic

compounds (VOC), carbon monoxide (CO), and total suspended particles (TSP). However, ﬁne

 

’3 The application of these intensities across countries is mm with numerous
problens. There are even large variations wiﬁnin countries (Paljal and Wheeler 1995).

225

analysis focuses on TSP, since it is ﬁne nnost consistent pollution indicator for human healtln.

Pollution from ﬁne process of consumption is omitted in ﬁne analysis, except for road transport

Sectoral abatement data expenditures for ﬁne United States are derived ﬁom ﬁne Low
(1992). This relationship is extrapolated to ﬁne oﬁner two countries. The assumption is that unit
abatement costs and emissions in Canada are identical wiﬁn ﬁnose of ﬁne U.S. Mexico’s
abatement costs are assumed to be substantially lower (one sixﬁn of ﬁne U.S. for all sectors),

based on simple data inspection of U.S. and Mexican emissions irnventories.

However, sectoral ennissions and abatement factors can vary as a result of changes in
regulatory stringency. Unit ennissions factors depend on unit abatement expenditures ﬁnrougln a
simple constant-elasticity function. For each sector, an increase in baseline abatenent

expenditures by 1%, decreases unit emissions by 0.6%.

The emissions functions allow a representation of four important eﬁ‘ects of trade on
pollution First, an increase in production is linked to an increase in emissions (scale eﬂ'ect).
Second, ennissiorns factors are based on production volume, not production value. The pollutiorn
factors per dollar of net output will drop (allocation eﬁ‘ect), because, ﬁne simple barter eﬁ‘ect of
trade improves welfare wiﬁnout even when production does not change and, furthermore, less
resources are spent on rent-seeking. Third, structural changes inn ﬁne economy translate into
emission changes (composition effect). Finally, ﬁnrough changes in ﬁne level of abatement, it is

possible to reduce emissions per unit of output (regulation eﬁ‘ect).

6.2.7. Extemality
Environmental extemalities are modeled in a very simpliﬁed way. Only ﬁne healﬁn eﬁ‘ect

of air pollution, or more precisely small particles, which are calculated from TSP emissions, is
incorporated Values for healﬁn eﬁ‘ects are taken from ﬁne econometric data of Ostro (1987),

226

which links air quality data to ﬁne number of sick days. This formula was applied to air quality

data of ﬁne OBCD(1995) and Ronnieu et al. (1990).

The approach translates emission changes into changes in labor output. In additiorn, ﬁne
welfare function assumes a hedonic value of pollution of twice ﬁne lost output value to take
account of suffering, sick days of non-workers, and early mortality. However, ﬁne exterrnality
ﬁgures are likely to underestimate ﬁne overall impact of pollutiorn, as damages to cr0ps arnd
capital equipment and ﬁne impact of oﬁner associated pollutants are omitted Sensitivity runs
were used to analyze ﬁne impact of a toxicity-weighted aggregate of pollutants ﬁnat increases

ﬁne extemality of particulates by roughly 40%.

6.2.8. Institutions

The permissible pollution and, consequently, ﬁne necessary pollution-abatement
expenditures per unit of production are model-endogenous. The model solution algoriﬁnm
determines ﬁnem simultaneously wiﬁn all oﬁner economic variables. Functionally, regulatory
stringency is linked to changes in real disposable income and follows a constant elasticity
fnmction. Unfortunately, ﬁnere is no literature ﬁnat would support any particular value. The
central case assumes ﬁnat an increase in private consumption by 1% leads to 0.75% tighter
emission standards per nunit of output The choice for a central value is based sirrnply on
plausibility considerations. If ﬁne value were one or larger, it would mean ﬁnat, in practice,
pollution would be unlikely to ever become a problem in any country over its wlnole
development paﬁn. This conclusion cannot be squared wiﬁn ﬁne empirical observatiorn of ﬁne

inverted U-shaped pollution curve.

By contrast, ﬁne model does not include any oﬁner emission reducing teclnrnology changes

ﬁnat might happen However, in a comparative static model formulation, such a modemization

227

eﬁ‘ect takes ﬁne same form as regulation-induced abatement The elasticity values could

ﬁnerefore even be interpretedto incorporate boﬁn factors.

6.3. Policy Scenarios and Baseline

6.3.1. Policy Scenarios
The analysis of ﬁne trade and environment complex ﬁnat is discussed at lengﬁn irn Chapter

5 centers on four main policy scenarios around which also a number of sensitivity runs were

undertaken.
The abolition of all NAFTA trade barriers asng no transborder capital rrnobility. In
ﬁne model, intra-N'AFTA tariﬁ'rates are set to zero. All oﬁner tax rates as well as ﬁne oveoll

provision of ﬁne public good remain constant. Changes in government revenues in ﬁne policy

scenario translate into changes in transfers.

The reduction in non-tariﬁ' barriers is assumed to make formerly urnproductive resource
(used for rent-seeking) available as increased net output. The trade closure of ﬁnis scenario
assumes ﬁnat exchange rates adjust to keep ﬁne balance of trade of each country at its pre-
NAFTAlevel (measured in international currency). Capital carnrnot be transferred across

countries.

Serenade;

The abolition of all NAFTA trade barriers assuming intra-NAFT A capital mobility. This
scenario resembles ﬁne previous, except ﬁnat it permits capital mobility wiﬁnin ﬁne NAFTA area.
This mobility means ﬁnat instead of leaving ﬁne balance of trade constant, ﬁne balance of

payment (including capital transfers) remains at pre-NAFT A levels.

228

Sammie};

Trade liberalization wiﬁn restrictions in ﬁne petroleum sector wiﬁn and wiﬁnout assumed
capital nnobility (Scenarios 3a and 3b). Simulations leave all bilateral trade barriers between
Mexico and ﬁne oﬁner two states for ﬁne petroleum sector intact, to examine its overriding
importance for ﬁne Mexican economy as well as its high pollution intensity. To some extent,
ﬁnis scenario reﬂects ﬁneactual NAFTA treaty, whereanumber ofrestrictiorns forinvestmerntin

ﬁne Mexicarn oil sector remain (cp. Hufbauer and Schott (1993, p. 33-36).
Scrum
Unilateral increase in environmental stringency. As a direct test of importance of

regulations on trade specialization, a set of simulations analyzes a unilateral reduction in unit

emission for each conmtry.

In addition to ﬁnese main variants, a number of oﬁner sensitivity runs were undertaken
Variations in elasticities of demand, productiorn, scale, labor supply, as well as diﬂ‘erent
marginal costs of abatement were analyzed These variations inﬂuence ﬁne order of magnitude
of ﬁne trade effect in a predictable way,however, and do not change ﬁne qualitative picture of
ﬁne results. Similarly, making abatement more expensive or introducing a substitution

relationship between labor and emissions does not aﬁ‘ect ﬁne results noticeably.

6.3.2. Dependence of Results on Pre-NAFTA Trade Barriers

The economic and environmental effects of ﬁne scenarios are substantially driven by ﬁne
economic structure irn 1988 before trade liberalization. To interpret ﬁne results, it is particularly
noteworﬁny ﬁnat pre-NAFT A trade barriers diﬁ‘er substantially across sectors. Predictably, rrnost

effects occur where barriers are highest Since, ﬁne highest pre-NAFT A trade barriers tend to

229

be directed against primary and heavy industrial goods, ﬁnere is a certain bias in ﬁne policy
scenario towards a specialization in relatively polluting goods. This bias is less likely to exist if
one wants to draw conclusions about trade in general. If pre-NAFT A trade barriers were ﬁne
same for each sector, national factor endowments and production functions would be ﬁne

exclusive drivers of ﬁne induced trade specialization.

Furﬁnermore, ﬁne CGB model cannot analyze ﬁne impact of regnnlatory diﬁ‘erences
between countries as such, because of ﬁne equilibrium assumption. This is because sectoral
proﬁts are given in ﬁne SAM, a higher assumed abatement expenditure would ornly lead to a re-
calibration such ﬁnat ﬁne additional costs would be compensated by a higher productivity of ﬁne
non-abatement capital. Therefore, ﬁne model can only analyze ﬁne impact of changes in

abatement expenditures, not ﬁne impact of ﬁne existing absolute abatement levels.

Factor endowments are important for ﬁne economic specializatiorn of ﬁne individual
countries. However, factor endowments for production are not constant The availability of ﬁne
environment as a production factor can vary due to regulation. Effective production capital can
be reduced by higher pollution abatement. Furﬁnermore, labor supply depends on wage rates
and income, as well as ﬁne healﬁl effect of changes in ﬁne pollution level. In addition, ﬁne

production functiorns and, hence, economic efﬁciency in each sector vary among countries.

Finally, ﬁne welfare assessment of ﬁne NAFTA scenario deviates from ﬁne GDP ﬁgures.
Welfare is based on three components. The ﬁrst component, private consumption, is largely a
leveraged GDP increase, because government cornsumption is ﬁxed to its original level. The
second component is leisure time, which is ﬁle inverse of ﬁne change in labor supply. The ﬁnird

component is ﬁne induced effect of NAFTA on healﬁn.

230

6.4 Macroeconomic Effects of Policy Scenarios

6.4.1. Scenario 1: Full Trade Liberalization with Immobile Capital
The abolition of trade barriers wiﬁnin Norﬁn American has a positive impact on all ﬁnree

econonnies, causing total annual GDP to increase by $40 bn (1988 dollars) both for
internationally mobile and immobile capital. In relative terms, ﬁne greatest winnes are Mexico
and Canada wiﬁn GDP increases of more than 2%, while U.S. GDP increased by 0.6 % In
absolute terms, however, two thirds of ﬁne beneﬁts accrue to ﬁne U.S., a quarter to Carnada, and

only one tenﬁn to Mexico.

The results are in line wiﬁn the predictions of oﬁner models on NAFTA (eg models
summarized in CBC 1993, Kehoe and Kehoe 1995, Brown 1994). However, a comparison is

made diﬁcult by ﬁne fact ﬁnat not all oﬁner models have included ﬁne eﬂ‘ect of CAFT A.

In ﬁne U.S. and Canada, capital rents rise slightly more ﬁnan wages because of two
factors. First, while ﬁne model assumes a cornstant capital stock, labor supply irncreases because
of higher wage rates. This supply increase dampens ﬁne real wage increase. Second, ﬁne
demand for abatement capital increases following ﬁne model-endogenous regulation tightening
ﬁnat results from ﬁne increased wealﬁl. In Mexico, ﬁne gap between rents arnd wages is even
larger, due to relative factor abundance. In terms of its production structure, Mexico is
relatively labor scarce. The large number of workers in ﬁne country is nnore than balanced out

by a low rate of labor productivity". The results replicate ﬁne Stolper-Samuelson ﬁneorem that

 

5‘ Tlnisisonlyatﬁrstglanceincontradictiontomanyoﬁnersmdies,whichdescribeMexicoasa
labor-abundant country. These studies use a deﬁnition based on work hours rather, whileﬁne
presentpaperlooksatthewagesum.

231

trade liberalization in a relatively capital-intensive country increases rents rrnore than wages. In

Canada and ﬁne U.S., ﬁnis factor works in ﬁne opposite direction.

Sectoral effects of ﬁne scenario are also in line wiﬁn ﬁne ﬁndings of oﬁner studies. Car
manufacturing is expected to increase everywhere. Similarly, electronics irncreases, while
textile and apparel growﬁn is only moderate. Irnportanﬁy, in ﬁne full liberalization scenario,
petroleum production in Mexico increases substantially. This result is not universally present in
oﬁner models, ﬁnough some derive similar results (e. g. Brown et al. 1995, Sobarzo 1995). Since
ﬁne petroleum sector is partly excluded from NAFTA, some auﬁnors have presented nnodel
simulations wiﬁnout ﬁnis sector, others like in ﬁnis paper have assumed ﬁnat trade barriers irn ﬁnis

area are also abolished. The consequences of ﬁnis assumption will be discussed furﬁner below

6.4.2. Scenario 2: Full Trade Liberalization with Mobile Capital
The possibility of transferring capital from one country to another changes ﬁne nature of

ﬁne trade closure. Capital is transferred to ﬁne country wiﬁl ﬁne highest rate of return. In ﬁnis ﬁne
model, capital ﬂows are exclusively driven by divergent developments in rnorrninal interest rates.
Since capital gains are relatively highest in Mexico, ﬁne country experiences a high irnﬂow of
capital from ﬁne U.S. This capital inﬂow leads to a substantially higher GDP growﬁn (3.3%
compared to 2.4% wiﬁn immobile capital), and an even more substantial clnange in production
volume (2.5% irnstead of 1.2%). F urﬁnermore, it reinforces ﬁne industrial specialization of ﬁne
country. Despite ﬁne higher GDP, private consumption in Mexico remains practically
unchanged compared to Scenario 1, as ﬁne proﬁts of ﬁne additional activity accrues to the

Urnited States.

Canada also experiences capital inﬂows from ﬁne U.S. However, ﬁney are insigniﬁcant

The changes on ﬁne U.S. side nnirror ﬁnose of Mexico, as GDP drops compared to ﬁne scenario

232

witln immobile capital. However, due to ﬁne large size of its economy, changes in ﬁne U.S. are

relatively smaller, wiﬁn GDP gains shrinking from 0.64% to 0.61%.

6.4.3. Scenario 3: Leaving out the Petroleum Sector

Unsurprisingly, ﬁne beneﬁts of a NAFTA scenario ﬁnat leaves out ﬁne petroleum sector
are less than in ﬁne ﬁrst two scenarios. There. is a noticeable reduction in ﬁne trade beneﬁts,
mainly for Mexico but also for ﬁne U.S. In ﬁne case of immobile capital(Scenario 3a), Mexico’s
GDP gain drops ﬁ‘om 2.4% to 1.9%, ﬁnat of ﬁne U.S. ﬁom 0.64% to 0.59%. Cannada remains
practically unaffected, not least, because oil trade between Mexico and Canada is minimal.
Neverﬁneless, ﬁne oil sector in Mexico still grows strongly by 6% instead of 14% driven by
indirect demand. Owing to ﬁne capital intensity of ﬁne sector, ﬁne reduced welfare gains are

borne slightly more by capital owners ﬁnan workers.

For mobile capital (Scenario 3b), ﬁne effects of ﬁne scenario change even nnore dramatic
for Mexico. Instead of a 3.3% GDP gain in Scenario 2, its economy increases only by 1.1%.
This is notably due to a reversal in ﬁne ﬂow of capital, which is now leaving ﬁne courntry
causing accelerated growﬁn in Canada and ﬁne United States instead. In ﬁlis case, ﬁne oil sector

even shrinks slightly.

6.4.4. Scenario 4: Unilateral Increase in Environmental Stringency

A unilateral decrease in permissible emission factors in ﬁne United States leads to a drop
in GDP in ﬁne country by 2.3%. The incidence of ﬁne tighter regulations falls exclusively on
wages (4.75%), because effective labor supply increases by 0.3% due to a large improvement
in healﬁn. By contrast, capital actually beneﬁts due to the demand for abatement equipment and

ﬁne increased labor supply (+3.16%). The U.S. economy ﬁnerefore becomes more labor-

233

intensive. The increased abatement costs ﬁnerefore imply a structural clnarnge away ﬁom

pollutiorn intensive and capital intensive sectors.

One can notice some countervailing increase in ﬁne output of ﬁnese sectors in ﬁne oﬁner
two courntries. However, Mexico and Canada do not suﬁ'ncienﬁy beneﬁt from ﬁne reduced
compeﬁtiveness of ﬁne U.S. in ﬁnese sectors to compensate ﬁnem for ﬁne decrease in GDP of
ﬁneir main trading partrner. GDP shrinks by 0.3% boﬁn in Mexico and Canada Ifﬁne unilateral
increase in stringency takes place in a setting wiﬁn intennationally rrnobile capital, ﬁne burden on
ﬁnese econorrnies is substantially higher. GDP shrinks by 1.1% in Mexico and by 0.8% irn
Canada, because capital ﬂows to ﬁne U.S. to proﬁt from ﬁne irncreased return This ﬂow is
accompanied by a reversal irn ﬁne structural change. The secondary effect ofcornnected capital
markets causes structural charnges to be in parallel wiﬁn ﬁnose ofﬁle United States. This change
contrasts wiﬁn ﬁne case of immobile capital, where structnnral changes in ﬁne oﬁner countries

move in ﬁne opposite direction of ﬁnose in ﬁne United States.

The case of unilateral action in Canada is directly comparable, given adjustments for its
smaller size. So is ﬁne case of Mexico. GDP drops irn all ﬁnree countries. Howeve, in ﬁne case
of Mexico, low abatement costs and high extemalities actually lead to loss irn GDP ﬁnat is an

order of magnitude smaller ﬁnan in ﬁne oﬁner two countries (0.2%).

234

6.5 Environmental Effects of Policy Scenarios

6.5.1. Scenario 1: Full Trade Liberalization with Immobile Capital

W '

Wiﬁnout tighter regulation, trade liberalization wiﬁn immobile capital would sirnnply lead
to higher emissions in Norﬁn America, if only because of economic growﬁn Due to ﬁne
increased efﬁciency in ﬁne NAFTA area (allocation eﬁ‘ect), ﬁne growﬁn-induced pollution is less
ﬁnan ﬁne increase irn GDP. Neverﬁneless, boﬁn effects combined would yield an increase in

emissions in ﬁne U.S. of0.2, in Mexico of 1.2%, and in Canada of 1.8%.

The compositioneﬁ‘ect modiﬁes ﬁne results. In particular, Mexico shows a furﬁne
increase in pollution of 2.2% because of economic specialization. This result means ﬁnat its
relative pollution-intensity is increasing. To a much smaller extent, Canada also experiences a
small positive composition eﬂ‘ect of 0.2%. By contrast, ﬁne value for ﬁne United States is
negative. The country specializes in clean sectors. As such, ﬁnis result gives support to ﬁne

poverty attraction hypoﬁnesis, as ﬁne poorer country attracts ﬁne polluting industry.

Alﬁnough ﬁne induced pollution specialization is not large, Mexico would notice a 3.3%
higher pollution level were it not for a substantial 1.8% reduction due to tighter regulation ﬁrst
is induced by ﬁne increased income in the country. The inclusion of ﬁne regulation eﬂ‘ect even
leads overall emissions in ﬁne U.S. to drop by 0.6%, while ﬁnose of Canada stay cornstant,
despite ﬁne substantial economic growﬁn and a slight specialization in pollution-intensive

production.

235

i f m 'v 11

The composition effect is robust to ﬁne choice of pollutants. Virtually an identical picture
emerges for sulfurdioxide (802), nitrogen dioxide (N02), volatile organic compournds (V CC),
and total suspended particles (T SP). The U.S. shows slighﬁy negative values. Those for
Mexico are strongly positive, while values for Canada are slighﬁy positive. However, carborn
nnonoxide (c0) and small particles (PM10) do not ﬁt the picture. co causes sigrn reversals for
Canada and signiﬁcantly lowers values for Mexico. PM10 even reverses signs for all countries.
Some variation is to be expected simply because relative sectoral emission intensiﬁes vary by
pollutant. This effect is reinforced by ﬁne dependence of ﬁne composition eﬁ‘ect on only a few

crucial sectors.

Management

These induced changes in pollution are also evaluated in welfare terms. Simulations
indicate that healﬁn (measured in changes in sick days) improves by 0.02% in ﬁne U.S. arnd
deteriorates by 0.09% in Mexico, while it is virtually unchanged in Canada Changing healﬁn
levels aﬁ‘ect welfare directly as one of its composite parts, and indirectly, because a lower
number of sick days increases ﬁne effective labor supply. Better healﬁn ﬁnerefore leads to a
higher level of GDP. For ﬁne simulation reported here, ﬁnese induced changes are small, but not
completely negligible. They shift ﬁne total beneﬁts of the trade agreement up by over 3% for ﬁne
U.S., and down by more ﬁnan 3% for Mexico. These ﬁgures are exclusively based on ﬁne
extemality of particles alone. Ifone also aggregates ﬁne effects of oﬁner air pollutants based on
toxicity weights, ﬁne share of the extemality in ﬁne overall welfare eﬁ‘ect would be over 5% for

boﬁn ﬁle U.S. and Mexico.

236

 

6.5.2. Scenario 2: Full Trade liberalization with Mobile Capital
In scenario 2, which assumes full trade liberalization wiﬁn internationally mobile capital,

ﬁne capital inﬂow to Mexico substantially increases ﬁne pollution effect in ﬁne country. Boﬁn a
higher absolute level of economic activity and a greater economic specialization drive up ﬁne
pollution ﬁgures by more ﬁnan 2%. However, ﬁne increased econonnic activity is not matched by
a simultaneous increase in environmental stringency, because ﬁne beneﬁts to of ﬁne capital
inﬂow accrues to foreigners. This leaves private consumptiorn, ﬁne driver of stricter regulations,

practically unchanged.

By contrast, in ﬁne U.S. capital outﬂows reduce pollution levels, because economic
changes in ﬁne U.S. are ﬁne reverse of ﬁnose in Mexico. Here, ﬁne ecornomy contracts sliglnﬁy,
and ﬁne country specializes more ill low polluting activities compared to ﬁne scenario wiﬁnout

international capital mobility. However, ﬁne relative changes are raﬁner small.

In ﬁne case of mobile capital, ﬁne induced environmental extemalities decrease Mexico’s
welfare gain by more ﬁnan 8%. Wiﬁn a toxicity-weighted index, extemalities would even reduce
ﬁne trade gains by nearly 14%. For Mexico, the additional beneﬁts of capital nnobility in terms
of higher GDP are outweighed by ﬁne welfare loss due to higher pollution However, ﬁlis
cannot be seen as an indictment of trade liberalization as such, because ﬁne overall welfare
gains are still solidly positive (+22%). The environmental damage ﬁom trade liberalizatiorn
would have to be very substantial to overwhelm ﬁne welfare beneﬁts in terms of lniglne

economic growﬁn.

237

6.5.3. Scenario 3: Leaving out the Petroleum Sector
In determining ﬁne overall pollution effect, ﬁne oil sector plays a crucial role - because of

its high pollution-intensity and its importance, in particular for Mexican exports. Bxempting ﬁne
petroleum sector ﬁom trade liberalization implies for Mexico a lower scale eﬁ‘ect a lower
composition effect, and a reduced regulation effect For immobile capital, ﬁne net impact on
Mexico’s pollution level remains only a ﬁnird of ﬁne full liberalization case (+07%). However,
no sign change occurs anywhere. Despite ﬁne restrictions on trade, ﬁne results are robust in ﬁnis

aspect, largely because ﬁne oil sector in Mexico still expands.

In ﬁle case of mobile capital, changes are more signiﬁcant. The capital outﬂow leads
Mexican emissions drop by more ﬁnan 1%, instead of increasing by nearly 4%. The sharply
reduced scale eﬂ‘ect and a substantially reduced composition eﬂ’ect (3% less) dominate ﬁnis
change. By contrast, ﬁne net emissions reduction in ﬁne U.S. is less strorng, while Canada’s

emissions even increase by 0.4%.

The scenarios therefore indicate ﬁnat ﬁne resultsare sensitive to a sirngle sector. This
sensitivity can also be measured in ﬁne fnnll trade liberalization scenario if ennissiorn changes
due to ﬁne petroleum sectorare set to zero. This would substantially aﬁ'ect ﬁne compositiorn
effect. For Mexico, ﬁnis modiﬁcation would imply a net emission eﬁ’ect ﬁnat is reduced by
1.8% in ﬁne case of immobile capital and 3.7% inn ﬁne case of mobile capital. In taking out ﬁne
eﬁ'ects of ﬁnis one sector, environmental beneﬁts are eiﬁner strongly positive or insigniﬁcant, as

ﬁne results are now dominated by ﬁne inﬂuence of tighter regulations.

238

6.5.4. Scenario 4: Unilateral Increase in Environmental Stringency

Sirnnulating ﬁne unilateral increase in regulatory stringency in one connntry is ﬁne nnost
direct test on ﬁne pollution haven hypothesis.” In ﬁne regulating country, ﬁne pollution reductiorn
is noticeably higher than what would be expected by ﬁne regulation effect only. Next to ﬁne
contracting GDP, ﬁne composition effect plays a substantial role, because as production moves
away from abatement and pollution-intensive goods. In general most of ﬁnis reﬂects actual
changes in consumption. Relatively little of ﬁne composition eﬁ‘ect is counterbalanced by
concomitant increases in pollution-intensity in partnner countries. Neverﬁneless, in ﬁne case of
immobile capital trading partners experience an increase in pollution. This outcome is

essentially ﬁne result of more lax regulations following a decreased private consumption.

The overall evaluation of a unilateral regulatory step depends, of course, on ﬁne
magnitude of ﬁne GDP and healﬁn changes, which move in opposite directions. While healﬁn
beneﬁts substantially reduce ﬁne welfare costs of decreased output, in ﬁne U.S. and Canada arnd
welfare decreases by 0.3, respectively 0.8%. By contrast, in Mexico a unilateral tightening of
environmental stringency provides signiﬁcant welfare gains of 1%. Healﬁn beneﬁts are large,
while GDP reductions are quite small in ﬁne ﬁrst place, due to improved labor productivity and

ﬁne low level of abatement expenditures.

As a variant of ﬁle calculating ﬁne eﬁ‘ect of increasing environmental stringency

unilaterally, one can derive for each country how large ﬁne regulation elasticity needs to be for

 

”Itisofnopracticalconscquenccwhetherﬁnisscenarioisimposcdonabenchmarkwiﬁlor
without trade barriers in place. 5‘ This can be seen by transforming it into U = (M‘HH’y ,
where [31 = 1, and (l-Bn = 11. The allocation consequence ofy is zero, and could be left out.

239

trade liberalization to be environmentally beneﬁcial. (Evidenﬁy, ﬁnis value will diﬁ'er by type of
pollutant). In ﬁne case of ﬁne two scenarios wiﬁn full NAFTA trade liberalization ﬁnis ﬁnreshold
value would be very low for ﬁne U.S., at about 0.2; for Canada, ﬁne value is somewhat lower
ﬁnan 1. Mexico, by contrast, would need values between 1.5 and 2. However, ﬁnere may be
good reasons to believe ﬁnat ﬁne elasticity in Mexico as a response to NAFTA is higher ﬁnarn irn
ﬁne oﬁner two countries due to irnstitutional cooperation between ﬁne U.S. and Mexico (Runge
1994). The country appears under-regulated, and is subject to external and interrnal pressures to
change ﬁnis situation. Variations in ﬁne form of policy functions (e. g. by making it dependent on

wages) do not inﬂuence ﬁnese results notably.

6.6. Conclusions

Bcononnic modeling in ﬁnis paper shows that ﬁne incorporation of induced regulation-
setting plays a crucial role in analyzing ﬁne environmental impact of trade liberalizatiorn. Under
a broad range of trade liberalization scenarios in Norﬁn America, ﬁne environmental situation
improves not simply in general but also in each individual country. This occurs despite ﬁne fact
ﬁnat ﬁne pre-NAFT A structure of trade protection biases ﬁne result towards an exparnsiorn of
pollution-intensive sectors. The, ﬁne net eﬁ‘ect of ﬁne scenarios depends on a relatively limited

number of factors. For NAFTA, changes in ﬁne petroleum sector are central.

However, ﬁne link between regulation setting and disposable income ﬁnat is employed in ﬁne
model must not be interpreted as being automatic and instantaneous. The functional form can at
best represent a proxy for a complicated political process ﬁnat hinges on a large number of
factors. The responsiveness of institutions depends certainly on ﬁne degee of democracy in ﬁne
country at hand. Furﬁnermore, income distribution or, more generally, ﬁne distnhution of

political power will modify ﬁne link between aggregate wealﬁn and regulation setting.

240

Neverﬁneless, contrary to much of ﬁne existing literature, ﬁne fully integrated pollutiorn
eﬁ‘ects analysis demonstrated here points to a fundamental redirection in ﬁne trade and
environment debate. In spite of diﬁ‘erences in environmental stringency among countries, trade
and environmental interests can be allies. Therefore, environmental concerns are best focused
on transforming ﬁne institutions of ﬁne home country and ﬁnat of ﬁne trading partrners, not on
restricting trade wiﬁl institutionally weak countries. Consequently, ﬁne essential researcln
question corncems ﬁne process ﬁnat leads to institutional changes. This paper could only touch

on ﬁnis issue vaguely, and has to rely on a more or less plausible approximation.

Next to deriving empirical evidence to ﬁne country transformation hypoﬁnesis, ﬁne
simulation results are consistent wiﬁn conventional ﬁndings irn ﬁne literature. First, ﬁney
reproduce the consensus arnswer on ﬁne classical trade and environment question Due to ﬁneir
relatively low cost impact, environmental policies matter only marginally inn industrial location.
The effect of stricter environmental regulations on trading partners depends crucially on ﬁne
assumed level of capital mobility. Second, in line wiﬁn ﬁne poverty attraction hypoﬁnesis,
simulations show ﬁnat wiﬁnin ﬁne NAFTA area dirty industry tends to move to ﬁne poorer
country (Mexico). However, ﬁnis conclusion depends strongly on developments irn ﬁne oil
sector. Third, ﬁne simulations show ﬁne importance of including extemalities into ﬁne analysis.
This inclusion leads to a noticeable revision in ﬁne overall welfare assessment of trade
liberalization. Furﬁnermore, it can be shown ﬁnat for an under-regulated conmtry like Mexico, a
urnilateral increase in regulations is possible that would allow for signiﬁcant welfare

improvements, even if sectors work in an internationally competitive environment

241

 

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253

APPENDIX

CALCULATION ON OPTIMAL REGULATION-INCOME ELASTICITY

Let utility U be deﬁned as a function of material well-being (M), and healﬁn (H),

according to ﬁne following formula:
(i) U = W " .

The formula is an extended Cobb-Douglas formula, leaving ﬁne total share of healﬁn and
material well being constant. 5‘ The model is simpliﬁed compared to ﬁne presentation inn
ETERNA since it neglects ﬁnat healﬁn has an impact on production itself via labor productivity.
Under non-restrictive assumptions, such incorporation will not inﬂuence ﬁne basic
proposition.” Furﬁnermore, material well being is a function of production (P) minus

abatement expenditure (A):
(ii) M = P — A.

Finally, ﬁne impact of abatement on healﬁn (H) follows ﬁne functiorn

(iii) H = %g) a.

This means that healﬁn improves wiﬁn an elasticity of or, if ﬁne share of abatenernt
expenditure in ﬁne economy increases, but worsens proportionally, if production increases.

Utility can ﬁnerefore be expressed as

254

(iv) U = (P - A)P"’" ’“’A"’.

The abatement expenditures is optimally set at:

 

(v) A: “'7 P.
I+an

Wiﬁn ﬁne chosen utility form, ﬁne optimal adjustment paﬁn for a country as it gets richer
would be to keep abatement expenditures at a constant ratio to overall income. This rate itself
is higher, ﬁne bigger ﬁne extemality (i.e., ﬁne higher or) is. A higher eﬂ‘ectiveness of abatement
expenditures (represented by a higher 11) has an analogous eﬂ‘ect The formulation therefore
would imply a unitary elasticity of pollution abatement expenditures with respect to income
increases. This means ﬁnat ﬁne regulatory elasticity of income would be zero. In other words,
ﬁne level of pollution per unit of output would remain constant Following equation (iii),
pollution would increase as a result of growﬁn. The reason for ﬁnis lies in equation (i). In ﬁnis
forrnulatiorn, boﬁn marginal costs and beneﬁts increase in proportion to income, leaving ﬁne

beneﬁt cost ratio unchanged.

 

s"ItisonlynecessarytoassurnetlnatmaterialoutputfollowsaCobb-Douglasfnrnctiornoflaborand
capital.Inﬁniscase,theoverallutilityfunctioncouldbepresentedinthcsamebasicformas
U=W",exceptthatnnowincludesbothproductiveandhedoniccﬂ’ectsofexternality.

255