Chiaramente, ogni formato ha i propri vantaggi e svantaggi acquista antibiotici online per effettuare un acquisto, non è necessario fornire la prescrizione medica.

## Disdier_marette_final-9-feblast

**The Combination of Gravity and Welfare Approaches for Evaluating Non-Tariff Measures **
**Anne-Célia Disdier and Stéphan Marette **
This article explores the link between gravity and welfare frameworks for measuring the impact
of non-tariff measures. First, an analytical approach suggests how to combine a gravity equation
with a partial equilibrium model to determine the welfare impact of non-tariff measures. Second,
an empirical application focuses on the effects of a standard capping antibiotic residues in
crustaceans in the United States, the European Union, Canada and Japan. While the econometric
estimation of the gravity equation reports a negative impact on imports, welfare evaluations
show that, in most cases, a stricter standard leads to an increase in both domestic and
international welfare.
Keywords: Gravity Equation, Non-Tariff Measures, Seafood, Welfare
JEL classification: F1, Q1
Running Head: The Combination of Gravity and Welfare Approaches
Anne-Célia Disdier and Stéphan Marette are researchers, INRA, UMR Economie Publique
INRA-AgroParisTech. The authors thank Jeffrey Dorfman, an anonymous referee, Sébastien
Jean and participants at ETSG 2009 for helpful comments. This work was financially supported
by the "AgFoodTrade - New Issues in Agricultural, Food and Bioenergy Trade" (Grant
Agreement no. 212036) research project, funded by the European Commission. The views
expressed in this paper are the sole responsibility of the authors and do not necessarily reflect
those of the Commission.
Non-tariff measures (NTMs) are defined as interventions other than tariffs that affect trade of
goods. With the reduction in tariffs under recent negotiations, NTMs are playing an increasing
role in swaying international trade (United Nations Conference on Trade and Development
2005).1 The problem of NTMs is potentially pervasive with issues linked to sanitary crises in
the agribusiness sector, market authorizations for genetically modified organisms,
nanotechnologies or animal cloning, but also issues such as animal welfare, absence of
recombinant bovine somatotropin, absence of antibiotic and pesticide residues, absence of child
labour in some products from poor countries or carbon emissions linked to products.
The effects of NTMs are ambiguous and politically sensitive. On one side, regulations are
often necessary to alleviate market failures, but on the other side, domestic regulations may be
imposed simply to impede imports of foreign competitors (Beghin 2008). Theoretical analyses
do not give any definitive conclusions on the overall effect linked to regulation, which requires
economists to turn to empirical analyses. Evaluating impacts of such NTMs is not simple and
requires tricky estimations (Dee and Ferrantino 2005).
In this article, we show how to take into account the coefficient measuring the forgone
trade linked to NTMs in a gravity equation to determine the relative variations of both price and
quantity in a partial equilibrium model used for welfare analysis, with the integration of
experimental results to evaluate the damage for consumers.
The related application measures the impact of a stricter standard to cap residues of
chloramphenicol in crustaceans. Chloramphenicol is an antibiotic often used in seafood farms in
developing countries and is toxic to human health. The estimation of the coefficient measuring
the forgone trade via the gravity equation is integrated in a partial equilibrium model, calibrated
to represent supplies of and demands for crustaceans in the United States, the European Union,
Canada and Japan. This calibrated model allows us to measure the impact of the stricter standard
on both foreign exporters' profits and domestic welfare defined as the sum of domestic
producers' profits and consumers' surplus. While the econometric estimation of the gravity
equation shows a negative impact of the standard on crustacean imports, welfare evaluations
show that, in most cases, a stricter standard has led to an increase in both domestic and
international welfare over the last decade because of a significant reduction in the
chloramphenicol damage. In other words, NTMs can be trade-restricting but welfare-enhancing.
Our article makes an important contribution to the literature on NTMs by bridging the gap
between mercantilist and welfare approaches. Many recent empirical assessments of NTMs have
been mercantilist focusing on forgone trade via gravity estimation (see for example Otsuki,
Wilson, and Sewadeh 2001a and b; Wilson and Otsuki 2004; Disdier, Fontagné, and Mimouni
2008; Anders and Caswell 2009). However, such an approach is restrictive and hampers a more
complete understanding of the actual effects of NTMs on all economic agents concerned (e.g.
producers but also consumers, importers and governments). Other papers aim at developing a
welfare approach of NTMs without gravity estimations (e.g. Dean 1995; Bureau, Marette, and
Schiavina 1998; Paarlberg and Lee 1998; Beghin and Bureau 2001; Warr 2001; McCorriston and
MacLaren 2005 and 2007; Wilson and Anton 2006; Yue, Beghin, and Jensen 2006; Pendell et al.
2007; Peterson and Orden 2008; Yue and Beghin 2009). The combination of both gravity and
welfare methodologies in a partial equilibrium context has been completely overlooked by these
studies and our article explicitly aims to remedy this absence.
A second contribution of our article is to provide up-to-date estimates in terms of gravity
equation estimation technology and to account for the impact of NTMs on both the probability
that trade takes place (extensive margin) and the intensity of trade (intensive margin) by
computing the full marginal effect.
The third contribution of our article is to estimate the welfare variations caused by a stricter
standard for crustaceans in the United States, the European Union, Canada and Japan. This
application is important since the welfare measures taking into account agents' surpluses justify
the tightening of standards on imported crustaceans. Our approach differs from the previous
seafood studies focusing only on the

*ex post* evaluation of past measures on trade via
econometric analysis (Hudson et al. 2003; Debaere 2005; Alberini et al. 2008; Anders and
Caswell 2009). In this article, we evaluate past policies (over the period 2001-2006) but also a
future policy with an

*ex ante* analysis linked to a potential standard eliminating all
chloramphenicol residues in seafood. Such a policy could be selected over the coming years
(Ababouch, Gandini, and Ryder 2005; Buzby, Unnevehr, and Roberts 2008). The welfare study
helps anticipate future price adjustments on markets and achieves quantified analyses directly
usable by the public decision-maker.
The article is structured as follows. The next section presents both mercantilist and welfare
approaches and their potential link from a theoretical point of view. The empirical application on
crustacean products is provided in the third section. The last section concludes.

**A simple framework **
We briefly present both gravity and welfare approaches and their potential links by focusing on
the impact of the standard.

*The gravity approach *
The trade effects of a NTM can be estimated by using a gravity equation. This equation provides
a measure of the expected bilateral trade given the size of both partners and the bilateral
transaction costs. By comparing expected and real trade, we obtain a measure of the trade effect
of the NTM. The theoretical foundations of the gravity equation have been enhanced over the
last few decades (see, among others, Anderson 1979; Bergstrand 1985; Anderson and van
Our theoretical foundation for trade patterns is the standard new trade monopolistic
competition-constant elasticity of substitution (CES) demand-Iceberg costs model introduced by
Krugman (1980). Producers in each country operate under increasing returns to scale and
produce differentiated varieties. These varieties are shipped with a cost to consumers in all
countries. Following Redding and Venables (2004), the total value of exports from country

*i* to
country

*j* can be written as follows:

*x *=

*n p*
with

*n * and

*p * the number of varieties and prices in country

*i*,

*E * and

*G * being the expenditure
and price index of country

*j*.

*T * represents the iceberg transport costs and

*σ* the elasticity of
Different specifications of this equation have been estimated. The usual practice consists of
proxying exporter and importer attributes with the gross domestic products (GDPs) and GDPs
per capita of both countries. However, the relevance of this specification has been questioned for
its distance to theory.
According to the theory, importer and exporter's attributes depend on their GDPs but also
on their implicit price indexes. Anderson and van Wincoop (2003) call these price indexes the
multilateral resistance terms, since they depend on the trade-cost term.2 The absence of control
for multilateral resistance terms could bias the estimation. Multilateral resistance terms are
unobserved but Anderson and van Wincoop (2003) suggest estimating a specification in which
the country's attributes are a function of GDPs and bilateral linkages. This approach makes (1)
non-linear in the parameters and they therefore estimate it via non-linear least squares. An
alternative solution is to rely on fixed effects by country.3
Transport costs are measured with the bilateral distance between both partners. We also
control for adjacency: cb

*ij *is a dummy variable that equals one if the two countries share a
border. Since cultural proximity can foster bilateral trade, we introduce two dummies,
respectively equal to one if the two partners share a language ( clang

*ij *) or have had a colonial
relationship ( colony

*ij *). We also control for non-tariff ( NT

*i*
M

*jt *) and tariff measures ( t ).
Finally, we include a set of year dummies to capture time-specific effects. Therefore, after taking
logs, equation (1) can be rewritten as follows:
Equation (2) can be estimated using ordinary least squares (OLS). However, in that case,
zero trade flows are dropped from the estimation, which could bias the results. One way to
account for these flows is to use a sample selection model, such as the Heckman model. This
model includes two equations: the first one (the selection equation) investigates the binary
decision whether or not to trade and estimates it through a probit, while the second (the outcome
equation) focuses on the amount, if any, of trade. Both equations can be estimated
simultaneously, using the maximum likelihood method, or successively. As suggested by
Helpman, Melitz, and Rubinstein (2008), both the selection and outcome equations should
include the same independent variables except one associated with the fixed trade costs of
establishing a trade relationship. This excluded variable will only be included in the selection
equation. Common language will be the excluded variable in our estimations.4
The Heckman approach allows investigation of the impact of a non-tariff measure on both
probability of trade (extensive margin) and amount of trade (intensive margin). To do so, one
should compute the full marginal effect, which is the sum of the effects of the NTM on the
extensive margin (likelihood to trade) and on the intensive margin (conditional on trade taking
place). If the NTM has no significant impact on the extensive and on the intensive margins of
trade, no further welfare analysis of the NTM will be necessary. If one of the effects is
statistically significant (at least on one margin), it will be used for the welfare analysis linked to
NTM. If both effects are significant, their sum will be used.
By taking the derivative from (2) and by abstracting from indexes, the relative variation of
exports in value linked to NTM can be defined as

*dx */

*x *= β

*d*NTM (everything else being
constant). The value of exports in (2) is defined by

*x *= .

*p q * , where

*p* and

*q* are respectively the
price and the quantity of exports. Thus, the relative variation of exports linked to the NTM can
be rewritten as:
= β

*d*NTM .
When the impact of the NTM is statistically significant, the gravity analysis can be
integrated into a calibrated model via equation (3) that isolates the effect of the NTM variation
from other effects. This measure provides precious information in a context where data linked to
border inspections are extremely difficult to collect. As Ababouch, Gandini, and Ryder (2005, p.
iii) mentioned in the introduction of an exhaustive study about border cases, their study "took
over three years to finalize in its present form. A major difficulty was accessing essential data
and in a format useful for their exploitation." Equation (3) can be applied uniformly across
different importing countries for the welfare analysis.5 The following welfare analysis focuses on
NTM impacts for a single country and its importers.

* *
*The welfare approach *
The welfare measure takes into account agents' surpluses for evaluating a NTM. In a simplified
framework, the market good being analyzed is assumed to be homogenous (i.e., same quality
attributes) except for a specific characteristic that is potentially dangerous to consumers and
linked to the foreign products. Therefore, only foreign producers are concerned by a standard
reinforcement selected by the domestic regulator for reducing consumers' risk. This analytical
simplification allows a sharper focus on the international implications of standards and
particularly fits the empirical example of the next section. Demands are derived from quadratic
preferences, and supply is derived from a quadratic cost function.
It is assumed that a representative consumer has the following utility function (Polinsky
and Rogerson 1983):

*b*(

*q *+

*q *+ 2θ

*q q *)
(4)

*U *(

*q *,

*q *,

*w*) =

*a*(

*q *+

*q *)
−

*I*γ

*rq *+

*w *,
where

*q *and

*q * are the respective consumptions of foreign and domestic products. The
parameters

*a*,

*b *> 0 allow the capture of the immediate satisfaction from consuming foreign and
domestic products and

*w * is the numeraire good. The parameter θ measures the degree of
substitutability between foreign and domestic products, with θ = 0 for independent products and
θ = 1 for perfect substitutes.
The expected damage linked to the foreign products is captured by the term

*I*γ

*rq *. The
parameter

* r *≥ 0 is the per-unit damage and γ is the probability of having a contaminated
product with 0 ≤ γ ≤ 1. With a probability (1- γ ), there is no damage. The parameter

*I* represents
the consumer's knowledge regarding the specific characteristic brought by the foreign product. If
the consumer is not aware of the specific characteristic, then

*I*=0

*,* and the cost of ignorance, γ

*rq *,
is negatively taken into account in the welfare

*. *In other words, the value γ
−

*rq * disappears from
the utility (4) when

*I=0*, but is taken into account in the welfare by a regulator accounting for all
the characteristics linked to a product. Conversely,

*I*=1 means that the consumer is aware of the
specific characteristic and negatively internalizes the damage in her/his consumption.6 The
maximization of utility defined by (4) with respect to

*q *and

*q *, subject to the budget constraint
with prices

*p*
for foreign goods and

*p*
for domestic goods gives the respective demands

*q *= [

*a*(1−θ ) −

*p *+θ

*p *−

*I*γ

*r*]/[ (

*b *1−θ )] and

*D*
*q *= [

*a*(1−θ ) −

*p *+θ

*p *+θ

*I*γ

*r*]/[ (

*b *1−θ )].
For the rest of the article, we focus on the situation where the damage is not internalized
(with

*I=*0), which is realistic for the situation presented in the following section (the internalized
case with

*I=*1 would directly impact the demand). To simplify the presentation and because of
the lack of data in the forthcoming example, we consider domestic and foreign goods as perfect
substitutes with θ = 1. The maximization of (4) with θ = 1,

*p *=

*p *=

*p * and

*Q *=

*q *+

*q*
to an overall demand

*p*) /

*b * and an inverse demand

*D*
*a bQ * with

*I=*0.
On the supply side, a perfectly competitive industry comprising domestic and foreign firms
with price-taking firms is assumed. A stricter standard has two major impacts on foreign firms.
(

*i*) First, it reduces the proportion of foreign products entering a market because of tougher
inspections linked to stricter thresholds, particularly for firms with difficulties complying with
the stricter standard. Empirically, this effect was observed in Europe, where the 2001
chloramphenicol standard drastically increased the number of border cases. Indeed, the
chloramphenicol cases represented 0% of European border cases for seafood in 2000 versus 36%
in 2002 (Ababouch, Gandini, and Ryder 2005, table 19 p. 32). (

*ii*) Second, compliance with the
stricter standard brings about an increase in marginal costs and sunk costs (linked to investments
that are sunk once undertaken). An increase in marginal costs leads farmers to reduce the
quantities supplied for each given price. Sunk investments do not figure in farmers' optimal
supplied quantities and have more indirect effects on market prices through the entry and exit of
farmers. Empirically, shrimp producers adjusted to the stricter standard by selecting new shrimp
varieties and starting to adopt Hazard Analysis Critical Control Point (HACCP) programs
(Anders and Caswell 2009). For the rest of the study and for the sake of simplicity, we only
focus on the first effect (

*i*), namely the reduction of the proportion of foreign products entering
the market. However, note that both explanations (

*i*) and (

*ii*) lead to similar impacts since they
contribute to reducing the quantities supplied by farmers and tend to increase the resulting
equilibrium prices.
We focus on a representative foreign producer subsuming all producers.7 This
representative foreign producer maximizes its profit:
λ

*q *−

*g q *−
where

*c *,

*g * are the variable cost parameters and

*K * is the sunk cost linked amongst others to
the firm's market entry and compliance with regulations (for the rest of the presentation,

*K *is
zero only for the sake of simplicity). The parameter λ is the proportion of foreign products
entering the domestic market when an output

*q * is offered before the border inspection. This
proportion 0 ≤ λ ≤ 1 depends on the standard and the inspection policy. Under the assumption of
rational expectations, the expected proportion taken into account by the producer corresponds to
the effective proportion linked to the policy. The more stringent the standard and the inspection
policy, the lower the proportion of products entering the market. The parameter

*t* is the ad-
valorem tariff on imports, implying a price

*p */(1 +

*t*) received by the foreign producers when
domestic consumers pay

*p*. To simplify the presentation, it is assumed that

*t=0*.
The representative producer maximizes its profits with respect to

*q * leading to a foreign
supply before the inspection equal to

*S*
*q *= (λ

*p *−

*g *) /

*c *. After the inspection, the foreign supply
of products entering the domestic market is

*Q *= λ

*q *. The foreign inverse supply of products
entering the domestic market is

*S*
*p *= (

*c Q *+ λ

*g *) / λ .
Using similar notations to equation (5), the representative domestic producer maximizes
the profit given by
π =

*pq *−

*g q *−

*c q *. The difference with (5) comes from the absence of
the parameter λ linked to the standard since it is assumed that domestic producers already
complied with it. This was the case with the new 2001 policy that mainly impacted Asian
exporters, since the chloramphenicol was already banned in many OECD countries as, for
instance, in the European Union since 1994. The supply is

*S*
*q *= (

*p *−

*g *) /

*c * and the inverse

*p *=

*c q *+

*g *. The total supply defined by the sum of foreign and domestic supply is

*Q *=

*Q *+

*q *= [(λ

*c *+

*c *)

*p *−

*c *λ

*g *−

*c g *] /

*c c *. The total inverse supply is

*p *=

*cq *+

*g *
*c *=

*c c */(λ

*c *+

*c *) and

*g *= (

*c *λ

*g *+

*c g *) /(

*c *λ +

*c *) .
Figure 1 shows domestic demand (

*D*), foreign supply (

*SF*) and total supply (

*S*) (the
domestic supply is omitted for the clarity of figure 1). The price,

*p*, is located on the vertical axis
and the quantity,

*q*, is shown along the horizontal axis.
Insert figure 1 here
For an initial situation A, linked to a proportion λ , the equilibrium price

* *
*p *= (

*ac *+

*bg *) /(

*c *+

*b*) clears the market by equalizing demand and supply with an overall
equilibrium quantity

*Q *= (

*a *−

*g *) /(

*c *+

*b*) (such that

*p *=

*p * with

*I*=0). In figure 1,
foreign output and

*Q *−

*Q * is domestic output. The profits correspond to area

*OwvpA* for foreign
producers (since sunk costs are zero) and area

*wzAv* for domestic producers. The usual surplus of
domestic consumers corresponds to area

*pAAa*. The damage linked to foreign products does not
impact the demand since

*I=0*. However, the cost of ignorance should be accounted for in the
welfare calculations and is equal to
γ

*rQ * represented by the area 0( γ
−

*r*)

*f*
*tQ *. Domestic welfare
is the sum of domestic producers' profits and consumer surplus minus the cost of ignorance and
is given by area (

*A*
*p vwzAa *− 0( γ
−

*r*)

*f*
*tQ *). International welfare is the sum of domestic welfare
and foreign producers' profits and is given by area ( 0

*zAa *− 0( γ
−

*r*)

*f*
*tQ *). Full analytical
expressions for equilibrium values as well as for all the components of welfare are easy to
compute and can be provided upon request.
With this initial situation preceding a reinforcement of the regulation, parameters of the
model are initially calibrated in such a way as to replicate prices and quantities over a period.
With the observed quantity ˆ

*Q * sold over a period, the average price ˆ

*p * observed over the period,
and the direct price elasticity $

*Q *⋅

*dp*) ) obtained from econometric estimates, the
calibration leads to estimated values for the demand equal to
1 /

*b *= ε
−

*Q */ ˆ

*p *, % % ˆ

*a *=

*bQ *+ ˆ

*p * (the
same method can be used for the supply side with a given proportion λ ). The value of

*r* can be
provided by experimental studies or by consumers' surveys.
When a standard is reinforced, the market allocation is modified as represented in figure 1
with bold curves and point B. First, a stringent policy increases border cases and consignments
of tainted food (Ababouch, Gandini, and Ryder 2005), which reduces the proportion of entering
the domestic market from λ to λ for foreign producers. The supply shifts upward from (

*S*) to
(

*S'*) leading to an equilibrium price

* *
*p * and an overall equilibrium quantity

*Q *. The stricter
policy increases the price with

*B*
*p *>

*p *and decreases the quantity with

*Q *<

*Q *. It also reduces
the probability of having contaminated products from γ to γ and the overall damage for
unaware consumers. At point B, domestic welfare is the sum of domestic producers' profits and
consumer surplus with the cost of ignorance linked to foreign production

*Q * and is given by

*p khnBa *− 0(−γ

*r*)

*uQ *). The profits correspond to area 0

*hkpB* for foreign producers.
International welfare is the sum of domestic welfare and foreign producers' profits and is given
by area (

*OnBa *− 0(−γ

*r*)
The effect of a stricter standard, i.e. the comparison between the initial domestic welfare

*p vwzAa *− 0( γ
−

*r*)

*f*
*tQ *) and the new domestic welfare (

*B*
*p khnBa *− 0(−γ

*r*)

*uQ *), is ambiguous
(a similar demonstration could be made between international welfare measures
( 0

*zAa *− 0( γ
−

*r*)

*f*
*tQ *) and (

*OnBa *− 0(−γ

*r*)

*uQ *)). If area (

*pBkmpA* +

*nzAB*) is lower than area
(

*whmv *+ ( γ

*uQ Q t*( γ
−

*r*)) , the increase in price is low enough for the regulation
reinforcement to be beneficial to the domestic country. Alternatively, area (

*pBkmpA*+

*nzAB*)

* *could
be larger than area (

*whmv *+ ( γ

*uQ Q t*( γ
−

*r*)) , when the regulation reinforcement involves a
relatively large contraction in the supply. In this case, additional regulation would result in
domestic welfare losses since the price effect offsets the damage reduction effect. With a stricter
standard, foreign producers will be injured by such a decision, if area

*pBkmpA* is lower than area
The change in the probability of having contaminated products, from γ to γ , can be
exogenously given or measured by studying the border inspection policy when the information is
available. When the coefficient β is statistically significant, equation (3) coming from the
gravity equation can be used with this welfare analysis to measure the price/quantity effects
linked to the stricter standard influencing the imports of foreign products with a change of the
parameter λ to λ . With the notation of figure 1, and by focusing on discrete variations with
∆ TM measuring the stricter-standard impact, equation (3) can be rewritten as:

*p *−

*p *)

*Q *−

*Q*
For a given value λ linked to the equilibrium A, the value of λ is determined by solving
(6).8 This value λ depends on the gravity coefficient β of equation (2) and provides a measure
of trade restrictions and welfare impacts.
This link between the gravity and welfare approaches was overlooked by the previous
literature and allows us to turn to the empirical estimation linked to the crustacean market.

**The Crustacean Example **
Production and trade of crustacean products9 have seen a significant rise over the last decade,
since between 1996 and 2006, the quantity produced increased by 54.1%. In 2006, Asian
countries accounted for 77.4% of world production, and OECD imports represented 91.1% of
world crustacean imports in value and 85.5% in quantity (United Nations Food and Agriculture
Organization - UN FAO - 2009). However, this boom comes at some health costs.10 To prevent
and treat bacterial infections (e.g. salmonella) and other pathogens, crustacean producers use a
range of pesticides, harmful drugs and antibiotics (such as chloramphenicol), which are highly
toxic to human health.
To protect their consumers, importing countries adopted sanitary measures and banned
contaminated consignments. In 2001, after detection of high levels of chloramphenicol residues,
the European Union banned any consignment of shrimps from China, India, Pakistan and
Southeast Asian countries tested positive (Ababouch, Gandini, and Ryder 2005). In January
2002, the European Union imposed a 30-month ban on shrimp imports from China because of
illegal antibiotic use. Between 2003 and 2005, Canada imposed 100% testing of seafood imports
from Vietnam after repeated detections of chloramphenicol. In July 2004, the European Union
started to import Chinese shrimps again only after the Chinese government guaranteed that it
would test 100% of shrimp exports. In 2006, the United States rejected shrimp imports from
China because of repeated antibiotics contamination. In December 2006, Japan imposed 100%
testing on Vietnamese shrimps after repeated chloramphenicol findings. In 2007, the European
Union imposed a ban on Thai shrimps contaminated with chloramphenicol and decertified all
seafood producers from Pakistan.11 The following gravity estimation linked to equation (2) aims
to integrate some of these regulatory measures taken by importing countries to combat the
chloramphenicol problem.

*The gravity estimation *
The data used to estimate (2) with the crustacean case are now presented. Our trade data come
from the United Nations Commodity Trade Statistics Database (COMTRADE). We focus on
bilateral imports of crustaceans. We select the main importing countries of crustaceans, namely
Canada, Japan, the United States and the European countries (European Union-15 taken
separately) and analyse their imports from all exporting countries over the 2001-2006 period.
Bilateral distances are calculated as the sum of the distances between the biggest cities (in terms
of population) of the two countries. The dummy variable cb

*ij *is set to 1 for pairs of countries that
share a border. Similarly, clang

*ij *and colony

*ij *are dummies equal to 1 if the two partners share a
language or have had a colonial relationship. Data for these variables are extracted from the
CEPII (Centre d'Etudes Prospectives et d'Informations Internationales) database on distance and
geographical variables.12
The NTM variable is defined using the Maximum Residue Limit (MRL) in part per billion
(ppb) for chloramphenicol applied by each importing country since 2001. This approach is
similar to the one presented in Otsuki, Wilson, and Sewadeh (2001a and b). MRLs vary between
countries13 and years. Following the repeated detections of chloramphenicol in crustacean
imports and improvement in detection methods, countries lowered the detection limits.
We do not specifically control for bilateral tariffs, and this for two reasons. First, bilateral
tariffs do not vary significantly over time. Second, while yearly data on bilateral tariffs are
available in the Trade Analysis Information System (TRAINS) database, there are many missing
values and these data do not include all specific duties, tariff quotas and anti-dumping duties
applied by importing countries. In our estimations, the influence of bilateral applied protection is
partly captured by country and year fixed effects.
Table 1 presents the results. Importer and exporter fixed effects, as well as year dummies
are included in all our regressions. Furthermore, the correlation of errors across years for the
same country-pair is taken into account by appropriate clustering and heteroskedasticity is
corrected with White's (1980) method. Model (1) provides the simple OLS estimation on the
sample of observations for which a positive trade relationship is observed. Model (2) applies the
Heckman selection procedure and accounts for zero trade flows. It uses the maximum likelihood
estimator and common language is the excluded variable in the trade equation. This choice is
based on Helpman, Melitz, and Rubinstein (2008, footnote 37).14 Besides, model (1) shows that
common language does not influence the amount of trade in our sample. For model (2), we
report both structural coefficient estimates and marginal effects at sample means.
Insert table 1 here
Our results in column (1) are in line with the gravity literature. Distance has a negative and
significant impact on the amount of trade flows, while contiguity and past colonial links foster
bilateral trade. The common language variable is not significant. One explanation could be that
crustacean products are homogeneous goods. Trade of homogeneous goods seems to be less
influenced by cultural linkages than trade of differentiated products (Rauch 1999). As expected,
the standard on chloramphenicol has a positive impact on trade (significant with

*p* = 0.07). In
other words, the lower the MRL allowed by the importing country, the lower the imports.
However, these results are potentially biased, since they are based only on positive trade flows.
Model (2) includes zero flows. The selection equation shows a negative and significant
impact of distance and a positive and significant effect of colonial links and common language
on the probability of trade. Interestingly, our results suggest that the decision whether to trade or
not is not affected by the MRL. This result differs from Jayasinghe, Beghin, and Moschini
(2009). These authors find that the sanitary and phytosanitary count variable used in their
estimations has a significant impact on both the probability and the amount of trade. The
estimated correlation coefficient ( ρˆ ) and the estimated selection coefficient ( λˆ ) are statistically
significant, confirming that the absence of control for zero flows generates biased results.
The amount of trade is much more impacted by distance than the probability of trade.
Results for the trade equation also show that this amount is positively and significantly
influenced by contiguity and colonial links. MRL also has a positive and significant effect on the
amount of trade (

*p* = 0.07). This latter result suggests that the reinforcement of the standard
between 2001 and 2006 (corresponding to a MRL decrease) had a negative impact on the amount
of crustacean imports. In the next subsection, we will use the marginal effect of the standard on
trade to estimate the welfare effect of past and future decisions regarding the acceptable levels of
chloramphenicol residues. Since the MRL variable has no significant impact on the probability
of trade (selection equation), we will just consider the marginal effect of the MRL factor on the
amount of trade (0.13, see last column of table 1) for the welfare analysis.

*The welfare estimation *
Standards that cap chloramphenicol residues have an impact on welfare, since the resulting
foreign-supply shift influences both equilibrium price and cost of ignorance (see figure 1). By
integrating the estimated-marginal effect of the MRL on the amount of trade in the calibrated
model, it is possible to assess the costs and benefits of a stricter standard. The framework of the
previous section based on equations (4) and (5) is directly used for this welfare estimation. In
particular, domestic suppliers are not impacted by the MRL regulation. Indeed, the new 2001
policy mainly impacted Asian exporters since chloramphenicol was already banned in many
OECD countries (for example since 1994 in the European Union).
Parameters of the model are initially calibrated so as to replicate prices and quantities for
the year 2001 and 2006 in the United States, Canada, Japan and the European Union. These
importing countries are considered without any interference with each other for the standard
compliance by foreign producers. With the baseline scenario (namely before the reinforcement
of the standard), it is assumed that the initial probability of contamination is γ =1 (see equation
(4)) and the initial proportion of foreign products entering the domestic market is λ =1 (see
equation (5)). Table 2 details the parameters used for calibrating the baseline scenario
represented by the situation A in figure 1.
Insert table 2 here
The value of the per-unit damage,

*r *, defined in equation (4), is determined by using results
from Lusk, Norwood, and Pruitt (2006) who elicited consumers' willingness-to-pay (WTP) in
order to avoid antibiotics. From a consumer survey in the grocery store environment in the
United States and a multinomial logit estimation, we have the mean WTP for pork without
antibiotic. The multinomial logit estimation allows us to isolate the premium for the absence of
antibiotic. The percent price premium for antibiotic-friendly product over conventional product
is equal to 76.704% (see table 2 p. 1025 in Lusk, Norwood, and Pruitt 2006). For each country,
we apply the domestic price

*pA* used for the initial calibration, which means that the per-unit
damage is equal to
×

*p *for each country and leads to the cost of ignorance. From
model (2) of table 1, the marginal effect of the MRL factor is equal to 0.13 and included in
equation (6) as β . For a given variation of the MRL with ∆NTM=∆MRL , equation (6) is
solved to determine λ linked to the shift of the foreign supply. 15
Table 3 presents

*ex post* estimations of welfare variation for the year 2001 in the United
States, the European Union, Canada and Japan. This table focuses on the impact of past MRL
reductions specific to each country and observed between 2001 and 2006 (for each country
∆MRL comes from the difference between the last lines of table 2 and is indicated in the first
column of table 3). To measure different possibilities regarding the efficiency of the policy
characterized by ∆MRL, we distinguish between

*case *1 with a probability of contamination
γ =3/4, and

*case* 2 with a probability γ =1/2.
Insert table 3 here
For each country, table 3 presents the variation in domestic consumers' surplus (including
the cost of ignorance linked to the damage), the variation in domestic producers' profits, the
variation in foreign producers' profits and the relative variation in international welfare, which
includes both domestic welfare and foreign producers' profits. The difference between cases 1
and 2 only concerns the cost of ignorance that does not impact the price, which explains the
similar variations in profits in both columns for domestic and foreign producers.
For the United States, Canada and the European Union, table 3 shows that the domestic
welfare variation is always positive (domestic welfare includes producers' and consumers'
surpluses). Domestic consumers benefit from the reduction in the cost of ignorance that
outweighs the negative effects coming from the price increase linked to the import restrictions.
Domestic producers benefit from the increase in domestic price. The profit variation for foreign
producers is always negative despite the price increase, since their sold quantities are strongly
reduced. The foreign producers' losses outweigh the domestic welfare increase only for the
United States leading to a decrease in international welfare. For the United States, the variations
are similar for both cases (and columns), since the large MRL variations lead to the full
elimination of foreign imports (with λ = 0 ), which corresponds to a drastic standard.16
Otherwise, for Canada and the European Union, the foreign producers' losses are outweighed by
the domestic welfare increase, leading to an increase in international welfare. The more efficient
the regulation (i.e., γ lower), the higher both domestic and international gains linked to the
regulation leading to the MRL reduction observed between 2001 and 2006. Japan did not change
its import standard between 2001 and 2006, leading to the absence of welfare variation.
Two remarks can be added to table 3. First, we abstracted from the cost of regulation and
inspection linked to the standard. By considering international (or domestic) welfare in table 3,
this cost could be subtracted from it for having the net-social benefit of regulation and
inspection.17 Second, under cases 1 and 2, the European Union shows the largest relative
variation in international welfare, which

*ex post* explains its appetite for more regulation.
Table 4 presents some

*ex ante* estimations of the welfare effects for the year 2006 with a
MRL equal to zero.18 From the last line of table 2, the variation of MRL to reach zero tolerance
is ∆MRL= -0.3 for countries, except for Japan for which the variation is ∆MRL= -50. Note that
as not all the products are inspected, the (in)efficiency of the policy is still acute justifying two
new cases regarding the value of γ . With the new baseline scenario (before the reinforcement of
the standard), it is assumed that λ =1 and γ =3/4, since some previous measures were already
existing. To measure different possibilities regarding the efficiency of a stricter standard in table
4, we will distinguish between

*case *3 with the probability of contamination γ =1/2 and

*case *4

*,*
Insert table 4 here
Table 4 shows large domestic welfare gains for the United States, Canada and the European
Union with a similar interpretation to the one provided in table 3. As the MRL is already low
(namely a relatively high standard), reinforcing the standard towards zero tolerance brings a
large gain for consumers via the reduction of the cost of ignorance, while the price effect linked
to the import restriction following the standard enforcement is relatively low. For Japan, the
large adjustment for some foreign producers not complying with pre-existing stringent standards
in other countries makes the new standard costly and explains the decline of consumers' surplus,
foreign producers' profits and international welfare. For Japan, the variations are similar for both
cases (and columns), since the large MRL variations lead to the full elimination of foreign
imports (with λ = 0 ), which corresponds to a drastic standard.

**Conclusion**
Using a very stylized framework, we studied how gravity models can be used for welfare
analysis. With our application based on crustacean products, we measured the impact of
standards capping chloramphenicol residues. While the econometric estimation of the gravity
equation shows a negative impact on imports, welfare evaluations show that, in most cases, a
stricter standard leads to an increase in both domestic and international welfare. This is an
important result since this analysis of international welfare justifies tightening the food safety
standards on imported crustaceans. This application illustrates the danger of treating NTMs as
equivalent to tariffs restricting trade. NTM reduction without a clear welfare framework may be
groundless and erroneous. Trade reductions and trade costs can be welfare improving in a second
best setting, since it alleviates market failures that should be taken into account.
In order to focus on the main economic mechanisms and to keep the mathematical aspects
as simple as possible, the analytical framework was admittedly simple. In order to fit different
problems coming from various contexts, some extensions could be integrated into the model
presented here. For instance, the crustacean species could be refined in the estimations. Taking
into account the selection of alternative species less sensitive to residues by producers (such as
the Penaeus Vannamei) may lead to a dynamic welfare approach. Data allowing demand and
supply elasticities specific to each country could be considered. Eventually, the case where the
damage is internalized in the consumers' demand can also be developed.
Our approach suggests that it is especially imperative for governments to examine both
gravity and welfare approaches when NTMs are analyzed. First, the gravity estimation helps
know whether or not a specific NTM really impacts trade by eliciting a statistically (non)-
significant effect. Second, the integration of a statistically significant effect in a calibrated model
provides a rigorous welfare measure of the NTM.
These results for estimating welfare variations particularly help assess the impacts of

*ex *
*ante* regulatory measures, that is to say, before the effective implementation of food,
environmental or health policies. The gravity and experimentation/survey results are a basis for
anticipating market reactions and they help anticipate the regulatory adjustments on markets and
achieve quantified analyses directly usable by the public decision-maker or by the World Trade
Organization when there is a conflict over NTMs. This methodology combining gravity and
welfare approaches may be systematically mobilized for cost-benefit analyses enlightening the
decision-makers on the consequences of various public choices.
1 Between 1995 and 2007, 261 specific trade concerns were examined by the World Trade Organization Sanitary
and Phytosanitary Committee (World Trade Organization 2008).
2 This approach assumes symmetric trade costs between source and destination countries. This strong assumption
could provide biased empirical results (especially in the case of use of disaggregated data). This bias will not
however greatly affect our estimations, which include few symmetric trade relationships (cf.

*infra* our sample's
3 Other approaches have been suggested in the literature. Baier and Bergstrand (2009) suggest using a first-order
log-linear Taylor expansion to approximate the multilateral resistance terms. It provides theoretically-motivated
exogenous multilateral resistance terms, which are then introduced into a reduced-form gravity equation. Hallak
(2006), Romalis (2007) and Head, Mayer, and Ries (2008) use the ratio of ratios to drop out indexes of the exporter
and importer's attributes, including the multilateral resistance terms.
4 Helpman, Melitz, and Rubinstein (2008) also control for the unobserved firm-level heterogeneity bias that results
from the variation in the fraction of firms that export from a source to a destination country. Their definition of the
extensive margin (cf.

*infra*) is therefore a bit different since it includes a change in the share of exporting firms.
5 A more accurate econometric estimation would be to add importer and exporter fixed effects interacted with the
NTM variable in equation (2).
6 It is also possible to consider the case with

*I* taking a value between 0 and 1, namely for situations where
consumers are partially aware of the characteristic.
7 The proportion of goods entering the domestic market also represents the combination of producer's probabilities
of being fully excluded from the domestic market when a small producer is detected with contaminated products.
8 Alternatively, the standard could equally influence foreign and domestic producers leading to an alternative
equation (

*p *−

*p *) /

*p *+ (

*Q *−

*Q *) /

*Q *= β ∆NTM , replacing equation (6).
9 Crustacean products include a large proportion of shrimps relatively to other crustaceans.
10 Concerns are also related to the environment (destruction of mangroves) and social costs (corruption of
authorities, employment of children and of illegal immigrants). However, we will not address these concerns in the
11 See Ababouch, Gandini, and Ryder (2005), Southern Shrimp Alliance (2007) and http://www.seafoodnews.com/
(available May 2009).
12 http://www.cepii.fr/anglaisgraph/bdd/distances.htm (available May 2009).
13 In the European Union, the MRL is defined at the European level and applied by all Member States.
14 Helpman, Melitz, and Rubinstein (2008) also use regulation costs and common religion as excluded variables.
However, such data are not available for all countries included in our sample. To avoid a substantial drop in sample
size, we do not use these variables as excluded ones in our estimations.
15 The proportion λ coming from (6) and welfare shifts of tables 3 and 4 were computed with the

*Mathematica*
software and are available upon request.
This case is such that (

*p *−

*p *) /

*p *+ (

*Q *−

*Q *) /

*Q *< β ∆NTM for λ = 0 .
17 The inspections and regulatory costs can be borne by consumers, domestic producers, taxpayers and/or foreign
producers depending on the selected fee (per-unit fee or fixed fee) that finances the inspection policy (see Crespi and
18 This situation with a MRL=0 does not correspond to a strict zero tolerance policy because of flaws in the test
procedures and the impossibility of testing all the products.

**References **
Ababouch, L., G. Gandini, and J. Ryder. 2005. "Detentions and Rejections in International Fish
Trade." Fisheries technical paper 473, Food and Agriculture Organization, Rome.
Alberini, A., E. Lichtenberg, D. Mancini, and G. Galinato. 2008. "Was It Something I Ate?
Implementation of the FDA Seafood HACCP Program."

*American Journal of Agricultural *
*Economics* 90(1):28-41.
Anders, S.M., and J. Caswell. 2009. "Standards as Barriers Versus Standards as Catalysts:
Assessing the Impact of HACCP Implementation on U.S. Seafood Imports."

*American *
*Journal of Agricultural Economics* 91(2):310-321.
Anderson, J.E. 1979. "The Theoretical Foundation for the Gravity Equation."

*American *
*Economic Review* 69(1):106-116.
Anderson, J.E., and E. van Wincoop. 2003. "Gravity with Gravitas: A Solution to the Border
Puzzle."

*American Economic Review *93(1):170-192.
Asche, F., and T. Bjørndal. 2001. "Demand Elasticities for Fish and Seafood: A Review."
Unpublished, Centre for Fisheries Economics, Norwegian School of Economics and Business
Baier, S.L., and J.H. Bergstrand. 2009. "

*Bonus Vetus OLS*: A Simple Method for Approximating
International Trade-Cost Effects Using the Gravity Equation."

*Journal of International *
*Economics* 77(1):77-85.
Beghin, J. 2008. "Nontariff Barriers." In S. Darlauf and L. Blume, eds.

*The New Palgrave *
*Dictionary of Economics*. 2nd edition. New York NY: Palgrave Macmillan LTD, pp. 126-129.
Beghin, J., and J-C. Bureau. 2001. "Quantitative Policy Analysis of Sanitary, Phytosanitary and
Technical Barriers to Trade."

*Economie Internationale *87:107-130.
Bergstrand, J. 1985. "The Gravity Equation in International Trade: Some Microeconomic
Foundations and Empirical Evidence."

*Review of Economics and Statistics* 67(3):474-481.
Bureau, J-C., S. Marette, and A. Schiavina. 1998. "Non-Tariff Trade Barriers and Consumers'
Information: The Case of EU-US Trade Dispute on Beef."

*European Review of Agricultural *
*Economics* 25(4):437-462.
Buzby, J.C., L.J. Unnevehr, and D. Roberts. 2008.

*Food Safety and Imports: An Analysis of FDA *
*Food-Related Import Refusal Reports*. Washington DC: U.S. Department of Agriculture,
ERS Econ. Information Bulletin 39. September.
Crespi, J., and S. Marette. 2001. "How Should Food Safety Certification Be Financed?"

*American Journal of Agricultural Economics* 83(4): 852-861.
Dean, J.M. 1995. "Export Bans, Environment, and Developing Country Welfare."

*Review of *
*International Economics *3(3):319-329.
Debaere, P. 2005. "Small Fish-Big Issues: The Effect of Trade Policy on the Global Shrimp
Market." Discussion paper 5254, Centre for Economic Policy Research, London.
Dee, P., and M. Ferrantino. 2005.

*Quantitative Methods for Assessing the Effects of Non-Tariff *
*Measures and Trade Facilitation*. Singapore: APEC Secretariat and World Scientific
Dey, M.M., U-P. Rodriguez, R.M. Briones, C.O. Li, M.S. Haque, L. Li, P. Kumar, S.
Koeshendrajana, T.S. Yew, A. Senaratne, A. Nissapa, N.T. Khiem, and M. Ahmed. 2004.
"Disaggregated Projections on Supply, Demand, and Trade for Developing Asia: Preliminary
Results from the Asiafish Model." Paper presented at IIFET Meeting, Tokyo, 21-30 July.
Disdier, A-C., L. Fontagné, and M. Mimouni. 2008. "The Impact of Regulations on Agricultural
Trade: Evidence from SPS and TBT Agreements."

*American Journal of Agricultural *
*Economics* 90(2):336-350.
Hallak, J-C. 2006. "Product Quality and the Direction of Trade."

*Journal of International *
*Economics* 68(1):238-265.
Head, K., T. Mayer, and J. Ries. 2008. "The Erosion of Colonial Trade Linkages After
Independence." Discussion paper 6951, Centre for Economic Policy Research, London.
Helpman, E., M. Melitz, and Y. Rubinstein. 2008. "Estimating Trade Flows: Trading Partners
and Trading Volumes."

*Quarterly Journal of Economics* 123(2):441-487.
Hudson, D., D. Hite, A. Jaffar, and F. Kari. 2003. "Environmental Regulation through Trade:
The Case of Shrimp."

*Journal of Environmental Management* 68(3):231-238.
Jayasinghe, S., J. Beghin, and G. Moschini. 2009. "Determinants of World Demand for U.S.
Corn Seeds: The Role of Trade Costs." Working paper 484, Center for Agricultural and Rural
Development, Iowa State University, Ames.
Krugman, P.R. 1980. "Scale Economies, Products Differentiation and the Pattern of Trade."

*American Economic Review *70(5):950-959.
Lusk, J.L., B. Norwood, and R. Pruitt. 2006. "Consumer Demand for a Ban on Subtherapeutic
Antibiotic Use in Pork Production."

*American Journal of Agricultural Economics *
88(4):1015-1033.
McCorriston, S., and D. MacLaren. 2005. "The Trade Distorting Effect of State Trading
Enterprises in Importing Countries."

*European Economic Review* 49(7):1693-1715.
_. 2007. "Deregulation as (Welfare Reducing) Trade Reform: The Case of the Australian
Wheat Board."

*American Journal of Agricultural Economics* 89(3):637-650.
Otsuki, T., J.S. Wilson, and M. Sewadeh. 2001a. "Saving Two in a Billion: Quantifying the
Trade Effect of European Food Safety Standards on African Exports."

*Food Policy*
_. 2001b. "What Price Precaution? European Harmonisation of Aflatoxin Regulations and
African Groundnut Exports."

*European Review of Agricultural Economics* 28(3):263-283.
Paarlberg, P.L., and J.G. Lee. 1998. "Import Restrictions in the Presence of a Health Risk: An
Illustration Using FMD."

*American Journal of Agricultural Economics* 80(1):175-183.
Pendell, D.L., J. Leatherman, T.C. Schroeder, and G.S. Alward. 2007. "The Economic Impacts
of a Foot-And-Mouth Disease Outbreak: A Regional Analysis."

*Journal of Agricultural *
*and Applied Economics* 39:19-33.
Peterson, E.B., and D. Orden. 2008. "Avocado Pests and Avocado Trade."

*American Journal of *
*Agricultural Economics* 90(2):321-335.
Polinsky, A.M., and W. Rogerson. 1983. "Products Liability and Consumer Misperceptions and
Market Power."

*The Bell Journal of Economics *14(2):581-589.
Rauch, J.E. 1999. "Networks Versus Markets in International Trade."

*Journal of International *
*Economics* 48(1):7-35.
Redding, S., and A.J. Venables. 2004. "Economic Geography and International Inequality."

*Journal of International Economics* 62(1):53-82.
Romalis, J. 2007. "NAFTA's and CUSFTA's Impact on International Trade."

*Review of *
*Economics and Statistics* 89(3):416-435.
Southern Shrimp Alliance. 2007.

*Request for Comments to the Presidential Interagency Working *
*Group on Import Safety [Docket No.2007N-0330]*. Tarpon Springs.
United Nations, Conference on Trade and Development. 2005.

*Methodologies, Classifications, *
*Quantification and Development Impacts of Non-Tariff Barriers.* TD/B/COM.1/EM.27/2.
United Nations, Food and Agriculture Organization. 2009.

*FishStat Plus - Universal Software *
*for Fishery Statistical Time Series*. Rome.
Warr, P.G. 2001. "Welfare Effects of an Export Tax: Thailand's Rice Premium."

*American *
*Journal of Agricultural Economics* 83(4):903-920.
White, H. 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct
Test for Heteroskedasticity."

*Econometrica *48(4):817-838.
Wilson, J.S., and T. Otsuki. 2004. "To Spray or not to Spray: Pesticides, Banana Exports, and
Food Safety."

*Food Policy* 29(2):131-146.
Wilson, N.L., and J. Anton. 2006. "Combining Risk Assessment and Economics in Managing a
Sanitary-Phytosanitary Risk."

*American Journal of Agricultural Economics *88(1):194-202.
World Bank. 2004.

*Saving Fish and Fishers. Toward Sustainable and Equitable Governance of *
*the Global Fishing Sector*. Report No. 29090-GLB. Washington DC.
World Trade Organization. 2008.

*Specific Trade Concerns.* G/SPS/GEN/204/Rev.8. Geneva.
Yue, C., and J. Beghin. 2009. "Tariff Equivalent and Forgone Trade Effects of Prohibitive
Technical Barriers to Trade."

*American Journal of Agricultural Economics *91(4):930-941.
Yue, C., J. Beghin, and H.H. Jensen. 2006. "Tariff Equivalent of Technical Barriers to Trade
with Imperfect Substitution and Trade Costs."

*American Journal of Agricultural Economics*
**Table 1. Impact of Standards on Chloramphenicol on Imports of Crustaceans, 2001-2006 **
(2) Heckman (maximum likelihood)
Coefficient estimates
Marginal effects
Estimated correlation coeff. ( ˆ
Estimated selection coeff. ˆ
Note: Fixed effects not reported. Standard errors (country-pair clustered) in parentheses with ***, ** and * denoting
significance at the 1%, 5% and 10% levels. Common language is the excluded variable.

**Table 2. Values of Parameters for the Calibrated Model of Crustaceans, in 2001 and 2006 **
European Union (EU15)
Consumption in 2001 (tons)
Priceª in 2001 (US $)
Consumption in 2006 (tons)
Priceª in 2006 (US $)
Own-price elasticity of demandb
Own-price elasticity of supplyc
MRLd in 2001 (in ppb)
MRLd in 2006 (in ppb)
Note: Quantities and prices in 2001 and 2006 come from UN FAO (2009). ª: The domestic prices were estimated by
dividing the value of imports by the quantity of imports (UN FAO 2009), since the import prices reflect and
approximate the domestic prices. b: Asche and Bjørndal (2001) for crustaceans in Canada, Japan and the European
Union and Hudson et al. (2003) for shrimps in the US by taking the average of own-price elasticities of demand over
the 4 destinations in table 4 (p. 236). c: Dey et al. (2004) for the aquaculture of shrimps by taking the average of
own-price elasticities of demand over the top 5 world producers of shrimps in table 3 (p. 5). d: MRLs for
chloramphenicol come from Debaere (2005), the World Bank (2004), the European Commission Decision
2002/657/EC, and http://www.seafoodnews.com/ (available May 2009).

**Table 3. Welfare Changes for the Year 2001 Linked to Reduction of the MRL Between **
**2001 and 2006 (***Ex Post*** Estimation) **
Case 1 ( γ =3/4)
Case 2 ( γ =1/2)

**United States ($) ∆MRL= -4.7 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare

**Canada ($) ∆MRL= -2.2 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare

**Japan ($) ∆MRL= 0 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare

**European Union ($) ∆MRL= -1.2 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare
Note: Relative variation (%) compared to the baseline scenario in parentheses.

**Table 4**.

**Welfare Changes for the Year 2006 with a Potential MRL Equal to Zero (***Ex Ante*
**Estimation)**
Case 3 ( γ =1/2)
Case 4 ( γ =1/4)

**United States ($) ∆MRL= -0.3 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare

**Canada ($) ∆MRL= -0.3 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare

**Japan ($) ∆MRL= -50 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare

**European Union ($) ∆MRL= -0.3 **
Domestic consumers and cost of ignorance
Domestic producers
Foreign exporters
International welfare
Note: Relative variation (%) compared to the baseline scenario in parentheses.

**Figure 1. Market Equilibrium **
Source: http://annecelia.disdier.free.fr/Disdier_Marette.pdf

Application # 103949 HIGHLIGHTS OF PRESCRIBING INFORMATION These highlights do not include all the information needed to use ----------------------- WARNINGS AND PRECAUTIONS ----------------------- SYLATRON safely and effectively. See full prescribing information for Depression and other serious neuropsychiatric adverse reactions. (5.1)

Impregnated central venous catheters for prevention of bloodstream infection in children (the CATCH trial): a randomised controlled trial Ruth E Gilbert, Quen Mok, Kerry Dwan, Katie Harron, Tracy Moitt, Mike Millar, Padmanabhan Ramnarayan, Shane M Tibby, Dyfrig Hughes, Carrol Gamble, for the CATCH trial investigators* SummaryBackground Impregnated central venous catheters are recommended for adults to reduce bloodstream infections but Published Onlinenot for children because there is not enough evidence to prove they are eﬀ ective. We aimed to assess the eﬀ ectiveness March 3, 2016of any type of impregnation (antibiotic or heparin) compared with standard central venous catheters to prevent http://dx.doi.org/10.1016/