Technical Barriers to Trade and Multi-destination firms.

Preliminary version∗

Lionel Fontagne † Gianluca Orefice ‡

February 19, 2016

Abstract

This paper analyzes the asymmetric trade effect of restrictive Technical Barriers to

Trade (TBT) measures on heterogeneous exporters with a focus on multi-destination

firms. By matching a database on TBT measures that have been raised as of concern

at the WTO (Specific Trade Concerns – STCs), with a detailed panel of French firm ex-

ports, we test the effect of restrictive TBT measures on the different margins of trade:

(i) the probability to export and to exit the export market, (ii) the value exported, and

(iii) export prices. We find that TBT concerns discourage the presence of exporters

in (encourage the exit from) TBT-imposing foreign markets. This negative effect of

TBT is attenuated for higher productivity firms. Interestingly, multi-destination firms

divert their exports to towards TBT-free destinations (extensive margin channel).

Key Words: Non-tariff measures, TBT, Multi-destination Firms, Trade Margins.

JEL Codes: F13, F14.

∗This paper has received funding from the FP7 of the European Commission (EC), under the PRONTOProject (Productivity, Non-Tariff Measures and Openness), grant agreement 613504. Views expressed heredo not engage the EC. We are grateful to participants [...].†PSE - Universite Paris 1 & CEPII. Correspondence: Centre d’Economie de la Sorbonne, 106-112 Bd de

l’Hopital, F-75647 Paris Cedex 13. Email: lionel.fontagne@univ-paris1.fr.‡CEPII. Correspondence: CEPII, 113 rue de Grenelle 75007 Paris. Email: gianluca.orefice@cepii.fr.

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1 Introduction

Technical Barriers to Trade (TBTs), concerning quality, labeling and technical standards,

represent a fixed cost of exporting discouraging small and less productive firms to serve

markets in which TBTs are imposed. With heterogeneous firms, the productivity cut-off

will differ by destination for a given exporting country and there will be selection of firms on

more difficult destinations Chaney (2008). Imposition of TBTs also raises the variable cost

of producing the exported goods: technical standards impose an upgrading or at least an

adaptation of the product or packaging, while different standards across destinations take a

toll on economies of scale. An adjustment at the intensive margin of trade is thus expected

as well. These are the effects of a NTM usually expected in the literature.

There is an additional effect to consider however. Interestingly, the imposition of a

such barrier to trade may lead exporters to divert trade towards other destinations that do

not impose TBT measures. Any exporter indeed compares the (fixed and variable) cost of

satisfying the new standard with the cost of diverting her shipments. Diversion towards a

new destination (at the extensive margin) will impose a fixed cost of entry, while diversion

towards an existing destination (at the intensive margin) will impose an incremental cost of

reaching marginal consumers (Arkolakis 2010). The higher the cost of complying with the

TBT, the higher the probability that exporters will divert trade towards other destinations.

However, given that diversion has a cost, incumbent exporters close to the exporting cut-

off will neither be able to comply with the standard nor to divert their exports (given their

insufficient productivity). The punch line is finally that not all firms will divert their exports

when the trade restrictiveness of a TBT is high. Trade restrictive TBTs will lead to trade

diversion, but differently for firms with different productivity. And small players might well

be simply driven out of the market.

So, the research question of this paper is the asymmetric effect of trade-hampering TBTs

on the export margins of heterogenous firms, but with a focus on the reorientation of exports

of multi-destination exporters.

To proceed, we need to focus on trade restrictive TBTs. The Specific Trade Concerns

raised by affected exporting countries at the TBT committee of the World Trade Organi-

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zation (WTO) are a good tracker of such situations.1 Exporting countries will concentrate

their claims on the most restrictive TBTs, because there is a cost of complaining: trade

representatives have a certain amount of time and energy to allocate among a potentially

very large number of idiosyncratic regulations. As a consequence, focusing on those TBT-

market pairs spotted by the trade representatives in the committee, we capture the most

trade restrictive measures. This is the sub-sample of technical measures-destinations, for

which trade diversion should be observed.

We combine this information with custom data at firm level for the universe of French

exporters in order to uncover the usual adjustments of exports at the extensive and intensive

margins. In order to be as close as possible from our theoretical motivation, we will define an

”exporter” as a legal unit (here identified by her administrative identifier) exporting within

an HS4 category of products. In other words, a legal unit exporting in two different HS4

categories will be assumed to have paid twice the cost of launching a new variety (once in

each HS4 category). The level of product aggregation (HS4) has been chosen for coherence

with the TBT data (TBT concerns are also recorded at the HS4 level of the Harmonized

System).

Our first hypothesis is that small and less productive firms will be unable to cope with

the additional fixed/variable cost of the restrictive TBT, while larger multi-destination firms

will reorient their exports. Accordingly, stringent TBT will drive small players out of the

market – with an induced effect on market structure and competition – and encourage multi-

destination players reorienting their shipments towards other destination countries in which

they are already present (for which the fixed cost of entry is already paid) with less stringent

TBTs. As we do not have a continuous measure of stringency (either a TBT imposed by an

importer is challenged in the Committee or not), we will simply oppose destinations with

TBT concerns to destination without concerns, and this will be considered within the (firm

specific) range of destinations contemplated by each individual exporter.

Our second hypothesis is that big players will also look for new destinations, and expand

1According to multilateral rules (TBT agreement Art. 2.5): “ A Member preparing, adopting or applyinga technical regulation which may have a significant effect on trade of other Members shall, upon the requestof another Member, explain the justification for that technical regulation. The TBT committee is the placewhere such justification shall be provided.”

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their geographical scope, as a result of stringent TBTs. They will accordingly bear the cost

of entering new markets, provided that these markets have less stringent TBTs. Here again,

we will simply oppose destinations with and without concerns. These two assumptions will

be confronted to the data subsequently.

Our findings nicely support the above theoretical predictions. We firstly show that the

mean effect of the presence of a stringent TBT within an HS4 product category on a given

destination is to induce exits of exporters. This selection is driven by exporters having

alternative destinations in their portfolio of markets – free of TBT for the considered HS4

category. This diversion effect is robust to the inclusion of a control for firm size (a proxy

of firm productivity). In line with theory again, the presence of a TBT concern is hitting

less the most productive firms. A side effect of this selection is to increase the market share

of incumbents (but less so for incumbents having alternative destinations in their portfolio

and diverting their trade to those TBT free markets). And prices charged by incumbent

exporters mirror this anti-competitive effects of stringent TBTs: they increase, but less

so for diverting firms. Our second series of results also support the theoretical prediction

regarding the search for new – TBT free – destinations. The presence of a stringent TBT

within an HS4 product category on a given destination incites exporters to bear the fixed

cost of entering into new markets. This effect is magnified for exporters having initially a

larger set of destination countries without TBTs, suggesting the presence of economies of

scope in market access – an element absent from our theoretical benchmark.

The rest of the paper is organized as follows. Section 2 summarizes the existing literature

on the trade effect of Technical Barriers to Trade. Section 3 describes the data and some

stylized facts. Section 4 discusses our empirical strategy. Section 5 presents the results. The

final section concludes.

2 Literature Review

TBTs are covered by a WTO agreement: in a nutshell, technical regulations, standards,

and conformity assessment procedures must be implemented in a transparent and non-

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discriminatory way.2 Member countries are also encouraged to base their measures on

international standards, but they are not obliged to do so.

TBTs are subject to a triennal review by the WTO. The last occurrence of such review led

to a report published in December 2015 and pointing to the rapid increase in the notification

of such measures (Table 1. Since the first review in 1997 the number of notifications of TBTs

has posted a 254% increase. This figure corresponds to the optimistic assumption that all

member countries actually notify.

Since countries hardly follow WTO recommendation of sticking to international standard,

there is a variety of standards of different restrictiveness for a given category of products

across destinations. No need to stress the cost of duplicating the effort of compliance for

businesses. But progress in alleviating the impact of TBTs is generally made at the regional

level or more generally within the framework of deep integration agreements. The impact

of such attemps on exports of member and third parties has been repeatidly examined in

the literature. Baller (2007) use bilateral trade data at the 3-digit level of the SITC and

examines the trade impact of harmonization (i.e. adoption of a common standard, possibly

more stringent than most of the initial ones) and mutual recognition (granting exporters the

possibility of sticking to the least standard in the region) agreements for testing procedures.

A two-stage gravity estimation provides nuanced results. Mutual recognition is shown to

have a strong and positive effect on parties, in contrast to harmonization. Third countries

do not benefit from harmonization? Chen & Mattoo (2008) adopt a different perspective,

as they analyze the implications for third countries of regional initiatives that deal with

technical barriers. The two options of harmonization and mutual recognition should have

different impacts on trade, in particular for third countries exporters. And the more so

that regional standards are associated with strict rules of origin. Harmonization is shown to

impact positively both the likelihood and the volume of trade within the region. Although

the impact of harmonization on a third country’s exports is positively correlated with the

country’s ability to meet the standards, third countries exports are suffering overall. Mu-

tual recognition has similar positive impacts on intra-regional trade but the effect on third

2In WTO parlance: “ Members shall ensure that technical regulations are not prepared, adopted orapplied with a view to or with the effect of creating unnecessary obstacles to international trade ”

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countries exports to the region is ambiguous, as tight rules of origin annihilate the benefits

of mutual recognition for third countries exporters. This series of conclusion is however very

much centered on harmonization / mutual recognition among developed countries. Disdier,

Fontagne & Cadot (2015) analyze how harmonization of technical barriers between devel-

oped and developing countries affects international trade. Using a gravity equation, they

show that, as a result of the deep integration associated with standards provisions included

in such economic integration agreements, developing countries partners’ trade expands with

the North, but at the expense of their trade with non-bloc developing partners. Moreover,

harmonization on the basis of regional standards impacts negatively the exports of develop-

ing countries to developed markets. Indeed developing countries often lack infrastructures

and technical capabilities making it possible to easily comply with TBTs. Essaji (2008) uses

US import data at the HS8 level for agricultural, mining and manufacturing imports and

examines the impact of technical regulations. The potential endogeneity of technical regu-

lations is addressed using instrumental variables. Results confirm that technical regulations

substantially hinder developing countries’ exports.

While there is ample evidence that TBTs have negative or positive effects on trade

depending on the measure, its enforcement and the market failure potentially corrected

by the measure,3 little is known about how he different margins of trade are impacted by

TBTs, meaning how technical measures shape the distribution of exporters to the imposing

markets. An exception is Bao & Qiu (2012), who study the TBT effects on trade based

on TBT notifications in the period of 1995 - 2008. Using a two-stage gravity model, they

find that TBTs reduce the extensive margin of export but increase the export intensive

margin. However, this result is based on aggregate data and we know little on how individual

exporters of different productivity actually adjust to stringent TBTs. Data limitation is the

main obstacle to uncovering these complex mechanisms.

3See Disdier, Fontagn & Mimouni (2008) for an illustration on SPS and TBTs. Li & Beghin (2012)perform a meta-analysis of the trade impact of SPS and TBT measures for 27 published articles.

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3 Data and stylized facts

Our analysis overcomes the data limitations experienced in the previous literature by using

two major databases: a recently-constructed database on specific trade concerns (STCs)

and a database of French firm exports.

3.1 The STCs database and examples of TBT measures

TBT measures cover technical regulations, standards and procedures that are not included

in the SPS scope (which relates to human/animal and plant protection). TBTs apply

to technical requirements introduced for: (i) health or safety purposes, (ii) standardize

products, (iii) ensure quality standard or (iv) avoid consumer deception. See figure 1 for an

illustration on whether a measure belongs to SPS or TBT.

The recently-released WTO database on specific trade concerns records the concerns

that have been raised at the dedicated committees of the WTO is available in a quantitative

format.4 In this paper we focus on the concerns raised in the TBT Committee, who provides

WTO members with a forum to discuss issues related to TBT measures taken by other

members (”specific trade concerns” - STCs). When a country complains about a TBT

measure against another WTO member country (the imposing or maintaining country),

it specifies the product of concern, the type of concern regarding the measure and the

objective of the measure concerned. The advantage of this information is that it provides a

systematic set of all TBT measures that are perceived as sizeable trade barriers by exporters

(i.e. measures important enough that countries whose exports are affected raise a ”concern”

to the TBT committee of the WTO). We thus rely on TBT barriers to trade. This represents

the main advantage of using the STC dataset with respect to other sources. Indeed, other

datasets listing the full TBT measures imposed by countries (TRAINS or Perinorm) mix up

together TBT measures that restrict trade with others that may even increase trade.5

Overall, we have 318 Specific Trade Concerns raised at the TBT committee of the WTO

over the 1995-2011 period. Each STC corresponds to a concern raised by one or more

4The dataset is available at http://www.wto.org/english/res_e/publications_e/wtr12_dataset_

e.htm5Some TBT measures indeed may boost trade by addressing problems of asymmetric information or

network externalities (Moenius 2004, Fontagne, von Kirchbach & Mimouni 2005).

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countries in relation to a TBT measure imposed by one or more of their trading partners.

This figure is low, compared to the cumulated number of notifications over the period 1995-

2009 reported in Table 1 – more than 13,000. We are really observing in this committee

the most stringent TBTs, which is exactly our research strategy. For each concern, we have

information on: (i) the country or countries raising the concern and the country imposing the

measure, (ii) the product codes (HS 4-digit) involved in the concern, (iii) the year in which

the concern was raised to the WTO, and (iv) whether it has been resolved and how. Since

we have detailed data on French firm exports, we focus here on a sub-sample of concerns

raised by the EU over the period 1995-2008 (the period for which we have information on

French firm-level exports). Moreover, given the lag structure of our econometric exercise

(see Section 4), in order to be consistent over the entire paper, we rely on the 1996-2008

period.

In Table 2 we show descriptive evidence on the sample if STCs on TBT we use in our

empirical exercise. In column 2 of Table 2 we show that the number of countries targeted

by (at least one) STC is increasing over time. Similarly in column 3, the number of HS-4

chapters under TBT concern (in at least one STC) are exponentially increasing over the

period we analyze. It clearly emerges the increasing use of STCs on TBT, and consequently

the increasing relevance of TBT measures in hampering trade.

In our dataset we also have information on the primary object of the STC on TBTs, this

allows us to characterize the nature of the underlying TBT measure. In Table 3 we show

the top-five most frequent objectives reported in the list of STCs on TBT. Finally, in Table

4 we show the number of HS-4 chapters under STCs by imposing country. It emerges that

European Union and China have been frequently targeted by STCs on TBTs. This does

not mean that EU and China are particularly active in imposing TBTs, it simply indicates

that EU and China, being attractive markets for exporting countries, are often targeted by

STC when they impose TBT measures.

The main difference between TBT and SPS measures relies on the welfare effect. While

SPS measures, by preventing the imports of unhealthy products, have an impact on the

consumers’ welfare in the imposing countries, TBTs have a limited welfare effect since

they simply regulate technical standards. For example, in 1995 Canada, Peru and Chile

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complained at the WTO TBT committee against a labeling measure imposed by the French

government, who laid down the official name and trade description of scallops. Complainants

claimed that this measure reduced the competition on the French market as their product will

no longer be able to be sold as ”Coquille Saint-Jacques” although there were no difference

(according to complaining countries) between their scallops and French ones in terms of

color, size, texture, appearance and use (it is claimed they are ”like products”). This

concern was solved after one year with mutual recognition and represents an interesting

example of how TBT measure might hamper trade and have no effect on welfare.6 Another

interesting example of labeling measure preventing trade is the concern raised by Peru in

2001 against EU. According to Peruvian government, the EEC regulation 2136/89 prevented

Peruvian exporters to continue to use the trade description ”sardines” for their products.

Peru submitted that, according to the relevant Codex Alimentarius standards (STAN 94-181

rev. 1995), the species ”sardinops sagax sagax” are listed among those species which can

be traded as ”sardines”. Peru, therefore, considered that the above Regulation constituted

an unjustifiable barrier to trade (Articles 2 and 12 of the TBT Agreement and Article XI:1

of GATT 1994). Also this measure was solved with a mutually recognition.7

Similarly, TBTs on packaging might hamper trade with no effect on welfare for the

imposing countries. On 4 April 2012, Honduras requested consultations with Australia

concerning certain Australian laws and regulations that impose trademark restrictions and

other plain packaging requirements on tobacco products and packaging. Honduras chal-

lenged the following measures: (i) an Act to discourage the use of tobacco products, and for

related purposes, Australia’s Tobacco Plain Packaging Act 2011, and its implementing reg-

ulations; (ii) the Trade Marks Amendment (Tobacco Plain Packaging) Act 2011. According

to the Honduras government such measures imposed by Australia were inconsistent with

Australia’s obligations under TRIPS and GATT agreement.8 Many other countries joined

Honduras on this trade concerns soon after in 2012 (Brazil, Guatemala, Nicaragua, New

Zealand, Ukraine, European Union, Canada, Indonesia, Norway, Philippines) and a panel

6See https://www.wto.org/english/tratop_e/dispu_e/cases_e/ds12_e.htm7See https://www.wto.org/english/tratop_e/dispu_e/cases_e/ds231_e.htm8Namely Articles 2.1, 3.1, 15.4, 16.1, 20, 22.2(b) and 24.3 of the TRIPS Agreement; Article 2.1 and 2.2

of the TBT Agreement; and Article III:4 of the GATT 1994.

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was established to discuss this concern.9

Similar disputes at the TBT committee of the WTO are rather common, suggesting that

indeed TBTs represent impediments to trade with a marginal welfare effect for consumers

in the imposing countries. For this reason, in the present paper we are not interested in the

welfare effect of TBT in neither imposing nor complaining country. We simply use STCs on

TBT measures as examples of increases in (fixed) trade cost.

3.2 French firm-export data

Individual export data on French firms are provided by French Customs for the 1995-2008

period.10 Our estimations will therefore focus on the 1996-2008 period as we lose the starting

year after calculating the firm’s exit probability and the inclusion of lagged variables in the

estimations (for details see the next section).

The French firm dataset includes export records at the firm, product and market level

for all French exporters.11 Although the dataset classifies product categories using the

Combined Nomenclature at 8 digits (i.e. CN8 is an 8-digit European extension of the HS6

comprising some 10,000 product categories) we aggregate export data at HS-4 level to be

coherent with STC TBT dataset.

Then, as the EU acts as a single country in WTO committees, we restricted our firm-level

sample to only extra-EU export flows. Given the huge amount of observation, in order to

work with a manageable dataset we selected a subsample of relevant destination countries for

French firms: we calculated total export flows by destination market and retained markets

with above-median exports. Next, we dropped those firms that exported only one of two

years within our time period (churning). This strategy reduces any bias from only occasional

exporters.

As acknowledged by Konings & Vandenbussche (2013), one advantage of individual ex-

porter data is their good quality and the possibility to see clearly whether NTMs affect the

intensive/extensive margins of trade, the exit dynamics from foreign markets, and firms’

export price setting. We can also control for firm characteristics in determining the effect of

9https://www.wto.org/english/tratop_e/dispu_e/cases_e/ds435_e.htm10These data are subject to statistical secrecy and have been acceded at CEPII.11We consider legal units, as defined by their administrative identifier.

10

NTMs. However, since we do not have information on turnover, employment or capital for

the universe of French exporters, we rely on export-based measures of firm characteristics.12

4 Empirical Strategy

The main objective of the paper is to study the asymmetric effect of trade stringent TBTs

(as reflected by STCs on TBT measures) on the export margins of heterogeneous firms with

a focus on the multi-destination status of firms. Recall that we aim at putting to the data

series of clear-cut theoretical predictions suggested by the trade theory with heterogeneous

firms and destinations.

The first prediction is that small and less productive firms will be unable to comply with

stringent standard. Their productivity does not allow them to cope with the additional

fixed/variable cost of the restrictive TBT. Larger and multi-destination firms13 will reorient

their exports towards TBT free markets for which they have already paid the fixed cost of

entry.

Our second prediction is that the most productive and multi-destination exporters will

also look for new markets as a result of stringent TBTs. They will further expand their

geographical scope towards TBT free markets and bear the fixed cost of entry.

In the following we will confront sequentially these two predictions to the data for the

French universe of exporters and the whole set of destinations.

4.1 Trade diversion within the initial geographical scope of in-

cumbent exporters

To test our first prediction, we estimate the following equation:

12Data on French firm characteristics are available only for firms with more than 25 employees. Over 50per cent of exporting firms have fewer than 20 employees. To correctly account for the extensive margin ofexports, we do not use data on French firm characteristics.

13Firms with high productivity can reach more destinations because they can enter into markets withhigher fixed or variable cost.

11

yi,s,j,t = α + β1TBTs,j,t + β2 (TBTs,j,t ∗MultiDesti,t−1) + β3MultiDesti,t−1

+β4 ln(size)i,t−1 + β5 (TBTs,j,t ∗ ln(size)i,t−1)

+β6Ln(tariff + 1)s,j,t + φHS2,t,j + µi + εi,s,j,t, (1)

where the subscripts i, s, j, and t stand respectively for firm, HS 4-digit product category

(or 2-digit sector if HS2), destination country and year. Our dependent variables are: (i) a

dummy variable for the firm exiting a certain product-market (a dummy for the firm not

exporting in the current year but having exported the year before); (ii) a dummy variable

for positive trade flows into a certain product-destination market combination to capture

the (firm-product) extensive margin of trade, or participation; (iii) the firm’s export values

(in logs) to capture the intensive margin of trade;14 and (iv) the price of exported goods

(in logs), proxied by unit export values. Despite the dichotomous nature of some of our

dependent variables, we estimate equation 1 via OLS. We rely on simple linear probability

models (LPM) rather than on non-linear probit (or logit) to avoid the incidental parameter

problem due to the sizeable set of fixed effects we include in all regressions. In addition,

LPM provides simple direct estimates of the sample average marginal effect.

TBTs,j,t, reflects the existence, at time t, of an ongoing (unresolved) TBT concern in

product category s between the EU and an importer country j. Sizei,t−1 is a firm-specific

characteristic and captures heterogeneous export performance across firms related to firm

productivity (which is here unobserved). Since we do not have exhaustive information on

French exporters’ balance sheets, we calculate the size variables in terms of exports and not

total sales.15 We define this variable as: ln(size)i,t−1 =∑s⊂S

∑j⊂J

exportsi,s,j,t−1. We use a

one-year lag in our regressions to reflect that firms’ past performance affects future export

decisions.

To investigate how TBT concerns shape the adjustment of multi-destination exporters

14The dependent variable in this regression includes only positive trade values.15The empirical literature has extensively shown that export values are a good proxy for the overall size of

the firm: big exporters are usually larger and more-efficient than are non-exporters (see Mayer & Ottaviano(2008))

12

we interact the TBT dummy with the number of destination markets free of TBT served by

firm i at time t− 1 - MultiDesti,t−1. According to our hypothesis they might prefer leaving

the market imposing the measure. We test this channel of adjustment by introducing in

Equation 1 the interaction between TBT and MultiDesti,t−1. Multi-destinations exporters

are also more productive and larger because of their higher productivity. Thus we need to

control for size since the effect of MultiDesti,t−1 might well absorb the effect of TBT for big

firms. So in Equation (1) we also include the interaction between the TBT dummy and the

size of the firm at t− 1 (in log). Heterogeneous-firm trade models16 suggest that the effect

of an TBT measure on export performance may depend on the size of a firm, provided that

size is associated with productivity, and hence with the ability to overcome the additional

costs of exporting. In other words, not all firms will be able to cope with the higher costs of

new TBT regulations. In order to isolate the effect of TBT concerns from traditional tariff

protection we also control for applied tariffs at the product level (Ln(tariff + 1)s,j,t).17

Finally we add two sets of fixed effects. We include a set of firm fixed effects (µi)

to control for firm-specific and time-invariant unobserved characteristics that might affect

the trade performance of exporters. We also include a set of three-way fixed effects (HS2-

Destination-Year) - φHS2,t,j, to control for country-time-HS2-level varying factors that may

affect trade, such as business cycles, import-demand shocks and multilateral trade resistance

(as highlighted by Head & Mayer (2014)). These three-way fixed effects also control for the

geographic orientation of French exports that may affect the probability of raising a concern.

Moreover, HS2-Destination-Year fixed effects also control for measures imposed by a country

in response to a negative domestic shock in a given sector.

The inclusion of these two wide sets of fixed effects drastically reduces any endogeneity

concern due to the omitted variables bias. Moreover, the inclusion in Equation 1 of Sizei,t−1

captures the impact of firm specific time-varying characteristics on export performance. The

reverse causality arises if the government of a certain destination market introduces a TBT

measure in response to high levels of imports from a specific French firm (and then a concern

16See e.g. Chaney (2008), Arkolakis (2010) and Spearot (2013)17The tariff data come from the TRAINS database. Since TRAINS provides tariff in percentage points

(i.e. 10% ad-valorem tariff listed as 10), we divide tariff by 100 and then compute the price equivalenttransformation log(tariff+1)

13

is raised by the EU against this measure). This is a remote possibility. Even more if we

consider that we use TBT concerns raised by the EU as a whole (and not STCs raised

specifically by France). However, as a robustness check, we estimate our regressions lagging

the TBT variable by one year: given that a concern raised in t− 1 is related to a measure

introduced in t − 2 or earlier, there is low chance that such concern would be driven by

exports at time t.

4.2 Trade diversion beyond the initial geographical scope of in-

cumbent exporters: new markets

In presence of TBT concern in a given destination country, the firm may well exit the

market but add a new TBT-free destination, as suggested by our reasoning above. This will

happen as soon as the fixed cost of exporting into a new destination is below the fixed and

variable cost of staying in the market imposing the TBT and complying with such stringent

regulation. In this case we should see a positive effect on the number of the new destinations

countries at (t+1).

To investigate this second channel of adjustment, we collapse the dataset at firm-product-

year, so that for each firm-product combination we keep track of the total number of new

TBT-free destinations. For each firm-product we then compare the set of destinations at

time t with those at time t− 1 and count the number of new TBT-free destinations.

An alternative strategy of identification of this channel is to compute the probability

for an exporter to serve a new TBT-free destination when confronted to a concern on an

existing destination (for the same HS4 indeed). We just code a dummy if the number of

new TBT-free destinations is ≥ 1.

We thus use the above mentioned variables as dependent variables in the following esti-

mating equation:

yi,s,t = α + β1TBTi,s,t−1 + β2MultiDesti,s,t−1 +

β3 (TBTi,s,t ∗MultiDesti,s,t−1) + φHS4,t + µi + εi,s,j,t, (2)

14

The main explanatory variable here is a dummy being equal to one if the firm-product had

at (t-1) at least one destination with active TBT concern. We also include as a control the

number of destinations served by firm i on product s at time t− 1. This approximates the

multi-destination status of the firm at time t−1. We also interact the two above mentioned

variables to test the peculiar behavior of multi-destination firms facing TBT concerns in

terms of destination portfolio. Finally, we include firm and product-by-year fixed effects to

control for firms specific characteristics and any product specific unobserved shock.

5 Results

5.1 The Effects of TBT on firms’ margins of trade

Results for the estimated Equation 1 are reported in Tables 5, 6, 7 and 8 for respectively

the exit, the extensive margin, the intensive margin and the price charged (here proxied by

the unit value).

In Table 5 we show the results for the exit probability of firms. The mean effect of

the presence of an active TBT concern within an HS4 is to push firms out of the market

(column 1). Interestingly, we observe in column 2 that multi-destination exporters (i.e.

firms exporting in alternative TBT-free destinations) drive this result: the coefficient on

the interaction term between TBT and MultiDesti,t−1 is positive and highly significant in

column 2, while the coefficient on TBT is no longer significant. Finally, we show in column

3 that large firms are less prone to exit in response to a TBT concern, as the interaction

between TBT and firm size is negative and highly significant. While big firms are more able

to cope with TBT (reduced probability of exit the market, as expected), multi-destination

firms are still more likely to exit the market when they face a TBT concern, which is our

focus. Finally, in column 4, as robustness, we use only manufacturing sectors are results

remain unchanged. The rationale for using only manufacturing as robustness check comes

from results in Table A1 showing that the effect of TBT measures concerns mainly the

manufacturing sector.

In Table 6 we show the effect of TBT concerns on the extensive margin of French ex-

porters (participation). Column 1 shows that the presence of TBT concerns reduces the

15

probability of exporting into the destination imposing the measure on the considered HS4

product category. This results is robust across all the specifications reported in Table 6.

In column 2 we show that the mean negative effect of TBT concern is exacerbated for

multi-destination firms: these exporters are even less incline than single-destination firms to

export in destination countries with active TBT concerns. Comparing the stringency and

related cost of the TBT, they are incline to divert their exports towards other destinations

of their geographic portfolio whereby (stringent – as revealed by concerns) TBTs are absent

for this HS4 category of product. Again, this interaction might capture the size effect. So in

column 3 we include also the interaction between size and TBT. The sign of this interaction

is positive and significant, suggesting that big firms are better equipped to comply with

stringent TBTs, but the sign of the interaction between TBT and the number of destination

served by the firm remains negative and significant. Control variables have the expected

sign, firm size is positively related with the export probability, while tariff in destination

country (when significant) negatively affects the participation probability.

In Table 7 we show results for the intensive margin of firms. In this case the presence of

a TBT concern has a positive and significant effect on the intensive margin (of incumbent

firms), and this across all specifications in Table 7.18 This suggests that (stringent) TBTs

act as a barrier to entry reducing the toughness of competition in the imposing country

for the surviving exporters. The positive effect of TBT on the intensive margin is however

reduced for multi-destination exporters (see columns 3 and 4) and magnified for big firms

(see interaction with firm size in columns 3). This is coherent with the evidence showed

above: multi-destination firms exit from the market imposing the measure and so reduce

their presence there (because the have wider portfolio of destinations to exploit), although

big firms are more able to comply with the measure, remain in the market and enjoy the

reduced competition. We accordingly expect a positive average effect of TBT on the export

price of firms, but magnified for big firms. This is what we find in Table 8, where the TBT

dummy has always a positive and significant impact on prices charged by exporters – this

effect being magnified for big firms (column 3). Finally, in Table 9 we show results by using

the same specification as in Equation 1 but using a one year lagged TBT dummy. This

18This result is is coherent with findings of Bao & Qiu (2012)

16

robustness check aims to reduce any endogeneity concern of the TBT concern. Results are

qualitatively the same as those described above.

5.2 The dynamics of multi-destination firms

The evidence reported in Subsection 5.1 suggests a peculiar behavior of multi-destination

firms facing TBT concerns: the presence of a stringent TBT increases the exit probability of

firms, in particular for multi-destination firms (who have wider portfolio of destinations to

exploit). In this sub-section we now want to go further on this line of reasoning: we study

the adjustment of firms at the extensive margin channeling through the inclusion of new

destinations in their geographic portfolio. Namely, does the firm enter new markets after

exiting from the TBT imposing market?

Results for the estimation of Equation 2 are reported in Table 10. As expected, when a

firm faces the presence of a TBT concern on product s in (at least) one of its destinations at

(t-1), she starts shipping the considered HS4 product category at least in one new – TBT-

free – destination in t (see columns 4 to 6 where the probability of serving a new destination

is used as dependent variable). This result is in line with our hypothesis: in presence TBTs,

exporters will balance the cost of complying with this regulation against the fixed cost of

entering in a new market and make the decision of serving a new market when the regulation

is really stringent (as revealed by the concern). More productive exporters, already serving

several destinations, are shown to be more prone to make this decision of entering a new

market. This result is suggesting economies of scope in terms of prospection, networks of

distribution, or even branding of the product.

In order to confirm this unexpected effect, based on the simple theoretical framework

used above, we examine how the number of new destinations served, and thus the extent of

the redeployment of the exporter on a wider geographic scale. Here again, we show that the

number of new TBT-free destinations is positively impacted when the exporter is hit by a

stringent TBT, for the same HS4 product category, on an existing destination (column 1).

But here, this effect seems to be specific to those firms being multi-destination at (t-1) - see

column 3.

17

6 Conclusion

Aiming to uncover the adjustment channels of heterogenous exporters confronted to stringent

technical barriers on certain markets, this paper combined information on TBT concerns in

the dedicated WTO committee with with custom data at firm level for the universe of French

exporters. Theory suggests that small and less productive exporters will be unable to cope

with the additional fixed/variable cost of the restrictive TBT. They will exit. In contrast,

multi-destination firms will reorient their exports towards markets free of TBT concerns (for

the same HS4 category of products). Theory also suggest that a sub-sample of firms will

be productive enough to envisage new destinations, expand their geographical scope, and

bear the associated fixed cost, provided that these markets have less stringent TBTs. These

predictions are confirmed by our data. Stringent TBTs actually drive small players out of

the market; Competition is reduced to the benefit of survivors. Besides multi-destination

players are firstly encouraged reorienting their shipments towards other destinations, clear

of TBT concerns, for which they already paid the fixed cost of entry. On these markets they

adjust at the intensive margin. At the same time, they go for new markets, where pay the

induced fixed cost of entry. The latter channel of adjustment, at the extensive margin, is

magnified for exporters initially diversified geographically. This is suggesting the presence

of economies of scope in foreign market access.

18

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porters’, Review of World Economics 149, 295–320.

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Mayer, T. & Ottaviano, G. (2008), ‘The happy few: The internationalisation of european

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International Economics 89(1), 26 – 41.

19

7 Tables and Figures

Figure 1: TBT vs SPS measures.

Source: WTO website.

Table 1: Total notifications of TBTs per triennal review period

1995-97 1998-00 2001-03 2004-06 2007-09 2010-12 2013-15

1737 2012 2096 2658 4673 5845 6150Source: WTO,Seventh triennal review of the operation and implementation

of the agreement on technical barriers to trade under article 15.4. 3 December 2015, p.12.

20

Table 2: TBT concerns by year

year Number of Countries Number of HS4 items under Average number of TBT

with at least one STC on TBT TBT STC in at least one country concerns by country

1996 3 33 1,06

1997 7 342 16,19

1998 5 355 21,84

1999 3 402 13,35

2000 6 247 10,03

2001 11 280 25,58

2002 11 335 23,61

2003 12 556 38,1

2004 12 454 21,06

2005 13 467 17,61

2006 11 454 18

2007 20 408 16,16

2008 17 495 25,19

Table 3: The top-5 motives for TBT concerns

Objective nb occurrences across STCs Frequency over the total specified objectives*

Protection of Human Health or safety 135 22,60%

Protection of the Environment 67 11,20%

Consumer Information or Protection 48 8,00%

Labelling 28 4,70%

Quality 26 4,30%

Each STC has one or more objectives. One occurrence is thus the combination STC-objective. The total number of occurrencesin the dataset is 598. The frequency reported in the column is thus the ratio between the number of occurrences of aobjective over the total number of occurrences in the dataset.

21

Table 4: Number of HS4 items object of a STC in TBT by imposing country and year

Country 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Argentina 0 0 0 0 0 0 0 161 161 0 0 7 7

Brazil 0 0 158 0 0 167 3 5 2 2 0 10 15

Canada 1 1 0 0 0 0 0 0 0 0 0 1 2

Chile 0 0 0 0 0 167 0 0 0 0 0 0 0

China 0 0 0 0 0 1 210 214 3 31 225 30 197

Colombia 0 0 0 0 0 0 0 0 0 5 0 0 1

Ecuador 0 0 0 0 0 0 0 4 4 0 0 0 0

Egypt 0 2 166 166 3 0 0 0 0 0 0 0 0

European Union 4 179 16 81 82 277 251 426 429 258 261 273 274

Hong Kong 0 0 0 0 0 1 0 0 0 0 0 4 0

India 0 0 0 0 0 2 171 10 14 0 7 18 14

Indonesia 0 0 0 0 0 4 0 0 0 2 0 0 6

Israel 0 3 0 0 0 0 0 0 0 0 0 1 1

Japan 0 0 0 0 167 167 5 2 0 0 14 0 2

Korea 0 0 9 0 49 0 14 10 3 16 5 5 8

Kuwait 0 0 0 0 0 0 0 131 0 0 0 0 0

Malaysia 0 0 0 0 0 0 0 0 0 18 0 0 0

Mexico 0 315 328 0 0 0 0 0 2 2 0 0 0

Moldova 0 0 0 0 0 0 0 0 0 0 0 2 8

New Zealand 0 0 0 167 4 4 4 4 4 4 4 4 0

Peru 0 1 0 0 0 0 0 0 5 11 5 5 5

Philippines 0 0 0 0 0 0 0 0 0 0 2 2 0

Qatar 0 0 0 0 0 0 0 0 0 0 0 8 0

South Africa 0 0 0 0 0 0 3 0 0 170 0 0 161

Switzerland 0 0 0 0 0 0 0 0 5 5 5 5 0

Taipei 0 0 0 0 0 0 0 0 0 0 0 52 1

Thailand 0 1 0 0 0 2 2 0 0 0 0 4 4

Turkey 0 0 0 0 0 0 0 0 0 0 0 2 0

United States 28 0 0 0 6 1 25 170 21 22 29 67 75

Uruguay 0 0 0 0 0 0 0 0 0 0 1 1 0

Venezuela 0 0 0 0 0 0 44 44 0 0 0 0 0

22

Table 5: Exit probability estimation

Dep. Var. Exit Dummy

(1) (2) (3) (4)

TBT 0.033** 0.021 0.028* 0.016

(0.016) (0.016) (0.016) (0.016)

TBT*Log(TBT free destinations)t−1 0.016*** 0.020*** 0.026***

(0.005) (0.005) (0.007)

Log(TBT free destinations)t−1 0.010*** 0.010*** 0.010***

(0.000) (0.000) (0.000)

Log(Firm Size)t−1*TBT -0.007***

(0.002)

Log(Firm Size)t−1 0.025*** 0.022*** 0.022*** 0.023***

(0.000) (0.000) (0.000) (0.000)

Ln(tariff+1) 0.008 0.007 0.007 -0.009

(0.009) (0.009) (0.009) (0.012)

Sample Full Full Full Manuf.

Observations 3,848,704 3,848,704 3,848,704 3,451,593

R-squared 0.070 0.070 0.070 0.057

Firm and destination-chapter-year Fixed Effects always included.

Clustered standard errors by destination-HS4-year in parentheses.

*** p < 0, 01; ∗ ∗ p < 0, 05; ∗p < 0, 1.

23

Table 6: Extensive margin estimation

Dep. Var. Participation Dummy

(1) (2) (3) (4)

TBT -0.070*** -0.035* -0.041** -0.041*

(0.019) (0.019) (0.019) (0.021)

TBT*Log(TBT free destinations)t−1 -0.014* -0.018** -0.010

(0.008) (0.008) (0.011)

Log(TBT free destinations)t−1 0.166*** 0.166*** 0.168***

(0.001) (0.001) (0.001)

Log(Firm Size)t−1*TBT 0.007**

(0.003)

Log(Firm Size)t−1 0.119*** 0.071*** 0.071*** 0.070***

(0.000) (0.000) (0.000) (0.000)

Ln(tariff+1) -0.008 -0.026** -0.026** -0.003

(0.012) (0.012) (0.012) (0.017)

Sample Full Full Full Manuf.

Observations 3,848,704 3,848,704 3,848,704 3,451,593

R-squared 0.117 0.157 0.157 0.146

Firm and destination-chapter-year Fixed Effects always included.

Clustered standard errors by destination-HS4-year in parentheses.

*** p < 0, 01; ∗ ∗ p < 0, 05; ∗p < 0, 1.

24

Table 7: Intensive margin estimation

Dep. Var. Log of export value

(1) (2) (3) (4)

TBT 0.144* 0.242*** 0.170* 0.287***

(0.082) (0.092) (0.098) (0.090)

TBT*Log(TBT free destinations)t−1 -0.055 -0.106*** -0.084**

(0.042) (0.038) (0.036)

Log(TBT free destinations)t−1 0.841*** 0.841*** 0.837***

(0.003) (0.003) (0.003)

Log(Firm Size)t−1*TBT 0.073***

(0.026)

Log(Firm Size)t−1 0.246*** 0.024*** 0.023*** 0.024***

(0.004) (0.004) (0.004) (0.004)

Ln(tariff+1) -0.128** -0.224*** -0.223*** -0.253***

(0.063) (0.060) (0.060) (0.079)

Sample Full Full Full Manuf.

Observations 2,271,564 2,271,564 2,271,564 2,014,243

R-squared 0.314 0.373 0.373 0.360

Firm and destination-chapter-year Fixed Effects always included.

Clustered standard errors by destination-HS4-year in parentheses.

*** p < 0, 01; ∗ ∗ p < 0, 05; ∗p < 0, 1.

25

Table 8: Export price estimation

Dep. Var. Log of Trade Unit Value

(1) (2) (3) (4)

TBT 0.161*** 0.142*** 0.104** 0.145**

(0.055) (0.055) (0.048) (0.059)

TBT*Log(TBT free destinations)t−1 0.015 -0.012 0.014

(0.013) (0.015) (0.021)

Log(TBT free destinations)t−1 -0.033*** -0.032*** -0.040***

(0.002) (0.002) (0.002)

Log(Firm Size)t−1*TBT 0.039***

(0.014)

Log(Firm Size)t−1 0.013*** 0.021*** 0.021*** 0.023***

(0.002) (0.002) (0.002) (0.002)

Ln(tariff+1) -0.348*** -0.345*** -0.344*** -0.362***

(0.036) (0.036) (0.036) (0.057)

Sample Full Full Full Manuf.

Observations 2,271,564 2,271,564 2,271,564 2,014,243

R-squared 0.769 0.770 0.770 0.745

Firm and destination-chapter-year Fixed Effects always included.

Clustered standard errors by destination-HS4-year in parentheses.

*** p < 0, 01; ∗ ∗ p < 0, 05; ∗p < 0, 1.

26

Tab

le9:

Rob

ust

nes

sch

eck

usi

ng

lagg

edT

BT

dum

my

Exte

nsi

veE

xit

Inte

nsi

veT

UV

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

TB

Tt−

1-0

.074***

0.0

08

0.0

21

0.0

12

0.1

22

0.4

03***

0.1

75**

0.1

58**

(0.0

25)

(0.0

22)

(0.0

20)

(0.0

19)

(0.0

96)

(0.0

92)

(0.0

69)

(0.0

68)

TB

Tt−

1*L

og(T

BT

free

des

tin

atio

ns)

t−1

-0.0

15**

0.0

27***

-0.0

62*

0.0

10

(0.0

07)

(0.0

04)

(0.0

33)

(0.0

12)

Log

(TB

Tfr

eed

esti

nat

ion

s)t−

10.1

66***

0.0

10***

0.8

41***

-0.0

33***

(0.0

01)

(0.0

00)

(0.0

03)

(0.0

02)

Log

(Fir

mS

ize)

t−1

0.119***

0.0

71***

0.0

25***

0.0

22***

0.2

46***

0.0

24***

0.0

13***

0.0

21***

(0.0

00)

(0.0

00)

(0.0

00)

(0.0

00)

(0.0

04)

(0.0

04)

(0.0

02)

(0.0

02)

Ln

(tar

iff+

1)-0

.008

-0.0

25**

0.0

08

0.0

07

-0.1

29**

-0.2

23***

-0.3

48***

-0.3

45***

(0.0

12)

(0.0

12)

(0.0

09)

(0.0

09)

(0.0

63)

(0.0

60)

(0.0

36)

(0.0

36)

Ob

serv

atio

ns

3,848,7

04

3,8

48,7

04

3,8

48,7

04

3,8

48,7

04

2,2

71,5

64

2,2

71,5

64

2,2

71,5

64

2,2

71,5

64

R-s

qu

ared

0.1

17

0.1

57

0.0

70

0.0

70

0.3

14

0.3

73

0.7

69

0.7

70

Clu

ster

edst

an

dard

erro

rsby

des

tin

ati

on

-HS

4-y

ear

inp

are

nth

eses

.F

irm

an

dd

esti

nati

on

-ch

ap

ter-

yea

rF

ixed

Eff

ects

alw

ays

incl

ud

ed.

***p<

0,0

1;∗

∗p<

0,0

5;∗

p<

0,1

.

27

Tab

le10

:T

he

Dynam

iceff

ect

ofT

BT

Nu

mb

erof

New

Pro

bab

ilit

yto

serv

ea

new

TB

T-f

ree

des

tin

ati

on

TB

T-f

ree

des

tinati

on

(1)

(2)

(3)

(4)

(5)

(6)

TB

Tt−

10,1

25***

0,0

87***

0,0

07

0,3

49***

0,2

55*

**

0,1

90***

(0,0

04)

(0,0

04)

(0,0

04)

(0,0

05)

(0,0

05)

(0,0

08)

N.

ofd

esti

nat

ions t−1

0,0

52***

0,0

51***

0,1

32*

**

0,1

31***

(0,0

01)

(0,0

01)

(0,0

01)

(0,0

01)

TB

Tt−

1*N

.of

des

tin

atio

ns t−1

0,0

67***

0,0

55***

(0,0

04)

(0,0

06)

Ob

serv

atio

ns

1920748

1920748

1920748

1920816

19208

16

1920816

R-s

qu

ared

0,1

15

0,1

33

0,1

34

0,1

54

0,1

76

0,1

76

Clu

ster

edst

an

dard

erro

rsby

firm

-HS

4in

pare

nth

eses

.F

irm

an

dH

S4-y

ear

Fix

edE

ffec

tsalw

ays

incl

ud

ed.

***p<

0,0

1;∗

∗p<

0,0

5;∗

p<

0,1

.

28

Appendix

29

Tab

leA

1:T

he

effec

tof

TB

Ton

man

ufa

cturi

ng

and

agri

cult

ure

sect

ors.

Exte

nsi

vem

arg

inE

xit

pro

bab

ilit

yIn

ten

sive

marg

inT

rad

eU

nit

Valu

e

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

TB

T-0

.075

***

0.0

01

0.0

36**

0.0

03

0.1

51*

0.1

07

0.1

63***

0.0

65

(0.0

21)

(0.0

28)

(0.0

17)

(0.0

17)

(0.0

89)

(0.1

04)

(0.0

59)

(0.0

83)

Log

(Fir

mS

ize)

t−1

0.11

8***

0.1

39***

0.0

26***

0.0

19***

0.2

40***

0.2

94***

0.0

12***

-0.0

04

(0.0

00)

(0.0

02)

(0.0

00)

(0.0

01)

(0.0

04)

(0.0

15)

(0.0

02)

(0.0

06)

Ln

(tar

iff+

1)0.

029*

-0.0

61***

-0.0

07

0.0

29**

-0.0

75

-0.2

34**

-0.3

71***

-0.3

52***

(0.0

17)

(0.0

18)

(0.0

12)

(0.0

12)

(0.0

84)

(0.0

95)

(0.0

57)

(0.0

41)

Sam

ple

Man

uf.

Agri

.M

anu

f.A

gri

.M

anu

f.A

gri

.M

anu

f.A

gri

.

Ob

serv

atio

ns

3,45

1,59

3372,5

91

3,4

51,5

93

372,5

91

2,0

14,2

43

241,2

02

2,0

14,2

43

241,2

02

R-s

qu

ared

0.10

40.2

41

0.0

57

0.2

07

0.3

00

0.4

85

0.7

45

0.7

78

Fir

man

dd

esti

nati

on

-ch

ap

ter-

yea

rF

ixed

Eff

ects

alw

ays

incl

ud

ed.

Clu

ster

edst

an

dard

erro

rsby

des

tin

ati

on

-HS

4-y

ear

inp

are

nth

eses

.

***p<

0,0

1;∗

∗p<

0,0

5;∗

p<

0,1

.

30