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The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence
Discussion paper by Marco Fugazza, 2013
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POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
STUDY SERIES No. 57
THE ECONOMICS BEHIND NON-TARIFF MEASURES:
THEORETICAL INSIGHTS AND EMPIRICAL EVIDENCE
New York and Geneva, 2013
U N I T E D N AT I O N S C O N F E R E N C E O N T R A D E A N D D E V E L O P M E N T
ii POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
The purpose of this series of studies is to analyse policy issues and to stimulate discussions in
the area of international trade and development. The series includes studies by UNCTAD staff and by
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The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence iii
The paper presents a review of recent work both theoretical and empirical related to the
impact of non-tariff measures with a focus on technical regulations. A minimalist theoretical set-up to
analyse non-tariff measures is first presented. Various empirical approaches and techniques used to
assess the impact of technical regulations are discussed. Empirical results obtained across strategies
are then surveyed.
Keywords: Non-tariff measures, trade barriers, welfare
JEL Classification: F13
iv POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
The author wishes to thank Céline Carrère for helpful comments and discussion.
Any mistakes or errors remain the author's own.
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence v
1 INTRODUCTION .......................................................................................................................... 1
2 MAIN ISSUES FOR THE THEORETICAL CHARACTERIZATION
OF NON-TARIFF MEASURES .................................................................................................... 2
2.1 A minimalist approach: the single market approach ......................................................... 2
2.2 Multiple overlapping non-tariff measures .......................................................................... 6
2.3 Welfare analysis ................................................................................................................. 7
2.4 Beyond the minimalist approach ....................................................................................... 8
3 MAIN METHODOLOGICAL ISSUES IN QUANTIFYING NON-TARIFF MEASURES ............... 9
3.1 Inventory measures ............................................................................................................ 9
3.2 Price comparison ............................................................................................................. 10
3.3 Business surveys ............................................................................................................. 10
3.4 Quantity impact ................................................................................................................ 11
3.5 Gravity models ................................................................................................................. 11
3.6 Applied general equilibrium models................................................................................. 13
3.7 Cost–benefit analysis ....................................................................................................... 14
4 EVIDENCE ................................................................................................................................. 15
5 CONCLUDING REMARKS ........................................................................................................ 18
REFERENCES ......................................................................................................................................... 19
vi POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
List of figures
Figure 1. Frequency index by broad type of non-tariff measures (1999 and 2010) ............................. 1
Figure 2. Application of a quota on imports ......................................................................................... 3
Figure 3. Internationalization of damage costs ..................................................................................... 5
Figure 4. Application of a public standard ............................................................................................ 5
Figure 5. Multiple overlapping non-tariff measures .............................................................................. 6
Figure 6. Application of a public standard and welfare ........................................................................ 8
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 1
Non-tariff measures (NTMs) and in particular technical measures have become a prominent
feature in the regulation of international trade in goods. This pattern is illustrated by figure 1. While
technical regulations were imposed on almost 37 per cent of tariff lines in 1999, the equivalent figure
for 2010 is more than 50 per cent. The bulk of technical regulations are grouped in two major
categories, namely sanitary or phytosanitary (SPS) measures and technical barriers to trade (TBTs). The
former includes regulations and restrictions to protect human, animal or plant life or health, while the
latter addresses all other technical regulations, standards and procedures. SPS measures and TBTs
are the objects of two World Trade Organization (WTO) agreements that impose disciplines to trade
that go beyond the usual non-discrimination. Independently from their objective and legal framework,
SPS measures and TBTs can have important effects on international trade. In terms of incidence, TBTs
are by far the most used regulatory measures, with the average country imposing them on about 30
per cent of products and trade. Countries also impose SPS measures on an average of approximately
15 per cent of trade. The large incidence of TBTs and SPS measures raises concerns for developing
countries’ exports. These measures impose quality and safety standards which often exceed
multilaterally accepted norms. However, policy is proceeding with little economic analysis. There is
substantial literature on individual types of NTMs, and in some instances sophisticated empirical
analysis of their effect (such as for antidumping). However, this information is likely to be instrument,
industry or country specific. There are good reasons why this is the case and these reasons are likely
to stay. Under a common denomination NTMs regroup a vast array of trade (and in some instances
non-trade) policy instruments. Unlike tariffs, NTMs are not straightforwardly quantifiable, not
necessarily easy to model, and information about them is hard to collect (figure 1).
Frequency index by broad type of non-tariff measures (1999 and 2010)
Technical Measures Price Control Quantity Control Other Measures
Source: Gourdon and Nicita (2013).
2 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
This paper offers a review of some recent work both theoretical and empirical related to the
impact of NTMs with a focus on technical regulations. The objective is not to review an exhaustive list
of relevant papers but rather to take the reader as close as possible to the frontier of current research
within a comprehensible analytical framework. The issue of legitimacy of a measure is only briefly
discussed as a proper treatment is beyond the scope of the paper.
The difficulty in analysing technical regulations essentially originates in the fact that such
measures could have contrasting effects on exports and consumption, and eventually on welfare. From
the producer point of view, a major difference between measures falling into the technical regulations
type, and other more standard NTMs is the existence of compliance costs that do not translate
straightforwardly into an ad valorem change in production costs and eventually prices. Those
compliance costs may include the fixed costs of upgrading the equipment and/or practice codes,
obtaining certificates, altering marketing strategies, and the like. Such compliance costs echo the
conventional “standards as barriers” argument in the international development literature on market
access (Otsuki et al., 2001). From the consumer point of view, however, a technical measure may
increase the demand for imports if the measure is informative (Thilmany and Barrett, 1997). For
instance, the measure can signal a higher quality of imports via information disclosure such as
trademarks, labelling requirements, detailed description of certain attributes or restricted toxic
residues. The quality improvement effect corresponds to the “demand enhancing effect” or “standards
as catalyst” argument.
The present paper is organized as follows. Section 2 presents and discusses a minimalist
theoretical set-up to analyse NTMs. Section 3 is dedicated to the empirical approaches and techniques
used to assess the impact of technical regulations. Section 4 is a survey of empirical results obtained
in a selection of papers. Section 5 concludes the paper.
2. MAIN ISSUES FOR THE THEORETICAL
CHARACTERIZATION OF NON-TARIFF MEASURES
The standard approach to appreciate price and quantity effects of NTMs is based on the
canonical supply–demand diagram for imports. Independently of the nature of the NTM this approach
allows qualification of the cost/price-raising, trade-restricting effect at the border, which can be termed
the protection effect or more generally the trade-cost effect. The term protection effect has an explicit
negative connotation. This would not be justified if the NTM responsible for the effect had no
protectionist objective. Hence, we will opt thereafter for the term of trade-cost effect.
2.1 A MINIMALIST APPROACH: THE SINGLE MARKET APPROACH
In this basic theoretical framework it is relatively easy to illustrate how any measure could be
made equivalent to an ad valorem tariff. The most discussed equivalence is that between a quota and
a tariff. Intuitively, a quota, similarly to a tariff, introduces a wedge between the price received by
foreign producers facing the quota and the price paid by domestic consumers for these imports. This is
illustrated in figure 2, which focuses on the import market.
Typically, the analysis of a quota gives similar results to that of a tariff. The quota limits the
level of imports to qA'. As a consequence the domestic price of imports rises to pAD' which is above the
world price pA. In the classical case of the large country, the world price of the imported good falls to
pA'. This is as if the demand curve becomes the dashed line labelled D' with a kink at qA'. It might be
the case that the quota is set above the level of free trade imports implying that it is not binding. In that
case the quota has no effect. Otherwise, the quota gives rise to “rents” because of the price wedge it
creates. These rents may be captured either by the government of the importing country if import
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 3
licences/rights are auctioned, the domestic residents if they are given import licences/rights with no
financial counterpart, or foreigners if they have the import licences/rights with no financial counterpart.
The way the quota is administrated will eventually affect welfare analysis but not new equilibrium
Application of a quota on imports
A similar analysis applies to NTMs such as voluntary export restraint, variable levy on imports,
government procurement regulation or any other measure whose main objective is to limit deliberately
imports of a specific good through the imposition of a wedge between the world price and the price
charged to domestic consumers (see, for example, Baldwin (1991) and Deardorff and Stern (1997) for a
However, NTMs could generate categories of economic effects which are not prima facie a
trade-cost effect (Beghin, 2008) even though they translate into a similar impact on traded prices and
quantities. This is essentially true for measures such as TBTs and SPS measures or any with a
technical regulatory content. The rationale or political intent for this kind of measures is not necessarily
the protection of local/domestic industries. These categories of NTMs often have other stated social or
administrative objectives designed to regulate the domestic market. Meeting these objectives also
leads to a shift in the supply curve and/or to a shift in the demand curve (Roberts et al., 1999) as in the
case of classical NTMs such as quotas. The difference is found in the fact that the change in prices
due to the measure does not generate any private or public rent.
Typically prices vary as a consequence of variations in the cost of production and or changes
in consumption behaviour. More precisely, supply-shifting effects occur when regulations are used to
tackle externalities affecting international trade of goods, such as preventing the sale of products
hazardous for health or creating standards to increase compatibility and interoperability. Such
regulations can specify the production process (for example, the use of a certain technology), or
product attributes (for example, a maximum content of given components) required for conformity.
4 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
Demand-shifting effects are required for certain types of market failures, for instance by making it
compulsory to provide certain information to consumers, thus affecting their behaviour.
Supply-shift effects are of particular relevance to TBTs and SPS measures. Demand-shift
effects can be identified for any sort of technical regulation.
Ganslandt and Markusen (2001) explain how standards and technical regulations have both
trade-impeding and demand-enhancing effects, the former by raising the costs of exporters and the
latter by certifying quality and safety to consumers. However, in order to illustrate the impact of NTMs
such as TBTs and SPS measures on prices and quantity traded, we adopt the theoretical framework
used by Disdier and Marette (2010). The framework is based on a set of simplifying assumptions but
without loss of generality in its main analytical features. The analysis focuses on a specific good market
and excludes any general equilibrium mechanisms. The market good is assumed to be homogeneous
(or quasi homogeneous) except for a characteristic potentially dangerous to consumers. Foreign and
domestic goods can carry this characteristic. Domestic consumers may or may not be aware of the
latter. If they are aware they internalize the damage in consuming that good. Demand is derived from
quadratic preferences and supplies are derived from a quadratic cost function. Assuming that foreign
and domestic products are perfectly homogeneous and thus perfectly substitutable, the result is a
standard linear demand and supply diagram. The most interesting refinements are the dissociation
between foreign and domestic supply and the possibility to undertake welfare graphical analysis.
In figure 3, consumers internalize the possible damage related to the dangerous characteristic
of the product under consideration. As a consequence and assuming that the demand curve is linear in
the cost related to the possible damage, the demand curve shifts to the left. The size of the shift
depends on whether the dangerous feature is in both the domestic and foreign good or not. The
demand curve moves independently of the implementation or not of a standard. The implementation of
a standard exclusively affects supply curves as its impact is on the production process and thus on
production costs. With internalization the new market equilibrium occurring in A' is characterized by
lower consumption (from qA to qA') and lower price (from pA to pA'). The fall in consumption is reflected
in lower levels of both domestic production and imports. Figure 4 represents the case where the
dangerous characteristic is possibly carried by foreign goods only. In that context, the
implementation/reinforcement of a standard by domestic regulators affects imports exclusively, that is
foreign producers. This implies that only the foreign supply curve is affected directly. We further
assume that consumers have internalized the damage before the action of the regulator. The starting
equilibrium is made to coincide with the post-internalization equilibrium illustrated in figure 2. The
consequence of the domestic standard is an increase in the equilibrium price (from pA' to pA'') and a fall
in imports and thus domestic consumption (from qA' to qA''). The overall impact (that is, with respect to
the initial equilibrium in figure 3 characterized by the coordinates of point A) with internalization by
consumers of the damage cost is clearly a fall in the quantity consumed but an indefinite impact on the
equilibrium price (pA stands above pA'). The sign of the change in the equilibrium price will depend on
the probability of contagion, the associated cost form the consumer point of view and the stringency of
the standard. Standard stringency could be modelled essentially in two ways. The most straightforward
one is by the inclusion of a parameter indicating the proportion of output exported that eventually
enters the destination market after inspection. With a more stringent standard this proportion is
reduced. The proportion parameter behaves as a standard supply-shift parameter. This approach has
been applied to figures 3 and 4 with the additional assumption that no fixed/sunk costs exist. The
second approach consists of having a sunk (or fixed) cost parameter that varies with the application
and stringency of a standard. Sunk costs are linked amongst other elements to the firm’s costs of
market entry and of compliance with regulations. These two approaches are not exclusive and if taken
separately they both generate comparable results from at least a qualitative point of view. In the case
of the presence of sunk/fixed costs, the supply curve is no longer linear.
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 5
Internalization of damage costs
Application of a public standard
6 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
Besides internalization of the damage, the so-called demand-enhancing effect could also lead
to a shift in the demand curve. A public standard possibly affects consumer’s information set and
behaviour. If the measure appears to be informative and signals a higher quality of the permitted
imports it may enhance the demand for imports. As a response to the measure the demand curve
would shift to the right, counteracting the demand shift coming from the internalization of damage by
consumers. The demand-enhancing effect should be considered separately from the internalization of
possible damage although the two could be related. Their correlation may not be of the most intuitive.
Indeed, if we allow internalization to be imperfect, then the implementation of the standard could raise
the awareness of consumers and as a consequence it would increase the incidence of internalization.
2.2 MULTIPLE OVERLAPPING NON-TARIFF MEASURES
The effect of a specific NTM on price and quantity may be difficult to identify in a situation
where several NTMs are implemented for the same product. Whether from a theoretical or an empirical
point of view, the simplest approach is to consider that the overall impact is related to the relative
strength in trade restrictiveness of each NTM in place. That is, there is a dominant NTM in terms of
impact which encompasses the impact of all other NTMs. This configuration is illustrated in figure 5
which represents the combination of a quota and some technical regulation. The quota is assumed to
be binding and its restrictiveness on imports is such that the cost effect of the technical regulation is
absorbed by the quota price effect. In other words, the equilibrium price increase gives no indication of
the technical regulation price effect.
Multiple overlapping non-tariff measures
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 7
However, there are also cases where the impacts of NTMs do not overlap but add to each
other. For instance, if we consider the case of a combination of any ad valorem para-tariff measure and
some technical regulation, the aggregate price effect would be the resultant of the price effect of both
NTMs. Theoretically, both measures affect the cost of exporting to the implementing country and thus
shift the supply curve to the left.
Generally speaking, when one of the NTM implemented has a quantity restriction dimension, it
is likely that multiple NTMs have a cumulative but not additive effect.1 If multiple NTMs all affect
production costs their respective effects cumulate and most probably add to each other.
2.3 WELFARE ANALYSIS
Welfare analysis in a basic single-market linear demand–supply framework such as the one
adopted in previous sections is straightforward. Consumer and producer surpluses are directly
reflected by areas under and above the demand and supply curves, respectively. Deadweight losses
are triangular areas whose size depends on the relative elasticity of demand and supply curves. In
figure 2 for instance, welfare is given by the sum of domestic consumers’ surplus and domestic and
foreign producers’ profits, the overall deadweight loss generated by the introduction of a quota
corresponds to the triangle ABC.
When considering measures such as SPS measures and TBTs welfare must also account for
the damage linked to the dangerous characteristic of the product whether the latter is internalized or
not by domestic consumers. The internalization leads to a change in demand which de facto affects
equilibrium and thus welfare. However, welfare is usually seen from the point of view of a social planner
implying that the cost of damage should be included in the set of welfare components. The overall
damage cost can be estimated by the probability of having contaminated products times the per unit
damage costs expressed in units of the reference good. The implementation of an SPS measure or a
TBT will reduce the probability of contamination. This is shown in figure 6, which is a reproduction of
Figure 3 with a graphical representation of the damage cost of the dangerous characteristic. We further
assume that there is no internalization of the damage possibly caused by the dangerous characteristic
and that the latter pertains to foreign goods only. The move from damA1' to damA1'' reflects the fall in
the probability of contamination due to the implementation of the measure. The welfare net impact is a
priori unclear, despite the existence of the standard deadweight triangle, as the damage cost related to
the dangerous product characteristic has been reduced by the public standard. As long as the
“savings” in damage cost are larger than the deadweight loss, the net welfare impact remains positive;
that is, as long as in figure 6 the area defined by qA'qA''defg (the reduction in damage cost) remains
larger than the area abc (deadweight loss).
1 See Tilton (1998) for an illustration based on Korean exports of cement to Japan.
8 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
Application of a public standard and welfare
2.4 BEYOND THE MINIMALIST APPROACH
There are two major shortcomings in the preceding approach. First, it is a partial–partial
equilibrium analysis and, second, it remains essentially static. A partial equilibrium model, as the one
underlying the graphical analysis used here, focuses only on one part or sector of the economy,
assuming that the impact of that sector on the rest of the economy and vice versa are either non-
existent or small. A general equilibrium analysis on the contrary explicitly accounts for all the links
between sectors of an economy – households, firms, governments and countries. It imposes a set of
constraints on these sectors so that expenditures do not exceed income and income, in turn, is
determined by what factors of production earn. These constraints establish a direct link between what
factors of production earn and what households can spend. A general equilibrium approach is not
necessarily easy to put into practice as it would require more elaborated modelling especially if the unit
of analysis had to be the product. In addition, before turning to general equilibrium considerations it is
important to make sure that those considerations would generate important additional information. As
to the second shortcoming mentioned previously, it can be illustrated qualitatively in our minimalist set-
up. Generally speaking, a dynamic set-up would allow to qualifying the adjustment process going from
the original equilibrium to the post policy reform one. The best that can be achieved in the situation
described is comparative statics but with the application of a multidimensional adjustment process. A
good illustration is given by the demand-enhancing effect of the implementation of a standard. Such an
effect comes simultaneously or with some lags after the public standard has been implemented. As
mentioned previously, the economic effect is a demand shift effect moving the demand curve to the
right. For the sake of simplicity we assume that the two behavioural features are orthogonal to each
other. A demand-enhancing effect can in theory be stronger in impact than the rise in production cost
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 9
due to the fulfilment of the standard requirements. If this is verified then the implementation of the
standard could lead to an increase in both price and quantity at equilibrium. It would also lead to an
improvement in overall welfare always assuming that the implementation of the standard has reduced
the probability of damage by raising the quality of products consumed.2 This result would hold whether
the dangerous characteristic is specific to the foreign product or its domestic equivalent, or both.
3. MAIN METHODOLOGICAL ISSUES IN QUANTIFYING
Among the methodologies expected to be the more reliable in quantifying NTMs, inventory,
price comparison and quantity impact are the most often used. However, even in the simplest
theoretical framework, the economic and welfare effects of NTMs cannot be unequivocally determined.
This feature is not exclusively inherent to multiple NTMs but also to NTMs such as SPS measures and
TBTs. The main objective in the quantification of NTMs has been to produce price effects estimates
and translate them into ad valorem equivalent measures (AVEs) (also called, although misleadingly,
implicit tariffs or implicit rates of protection). This approach is particularly attractive as it would
synthesize in one single metric the impact of an instrument with multiple dimensions often interrelated
with each other. However, the analysis undertaken in the previous section has pointed to the fact that
this ad valorem equivalent does not necessarily have to be positive, and even if it is positive it does not
necessarily reflect a restrictive quantity effect. Hence, the ideal empirical strategy should provide
estimates of both quantity and price effects in order to allow for a proper qualification and identification
the NTM impact. Recently, advances in gravity-based analysis have set the basis to disentangle the
various effects of the implementation of technical measures for a specific good market. Accounting for
the possible existence of contrasting effects due to the implementation of an NTM also drives the
recently revived cost–benefit analysis.
3.1. INVENTORY MEASURES
The simplest aggregate indicators of the use and incidence of NTMs are the frequency index
and the coverage ratio. A frequency index is the share in total tariff lines containing one or more NTMs.
The share can be expressed in weighted terms based on either imports or production. The coverage
ratio is the percentage of imports affected by one or more NTMs to total imports. These inventory
measures allow the summarization of information on NTMs collected at a disaggregated level in one
indicator. Detailed information collected for a country at a disaggregated level is necessary for the
computation of these measures.
The frequency index accounts only for the presence or absence of an NTM, and summarizes
the percentage of products to which one or more NTMs are applied. In more formal terms, the
frequency index of NTMs imposed by country j is computed as:
2 See Carrère and De Melo (2011) for discussion and further illustrations.
3 Refer to Deardoff and Stern (1997) and Ferrantino (2006) for a comprehensive review and discussion of the issue. Useful
discussions are also found in Maskus et al. (2001) on quantification of technical barriers to trade. Beghin and Bureau
(2001) discuss sanitary and phytosanitary standards.
10 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
where D is a dummy variable reflecting the presence of one or more NTMs and M indicates whether
there are imports of product i (also a dummy variable). Note that frequency indices do not reflect the
relative value of the affected products and thus cannot give any indication of the importance of the
NTMs on overall imports.
A measure of the importance of NTMs on overall imports is given by the coverage ratio which
measures the percentage of trade subject to NTMs for the importing country j. In formal terms the
coverage ratio is given by:
where D is defined as for the previous equation, and V is the value of imports in product i. One
drawback of the coverage ratio, or any other weighted average, arises from the likely endogeneity of
the weights (the fact that imports are dependent on NTMs). This problem is best corrected by using
weights fixed at trade levels that would arise in an NTM- (and tariff-) free world, otherwise, the
coverage ratio would be systematically underestimated. While that benchmark cannot be reached, it is
possible to soften the endogeneity problem (and test for the robustness of the results) by using trade
values of past periods.
The immediate advantage of such instruments is the relative ease with which they can be
collected, in essence not much more difficult than compiling tariff schedules. Inventories of NTMs do
represent valuable information that could, if updated on a regular basis, help keep track of the
evolution of the relative incidence of different types of NTMs on trade flows of goods, and of the
evolution of their incidence relative to tariffs. Another obvious advantage is that information can be very
NTM type-specific and highly disaggregated at the product level. On the other hand, these indicators
have limitations in that they do not give any direct information about possible impact on price and
quantities produced, consumed or traded. They are normally used to construct indicators of trade
restrictiveness that in turn can be used to estimate quantity and/or price effects.
3.2 PRICE COMPARISON
A more direct measurement of the price impact of NTMs is price comparison (also called price
wedge). This enables the easy computation of so-called ad valorem equivalents. Yet serious
conceptual and data problems are likely to arise in the estimation and interpretation of tariffs
equivalents. First, it is necessary to identify the appropriate prices to use and this is likely to be
problematic. While it is fairly easy to obtain information on the price paid by the importers of a good, it
might become difficult to obtain the corresponding price prevailing in the domestic market especially at
a fairly disaggregated level. This becomes even more difficult if data collection has to be done for a
large set of countries. Other drawbacks are: the price comparison implicitly assumes perfect
substitution between imported and domestic goods and the price differential does not convey
information about how the NTM operates in practice (Beghin and Bureau, 2001). Another factor is that
the comparison is made in the presence of the NTM distortion (and not by comparison to a benchmark
case without distortion; see Deardoff and Stern, 1997).
3.3 BUSINESS SURVEYS
Business surveys or structured interviews have also been used to obtain information on the
prevalence of NTMs. Survey investigations could be used to collect data for a specific analytical
purpose such as information about the frequency of NTMs, or the relative importance of different
measures, such as their trade restrictiveness or trade impact. One problem is that surveys tend to be
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 11
very resource intensive. This feature is likely to constrain the scale and scope of the investigation and
the extent to which the collected information can be seen as representative of the sector or industry.
Surveys also tend to rely on perception information rather than on statistical data, and differences in
methodology make comparisons between different survey sources difficult.
3.4 QUANTITY IMPACT
Quantity-impact calculations should also provide precise information about the effect of NTMs
on trade, but similarly to price comparison it may be challenging to obtain appropriate data to compute
the exact impact. An advantage of quantity-based indicators is that a general approach to the
measurement of the quantity effects of NTMs can be undertaken, leading to the possibility of
systematic and repeated estimation. Such an approach could ideally (with a sufficiently large dataset)
include all categories of NTMs and thus isolate the individual impact of each. Quantity estimates
associated with information about import demand elasticities that can be used to derive price effect
estimates, and thus the computation of AVEs. This is the methodology followed in Kee et al. (2009).
The theoretical foundation for this kind of study is the n-good n-factor general equilibrium model with
log-linear utilities and log-linear constant returns to scale technologies (see for instance Leamer, 1988).
This model allows for both tariffs and NTMs to deter trade with effects that vary by importing country
and good. The empirically tested, reduced form of the model is given by:
cknncn utarDSCoreCm ,,,,,,,,, )1ln(lnln ++++++= ∑ φαγαα (1)
Once ad valorem equivalents of each NTM are computed then it is also possible to obtain an
overall level of protection at both the good and country level. There are drawbacks to this
methodology, the most important being certainly that it cannot fully account for the endogeneity of
imports to the presence of NTMs, and this is likely to bias the elasticities estimates.
3.5 GRAVITY MODELS
The gravity model of trade has also been used to estimate the value impact of NTMs. In a
cross section, a value impact is comparable to a quantity impact after some price normalization.
However, in terms of identification of the effect of the implementation of an NTM measure, a panel
structure is preferable even if it may complicate the empirical decomposition of variations in value into
price and quantity variations.
The standard gravity estimation is implemented at the product level or at the industry level. In
the former, estimation is in most cases product specific and often limited to a restricted sample of
countries (see, for example, Disdier and Marette (2010)). In the case of implementation at the industry
level, although the analysis could be exhaustive in terms of industry coverage it is usually restricted to
a limited number of countries (see, for example, Xiong and Beghin (2011)). Besides data availability,
empirical strategies must also account for computational constraints. A full fledge gravity model run at
the product level (for example, HS-6 digit) for a multiple-country sample (more than 20 countries) for a
period of 3 years or more may not be easily estimated, especially when controlling for possible
The general specification of the gravity model is as follows:
( ) tsijtjsiijtsjtsijtsijtsij fefefezNTMtarx ,,,,, ''1lnln εβγφ +++++++= (2)
12 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
where tar is the tariff applied by country j on imports of good s from country i, NTM is a set of NTM-
implementation-related indicators, z is the typical set of bilateral gravity variables and the fe variables
refer to fixed effects sector exporting country specific, importer specific and time specific. The NTM set
could reduce to the standard dichotomic indicator of the existence of an NTM, possibly capturing its
trade cost effect. However, it could also include variables allowing for the identification and estimation
of the demand-enhancing impact discussed above. In Xiong and Beghin (2011) a variable measuring
the difference in stringency between the SPS measure applied domestically and that applied in the
destination country is expected to capture the demand-enhancing effect. Another variable taking the
most stringent SPS measure as reference is expected to capture the trade cost effect.
In the “new” new trade theory, the existence of sunk costs to export affects the probability of
firms’ capability to export. This translates into a selection bias à la Heckman when dealing with
empirical analysis. Hence, the use of the Heckman sample selection model seems appropriate when
observing a high incidence of zeros in the bilateral trade relationships matrix. The Heckman selection
model applied to the gravity model writes:
( ) ( ) tsijtjsiiijtsjtsijtsijtsijtsij fefefeIMRzNTMtarxx ,,,,,, ''1ln0|ln εηβγφ ++++++++=>
( ) tsijsiijtsjtsij tjtsijtsijtsij fefefezNTMtarx ,,, '*'1ln ,,, µβγφ +++++++= ∗∗∗∗∗∗ (2')
>tsijx if and only if 0
x . IMR is the standard inverse Mill’s ratio obtained from the
selection equation. The error term in the exports value equation and the error term in the selection
equation are assumed to have a bivariate normal distribution with zero means, standard deviation
εσ and µσ and correlation εµρ . With selection, NTMs’ marginal effect in the outcome equation does
not correspond to the coefficient any more.4 Assuming that the NTM set of variables reduces to a
single continuous indicator its unconditional marginal effect is given by:
( ) ( )
is the inverse Mill’s ratio. Φ and φ are the cumulative standard normal
function and standard normal density function respectively. iδ is a function of the IMR and of
selectionk'θ , which corresponds to a set of regressors appearing in the selection equation of (2').
Assuming that the NTM set of variables reduces to a single binary indicator its unconditional
marginal effect when going from 0 to1 is given by:
4 See, for example, Greene (2011) or Hoffmann and Kassouf (2005) for a complete derivation.
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 13
( ) ( )
θ 0'1'ln'ln selectionselectionselection kkk
when the marginal effect is computed at the mean values.
In both expressions the unconditional marginal effect is a combination of the effect associated
to a change in the value of exports for exporting firms, and the effect associated to a change in the
probability of observing positive exports.
Sufficient variation is needed to identify parameters in the selection and outcome equations. In
theory this implies that variables explaining selection should differ from variables explaining outcome.
In practice enough variability would be obtained by identifying at least one variable that affects the IMR
but not the exports value equation. This is referred to as the exclusion restriction. In the gravity context
the identification of such a variable remains problematic and often identification is made to rely
exclusively on the normality of the residuals that is on the condition that ( ) 0,
=tsijtsijCov µε . The
variable repeatedly used in the restricted model is common language. Helpman et al. (2008) used
common religion and proxy variables for fixed costs of exporting taken from the Doing Business World
Bank database. These authors further argue in the light of their theoretical insights that the empirical
model should also correct for the fact that the shape of the distribution of firms’ productivity
determines the share of exporting firms. Correction terms for both the export selection bias and the
intensive margin bias should be included. Correction for the intensive margin bias is usually omitted
although its influence may dominate the export selection bias, especially in North–North trade
relationships (Belenkiy (2009)).
A proper disentangling strategy should permit the determination of how a change in technical
regulations policies affects different agents in international trade. Identifying the two separate effects
could also lead to better policy, especially in presence of externalities associated with trade. The
information retrieved from such investigation could be used to assess the legitimate nature of the
measure. For instance, in the case that consumers are not found to respond to the quality
improvement induced by a tighter measure, the latter should be subject to further scrutiny for possible
protectionism. However, qualitative features may also have to be taken into consideration. It may be
the case, for example, that the absence of direct demand-enhancing effect could also be consistent
with policies addressing long-term deleterious health or environmental effects valued by society but
neglected by consumers (see Peterson and Orden (2008) for a detailed discussion).
3.6 APPLIED GENERAL EQUILIBRIUM MODELS
Thanks to advances in computer and simulation technology, such as the Global Trade Analysis
Project (GTAP) (Hertel, 1997) and efforts to improve data collection and availability (trade analysis and
information system (TRAINS) being a leading example). Applied general equilibrium (AGE) simulations
of tariff reductions can now be carried out almost routinely. General equilibrium modelling has played
an important role in the WTO multilateral negotiations, helping assess complex negotiation modalities
and global interdependencies but also fuelling a public debate on the direction and magnitude of
estimates. The same cannot be said of NTMs. The Fugazza and Maur (2008) paper offers a truly global
and detailed assessment of NTMs in an AGE model (the standard GTAP model) using recent
econometric estimates of NTM AVEs computed by Kee et al. (2009). The authors follow the path
opened by the work of Andriamananjara et al. (2004), which was limited to a subset of sectors.
14 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
Of the three effects mentioned above, the protection effect of NTMs is the most immediate
candidate for assessment in a AGE model, provided that the correct impact estimates are available.
Protection effects are usually assessed at the border. These border effects generate a wedge either
between the world price and the domestic price in the importing country or between the world price
and the domestic price in the exporting country. As discussed previously, protection effects also arise
beyond (within) the border because NTMs do not necessarily discriminate between domestic and
imported goods. Tackling these beyond-the-border effects would require a model including increasing
returns to scale and export specific costs. Moreover, the assessment of the other economic effects in
an AGE context is much more complex. Although it would be desirable to investigate how one can
identify and separate the cost and the welfare-enhancing dimension of NTMs, it is difficult to think of a
methodology that would allow this to be carried out in a systematic way. Detailed information is
needed; it would have to be provided by technical experts (Deardoff and Stern, 1997) and probably
only for specific products or a limited range of countries.
All in all, standard AGE models do not offer many ways to include demand-shift and supply-
shift effects and none of them are fully satisfactory.
3.7 COST–BENEFIT ANALYSIS
Since NTMs do not necessarily embody the economic inefficiencies that are associated with
classical trade barriers, it is not always the case that the trade impacts of regulations are inefficient, or
that removal of associated non-tariff measures that affect trade would achieve efficiency gains that
would exceed the losses from weaker regulation. For this reason, specific NTMs are often analysed in a
cost–benefit framework. An example of a cost–benefit framework applied to NTMs is given by Van
Tongeren et al. (2009). The main advantage of such an approach is that the quantification of costs and
benefits for all the different economic actors (domestic consumers, domestic and foreign producers,
domestic government, and the like) involved allows for a more tailored evidence-based treatment of
specific NTMs. This comparative approach to NTMs allows for the identification of alternative ways to
address specific regulatory problems. Cost benefit analysis is generally used only in specific case
studies of NTMs of particular importance where detailed information can be obtained. In practice, the
traditional cost–benefit framework expands the analysis to cover not only one cost or benefit
associated to the presence of the NTMs, but also those associated with not having the measure in
place. Ultimately, this methodology contributes to a more comprehensive welfare analysis of NTMs
than that offered by looking at trade affects alone. In the cost–benefit framework the costs of the
measures are generally imputed on the bases of the “willingness to pay” methods. That is the value (or
costs) that consumers and producers impute to removing (or implementing) the measure. For example,
the value that consumers give to avoid an undesired product characteristic is a key variable in the
cost–benefit assessment. Clearly, the validity of the cost–benefit analysis depends on the accuracy to
which the willingness to pay is computed. This can be quite challenging to compute. There are various
methods used to measure willingness to pay (reviewed by Lusk and Shogren, 2007). Contingent
valuation methods involve directly asking individuals about their willingness to pay to obtain an
otherwise unavailable good. Choice experiments indirectly determine the willingness to pay by
econometric estimation based on choices models. Experimental economics uses simulations and
control groups to reveal the willingness to pay of agents.
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 15
The following review of the empirical evidence of the impact of NTMs on trade is not
exhaustive and includes essentially trade and welfare impacts obtained in gravity or gravity-related
estimations and AGE models simulations.
Empirical work on the trade impact of technical measures has proliferated rapidly over the last
twenty years, especially with investigations based on gravity equations. The literature shows a wide
range of estimated effects from significantly impeding trade to significantly stimulating trade.
Several indicators have been used to proxy the strength of technical measures. For instance
Otsuki et al. (2001), Wilson and Otsuki (2004) and Wilson et al. (2003) use maximum residue levels
(MRLs). MRLs enter the regression as numerical values, a straightforward and accurate measure of the
technical measures of interest. However, in most cases, technical measures do not have any direct
numerical measurement and their identification remains purely qualitative. In that context, proxies have
to be constructed. The most commonly used proxies of technical measures are dummy variables,
AVEs of the policies, frequency ratios and count variables. Choices among these different proxies
could lead to different estimates of trade effects of technical measures. Few researchers have tried and
compared different proxies within their investigations (see Disdier et al. (2008), discussed below) and
most researchers focus on one of them only.
One of the early and more discussed studies on the impact of SPS standards on trade is
Otsuki et al. (2001). These authors provide one of the first empirical analyses on the large impact of
SPS measures on developing countries exports. Using a gravity model framework, their analysis
investigates the impact of European Union regulations on aflatoxin (a naturally occurring mycotoxin
that frequently contaminates fruits and grains) on a few selected African export products. Their findings
indicate a quite important effect of the European Union regulation on African exports of cereals, dried
fruits and nuts. They quantify it as accounting for about 65 per cent export loss. Since this paper, a
number of other studies have investigated similar issues in different countries and sectors using
Wilson and Otsuki (2004) find that a 10 per cent increase in stringency of the MRL on
chlorpyrifos (an organophosphate insecticide) on bananas could lead to a 14 per cent decrease in
international trade of this good. Wilson et al. (2003) find that if MRLs of antibiotics on beef were
harmonized to the Codex Alimentarius standard, the rise in beef world exports would exceed 3 billion
tons. More than twenty per cent of that rise would originate from South Africa, Brazil and Argentina.
Again using data for the European Union, Chevassus-Lozza et al. (2008) find positive trade effects of
sanitary measures, and negative or insignificant impacts of phytosanitary and quality measures. More
specifically, their results suggest that for new member States (Bulgaria and Romania excepted) sanitary
measures do not act as a barrier to trade at entry to the European Union market and even significantly
stimulate traded volume for firms in those States fulfilling sanitary requirements. As far as Bulgaria and
Romania are concerned these measures still act as barriers to trade. However, once the barrier has
been overcome, the impact on traded volume is slightly positive.
For third countries, applying the quality measures reduces both the decision to export and the
volume traded. In addition, the authors can infer from their results that the impact of NTMs on the
degree of European market access is less a matter of the specific nature of the NTM than of the degree
of harmonization of the various measures amongst European Union countries.
Anders and Caswell (2009) find that implementation of hazard analysis critical control points
(HACCP) reduces United States’ seafood imports from large exporting countries.
16 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
Disdier et al. (2008) find, in their preferred specification with the AVE of NTMs, negative or
insignificant impacts of TBTs and SPS measures on agricultural and food aggregate trade amongst the
Organization for Economic Cooperation and Development (OECD) countries. However, they also find
that trade from developing countries towards OECD countries does see a significant reduction
because of NTMs. The originality of their approach lies in the fact that they investigate the impact of
NTMs using different proxies for the incidence of the latter. In a standard gravity model the authors
regress, along with the usual gravity explanatory variables, the bilateral tariff rate and three different
variables for SPS measures and TBTs: the tariff AVE of NTMs as computed in Kee et al. (2009), a
dummy equal to unity when the HS-6 level line has a notified SPS measure and a frequency index of
NTMs. They also investigate the impact of 30 disaggregated technical measures amongst industries
defined at the HS-2 aggregation level. Effects are estimated to be positive for 8 industries, insignificant
for 12 industries, and negative for 10. The disaggregated findings of Nardella and Boccaletti (2004),
Fontagné et al. (2005) and others further underline that the direction and the significance of trade
effects of technical measures appears to vary considerably across product groups and trading
These papers constitute a rich, although not exhaustive, set of illustrations of both trade-
impeding and trade-enhancing effects of technical measures. However, coherence in results may be
difficult to appreciate without further formal investigation. In this regard, Li and Beghin (2010) conduct a
meta-analysis to identify the sources of systematic variations found in estimated trade effects of
technical measures. In that regard, they investigate both data sampling and methodology differences.
They find that analyses of agriculture and food industries lead to estimates of trade effects of technical
measures, which are less likely to be positive. They also find systematic impeding effects of SPS
regulations on agricultural exports sourced from developing countries and going to developed
countries. This finding is robust and emerges in different estimation strategies (robust regression and
multinomial logit), suggesting that SPS regulations appear to be trade barriers rather than catalysts.
These authors also find that econometric models that control for unobservable country–pair
heterogeneity are more likely to produce positive (and less likely to produce negative) and significant
estimates of trade effects of technical measures than those models that do not control for it. The
aggregation level of the trade data is also expected to affect the estimated trade effects. The authors
find, although not unequivocally, that the more disaggregated data tend to provide relatively more
positive significant estimated trade effects of technical measures.
Xiong and Beghin (2011), as previously referred to in section 3.5, establish an econometric
approach to disentangle the demand-enhancing effect and the trade-cost effect of any
standard/technical regulation. Their econometric model is used to examine the impact of technical
measures on agricultural trade among OECD countries in 2004 and as such significantly refines the
findings of Disdier and al. (2008). Technical measures facilitate intra-OECD agricultural trade, as these
measures enhance consumers’ demand for imports more than they impede exports. In a further
disaggregated analysis of technical measures imposed on vegetable preparations primarily targeting
mycotoxins, they find that these measures tend to lead to additional intra-OECD trade in vegetable
products. However, they also find that technical measures affecting dairy products tend to decrease
trade in those products among OECD countries in their net effect. In both sectors demand-enhancing
effects are estimated to be significant. In a comparable disaggregated analysis focusing on Japanese
cut flowers, Lan and Yue (2009) show that estimates of the trade effects of SPS measures are biased
when the induced quality changes are not considered.
Hence, the separate identification of supply and demand effects is expected to help to
determine if a standard/technical regulation is driven by public awareness or potential protectionism.
The disentanglement of the effects of SPS measures on consumers and producers makes also
possible the welfare evaluation of a policy change, as pursued in Disdier and Marette (2010). These
authors use an analytical framework, applied to crustacean imports in several countries, to link the
mercantilist and welfare aspects of NTMs. Their estimates suggest that although antibiotic residue
limits reduce crustacean imports into the United States, the European Union, Canada, and Japan, they
improve both domestic and international welfare.
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 17
Applied general equilibrium exercises
Andriamanajara et al. (2004) offer a large-scale study of impact of NTMs in an AGE model.
They include 14 product groups and 18 regions. This work first estimates global AVEs for NTMs, using
price data from Euromonitor and non-tariff barrier (NTB) coverage information from UNCTAD. The price
effects obtained are generally very large: up to 190 per cent in the wearing apparel sector in Japan and
the bovine meat sector in China. The estimate of the price incidence in wearing apparel in the
European Union is 60 per cent. The authors then use their AVEs to simulate in GTAP the welfare effects
of a removal of the selected NTMs. Global gains are important (US$90 billion) arising mostly from
liberalization in Japan and Europe and in the textile and machinery sectors.
Other important works such as Gasiorek et al. (1992) and Harrison et al. (1994) simulate the
effects of regulations harmonization in the European Union in the post Maastricht era. The former
adopt the sand in the wheel approach and assume that trade costs are reduced uniformly by 2.5 per
cent, allowing for the characterization of short run and long run equilibrium. The latter use a similar
framework, extended to endogenize the elasticity of substitution between domestic and European
Union goods to account to some extent for the demand-shift effect mentioned previously. Results in
these two studies suggest that the impact of harmonization could reach 2.4 per cent of gross domestic
product (GDP). In a country-focused but otherwise similar computational set-up, Chemingui and
Dessus (2008) assess the impact of NTBs in Syria. They introduce estimates of price effects of NTBs
as regular tariffs. AVEs of NTBs are obtained in their study using the price comparison approach.
Welfare gains could range between 0.4 and 4.8 per cent of GDP depending on whether or not dynamic
effects (associated with a technological catch-up with the rest of the world) are taken into
With the surging political interest in trade facilitation, several recent studies have attempted to
capture its potential benefits, using the sand in the wheels approach. Hertel et al. (2001) are the first to
introduce an efficiency-shock variable in GTAP to simulate the impact of lower non-tariff trade costs
such as customs clearance costs in the free trade agreement between Japan and Singapore. Total
expected welfare gains for the agreement are worth $US 9 billion annually, with most of these accruing
from the trade facilitation component. Fox et al. (2003) account for the different nature of costs created
by NTMs by modelling both the direct costs and the indirect transaction costs of lack of trade
facilitation at the United States–Mexico border. Direct transaction costs are modelled as a usual import
tax, reflecting a transfer of rent between importers and domestic agents, while indirect transaction
costs are modelled as pure efficiency losses. They find indirect costs to be the major source of welfare
gains. Walkenhorst and Yasui (2005) follow the same approach to estimate the gains to be expected
from trade facilitation liberalization, additionally splitting the taxes between those borne by importers
and those borne by exporters. They find important welfare gains, around US$40 billion (arising for
nearly 80 per cent from efficiency gain effects). Francois et al. (2005) assess the impact of trade
facilitation reform related to the WTO Doha round of negotiations. They adopt the trade efficiency cost
approach to simulate the impact of improvements in trade logistics. In their baseline simulation
scenario, trade logistics impediments represent 1.5 per cent of the value of trade. Results suggest that
income effects related to trade facilitation reform could represent 0.2 per cent of GDP and two fifths of
overall reform impact.
Fugazza and Maur (2008) demonstrate the importance of modelling both the demand and
supply-shift effects of technical measures in policy analysis using AGE models. Most importantly their
simulation results underline substantial differences in effects, depending on whether AVEs are
introduced using shocks on import tariffs or on technological change. The sign of the welfare impact
can be reverted in more than 50 per cent of the cases.
18 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
5. CONCLUDING REMARKS
The incidence of technical regulations in the world of NTMs has increased substantially over
the last two decades and the trend is not expected to revert. Technical regulations can impact directly
both exporters’ and importing consumers’ behaviour with ambiguous net effects in contrast to more
standard NTMs such as quotas. Theoretical analysis, even in a partial–partial equilibrium context (one
good one market) reveals that technical measures can affect trade volumes and/or the propensity to
trade in either direction. Indeed, a tighter public regulation/standard promotes trade if its demand-
enhancing effect dominates its trade-cost effect; it impedes trade if its demand-enhancing effect falls
short of the trade-cost effect. The analytical ambiguity of the impact of technical measures on
international trade calls for a more careful empirical quantification and identification of the trade effects
of these measures, a task we pursue in this investigation.
The present review, although not exhaustive of existing empirical works, has revealed a mixed
picture of estimated impacts. Different TBTs and SPS measures are found to generate different trade
effects for different exporters and different industries. The variations in findings can be explained by
variations in data samples, mostly variations in industry, country, and aggregation level. Variations in
estimated trade effects may also be caused by different forms of technical measures proxies, model
specifications, and other methodology variations.
The most recent empirical works based on a refined theory underlying gravity equations and
econometric estimation techniques have addressed new issues, such as the treatment of zero trade
flows. These advances in empirical approaches represent a clear improvement although they are
limited to country- sector- or measure-specific analysis. This is not only due to the very nature of
technical regulations but also to binding constraints in econometric estimation.
Nevertheless, these recent contributions represent an important step towards a systematic
qualification of the nature of a technical regulation. Indeed, the empirical estimates obtained can help
identify whether a measure is legitimate or has been implemented essentially for protectionist
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UNCTAD study series on
POLICY ISSUES IN INTERNATIONAL TRADE
No. 1 Erich Supper, Is there effectively a level playing field for developing country
exports?, 2001, 138 p. Sales No. E.00.II.D.22.
No. 2 Arvind Panagariya, E-commerce, WTO and developing countries, 2000, 24 p. Sales
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models for future negotiations?, 2000, 29 p. Sales No. E.00.II.D.25.
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development issues: Exploring the welfare and distribution issues, 2001, 43 p. Sales
No. 12 Marc Bacchetta and Bijit Bora, Post-Uruguay Round market access barriers for
industrial products, 2001, 50 p. Sales No. E.01.II.D.23.
No. 13 Bijit Bora and Inge Nora Neufeld, Tariffs and the East Asian financial crisis, 2001,
30 p. Sales No. E.01.II.D.27.
No. 14 Bijit Bora, Lucian Cernat, Alessandro Turrini, Duty and quota-free access for LDCs:
Further evidence from CGE modelling, 2002, 130 p. Sales No. E.01.II.D.22.
24 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
No. 15 Bijit Bora, John Gilbert, Robert Scollay, Assessing regional trading arrangements in
the Asia-Pacific, 2001, 29 p. Sales No. E.01.II.D.21.
No. 16 Lucian Cernat, Assessing regional trade arrangements: Are South-South RTAs more
trade diverting?, 2001, 24 p. Sales No. E.01.II.D.32.
No. 17 Bijit Bora, Trade related investment measures and the WTO: 1995-2001, 2002.
No. 18 Bijit Bora, Aki Kuwahara, Sam Laird, Quantification of non-tariff measures, 2002,
42 p. Sales No. E.02.II.D.8.
No. 19 Greg McGuire, Trade in services – Market access opportunities and the benefits of
liberalization for developing economies, 2002, 45 p. Sales No. E.02.II.D.9.
No. 20 Alessandro Turrini, International trade and labour market performance: Major
findings and open questions, 2002, 30 p. Sales No. E.02.II.D.10.
No. 21 Lucian Cernat, Assessing South-South regional integration: Same issues, many
metrics, 2003, 32 p. Sales No. E.02.II.D.11.
No. 22 Kym Anderson, Agriculture, trade reform and poverty reduction: Implications for
sub-Saharan Africa, 2004, 30 p. Sales No. E.04.II.D.5.
No. 23 Ralf Peters and David Vanzetti, Shifting sands: Searching for a compromise in the
WTO negotiations on agriculture, 2004, 46 p. Sales No. E.04.II.D.4.
No. 24 Ralf Peters and David Vanzetti, User manual and handbook on Agricultural Trade
Policy Simulation Model (ATPSM), 2004, 45 p. Sales No. E.04.II.D.3.
No. 25 Khalil Rahman, Crawling out of snake pit: Special and differential treatment and
post-Cancun imperatives, 2004.
No. 26 Marco Fugazza, Export performance and its determinants: Supply and demand
constraints, 2004, 57 p. Sales No. E.04.II.D.20.
No. 27 Luis Abugattas, Swimming in the spaghetti bowl: Challenges for developing
countries under the “New Regionalism”, 2004, 30 p. Sales No. E.04.II.D.38.
No. 28 David Vanzetti, Greg McGuire and Prabowo, Trade policy at the crossroads – The
Indonesian story, 2005, 40 p. Sales No. E.04.II.D.40.
No. 29 Simonetta Zarrilli, International trade in GMOs and GM products: National and
multilateral legal frameworks, 2005, 57 p. Sales No. E.04.II.D.41.
No. 30 Sam Laird, David Vanzetti and Santiago Fernández de Córdoba, Smoke and mirrors:
Making sense of the WTO industrial tariff negotiations, 2006, Sales No.
No. 31 David Vanzetti, Santiago Fernandez de Córdoba and Veronica Chau, Banana split:
How EU policies divide global producers, 2005, 27 p. Sales No. E.05.II.D.17.
No. 32 Ralf Peters, Roadblock to reform: The persistence of agricultural export subsidies,
2006, 43 p. Sales No. E.05.II.D.18.
The Economics Behind Non-tariff Measures: Theoretical Insights and Empirical Evidence 25
No. 33 Marco Fugazza and David Vanzetti, A South-South survival strategy: The potential
for trade among developing countries, 2006, 25 p.
No. 34 Andrew Cornford, The global implementation of Basel II: Prospects and outstanding
problems, 2006, 30 p.
No. 35 Lakshmi Puri, IBSA: An emerging trinity in the new geography of international
trade, 2007, 50 p.
No. 36 Craig VanGrasstek, The challenges of trade policymaking: Analysis, communication
and representation, 2008, 45 p.
No. 37 Sudip Ranjan Basu, A new way to link development to institutions, policies and
geography, 2008, 50 p.
No. 38 Marco Fugazza and Jean-Christophe Maur, Non-tariff barriers in computable general
equilibrium modelling, 2008, 25 p.
No. 39 Alberto Portugal-Perez, The costs of rules of origin in apparel: African preferential
exports to the United States and the European Union, 2008, 35 p.
No. 40 Bailey Klinger, Is South-South trade a testing ground for structural
transformation?, 2009, 30 p.
No. 41 Sudip Ranjan Basu, Victor Ognivtsev and Miho Shirotori, Building trade-relating
institutions and WTO accession, 2009, 50 p.
No. 42 Sudip Ranjan Basu and Monica Das, Institution and development revisited: A
nonparametric approach, 2010, 26 p.
No. 43 Marco Fugazza and Norbert Fiess, Trade liberalization and informality: New stylized
facts, 2010, 45 p.
No. 44 Miho Shirotori, Bolormaa Tumurchudur and Olivier Cadot, Revealed factor intensity
indices at the product level, 2010, 55 p.
No. 45 Marco Fugazza and Patrick Conway, The impact of removal of ATC Quotas on
international trade in textiles and apparel, 2010, 50 p.
No. 46 Marco Fugazza and Ana Cristina Molina, On the determinants of exports survival,
2011, 40 p.
No. 47 Alessandro Nicita, Measuring the relative strength of preferential market access,
2011, 30 p.
No. 48 Sudip Ranjan Basu and Monica Das, Export structure and economic performance in
developing countries: Evidence from nonparametric methodology, 2011, 58 p.
No. 49 Alessandro Nicita and Bolormaa Tumurchudur-Klok, New and traditional trade flows
and the economic crisis, 2011, 22 p.
No. 50 Marco Fugazza and Alessandro Nicita, On the importance of market access for trade,
2011, 35 p.
26 POLICY ISSUES IN INTERNATIONAL TRADE AND COMMODITIES
No. 51 Marco Fugazza and Frédéric Robert-Nicoud, The ‘Emulator Effect’ of the Uruguay
round on United States regionalism, 2011, 45 p.
No. 52 Sudip Ranjan Basu, Hiroaki Kuwahara and Fabien Dumesnil, Evolution of non-tariff
measures: Emerging cases from selected developing countries, 2012, 38p.
No. 53 Alessandro Nicita and Julien Gourdon, A preliminary analysis on newly collected data
on non-tariff measures, 2013, 31 p.
No. 54 Alessandro Nicita, Miho Shirotori and Bolormaa Tumurchudur Klok, Survival analysis
of the exports of least developed countries: The role of comparative advantage,
2013, 25 p.
No. 55 Alessandro Nicita, Victor Ognivtsev and Miho Shirotori, Global supply chains: Trade
and Economic policies for developing countries, 2013, 33 p.
No. 56 Alessandro Nicita, Exchange rates, international trade and trade policies, 2013, 29 p.
No. 57 Marco Fugazza, The economics behind non-tariff measures: Theoretical insights and
empirical evidence, 2013, 33 p.
Copies of UNCTAD study series on Policy Issues in International Trade and Commodities may be
obtained from the Publications Assistant, Trade Analysis Branch (TAB), Division on International
Trade in Goods and Services and Commodities (DITC), United Nations Conference on Trade and
Development, Palais des Nations, CH-1211 Geneva 10, Switzerland (Tel: +41 22 917 4644).
These studies are accessible on the website at http://unctad.org/tab.
Since 1999, the Trade Analysis Branch of the Division on International Trade in Goods and
Services, and Commodities of UNCTAD has been carrying out policy-oriented analytical work
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UNCTAD Study series on
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