Discussion Paper Series No.197
Pollution Havens and Industrial Agglomeration

Dao-Zhi ZENG
Laixun ZHAO
NovemberKagawa University
Kobe University
2006

The Discussion Papers are a series of research papers in their draft
form, circulated to encourage discussion and comment. Citation anduse of such a paper should take account of its provisional character.
In some cases, a written consent of the author may be required.

Pollution Havens and Industrial Agglomeration
Dao-Zhi Zeng∗

Laixun Zhao†

November 13, 2006

Abstract
Pollution-intensive industries are generally characterized by imperfect competition, increasing returns to scale and large transportation costs. We investigate twocountries, N and S, each with two sectors. Manufacturing generates cross-borderpollution which reduces agricultural production. Firms can freely move across country borders, but not workers. First, we show that pollution lowers local income since
it reduces agricultural production. This income-reduction eﬀect discourages ﬁrms
to move to the country with laxer environmental regulations that generate morepollution. Second, our analysis demonstrates that manufacturing agglomeration
forces can alleviate the pollution haven eﬀect. And a pollution haven may not arise,
if environmental regulation is slightly more stringent in the larger country N thanin the smaller country S. These results are strongly supported by recent empiricalﬁndings. In addition, the model predictions call for international cooperation ofenvironmental policies, especially when trade becomes freer.
Keywords: Pollution, Industrial Agglomeration, Trade Costs
JEL Classiﬁcation: Q5, R3∗

Graduate School of Management, Kagawa University, Saiwai-Cho 2-1, Kagawa 760-8523, Japan.
E-mail: zeng@ec.kagawa-u.ac.jp.
†
Laixun Zhao, Research Institute for Economics and Business, Kobe University, Kobe 657-8501, Japan.
E-mail: zhao@rieb.kobe-u.ac.jp.

1

Introduction

The so-called “pollution haven” hypothesis1 states that pollution-intensive industries will,in response to globalization (e.g. freer trade or capital mobility), tend to move to countries with laxer environmental regulations.2 The issue plays important roles in the designof international agreements such as the Kyoto Protocol on greenhouse gas control andthe Montreal Protocol on ozone-depleting substances. However, while it is intuitively
understandable that polluting ﬁrms relocate to countries with lenient environmental regulations, a majority of the empirical ﬁndings on the pollution-haven eﬀect are weak andcontroversial.3
A number of studies have attempted to explain for the huge gap between the existing theoretical literature and the empirical ﬁndings. For instance, Grossman and Kruger(1993) state that the direction of trade in dirty goods is primarily determined by conventional determinants of comparative advantage-factor endowments and diﬀerences intechnology and thus it might be diﬃcult to detect pollution-haven eﬀects. Copeland andTaylor (2004) argue that the increase of pollution in developing countries might be causedby economic development rather than by dirty industry migration from overseas. Levinson and Taylor (2004) use imports instead of outward foreign direct investment (FDI) tomeasure the migration of ﬁrms. Their results indicate that the industries where abatement
costs have increased most have seen the largest increases in net imports.
This paper provides an alternative explanation. In our view, pollution-intensive industries are generally characterized by imperfect competition, increasing returns to scaleand large transportation costs, for instance, petroleum & gas, chemicals, steel and othermetals, pulp, automobile making, airlines, etc. Moreover, a proportionally larger share ofsuch industries are located in the developed countries. Therefore, in this paper we investi1

Copeland and Taylor (2004) distinguish between the pollution haven eﬀect and the pollution havenhypothesis, the former of which refers to the eﬀect of environmental policies on the migration of dirty
ﬁrms, while the latter of which is related to the eﬀect of a reduction in trade barriers on the migrationof such ﬁrms. We shall investigate both, and as will soon become clear, these correspond to the impactsof respectively t and ϕ in our model.
2See, for instance, Pethig (1976), Markusen et al. (1993), Chichilnisky (1994), Antweiler, Copelandand Taylor (2001), and Copeland and Taylor (2004).
3
See, Walter (1982), Levinson (1996), List and Co (2000), Keller and Levinson (2002), Eskeland andHarrison (2003), and survey papers by Jaﬀe et al. (1995), Repetto (1995), and Xing and Kolstad (1996).

1

gate a world of two countries, called the North N and the South S, each with a continuumof manufacturing industries under monopolistic competition and increasing returns. Manufacturing generates cross-border pollution which reduces agricultural production. The
government in each country adopts a pollution abatement policy that requires ﬁrms toclean up their pollution by employing more workers. Firms can freely move across country
borders, but not workers.
The model ﬁrst enables us to clearly extract an income-reduction eﬀect of pollution,even if two countries are completely symmetric. It arises from our cross-sectoral assumption that manufacturing pollution reduces agricultural production, which in turn decreases
the local wage if pollution aﬀects the emitting country more heavily than the other country. This results in a lower national income and a lower demand for manufacturing goods.
We show that this income-reduction eﬀect discourages ﬁrms to move to the country withlaxer environmental regulations.
A second related eﬀect is what we call the cost-reduction eﬀect in manufacturing
production, stemming from laxer environmental regulation, which requires ﬁrms to spend
less labor on pollution abatement, and thus results in a lower manufacturing cost andgenerates more pollution. This is the mechanism that leads to the so-called pollution
haven in the received literature.
In our model, the above two eﬀects work in opposite directions and jointly determine
the total eﬀects of pollution. They can partly explain the empirical ﬁndings of Eskelandand Harrison (2003) that there exists some pollution-haven eﬀect in industries with air
pollution but not in industries with water pollution. According to our model, this arises
because air pollution is more global which hurts both countries to more or less the same
degree, and therefore the income-reduction eﬀect is small. In contrast, water pollution ismore local and the corresponding income-reduction eﬀect is large enough to obscure thecost-reduction eﬀect.
We further ﬁnd that under asymmetry in country sizes, the manufacturing agglomeration force in the larger country N, stemming from imperfect competition and increasing
returns to scale, can alleviate the pollution-haven eﬀect in the smaller country S, stemmingfrom laxer environmental regulations. In other words, in models without incorporating2the agglomeration force, the pollution haven eﬀect may be exaggerated. For instance, thetheoretical literature so far has overlooked these factors, and the hypothesis of pollution
haven eﬀects seemed so obvious. Our analysis demonstrates that if environmental regulation is slightly more stringent in N than in S, then agglomeration forces can dominate thepollution eﬀect and a pollution haven does not arise. This provides another explanation
to why evidence of the pollution haven is hard to ﬁnd.
The agglomeration force is strongly supported by a recent empirical study by Wagner
and Timmins (2004), who test the pollution haven hypothesis using panel data of German
FDI outﬂows in 6 manufacturing industries. They show that externalities associatedwith FDI agglomeration can bias estimates away from ﬁnding pollution haven eﬀects.
By including FDI stock to capture agglomeration eﬀects, and controlling for possible
correlation between unobservable attributes of FDI recipients and their environmental
stringency, which had been ignored in previous analysis, they ﬁnd strong support for thepollution haven hypothesis in the most pollution intensive industries such as chemicals andpaper. They report that (p.22) “...(there exists) a spurious positive correlation between
regulations and investment. It seems as if tough regulations attract pollution-intensive
industries whereas in reality they relocate to a country because they beneﬁt from FDI
agglomeration.” On the other hand, for some other industries such as primary metals,
they ﬁnd that the bias works in the opposite direction. This eﬀect corresponds to thecase when agglomeration forces are dominated by pollution eﬀects in our model.
Perhaps the novel contribution of the present paper lies in that we integrate a model of
economic geography with cross-border pollution. Speciﬁcally, manufacturing pollution ismodeled as a bad that will decrease agricultural production. To the best of our knowledge,
such cross-sectoral eﬀects have not been analyzed in geography models yet. The known
anti-agglomeration forces such as congestion directly reduce industrial instead of agricultural production in the literature. Modeling such cross-sectoral pollution in the foot-loose
capital model enables us to discover the income-reduction eﬀect, which reveals ﬁndingsthat are consistent with recent empirical studies. We also obtain clear-cut results in ananalytically solvable manner, which is rare in models of spatial economics, considering
the complexity of the present context. And ﬁnally, we show that as trade becomes freer,3

a “race to the bottom” of abatement policy may arise if countries choose their individual
optimal policies noncooperatively. This calls for international cooperation, such as theMontreal Protocol and the Kyoto Protocol, especially in this age of globalization.
Our results also complement other ﬁndings in the literature. In contrast to the explanations in Grossman and Kruger (1993), Copeland and Taylor (2004) and Levinson andTaylor (2004), we demonstrate that even when two countries are completely identical (withneither comparative advantage no agglomeration forces) except the pollution abatement
policy, the pollution haven eﬀect can still be dominated due to the income-reduction eﬀect
of pollution. McAusland (2002) shows that capital owners have an incentive to cross-haulpolluting factors across jurisdictions, because when capital generates pollution, those residents who are also capital owners consciously will invest their pollution-generating capitalin a diﬀerent jurisdiction in order to reduce pollution at home, whose mechanism is very
diﬀerent from ours. Pﬂüger (2001) studies ecological dumping under monopolistic competition, but countries are assumed to be symmetric, and the equilibrium analysis is limited
to the cases of autarky and free trade.
This rest of the paper is organized as follows. Section 2 presents a brief setup of themodel, describing the transboundary pollution and the increasing-returns-to-scale technology in industrial production. Section 3 describes the equilibrium. Section 4 demonstrates
how the income-reduction eﬀect and the cost-reduction eﬀect work against each other andjointly determine the total pollution eﬀect under symmetric countries. Section 5 analyzes
the case of asymmetric countries in size and shows how the agglomeration force is related
to the pollution eﬀects. Section 6 looks into the optimal policies of the governments. We
show that a race-to-the-bottom arises when transport costs are small, which calls for international coordination of environmental policies. Finally, we summarize our conclusions
in Section 7.

2

Brief Setup

To character the manufacturing industry with imperfect competition, increasing returns,
and transport costs, we employ the framework of spatial economics (see Krugman, 1980

4

and Fujita et al., 1999). Speciﬁcally, we embed pollution into the standard “footloose
capital (FC)” model (Martin and Rogers, 1995; Baldwin et al., 2003). The justiﬁcation
for using the FC model is that it allows the international mobility of capital but notlabor, which serves our purpose of analyzing pollution problems between the North andthe South, where there are far more barriers for the migration of labor than capital. Thisimplies that a ﬁrm produces the same product after moving (Markusen (1995) documentsthat a majority of multinationals are horizontal in nature). More importantly, it is in linewith the argument that capital used in the production of pollution-intensive goods yields
a higher return in countries where ﬁrms bear lower costs of compliance with environmental
regulations. Thus the pollution haven hypothesis says that dirty industries relocate tocountries with lax environmental regulations.
There are two countries (the north N and the south S), two sectors (manufacturing andagriculture), and two productive factors physical capital and labor, with capital being theinternationally mobile factor and labor the immobile one. The name of “agriculture” here
is not limited to pure agriculture, but represents any environmentally sensitive industry
including ﬁshing, forestry, bio-medicine, tourism, etc. Denote the amounts of capital andlabor in country N as K and L respectively, and the counterparts in country S withan asterisk ∗ . The worldwide endowments are ﬁxed at K w and Lw . Manufacturing ischaracterized by increasing returns, monopolistic competition and iceberg trade costs,
while the agricultural sector produces a homogeneous good under constant returns toscale and perfect competition with zero trade costs (free trade in agriculture).
The production cost of a typical manufacturing ﬁrm in the FC model consists of twoparts: ﬁxed cost and variable cost. To keep the model simple and tractable, we assume
that the ﬁxed cost involves only one unit of capital while the variable cost l units of labor.
In addition, ﬁrms must dispose their pollution according to the national environmental
abatement policy. While many papers in the literature model this by an environmental
tax, we assume that the manufacturing ﬁrms must employ additional workers for pollution
abatement. Speciﬁcally, each manufacturing ﬁrm in country N must spend t units of extralabor for waste disposal per unit of output and the counterpart in country S is t∗ units oflabor. The total cost function for a ﬁrm in country N (resp. S) is therefore r + (l + t)wx

5

[resp. r∗ + (l + t∗ )w∗ x], where r (resp. r∗ ) and w (resp. w∗ ) are the rewards to capitaland labor in country N (resp. S) respectively, and x is the ﬁrm-level output. The useof an abatement policy instead of a tax simpliﬁes the model so that we do not need toconsider how to spend the tax revenue.
As noted in Copeland and Taylor (1999, P. 138), ample empirical evidence links industrial pollution to reduced ﬁshing and agricultural yields, to negative eﬀects on thevalue of standing forests, and to beach closures that hurt tourism. The problem is further complicated by the fact that pollution is transboundary (such as carbon emissions),
under which the amount of pollution is determined by the environmental policies of not
one but both countries. Many studies usually adopt a speciﬁc function of transboundary
pollution. For instance, Benarroch and Thille (2001) assume a linear production functionin the agricultural sector. Here we assume a more general one, by denoting the agricultural production of a worker in country N by α(t, t∗ ) > 0, which is not necessarily linear.
And the counterpart in country S is α∗ (t, t∗ ) > 0. We can call them the agricultural
productivity in N and S respectively. The productivity function is symmetric in the sensethat α(t, t∗ ) = α∗ (t∗ , t). In other words, there is no other ﬁrst-nature diﬀerence between
the two countries in agricultural production, except the eﬀects of industrial pollution.
Furthermore, we assumeα(t, t∗ )≥ α∗ (t, t∗ ) if t > t∗= α∗ (t, t∗ ) if t = t∗ ≤ α∗ (t, t∗ ) if t < t∗ .

∂α
> 0,
∂t

∂α
> 0.
∂t∗

(1)

(2)

Relationship (1) indicates that agricultural production is considered to be higher in acountry with more stringent environmental policy. Some types of pollution (e.g., watercontamination and sulfur dioxide emission) impact local areas more heavily than far-away
areas, so that the strict inequalities hold in (1). However, other types (e.g., carbon dioxide
emission) are more global and impact local and far-away areas more or less the same, thenα(t, t∗ ) = α(t∗ , t) holds even if t ̸= t∗ . In addition, (2) indicates that a better environment

6

(less pollution or more stringent environmental policy) generates a higher agricultural
production in both countries.
Denote the share of capital owned by country N as θK = K/K w , and the share ofcapital employed in country N as θ, which is exactly N’s share of world industry: θ = n/nw ,where notation nw denotes the mass (roughly speaking, the number) of industrial varieties
available worldwide, and n is the counterpart in N only. Note that we have adopted thestandard assumption in the FC model that one ﬁrm uses only one unit of capital, andtherefore, nw = K w .
In each country, each individual shares the same Cobb-Douglas tastes for the two typesof goods:
U=1µµ (1 − µ)1−µµCMCA1−µ ,

where CM represents a composite index of the consumption of M -sector goods, CA isthe consumption of the A-sector good, and µ ∈ (0, 1) is a constant representing theexpenditure share of manufactured goods. The quantity index CM is a subutility functionσ( ∫ nw 1− σ1 ) σ−1
di.
deﬁned over a continuum of varieties of manufactured goods CM =ci0Notation ci denotes the consumption of each available variety i, σ > 1 is the constantelasticity of substitution between any two varieties and 1 − 1/σ is the intensity of thepreference for variety in manufactured goods.
Let E be the total expenditure in country N. Then the indirect utility can be written
as
E
V = ,
P

( ∫ nw
P = p1−µ
A

p1−σ
di
i

µ
) 1−σ

,

(3)

0

where P is called the price index, pi is the price of manufacturing variety i, and pA is thatof A. Analogous deﬁnitions hold for Southern variables, all of which are denoted by anasterisk.
As in the standard literature of spatial economics, this paper assumes that the agricultural product is freely transported between two countries. Assuming that no country
has enough labor to satisfy world demand for A, then the prices of the agricultural goodin two countries are the same: pA = p∗A . We use agriculture as the numéraire good suchthat pA = p∗A = 1. In the manufacturing sector, we assume Samuelson’s iceberg form of7

interregional transportation costs: τ > 1 units of the manufactured good must be shippedfor one unit to reach the other region.
Physical capital moves in search of the highest nominal reward. Following establishedtradition in economic geography, we assume that markets for goods adjust instantaneously,
while interregional migration of capitals is relatively slow, implying that wages adjust
much faster than the capital share. Also following the literature, we apply a standard
dynamic system to describe the international factor ﬂows:
θ̇ = (r − r∗ )(1 − θ)θ.

(4)This is adopted from replicator dynamics, routinely used in evolutionary game theory(Weibull, 1995, p. 73), and is also used in standard textbooks such as Fujita et al. (1999,
p. 62) and Baldwin et al. (2003, p. 72). Intuitively, capital moves to country N if r > r∗ ,in proportion to the present shares θ in country N and 1 − θ in country S.

3Equilibrium

Utility maximization yields the demand function for A as CA = (1 − µ)E/pA , where E
is the expenditure in country N. Perfect competition in the A sector forces marginal costpricing, adjusted by agricultural productivity: pA = w/α(t, t∗ ), p∗A = w∗ /α∗ (t, t∗ ). Since
pA = p∗A = 1, we have w = α(t, t∗ ) = w∗ = α∗ (t, t∗ ). Therefore, the wage in the country
with a better environment is higher if transboundary pollution aﬀects the local country
more severely, while wages in both countries are the same if transboundary pollution issymmetrically global.
Because of the transport costs, the prices of the manufacturing goods in the twocountries are diﬀerent. Let pi be the price of product i in country N made in country N,
p∗i be the price of product i in country S made in country S, p̄i be the price of a producti in country N made in country S and p̄∗i be the price of a product i in country S made incountry N. Then Dixit-Stiglitz monopolistic competition impliespi =w(l + t)σw∗ (l + t∗ )στ w∗ (l + t∗ )στ w(l + t)σ, p∗i =
, p̄i =, p̄∗i =
.
σ−1
σ−1
σ−1
σ−1
8

Country N’s consumption of product j manufactured in country N isp−σ
j µE
cj = ∫ θK w,
∫ θ∗ K w
1−σ1−σ(pi ) di +(p̄i ) di00

and country S’s consumption of this variety isc̄∗j = ∫ θK w

(p̄∗j )−σ µE ∗,∫ θ∗ K w(p∗i )1−σ di(p̄∗i )1−σ di +00where the expenditures are calculated as E = rK + wL and E ∗ = r∗ K ∗ + w∗ L∗ .
Let

[ ∗]σ−1 [ ∗]σ−1w l + t∗α (t, t∗ ) l + t∗
δ≡
=
,
w l+t
α(t, t∗ ) l + t

which represents the trade-oﬀ between the impacts of pollution on the industrial andagricultural productions. The following lemma shows that δ summarizes the impact ofpollution policies in the two countries and, therefore, it is called the South-North policy
burden ratio subsequently. Intuitively, if country N imposes a higher t for a cleaner
environment, manufacturing in this country must consume more labor and becomes morecostly. And as a beneﬁt of a better environment, the agricultural sector becomes moreproductive and Northern workers enjoy a higher wage. This results in δ < 1.
Lemma 1 The following holds< 1 if t > t∗δ

= 1 if t = t∗
 > 1 if t < t∗ .

Proof : Straightforward from (1) and the fact that σ > 1. ¥Note that the higher wage in country N leads to a higher national income, which inturn creates a larger consumption market for goods than country S. Therefore, a more
stringent environmental policy does not necessarily imply that ﬁrms will be driven out of
the country, which we shall investigate in detail soon.
9Under Dixit-Stiglitz competition, if ﬁrms are located in both countries, then the operating proﬁt of a manufacturing ﬁrm in N isϕ(pj )1−σ µθ∗E E w+
σ[p1−σθK w + ϕ(p∗i )1−σ (1 − θ)K w ] σ[ϕp1−σθK w + (p∗i )1−σ (1 − θ)K w ]
i
i
[
]
bE W
θE
ϕθ∗E
= w
+
K
θ + ϕδ (1 − θ) ϕθ + 1−θ
δ
bBE w
=
,
Kw

r=

pj1−σ µθE E w

(5)

where
µ
θE
θ∗
,
B=
+ ϕ E∗ ,
σ
∆
∆
∗
E
E
ϕ = τ 1−σ ∈ (0, 1),
θE = w , θ∗E = w ,EE
ϕ(1 − θ)1−θ∆=θ+,∆∗ = ϕθ +.
δδb=Notation ϕ decreases with the transport cost τ and also measures the freeness of trade.
To simplify notation, we use it to substitute for τ subsequently. Similarly, the operating
proﬁt of a manufacturing ﬁrm in S isr∗ =bB ∗ E w,
δK w

B∗ = ϕθ∗θE+ E∗ .
∆
∆

where

(6)

Note that with Cobb-Douglas preferences, total worldwide spending on manufacturing
equals µE w , and the total operating proﬁts of all ﬁrms are simply µE w /σ = bE w (as aresult from (5) and (6), B = B ∗ /δ = 1). Meanwhile, the deﬁnition of E w gives E w =wθL Lw + w∗ (1 − θL )Lw + bE w , so we have
E w = [wθL + w∗ (1 − θL )]

Lw
.
1−b

(7)

Under the assumption that θK of the capital in each country belongs to Northern

10capital owners regardless of the industry distribution ratio θ, then the average reward tocapital is the same in the two countries, regardless of the spatial allocation of industry
and the degree of openness. Therefore, E = wθL Lw + bθK E w holds and we obtainθE =w(1 − b)θL + bθK ,θL w + (1 − θL )w∗

θL =

L
,
Lw

θK =

K
.
Kw

(8)

In the long-run equilibrium, r = r∗ holds for 0 < θ < 1, which yieldsθ=θE
ϕ(1 − θE )−≡ θ0 .
1 − δϕδ−ϕ(9)

If θ0 ̸∈ (0, 1), then we obtain a corner equilibrium. Speciﬁcally, if δ ≥ 1/ϕ, then B > B ∗ /δand r > r∗ holds from (5) and (6), which results in a corner equilibrium θ = 1. Similarly,
if δ < ϕ, then θ = 0 is a corner equilibrium. In summary, the equilibrium is generally
written as




1,


θ=
0,



 max{0, min{1, θ }},0

if δ ≥ ϕ1 ,if δ ≤ ϕ,(10)

if ϕ < δ < ϕ1 .

In the following, we implicitly assume that δ ∈ (ϕ, 1/ϕ) when we discuss θ0 .

4

Symmetric Countries and Income-Reduction Effects

Grossman and Kruger (1993) state that the direction of trade in dirty goods is primarily determined by conventional determinants of comparative advantage. For instance, acountry’s comparative advantage may lie in the production of “dirty” goods, and thus itis diﬃcult to extract evidence of a pure pollution haven. In contrast, in the present paper
we wish to show that even in the absence of comparative advantage, a pollution havenmay not arise. To do this, we rule out comparative advantage á la Heckscher-Ohlin, byassuming θL = θK = Θ in the subsequent analysis.
Furthermore, this section considers the benchmark of completely symmetric countries11(i.e., Θ = 1/2), except that N is more stringent in pollution abatement policy. Note thatin the original footloose capital model with Dixit-Stiglitz monopolistic competition, no
agglomeration force is observed when two countries are completely identical. We show
instead that an income-reduction eﬀect of cross-sectoral pollution might be strong enoughto dominate a cost-reduction eﬀect of pollution, and as a result a pollution haven does
not arise. The only condition we need is that pollution aﬀects the emitting country more
severely than the other country.
We proceed as follows. Since θK = θL = 1/2, the expenditure ratio θE of (8) can be
written as θE = [(2 − b)w + bw∗ ]/[2(w + w∗ )]. Substituting it into (9), we obtain theindustry distribution ratio
θ0 =
where
θC ≡

ϕ(1 − δ 2 ),2(δ − ϕ)(1 − δϕ)1− θC + θI ,
2

θI ≡

(11)

w − w∗ (1 − b)δ(1 − ϕ2 ).
w + w∗ 2(δ − ϕ)(1 − δϕ)

Recall as in (10), θ0 is the candidate of an interior equilibrium. Therefore, it alsocharacterizes the location of ﬁrms as θ does. In (11), the ﬁrst term on the RHS, 1/2,
comes from the symmetry between the two countries. The second term, −θC , represents
the cost-reduction eﬀect in manufacturing production that ﬁrms are likely to locate in the
country with cheaper labor, stemming from a laxer pollution abatement policy. In fact,−θC increases with δ. This term is negative if country N is more stringent (i.e., δ < 1) andpositive if country N is laxer in pollution abatement. The third term, θI , is the incomereduction eﬀect, showing that ﬁrms seek to locate in the country with a higher purchasing
power. It arises because manufacturing pollution reduces agricultural production, and inturn lowers the local wage if pollution aﬀects the emitting more severely than the foreigncountry. To be speciﬁc, when t > t∗ we have w = α(t, t∗ ) > w∗ = α∗ (t, t∗ ). Then the local
demand in country S is smaller because of the lower wage. In other words, although the
production cost for a ﬁrm locate in country S is lowered due to the laxer environmental
policy, the ﬁrm bears a higher transport cost for its products to be shipped to the N
market to be consumed, which has a higher purchasing power due to its higher income
arising from higher agricultural productivity (less pollution). This eﬀect is also caused by

12the diﬀerence in abatement policy.
Note that simultaneously demonstrating the cost-reduction eﬀect and the incomereduction eﬀect and that they work against each other are novel contributions of thepresent paper. In the received literature, only the former eﬀect has been analyzed. Studies
such as Pﬂüger (2001) also use the monopolistic competition model, but with logarithm
in the utility function instead, and the income-reduction eﬀect cannot be seen. Thus thereceived literature straightforwardly generates the so-called pollution haven, but not casesof a reverse pollution haven which we shall discuss shortly.
One might argue that developing countries attract FDI because wages there are low.
As more FDI comes in, wages increase. This is true without counting the negative eﬀects
of pollution. If such externalities in other environmentally sensitive sectors are included asin the present model, then the increase in income will be discounted. South Korea during
its high-growth period (1960s and 1970s), used to dump industrial waste along its rivers,
especially the Han river. Recently the government decided to spend huge budgets to clean
them up and introduced comprehensive water management measures. A couple of acts
were enacted in 1999 and 2000 for the Han river, the Nakdong river, the Geum river andthe Yeongsan river (Republic of Korea: World Health Organization, 2004). Also, manyargue that the recent rapid growth of the Chinese economy comes at the expense of future
resources, whose negative impact can only be more fully understood 20 or 30 years later.
Let us continue with more discussion of the cost-reduction eﬀect and the incomereduction eﬀect, which are both related to the diﬀerence of pollution policies. In particular, when the two countries adopt the same pollution abatement policy t = t∗ , thepolicy burden ratio becomes δ = 1. Then both the cost-reduction eﬀect and the incomereduction eﬀect disappear. In this special case, there is only one equilibrium θ = 1/2,
which is stable for arbitrary ϕ under dynamic system (4). This simplest case obscuressome important features so that the trade pattern variations do not show up.
However, the cost-reduction eﬀect is independent of the agricultural production which
the income-reduction eﬀect depends on. To see this, we now consider the case thatindustrial pollution on the agricultural sector is globally symmetric so that α(t, t∗ ) =α∗ (t, t∗ ). In this case, w = w∗ holds, and hence the income-reduction eﬀect disappears.

13

If country N is more stringent in environmental regulation, then t > t∗ and the costreduction eﬀect −θC is negative. Seeking for a lower production cost, more ﬁrms move tolocate in S. According to (10), the equilibrium in this case is described as follows.




1,





(1 )



∈
,1 ,


2

θ = 1/2,



( 1)


∈ 0, ,



2





 0,

1 + ϕ2≤ δ,
2ϕ
1 + ϕ2
if 1 < δ <,2ϕif δ = 1,
2ϕif< δ < 1,
1 + ϕ22ϕ
if δ ≤.
1 + ϕ2if(12)

Dynamic system studies (e.g., Tabuchi and Zeng 2004) show that an interior equilibrium of (4) is stable iﬀ d(r − r∗ )/dθ is negative at the equilibrium. Using this stability
condition, we know that (11) is stable when 2ϕ/(1 + ϕ2 ) < δ < (1 + ϕ2 )/(2ϕ). On thecontrary, for small δ such that δ < 2ϕ/(1 + ϕ2 ), we have B < B ∗ /δ at θ = 0 so the corner
equilibrium θ = 0 is stable. Similarly, for large δ such that δ > (1 + ϕ2 )/(2ϕ), the corner
equilibrium θ = 1 is stable. Meanwhile, (12) shows that more ﬁrms locate in S (i.e.,θ < 1/2) if country S has laxer environmental regulations. This special case conﬁrms thepollution haven hypothesis in the literature.
More generally, one expects α(t, t∗ ) ̸= α∗ (t, t∗ ) because pollution might aﬀect local
agriculture more severely. Speciﬁcally, α(t, t∗ ) > α∗ (t, t∗ ) so that w > w∗ if t > t∗ .
Then the income-reduction eﬀect arises, and if it dominates the cost-reduction eﬀect, apollution haven may not arise. Also, it is straightforward to check that both θC andθI are increasing with ϕ when δ < 1. However, since the two eﬀects are opposite insign, the whole pollution eﬀect is not a monotone function of ϕ. The net pollution eﬀect
is observed only if the cost-reduction eﬀect dominates the income-reduction eﬀect. For
example, if consumers prefer more manufacturing goods (µ is large), and/or the elasticity
of substitution σ between varieties is small, and/or pollution is very local, then θI issmall so that it is dominated by θC . Otherwise, θI is large, and we can observe a reverse
pollution haven eﬀect.

14

These results can partially explain the empirical ﬁndings of Eskeland and Harrison(2003, p. 13), who report that for more global pollution such as air pollution, there isa signiﬁcantly positive association between pollution and the pattern of FDI in several
countries, even after controlling for other factors. According to our model, this arises
because the income eﬀect disappears, and hence the pollution eﬀect can be more easily
picked up by empirical studies. But for more local pollution such as water pollution or
toxicity, the income eﬀect still remains, working against the pollution eﬀect. And hence
the pattern might be found to be reversed: FDI is less likely in sectors where emissions
are higher.
The above results are obtained under neither comparative advantage nor agglomeration forces, since the two countries are assumed to be completely identical except in
pollution abatement policy. Summarizing these results, we can establish:
Proposition 1 Under the conditions of completely symmetric countries and globally asymmetric pollution in the sense that pollution aﬀects the emitting country more severely thanthe other country, the “pollution haven” eﬀect is the compound of the cost-reduction eﬀect
and the income-reduction eﬀect. The former encourages ﬁrms to locate in the pollution
haven but the latter discourages them. As a consequence, a pollution haven arises only if
the former dominates the latter. Otherwise a reverse pollution haven may arise.

5

Asymmetric Countries and the Home Market EffectNow we are ready to tackle the asymmetric case of Θ ̸= 1/2, i.e., countries are diﬀerent
in size. Without loss of generality, we assume that N is larger than S, i.e., Θ > 1/2.
Our purpose is to demonstrate that the pollution haven eﬀect can be dominated by otherforces even when pollution is globally symmetric in the sense that pollution aﬀects all
countries the same, near or far. In this case the income-reduction eﬀect derived in theprevious section disappears, but we show that agglomeration forces work against and candominate the cost-reduction eﬀect.

15

We continue to rule out comparative advantage by setting θL = θK = Θ. Then theﬁrm ratio (9) becomesϕ(1 − 2ϕδ + δ 2 )(2Θ − 1)ϕ(1 − δ 2 )−2(δ − ϕ)(1 − δϕ)2(δ − ϕ)(1 − δϕ)∗(w − w )Θ(1 − Θ) (1 − b)δ(1 − ϕ2 )+.
wΘ + w∗ (1 − Θ) (δ − ϕ)(1 − δϕ)θ0 =Θ +

(13)

If the two countries adopt the same environmental policy t = t∗ , then δ = 1 and (13)is simpliﬁed asθ01 ≡ Θ +

2ϕ (
1)
Θ− .
1−ϕ
2

Obviously θ01 > Θ, which says that the country with relatively larger local demand(country N) attracts a more-than-proportionate share of ﬁrms in the monopolisticallycompetitive manufacturing industry. This is called the home market eﬀect (HME) in theliterature of spatial economics (Krugman, 1980). Davis and Weinstein (1999) interprete
the HME as a magniﬁed impact of a high demand for production and ﬁnd some evidenceof it. Notice that the HME originates from increasing-returns-to-scale technologies inmanufacturing. It is diﬀerent from the scale eﬀect in the literature of environmental
economics (e.g., Grossman and Krueger (1993), Copeland and Taylor (2004)), which is
the increase in pollution generated if the whole economy were simply scaled up using aframework of constant-returns-to-scale technologies.
Diﬀerentiation gives∂θ01
2Θ − 1=> 0,∂ϕ(1 − ϕ)2(14)

which implies that the Northern relative market size matters more when trade barriers arelower. This is called the secondary magniﬁcation eﬀect in spatial economics, e.g., Headand Mayer (2004).
When δ ̸= 1, the HME is accompanied by the pollution eﬀect, which is represented
by the third and forth terms of (13) on the RHS. To examine how various eﬀects are
combined, we ﬁrst consider the case of globally symmetric pollution so that w = w∗ . Then16the income-reduction eﬀect disappears and (13) becomesθ02 ≡ Θ + θHME − θC ,where
θHME =(15)

ϕ(1 − 2ϕδ + δ 2 )(2Θ − 1)ϕ(1 − δ 2 )and θC =.
2(δ − ϕ)(1 − δϕ)2(δ − ϕ)(1 − δϕ)In the above, expression θHME represents the HME and θC is the cost-reduction eﬀect ofpollution.
Note that θHME is positive while −θC is negative iﬀ δ < 1 (i.e., t > t∗ : the larger
country N holds a more stringent environmental policy). Furthermore, θHME decreases
with δ if δ < 1 and θC always decreases with δ:∂θHME(1 − δ 2 )(2Θ − 1)ϕ(1 − ϕ2 )=−< 0, iﬀ δ < 1;∂δ2(δ − ϕ)2 (1 − δϕ)2
∂θC
ϕ[(1 − δϕ)2 + (δ − ϕ)2 ]
=−
< 0.
∂δ
2(δ − ϕ)2 (1 − δϕ)2

(16)

Evidently, θ02 is an interior equilibrium (i.e., θ02 ∈ (0, 1)) iﬀ
(
δ∈ Θ

)
1
1−Θ
,
+ Θϕ ,
ϕ
+
(1
−
Θ)ϕ
ϕ

(17)

which is a subinterval of (ϕ, 1/ϕ). Furthermore, condition (17) ensures stability of theinterior equilibrium under dynamic system (4). Corner equilibrium θ = 1 is stable for alarger δ outside of (17), and corner equilibrium θ = 0 is stable for a smaller δ.
We can make the following statement to synthesize the HME and the pollution eﬀect.
Proposition 2 If pollution is globally symmetric, then for any ϕ ∈ (0, 1), θ02 increases
with δ of (17), and there exists a critical δ ♯ ∈ (ϕ, 1), such that the equilibrium distribution
is




> Θ if δ > δ ♯ ,θ = Θ if δ = δ ♯ , < Θ if δ < δ ♯ .

17

Proof: The derivative of θ02 with respect to δ is∂θ02
ϕ[(1 − δϕ)2 − (1 − δ 2 )(1 − ϕ2 )Θ]ϕ(δ − ϕ)2
=
≥
≥ 0,
∂δ
(δ − ϕ)2 (1 − δϕ)2(δ − ϕ)2 (1 − δϕ)2
where the ﬁrst inequality holds evidently if δ ≥ 1 and is also true if δ < 1 because Θ ≤ 1.
Therefore, θ02 increases with δ.
Given the above monotonic relationship, from (15) we also obtain
θHME − θC =ϕ[Θδ 2 − ϕ(2Θ − 1)δ + Θ − 1].
2(δ − ϕ)(1 − δϕ)

The expression in square brackets is a quadratic function of δ. It is negative at δ = ϕ andpositive at δ = 1. Thus there exists a unique solution (denoted by δ ♯ ) satisfying
Θδ 2 − ϕ(2Θ − 1)δ + Θ − 1 = 0(18)

in (ϕ, 1). Proposition 2 immediately follows from (10) and (15). ¥We can use Figure 1 below to explain Proposition 2 in detail, which can be divided
into 3 cases.
θ

r6
1

rΘ
r

u

0 r ϕrδr♯

1/2

Case 3

1r
Case 2

1/ϕr- δCase 1Figure 1: The Location of Manufacturing Firms w.r.t. δ

Case 1: If country N has laxer environmental regulations than country S (t < t∗ ), then18δ > 1 (> δ ♯ ). The home market eﬀect and the cost-reduction eﬀect enhance each other.
As a result, the share of manufacturing ﬁrms located in country N, θ, is much higher thanN’s share of factor endowments Θ.
According to Taylor (2004), the pollution haven hypothesis also indicates that a movement from autarky to free trade would lead to the relocation of dirty production fromcountry N to country S if t∗ < t. We obtain the same result here, but with a little difference. To see this, note that t∗ < t leads to δ < 1. Since interval (17) converges to one
point, 1, when ϕ approaches 1, δ is in the left of interval (17). Therefore, all ﬁrms move tocountry S in the unique stable equilibrium when the transport cost τ is very small. The
diﬀerence from the existing literature is, our research suggests that one reason we might
not observe the pollution haven eﬀect from the empirical data is because the transport
cost in the real world is not free at all, as in case 1 of Figure 1.
Case 2: If country S has a slightly laxer regulation than N, i.e., t > t∗ but thatδ ♯ < δ < 1, then the HME and the cost-reduction eﬀects work in opposite directions but
the former dominates the latter. In other words, a more than proportionate share of ﬁrms
still agglomerates in country N despite that country S would be a pollution haven without
counting the agglomeration forces. This provides another explanation why the pollution
haven eﬀect is diﬃcult to pick up in empirical studies. As mentioned in the introduction,
our theoretical results are supported by the empirical study of Wagner and Timmins(2004), who include FDI stock to capture agglomeration eﬀects in their analysis. They
conclude that it would seem that tough regulations attract pollution-intensive industries
whereas in reality they relocate to a country because they beneﬁt from FDI agglomeration,
which is consistent with case 2 in Figure 1.
Further, the analytical solvability of the present model allows us to say more. For
example, we ﬁnd that the critical value δ ♯ of (18) increases with ϕ and decreases with Θ
because(2Θ − 1)δ ♯ + 1 − Θ∂δ ♯) > 0,(=
2Θ − 1∂ϕ♯ϕ
2Θ δ −
2Θ

19

∂δ ♯
(δ ♯ − ϕ)2 + ϕ(1 − ϕ)
) < 0.
=− (2Θ − 1∂Θ♯
2Θ δ −
ϕ2Θ
Therefore, case 2 is more likely to arise when transport costs are high and/or whencountries are more diﬀerent in size.
Case 3: Finally, if country S has much laxer environmental regulations than N suchthat δ < δ ♯ , then the cost-reduction eﬀect dominates the HME. In other words, a morethan proportionate share of ﬁrms locate in country S in order to escape from the more
stringent environmental regulations in country N. This corresponds to the industries withsmall agglomeration forces such as primary metals in the study of Wagner and Timmins(2004). Researchers in spatial economics ﬁnd that often it is hard to pick up the HME
in empirical studies (e.g., Davis and Weinstein, 1999 and 2003), and they even term thephenomenon “reverse HME” (e.g., Yu, 2005). The present model clearly shows that theHME exists, but we provide an explanation from a diﬀerent angle—the cost-reductioneﬀect of pollution, which can dominate the HME.
Now we turn to examine how industrial location changes with decreasing transport
costs (i.e., increasing ϕ), given the policy burden ratio δ. For simplicity, we keep theassumption of globally symmetric pollution and focus on the case of θ > 1/2 and δ < 1(the larger country N holds a more stringent regulation policy).
The equilibrium expression (10) is rewritten as

θ=


 0

if ϕ ≥ δ max{0, min{1, θ }} if ϕ < δ.
02where θ02 is deﬁned in (15). It includes two cases. (i). When the trasport costs are small(ϕ ≥ δ), the cost-reduction eﬀect dominates so that country S attracts all ﬁrms; (ii). For
larger transport costs (ϕ < δ), θ02 is not a monotone function of ϕ. In this case, similarto (14), the HME is increasing in ϕ:δ(2Θ − 1)[(1 − δϕ)2 + (δ − ϕ)2 ]
∂θHME
=
> 0,
∂ϕ
2(δ − ϕ)2 (1 − δϕ)220

i.e., the HME is stronger for smaller transport costs. However, it is complicated by the
cost-reduction eﬀect. In fact, from (15) we derive∂θ02Θ[(1 − δϕ)2 + (ϕ − δ)2 ] − (1 − δϕ)2=.
δ∂ϕ(δ − ϕ)2 (1 − δϕ)2
The ﬁrst term of the numerator on the RHS is positive while the second term is negative. If√
the pollution policies are very diﬀerent such that δ ≤ (1 − Θ)/Θ, then ∂θ02 /∂ϕ is always
negative so that the equilibrium ratio θ strictly decreases from Θ to 0 with decreasingtransport costs τ . The situation is plotted on the left panel of Figure 2. On the other√
hand, if the pollution policies are not too much diﬀerent so that δ > (1 − Θ)/Θ, then
θ02 increases with ϕ until√√Θ δ− 1−Θ
ϕ ≡√,√Θ− 1−Θ δ♯and then decreases to 0 after ϕ♯ . The situation is plotted on the right panel of Figure 2.
Therefore, we can conclude with
Proposition 3 The Northern relative market size matters less when the environmental
policy in country S is suﬃciently lax, and freer trade is more likely to cause a pollution
haven to arise.

θ

θ

6
s1

6
s1

Θ s

Θ s

1/2 s

1/2 s
√

0s

s

δ

1−Θ
Θ

s

ϕ

s-

0

1

s

ϕs♯

√

s

δs

1−Θ
Θ

Figure 2: The Location of Manufacturing Firms w.r.t. ϕ

21

s- ϕ

1

Having explained Proposition 3, now we are ready to examine the most general situation in which manufacturing pollution impacts agricultural production in the emitting
country more heavily than that in the foreign country. Due to pollution, the beneﬁt ofmore industrial ﬁrms is accompanied by the loss of lower agriculture production and lower
wages. That is, α(t, t∗ ) > α∗ (t, t∗ ), w > w∗ and δ < 1 hold if t > t∗ . We already know that
this leads to a small local demand for the manufacturing good, and a ﬁrm in S must pay
transport costs to sell in the larger N market, i.e., the income-reduction eﬀect. Precisely,(13) can be re written asθ0 = Θ + θHME − θC + θI ,where,(w − w∗ )Θ(1 − Θ) (1 − b)δ(1 − ϕ2 )θI =.
wΘ + w∗ (1 − Θ) (δ − ϕ)(1 − δϕ)

Since θI decreases with Θ, the income-reduction eﬀect is the largest in the case of symmetric countries. Meanwhile, since δ/[(δ − ϕ)(1 − δϕ)] decreases with δ iﬀ δ < 1, θI islarger for a smaller δ. And since θC and θI have opposite signs, we know that the larger
the diﬀerence between α(t, t∗ ) and α∗ (t, t∗ ), the more the pollution eﬀect is weakened by
θI . However, because of (16), the sign of the whole pollution eﬀect is determined by the
relative size of parameters b, Θ, among others.
Overall, for δ < 1 and Θ > 1/2, the HME and the income-reduction eﬀect combined
can alleviate the cost-reduction eﬀect in S, which makes it more diﬃcult to observe thepollution eﬀect in S empirically.
We are in a position to summarize the main conclusions of this section:
Proposition 4 Under the conditions of asymmetric country sizes without comparativeadvantage, there are three eﬀects jointly determining the industrial location. The costreduction eﬀect of pollution encourages the ﬁrms to locate in the country with laxer regulation, the income eﬀect discourages it, and simultaneously ﬁrms prefer the larger country
due to the home market eﬀect.
This Proposition implies that in industries characterized by imperfect competition
and increasing returns to scale, a pollution haven may not arise in the smaller developing
22

country with laxer environmental regulations, either because the agglomeration forces in
the larger developed country dominates the pollution haven eﬀect, and/or because theincome-reduction eﬀect of pollution dominates the cost-reduction eﬀect.

6

The Need for International Policy Coordination

We have examined the industrial location given each country’s environmental policy in theprevious sections. Now we turn to the decision making of each governments and examine
the issue of a “race to the bottom” in abatement policy. We demonstrate that without
international policy cooperation, if countries were to choose their individual abatement
policies optimally but noncooperatively, then as trade costs decrease, a “race to the bottom” arises. On the other hand, with international coordination, it can be avoided. To
illustrate our point, we only need to focus on the case of completely symmetric countries:
Θ = 1/2. Furthermore, our argument is concentrated on the case that the two policies
are not too diﬀerent so that θ0 of (9) is indeed an interior equilibrium.
Using (3), (7), (8) and (9), the welfare in N can be written as
[
]µ
µ
µ
σ−1
E
w
w σ−1
VN = = θE E (K ) [θδ + (1 − θ)ϕ] σ−1 ∗Pw (l + t∗ )σ[]µ∗µ (2 − b)w + bw
µ
σ
−
1
w
w σ−1
=[θ0 δ + (1 − θ0 )ϕ] σ−1L(K)
4(1 − b)w∗ (l + t∗ )σ=Γ × W (t, t∗ ),
where

µ

µ

Γ=

Lw (K w ) σ−1 (1 − ϕ2 ) σ−1µ

22+ σ−1 (1 − b)

(

σ−1
σ

)µ

is a positive constant and independent of the abatement policies t and t∗ , andµ∗W (t, t ) =[(2 − b)w + bw∗ ]1+ σ−1µµ{[w(l + t)]σ−1 − ϕ[w∗ (l + t∗ )]σ−1 } σ−1 (w + w∗ ) σ−1.

Now consider a noncooperative game between the two governments of N and S. Eachgovernment maximizes its own welfare choosing own abatement policy, simultaneously.

23

In other words, given t∗ , the government of country N maximizes W by choosing t. The
ﬁrst order condition for the optimal t is)∗∗
+ b ∂w+ ∂w(2 − b) ∂w
µ
µ ∂w
∂t
∂t
∂t
∂t
1+
−
σ − 1 (2 − b)w + bw∗
σ − 1 w + w∗∗
∗ σ−2 ∂w∗
∗ }
(l
+
t)
+
w]
−
ϕ[w
(l
+
t
)]
[
(l
+
t
)]
[w(l + t)]σ−2 ][ ∂w∂t∂t−µ[w(l + t)]σ−1 − ϕ[w∗ (l + t∗ )]σ−1

∂W
=W
∂t

{(

=0.
Analogously, the Southern government maximizes W ∗ (t∗ , t) which can be deﬁned symmetrically as W (t, t∗ ). And its ﬁrst order condition can be derived similarly as above.
Solving the two equations, given that the two countries are completely identical, we
must obtain t = t∗ ≡ te , where te is the noncooperative pollution abatement policy thatsolves[][]∂α(te , te )b (1 − b)µµ∂α∗ (te , te ) b (1 − b)µ
ϕµ
1− +
−
+
−
+
∂t
2 2(σ − 1) 1 − ϕ∂t
2 2(σ − 1) 1 − ϕµα(te , te )=.
(1 − ϕ)(l + te )In particular, if pollution is globally symmetrical, then the above equation is simpliﬁedas∂α(te , te )
1
µ
=
.
e
e
α(t , t )∂t
(1 − ϕ)(1 − µ)(l + te )(19)

The RHS converges to inﬁnity if ϕ approaches 1. Therefore, as a solution of (19), te
becomes very small, implying a very low noncooperative abatement. This gives rise to
the so-called a “race to the bottom” of environmental policy.
Notice that this phenomenon is related to Proposition 3, in which we showed that as
trade becomes freer, a pollution haven is more likely to arise. Basically there is a trade-oﬀ
involving the optimal regulation policy t. We know that on the one hand, the incomereduction eﬀect of a laxer regulation decreases the local nominal wage; on the other hand,a laxer regulation attracts more ﬁrms due to the cost-reduction eﬀect. The latter eﬀect
lowers the local price index by increasing the number of manufacturing varieties. Thisdecrease in the price index in turn raises the real wages of its residents. As trade cost falls,
24each country will then try to attract more ﬁrms into its boundary by choosing a lower
abatement, the only policy considered here. Note that this result is obtained without
taking into account the negative impacts of pollution on consumer utility. Depending on
how severe such negative externalities are, if they are also considered, then this result
may change.
In order to avoid the “race to the bottom”, we now consider the optimal environmental
policy if there is a worldwide planner who can specify t = t∗ = to . Summing up the welfareof the two countries yields
E E∗
VN + VS = + ∗
P
P
w

=(K )

µ
σ−1

(1 − ϕ )
2

µ
σ−1

(

σ−1
σ

)µ

µ ]
[
1+ µ
Ew
θE σ−1(1 − θE )1+ σ−1
+
,
µ
µ
µ
σ−1
σ−1
p1−µ
[w(l
+
t)]
(1
−
δϕ)
(δ
−
ϕ)
A

where θE is determined by (8).
Setting t = t∗ = to , we have
1wL2
w = w∗ , δ = 1, θE = , E w =.
2
1−bThen the total welfare is simpliﬁed as
VN + VS =w1−µ[α(t, t)]1−µ× Constant.
×Constant=µ(l + t)µp1−µ
A (l + t)

Therefore, optimal policy to is the solution to:1µ
dα(to , to )
=
.
o
o
o
α(t , t ) dt
(1 − µ)(l + to )(20)

Diﬀerent from (19), expression (20) is independent of ϕ. This implies that even when
trade is completely free, the worldwide planner would not choose zero abatement. Therefore, when transport costs decrease (especially in the age of globalization), international
cooperation such as the Montreal Protocol and the Kyoto Protocol is called for to prevent25

a “race to the bottom” in environmental standards. And the call becomes stronger withdecreasing trade costs.

7

Conclusion

The pollution haven hypothesis, that a tightening up of pollution regulation will havean eﬀect on ﬁrm location, has strong support from theory but little from empirics. To
explain for this gap, some authors conclude that the location of industries is conventionallydetermined by comparative advantage of factor endowments and diﬀerences in technology,
instead of the pollution policies.
While comparative advantage is evidently one factor, it is not the unique one. Recognizing that manufacturing production usually involves technologies of increasing returns
to scale and imperfect competition, we constructed a model demonstrating that the agglomeration force of industries is a potential reason for ﬁrms not to locate in the“pollution
haven”. Incorporating cross-sectoral and transboundary pollution into the footloose capital model of spatial economics, we indeed ﬁnd three eﬀects besides the usual explanationof comparative advantage. While the cost-reduction eﬀect encourages polluting ﬁrms tomove to the country with lax regulations, the income-reduction eﬀect discourages sucha move. In addition, the agglomeration force of the home market eﬀect hinders ﬁrms
from moving out of the larger developed country. These results are supported by recent
empirical ﬁndings.
To keep the model tractable, we have abstracted from incorporating the negative
impacts of pollution in the consumer utility function and the national welfare function.
Such eﬀects work in the same direction as the income-reduction eﬀect of pollution. Thus,taking into consideration such negative externalities makes it more diﬃcult to ﬁnd apollution haven.

26

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