Environmental regulation through trade: the case of shrimp

Darren Hudsona,*, Diane Hiteb, Abdul Jaffara, Fatimah Karia

aDepartment of Agricultural Economics, Mississippi State University, Mississippi State, MS 39762, USAbDepartment of Agricultural Economics, Auburn University, USA

Received 30 October 2002; revised 2 January 2003; accepted 19 February 2003

Abstract

The implications of a potential ban on shrimp imports by the US from countries that do not utilize the Turtle Excluder Device on

commercial shrimp nets is explored in this paper. A Linear Expenditure System (LES) was used to determine the own-price elasticities of

demand for shrimp imports. The system of estimated equations was then solved for quantity levels under assumptions made about the trade

restrictions, resulting in a set of prices for those import levels. These estimated prices were then used to estimate the compensating variation

impact of the trade restrictions. Findings suggest that the environmental regulation would have a negative impact on US consumers, but the

magnitude of that effect depends on assumptions made regarding the distribution of US imports after the trade restriction is imposed.

q 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Shrimp; Linear expenditure system; Compensating variation; Import restrictions; Environmental regulation

1. Introduction

Trade and the environment are inexorably linked. Recent

discussion on a broad range of issues has clearly shown that

trade has both environmental benefits and costs (Copeland

and Taylor, 1995, 765–771). These developments in the

literature have improved our understanding of the linkages

between trade and the environment and allowed the design

of better models that incorporate these linkages. Despite

these advances in the literature, there has been only minor

treatment of the consequences of environmental regulation

implemented through trade. Most available literature

focuses on the trade impacts of environmental regulations

(Valluru and Peterson, 1997, 261–272; Bohman and

Lindsay, 1997, 17–38; Marchant and Ballenger, 1994,

108–128; Seale and Fairchild, 1994, 97–107).1 One

example of potential environmental regulation implemented

through a trade restriction lies in the shrimp industry.

Commercial shrimp trawling often creates by-catch

problems, especially with sea turtles in warm waters. A

recent development called the Turtle Excluder Device

(TED) has shown some promise in reducing turtle by-catch

when attached to shrimp nets. The US has sought wide-

spread adoption of the TED system on commercial

shrimping fleets worldwide. However, some countries

dispute the efficacy of the TED system and have refused

its adoption (Holloway, 1998, 3; Stewart, 1998, 197–219).

To promote adoption, the US placed an import ban on

shrimp originating in countries that do not have the TED

system on their commercial fleets.2 However, the World

Trade Organization (WTO) found that this action was in

violation of the General Agreement on Tariffs and Trade

(GATT).3 Undaunted, the US placed a de facto ban on

shrimp imports from non-complying countries through

Food and Drug Administration (FDA) safety and inspection

regulations on December 18, 1998.4 While there are other

0301-4797/03/$ - see front matter q 2003 Elsevier Science Ltd. All rights reserved.

doi:10.1016/S0301-4797(03)00061-6

Journal of Environmental Management 68 (2003) 231–238

www.elsevier.com/locate/jenvman

* Corresponding author. Tel.: þ1-662-325-7998; fax: þ1-662-325-6614.

E-mail address: hudson@agecon.msstate.edu (D. Hudson).1 The reader is referred to The Greening of World Trade Issues edited by

Anderson and Blackhurst, which lays out in detail the linkages between

trade and the environment.

2 This, of course is a simplification of the issue. For a good discussion on

the history and issues underlying the TED debate and the shrimp import

ban, see Stewart (1998, 197–219).3 The precedent for this ruling had already been set. The US placed a ban

on imports of tuna not caught in a ‘dolphin safe’ manner. The WTO ruled

against the US in this case. This ultimately led to a labeling of tuna as

‘dolphin safe’ for those supplies caught with different, larger sized nets.

Other countries adopted these nets in order to insure their tuna could be

labeled ‘dolphin safe’.4 The original import ban was aimed only at wild caught shrimp.

However, the Earth Island Institute sued the US government, and now the

ban is applied to all shrimp imports from countries not in compliance with

the TEDs. Thus, all imports, whether aquaculture or wild caught, are

affected by the ban.

motivations for safety restrictions such as disease outbreaks

in shrimp supplies, it has facilitated the implementation of

an environmental policy through a trade restriction.

There are many economic and social issues surrounding

such a ban. For example, is it equitable for the US to utilize

unilateral trade restrictions in an attempt to force other

countries to follow what the US deems an appropriate

environmental policy? Is this consistent with the free trade

principles of the WTO? What are the costs of such a policy?

Are there alternative methods of achieving the environ-

mental goal of reducing sea turtle by-catch?

The legal ramifications and equity issues associated with

the trade ban are beyond the scope of this study. However,

some knowledge of the potential welfare impacts of the ban

would be useful in the debate. No previous study has

addressed the impacts of the shrimp import ban. Artificial

trade distortions lead to expectations of decreased welfare

for US consumers. However, in a system of multiple price

changes, analytical expectations become complex and can

be misleading. Thus, it becomes necessary to expand the

analytical framework in order to quantify the effects of these

policies. The objective of this paper is to analyze the import

demand for shrimp in the US and assess the implications of

a ban on specific shrimp imports. This should provide an

estimate of the opportunity cost to US consumers of

achieving the environmental goal.

2. Shrimp imports

Shrimp imports into the US have become increasingly

prevalent, growing from 40% of domestic consumption in

1980 to 67% by 1996. Table 1 shows that the distribution of

imports has changed substantially as well.

In general, imports have shifted away from Central and

South American countries to Association of Southeast Asian

Nations (ASEAN) or Asian countries. The exception to this

has been Equador, which has exhibited an increasing market

share. The increase in ASEAN market share has come in the

face of increasing ASEAN prices (Table 2).

ASEAN prices increased by 188% during the study

period while the rate of increase for other countries ranges

from just 13–76%. Furthermore, in 1996, the ASEAN price

is 33% higher than the next highest price. This phenomenon

may indicate a relative preference for Asian shrimp or that

Asian shrimp is of superior quality. However, no data are

available to directly support this hypothesis.

A second element not captured in the data is the

increasing prevalence of aquaculture or farm-raised shrimp.

Some countries such as Thailand have increased aqua-

culture production and now harvest virtually no wild caught

shrimp. However, the data on aquaculture shrimp are

inconsistent. Data on imports are not differentiated by

aquaculture or wild caught. However, because the ban is

currently applied to all shrimp imports from specific

countries, this distinction is not germane.4

3. Related literature

Previous economic studies on shrimp have typically

focused on price determination and domestic marketing

issues. One of the earliest studies by Doll (1972, 431–440)

examined the ex-vessel shrimp price movements between

1950 and 1968. Adams et al. (1987, 103–112) analyzed the

price relationships between market levels for different sizes

of shrimp incorporating the dynamic nature of price

transmission between market levels. Hopkins (1980) also

Table 1

Market share for shrimp imported into the US, 1980–1996

Year Total imports ($000) NAFTA (%) Brazil and Argentina (%) ASEAN (%) EU (%) Equador (%) India (%) China (%) ROW (%)

1980 719,263 44.81 2.83 4.19 0.76 9.47 2.91 1.36 33.69

1981 723,875 40.71 3.30 2.35 0.75 11.09 4.52 2.44 34.83

1982 980,233 38.92 4.37 2.32 0.18 13.93 5.05 1.17 34.06

1983 1,233,522 32.58 4.55 5.16 0.61 17.88 4.35 0.49 34.38

1984 1,216,350 31.34 6.69 6.50 0.74 15.25 3.38 1.02 35.07

1985 1,152,912 26.75 7.10 8.76 1.59 14.41 3.70 1.85 35.84

1986 1,434,337 23.89 4.76 7.90 1.16 19.37 3.26 4.36 35.29

1987 1,710,224 24.33 3.03 7.88 0.85 22.13 6.95 3.33 31.49

1988 1,754,690 18.51 3.45 10.28 0.46 21.78 17.10 3.14 25.28

1989 1,705,192 17.26 2.93 20.19 0.28 18.10 3.03 16.23 21.98

1990 1,658,691 11.31 1.31 25.07 0.16 17.55 3.41 21.41 19.78

1991 1,856,667 10.53 1.27 34.69 0.07 19.51 3.63 11.83 18.46

1992 2,017,433 7.84 1.97 35.86 0.16 18.77 3.00 15.75 16.66

1993 2,169,581 10.28 1.76 40.06 0.04 17.09 3.80 8.47 18.50

1994 2,667,755 10.25 1.31 42.86 0.15 17.06 5.33 3.94 19.11

1995 2,580,891 14.30 0.62 42.05 0.22 17.18 4.26 3.08 18.29

1996 2,457,500 14.42 0.27 42.78 0.15 15.05 4.83 1.44 21.07

Average share 22.24 3.03 19.94 0.49 16.80 3.82 6.99 26.69

Source: Current Fisheries Statistics, various issues (US Department of Commerce).

D. Hudson et al. / Journal of Environmental Management 68 (2003) 231–238232

focused attention on domestic issues of the shrimp industry

without much elaboration on shrimp imports. No previous

study, however, has derived system wide shrimp import

demand elasticities, which are necessary to assess the

impacts of trade restrictions.5 The systems approach is

advantageous in the context of the current study because it

allows differentiation of imports by source, which in turn

allows the analysis of trade restrictions on specific import

sources. Furthermore, the system can capture complex

price/quantity interactions in the shrimp import market that

are lost in a single equation framework.

A wide variety of demand system models have been

applied in the literature. A number of studies have utilized

the Linear Expenditure System (LES) or versions of LES

(Richards et al., 1997, 825–837; Green et al., 1979, 41–52;

McIntosh, 1974, 45–51; Goddard, 1983, 291–318; Deaton

and Muellbauer, 1980). The LES model is parsimonious in

its estimation requirements and is ideal for situations where

data is limited. It is, however, a relatively restrictive model

structure. Weatherspoon and Seale (1995, 536– 543)

estimated a system-wide beef import demand model for

Japan. In their analysis, they suggested the use of a nested

test of the Rotterdam and Central Bureau of Statistics (CBS)

model to test for proper functional form. They concluded

that the CBS model best fit the data for their analysis.

Despite being more flexible, however, these models require

more data for accurate estimation.

Huang (1993, 217–227) analyzed meat trade effects on

US consumers through a demand systems approach. In

particular, he estimated an inverse demand system to predict

price changes as a result of quantity changes coming from

trade. Huang (1993, 217–227) also estimated an ordinary

demand system to derive own- and cross-price elasticities of

demand. Combining the results of both models, he was able

to derive estimates of Hicksian compensating variation

(CV) for different scenarios of quantity effects as a result of

meat trade.

The appealing feature of the Huang (1993, 217–227)

approach is that it explicitly accounts for price changes as a

result of trade changes. However, it does so in an indirect

fashion. That is, Huang’s (1993, 217–223) method requires

the estimation of two separate models, which requires two

sets of assumptions and are subject to two sets of random

error. A more direct approach requiring estimation of one

system of equations would be desirable to estimate the

welfare effects of quantity changes.

4. Methods

The traditional method of estimating trade models

centers on the assumption, attributed to Armington (1969,

159–178), that product importation is differentiated by

region of origin. Armington (1969, 159–178) developed an

empirical framework in which to estimate import/export

demand functions. However, some researchers have deemed

the Armington (1969, 159–178) framework too restrictive

and have opted for more flexible estimation methods (Yang

and Koo, 1994, 396–408). While achieving some degree of

flexibility, analyses that utilize more flexible estimation

methods maintain the underlying assumption that product

imports–exports are differentiated by region of origin. For

purposes of this analysis, the assumption that shrimp

imports are differentiated by region of origin is maintained.

Table 2

Trade weighted shrimp import prices from various regions, 1980–1996

Year NAFTAa Brazil and Argentinaa ASEANa EUa Equadora Indiaa Chinaa ROWa

1980 4.99 2.81 2.28 2.91 4.09 1.95 2.18 3.91

1981 4.88 2.62 2.67 3.53 3.94 2.09 4.30 3.82

1982 5.52 3.79 2.76 3.16 4.59 2.23 5.01 4.06

1983 5.43 3.74 3.22 3.34 5.17 2.15 3.92 4.10

1984 5.47 3.82 3.65 3.25 4.83 2.15 4.65 4.00

1985 5.21 3.36 3.32 4.22 4.59 2.16 3.73 3.55

1986 5.33 4.02 3.37 3.93 5.44 2.32 3.67 4.14

1987 5.43 3.72 3.65 4.33 4.54 3.40 2.44 4.43

1988 5.72 3.60 4.63 4.35 4.46 3.49 2.08 4.32

1989 5.54 3.22 4.53 3.92 4.62 2.19 3.26 4.02

1990 5.43 2.99 5.07 4.19 4.19 2.19 3.40 3.69

1991 5.38 3.47 5.02 3.84 4.08 2.12 3.44 3.87

1992 5.30 3.68 5.08 3.36 3.81 1.88 3.54 3.94

1993 5.17 3.85 5.47 3.65 4.15 2.37 3.27 3.91

1994 5.45 4.04 6.40 3.75 5.21 3.47 2.53 4.68

1995 5.02 4.49 6.78 5.06 4.72 3.41 2.99 4.68

1996 4.91 3.97 6.57 3.28 4.62 3.45 2.52 4.45

Source: Current Fisheries Statistics, various issues. (US Department of Commerce, 1985–1998).a 1984 constant dollars per pound.

5 The systems approach refers to the use of a complete demand system for

shrimp imports. The complete demand system has the advantage of

accounting for all of the interactions between shrimp imports from different

regions. It does not, however, allow for explicit treatment of supply effects.

D. Hudson et al. / Journal of Environmental Management 68 (2003) 231–238 233

Given the wide variance in observed regional prices, this is

probably a reasonable assumption, but the assumption is

tested empirically.

Differentiation of shrimp imports by region of origin

suggests that a system of equations estimation method

should be employed. There is a wide variety of demand

system models available for use in analysis, each with its

relative strengths and weaknesses. The preference in the

literature is for the use of flexible functional form models

such as the AIDS. Computational difficulties associated

with maximum likelihood estimation of the non-linear

AIDS model has led to the widespread use of the Linear

Approximation to the AIDS model (or LA/AIDS). How-

ever, as Buse (1994, 781–793) points out, the potential bias

in the LA/AIDS model and the widespread availability of

solution algorithms has led researchers to prefer the AIDS

model over its linear counterpart.

Flexible functional form models are thought to be

superior because they do not impose restrictions on the

underlying utility function, and can be used to test the

assumptions of homotheticity and homogeneity. However,

they can be quite data intensive, requiring more degrees of

freedom than more restrictive models such as the LES. The

LES is the most parsimonious of commonly used demand

system models, requiring the least number of observations

to obtain an estimate. This can be advantageous when data

are scarce. However, the LES has limitations as well,

primarily stemming from the simplicity of the Stone–Geary

utility function from which it is derived. The primary

limitation is that the LES cross-price elasticities are

negative by construction, which allows consideration of

Marshallian gross complements only and limiting compari-

son to Hicksian substitutes. Thus, the LES is typically used

to describe broad product groupings. That is, the LES is

used to describe groupings that account for a large portion of

total expenditures so that each grouping is seen as

competing with the other groups for a portion of total

expenditure in Hicksian terms.

4.1. Empirical model

The LES model was chosen for this analysis. This choice

was made for three primary reasons. First, to reduce the

probability of crossing multiple unknown structural changes

in the market, the time period was restricted to that found in

Table 1 (1980–1996). The relatively small number of

observations resulting from this restriction necessitated a

model form that was parsimonious. Second, calculation of

elasticities from the LES model is straightforward limiting

ambiguity about their calculation and interpretation. Third,

the Stone–Geary utility function on which the LES is based

is easily solved to obtain a unique, closed-form measure of

CV for use in welfare analysis. The linear nature of the

model also lends itself more readily to analytical solutions

to the system of equations for simulation purposes. On

the downside, however, the LES is quite restrictive because

it is only relevant for Hicksian substitutes. The fact that only

Hicksian substitute products are considered was not deemed

to be a problem as all imports are competing for market

share.

To conserve degrees of freedom for estimation, the

regions were further aggregated from the data in Table 1.

The NAFTA countries, Brazil, Argentina, and Equador

were combined into a group called WEST. The countries of

the ASEAN group were kept in an individual region and

India was kept in an individual region because these two

areas are the primary focus of the US ban on shrimp imports.

All other countries were combined into the Rest of the

World (ROW). This led to four regions for estimation,

greatly reducing the number of parameters to be estimated.

The Stone–Geary Utility function is given as

U ¼X

i

bi logðqi 2 giÞ; ð1Þ

with 0 , bi , 1;P

bi ¼ 1; and qi . gi: The bi are

interpreted as the marginal budget shares, qi are the total

quantities of i; and gi are the subsistence or minimum

typical quantities. Maximizing utility subject to a budget

constraint yields the LES system of equations. To maintain

consistency with demand theory, the gis were restricted to

be the same across equations

piqi ¼ pigi þ bi x 2X

jpjgj

� �i ¼ j ¼ 1;…; 4; ð2Þ

where pi and pj are the prices of goods i and j; and x total

expenditure. The standard interpretation of pigi is that it

represents the minimum expenditure required to attain a

subsistence level of consumption. In the current context,

pigi can be viewed as the minimum typical expenditures for

shrimp imports from a particular region. Thus,P

pjgj is the

sum of all minimum expenditures on imports. The term

(x 2P

pjgj) is the portion of total expenditure available

after the minimum expenditure for each product has been

accounted for, which is allocated to group i by the marginal

expenditure share bi:

Eq. (2) can be rewritten in quantity dependent form as

qi ¼ gi þbix

pi

1 2

Xjgjpj

x

0@

1A i ¼ j ¼ 1;…; 4: ð3Þ

The demand system represented by Eq. (3) was estimated

using Full Information Maximum Likelihood (FIML)

estimation. A Monte Carlo analysis was then used to

examine parameter consistency given the small sample size.

Using the variance–covariance matrix of the parameter

estimates as well as the variance–covariance matrix of the

residuals, 100 random iterations at each observation were

performed, generating an additional 1800 observations.

These observations were then used to re-estimate Eq. (3)

using FIML. The resulting parameter estimates were

compared to the original parameter estimates to check for

consistency.

D. Hudson et al. / Journal of Environmental Management 68 (2003) 231–238234

The income elasticity of demand is given by the

following equation

eix ¼bi

wi

; ð4Þ

where wi is the expenditure share for region i: By definition,

eix is always positive in the Stone–Geary utility function,

which precludes the possibility of an inferior good. The

own-price elasticity of demand is given by

eii ¼ 21 þ ð1 2 biÞgi

piqi

; ð5Þ

and the cross-price elasticity of demand is given by

eij ¼ 2bi

pjgj

piqi

i – j: ð6Þ

One question is whether the imports from different

regions are truly perceived differently in the market. This

issue was examined by performing a likelihood ratio test for

the equality of the own-price elasticity of demand for

different regions. If the own-price elasticities were different,

it was concluded that each region was treated separately.

4.2. Policy simulation

The second step in the analysis was to estimate the

anticipated impacts of the trade ban on shrimp. This was

accomplished by utilizing the resulting parameter estimates

from above. First, assumptions had to be made about the

quantity impact of the trade restrictions. There are no a

priori expectations about the quantities that will be affected

by the trade ban. ASEAN countries and India are likely to be

the most affected because they are not currently in TED

compliance and have a larger individual market share in the

US import market.6 For simulation purposes, it was assumed

that a 30% reduction in imports for ASEAN countries and

India would result from the ban.

Two scenarios were analyzed. First, it was assumed that

the reduction in imports from ASEAN and India were

reallocated to the WEST and ROW regions on the basis of

the percentage of imports these countries contribute.

Underlying this allocation is the assumption that the natural

fisheries and aquacultural industries in these regions could

sustain the increase in demand from the US. The second

scenario assumed that there was no reallocation of imports

to other regions. That is, the US simply reduced the quantity

of shrimp imports by the amount decreased as a result of

the trade ban. All quantities and quantity changes were

taken from the historical mean levels.

Interestingly, these two scenarios provide an illustration

of the impacts of substitutes on the welfare impacts of

policy changes. That is, the first scenario is one in which the

US has the ability to substitute other imports for the lost

imports as a result of the ban. The second scenario has no

provision for substitutes. Thus, a comparison of both

simulations reveals the impact of the ability to substitute.

The expectation is that the ability to substitute will offset

welfare losses, resulting in a lower net welfare loss when

substitution is allowed.

Using the assumed quantities, the system of equations

resulting from Eq. (3) was solved simultaneously using

Newton’s method.7 That is, prices were solved endogen-

ously given assumed quantities. This solution provided the

expected prices under the assumed quantities of imports.

Fig. 1 demonstrates the method graphically, assuming two

goods for simplicity: one good is the numeraire ðxÞ; and the

second good, Q; is quantity of shrimp imports from an

arbitrary region.

Under a non-quota scenario, the quantity of shrimp

imported is Q0; and the price of Q0 is P0; given by the slope

of the budget constraint. If quantity is reduced from Q0 to Q1

under the quota, the virtual price of Q1 (i.e. P1) is found to

be the slope of the expenditure function as it rotates inward.

The virtual prices of all import categories in this analysis are

simultaneously determined by perturbing a regional quan-

tity and then solving all the virtual prices in the system.

The CV was found by using the estimated prices under

the assumed quantities. In this case, the Stone–Geary

indirect utility function was solved using the formula

Vðp0; x0Þ2 Vðp1

; x0 2 CVÞ; ð7Þ

which gives a unique empirical measure of CV based on

parameter estimates from the demand equations. With a

constant income, the restrictions are hypothesized to result

in a negative impact on welfare. A negative impact on the

welfare of US consumers is expected because the utility at

the new prices (which should be higher because quantity is

restricted) is expected to be lower than when quantity

restrictions are not in effect.

5. Results

Table 3 shows the results of the estimated equations with

the original data and under the Monte Carlo simulation.8

The parameter estimates appear to be consistent given

that there are no substantial differences between those

generated from the simulation and those of the original

6 There are other, much smaller, import sources that may be affected by

the ban. However, these countries are scattered around the world and make

up a very small portion of total imports. Separating them out would reduce

degrees of freedom and not add much to the model. However, the reader

should be aware that the welfare estimates presented in this paper are likely

slightly underestimated.

7 This option is available in the ‘goal seeking’ capability of SAS’s PROC

Model package (SAS Institute, 1997).8 Note that it was not possible with these data to perform Monte Carlo

simulation to estimate more flexible functional forms. This is because there

are too few observations to estimate initial variance–covariance matrix on

which to base the simulation.

D. Hudson et al. / Journal of Environmental Management 68 (2003) 231–238 235

model estimate. White’s test was performed and suggested

no signs of heteroskedasticity, and Godfrey’s test suggested

no signs of serial correlation.

No minimum import quantity from a region ðgjÞ is

significant, suggesting that total expenditure, x; is allocated

across regions on the basis of the marginal expenditure

shares, bi: Results show that approximately 40% of US

shrimp import expenditure is allocated to imports in the

WEST region, about 24% to the ASEAN region, 2% to

India, and the remainder to the ROW. The relatively low

share for India suggests that the shrimp import ban for that

country will have little impact on US consumer welfare by

itself. However, the ASEAN group makes up a large portion

of total US expenditure so that changes in the quantity

coming from that region will likely have a much larger

impact on US consumer welfare.

Table 4 shows the uncompensated own-price and cross-

price as well as the income elasticities of demand for each

region.

The WEST exhibited the most inelastic demand with an

own-price elasticity of 20.798. This result is expected

given the proximity of the WEST countries to the US The

ASEAN group exhibited the largest price elasticity of

import demand at 21.263, suggesting that US demand is

considerably more responsive to ASEAN shrimp price

changes.

Imports from ASEAN countries were most sensitive to

changes in US consumer expenditures. A 1% increase in US

expenditures for imported shrimp results in a 1.61% increase

in imports of shrimp from ASEAN countries. The magnitude

of this elasticity relative to the other regions suggests that US

consumers treat ASEAN shrimp as more of a luxury than

shrimp from other regions. That is, as income increases,

imports from ASEAN countries are expected to increase the

most. The ROW is also slightly elastic. The WEST region

and India are both inelastic, suggesting that these regions

benefit the least from income increases in the US.

The own-price elasticities were tested for equivalence

using the likelihood ratio test and these results are shown in

Table 5.

These results strongly suggest that the own-price

elasticities of demand for each region are different, implying

that each region is viewed differently by importers. The

exception was the WEST and ROW regions. These regions

did not appear to be statistically different. These results

generally support the maintained hypothesis that it is

consistent to model these regions separately.

The CV estimates for the two scenarios are presented in

Table 6.

In both cases (reallocation of imports to other regions and

no reallocation of imports), there is a welfare loss to US

consumers. However, when reallocation is possible, the

welfare loss is roughly 1/5 of that when reallocation is not

possible. Thus, if fisheries and aquacultural enterprises in

other regions have the ability to sustain the increase in

demand from US imports, then the cost of the shrimp import

ban is expected to be much lower than if a reallocation of

imports is not possible.

Fig. 1. Estimation of CV using virtual prices.

Table 3

Estimated parameters for LES model

Parameter Estimated model

using original data

Estimated model

using Monte Carlo

simulation

b1 0.398 (0.0975) 0.408 (0.0055)

b2 0.241 (0.0484) 0.237 (0.0022)

b3 0.023 (0.0070) 0.023 (0.0005)

b4 0.332 (0.0655) 0.326 (0.0040)

g1 6220.15 (67,799.7) 14,102.13 (2952.8)

g2 229,243.67 (12,741.9) 230,910.13 (1494.2)

g3 10,697.28 (9048.9) 12,121.45

g4 4329.2 (40,696.4) 6944.45 (3018.1)

Number of

observations

18 1818

Log likelihood

of system

2736.6 277,277

Numbers in parentheses are standard errors.

Table 4

Uncompensated own-price, cross-price, and income elasticities of demand

for shrimp imports

West ASEAN India ROW

West 20.798

ASEAN 0.052 21.263

India 20.000a 20.000a 21.00

ROW 20.011 20.021 20.008 20.978

Income 0.744 1.607 0.516 1.049

a Smaller than 0.000 in absolute value.

D. Hudson et al. / Journal of Environmental Management 68 (2003) 231–238236

6. Discussion

The results clearly indicate that the ban on shrimp

imports from certain countries will have (or is having) an

adverse impact on the welfare of US consumers, at least in

monetary terms. However, one could interpret this loss in

welfare as the opportunity cost of achieving the environ-

mental goal of reducing sea turtle by-catch. Interpreted in

this way, US consumers are willing to forgo the CV

estimated here to reduce the loss of sea turtles. The question

becomes, are trade restrictions the most equitable and

efficient way to reduce sea turtle by-catch? Are there

alternative ways to achieve this goal?

The issue of equity is beyond the scope of this paper.

Some authors such as Bhagwati and Srinivisan, 1996 have

taken the position that environmental and social goal-setting

is allowed under the WTO if the impacts are borne directly

by the domestic consumers/producers. In this case,

however, there would likely be some direct impacts

experienced by producers in the nations that are affected

by the ban (Stewart, 1998, 197–219). If the CV estimate is

viewed as the opportunity cost that US consumers are

willing to take to achieve the environmental goal, then it

seems plausible to devise some type of compensation

scheme that would be more efficient in achieving the goals.

For instance, if the cost of equipping the ASEAN countries’

fleets with TEDs is lower than the foregone CV from

reduced imports, then a welfare gain could be achieved via a

policy in which the US compensates and/or provides

ASEAN countries with TEDs.

We attempt here to provide a rough estimate of the

difference in costs and benefits of such a compensation

scheme.9 The price of a TED is $300/trawler (Stewart, 1998,

197–219), and there are approximately 2,79,261 trawlers in

ASEAN countries and India (this is an approximation from

Food and Agriculture Organization (1995) fisheries data).

Assuming that TEDs will require replacement approxi-

mately every 3 years, we can calculate the net present value

of the cost of the policy over the next 10 years as10

NPVðTEDÞ ¼X10

t¼1

TEDcost

ð1:10Þt: ð8Þ

Making the simplifying assumption that the CV measure

will remain static, we can estimate the lost welfare as

NPVðCVÞ ¼X10

t¼1

CV

ð1:10Þt: ð9Þ

In order to estimate the NPV of the policy, the ‘without’

policy scenario is interpreted as being the trade restriction

alone, and the ‘with’ policy scenario as the compensation

scheme instead of the trade restriction. Thus, if equipping

ASEAN and Indian shrimpers with TEDs results in an

increase in imports back to the pre-restriction level, the net

welfare gain (loss) would be W ¼ NPVðCVÞ2 NPVðTEDÞ:

There are two CV estimates, one with and one without the

ability to reallocate shrimp imports. Thus, there are two

estimates of W (Table 6).

When no reallocation of imports is possible, the resulting

NPV of equipping the trawlers with TEDs is $46,62,18,965,

suggesting a positive impact on US consumers if ASEAN

and Indian shrimpers are compensated for adopting the TED

system. In contrast, when reallocation of imports to other

regions is possible, the compensation for the TEDs results in

a negative welfare impact of 2$84,461,686. This indicates

that there is no real incentive for compensation when the US

has the ability to make up for import shortfalls by increasing

its own production and reallocating imports from other

regions. Again, there is no consideration here of the impacts

on other parties. Thus, this represents only a partial analysis

of the welfare effects and potential benefits of

the compensation scheme.

7. Conclusions

This analysis utilized an LES model of shrimp imports to

address the impacts of a shrimp import ban to achieve

Table 5

Likelihood ratio tests for equivalence of own-price elasticities of demand

Elasticitiesa Likelihood ratio

eWEST ¼ eASEAN 568.88b

eWEST ¼ eIndia 469.62b

eWEST ¼ eROW 0.04

eASEAN ¼ eIndia 1116.79b

eASEAN ¼ eROW 1008.18b

eIndia ¼ eROW 251.85b

a Own-price elasticities of demand in each region.b Statistically significant at the 0·001 level or better.

Table 6

Estimated CV for two alternative scenarios

Scenario CV estimate W estimate

No reallocation of imports $ 2 109,835,930 $466,218,965

Reallocation of imports between

West and ROW regions

on the basis of

previous import percentages

$ 2 20,215,190 $ 2 84,461,686

9 We do not directly consider the price impacts of the capital investment

in the TED device. That is, the TED may make the shrimpers more or less

efficient, which ultimately may impact prices. To the extent that it makes

shrimpers less efficient, the reported impacts would be underestimated.10 A 10-year planning horizon was chosen given the uncertainty about the

length of time for political agreements. A discount rate of 10% was

assumed for this analysis, but further analysis reveals that the results

presented in Table 6 are insensitive (that is, the signs on the results do not

change) to the assumed discount rate.

D. Hudson et al. / Journal of Environmental Management 68 (2003) 231–238 237

the environmental goal of reduced sea turtle by-catch. The

CV estimates suggest a negative impact on US consumers

resulting from the ban, but the magnitude of the impact

depends on whether the lost imports from the banned

countries are reallocated to other countries.

The fact that the shrimp import ban reduces consumer

welfare is not surprising. However, the fact that the

magnitude of the impact is dependent on whether imports

are reallocated or not demonstrates the implications of

being in a multi-product versus single product world.

That is, when consumers have the ability to substitute

between regions for imports, this appears to greatly

dampen the effects of the trade restriction on US

consumers. Thus, it appears that it is important to

consider substitution possibilities in policy impact anal-

ysis because failure to do so may overstate the true

impact of the policy.

Finally, interpretation of the welfare loss as an

opportunity cost opens the door for designing compensation

schemes so that those countries that are affected by the ban

can be compensated. Results of this analysis suggest that the

efficacy of any compensation scheme will depend on

the ability to substitute shrimp from other regions. That is,

the greater the ability to substitute, the less incentive for

compensation. However, two factors should be considered.

First, the positive impact when substitution is not possible is

disproportionately larger than the negative impact when

substitution is possible. Coupled with the fact that most

global fisheries are already pressured and may not sustain

increased demand from shifting US imports suggests that

the effect of compensation is likely to be positive. However,

this question needs further research. Approaching the

problem from this perspective may result in a more efficient

method of achieving the environmental goal than through a

trade restriction.

Further research into the shrimp ban is warranted

because several questions have yet to be answered. What

is the impact of the ban on producers in both countries that

do and do not use the TED system? What are the impacts on

consumers around the world? If data were available on

aquaculture shrimp imports, this might improve the quality

of the estimates. The lack of data is likely to have only a

marginal effect on the magnitude of the estimates, but

distinction between aquaculture and wild caught imports

would improve the analytical richness of the model. As

trade rules become more complex and the demand for

environmental regulation increases, more problems such as

the shrimp ban debate will arise. This paper clearly

demonstrates an example of environmental regulation

through trade and that these regulations have impacts on

the distribution of income.

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