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Competing liberalizations: tariffs and trade in the twenty-first century


This paper proposes a unique overview of trade policies since 2001, based on detailed data on tariffs and trade covering 130 countries. It shows that regionalism has delivered limited liberalization, representing only a 0.3 percentage point (p.p.) cut in the worldwide average applied tariff between 2001 and 2013. WTO commitments (1.0 p.p. average cut) and unilateral liberalizations on a most-favored-nation basis (1.3 p.p.) mattered far more. The study also shows that GVC participation was a powerful motivation underlying tariff liberalizations, including those carried out at governments’ own initiative. The paper finally assess that recent trade policy changes more than halved the worldwide welfare gains expected from multilateral tariff-cutting. If all PTA negotiations were concluded, gains would fall to one-third of their 2001 level.

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Fig. 1

Source: Authors’ calculations based on MAcMap-HS6 database (CEPII-ITC), WTO and national sources. Weighted averages computed using MAcMap-HS6 methodology (Bouët et al. 2008). In addition to the years 2001–2013, three hypothetical situations are considered, reflecting respectively the case in which PTAs already signed (between 2013 and 2015) but still to be implemented would be fully enforced (“2013 & phased-in”), the case where the three potential mega-deals between rich countries (EU-Japan, TPP, TTIP) would be signed and fully enforced (“2013 & mega-deals”), and the case where all agreements under negotiation at the end of 2013 would be concluded and enforced (“2013 & negotiations”). Computations for these hypothetical situations are based on 2013 trade flows, updating their PTA status (within-PTA or not)

Fig. 2

Source: Authors’ calculations based on MAcMap-HS6 database (CEPII-ITC), WTO and national sources. Note: Share in world imports (in %) are on the x-axis, binding overhang (in percentage points) on the y-axis. The figure represents the distribution of binding overhang in world trade, based on import share. Reading: point (80, 10) of the curve for 2001, for instance, means that 80% of imports were made in products in which the binding overhang, i.e. the difference between the bound and the preferential applied tariff was lower than 10%. The plateau corresponding to a binding overhang level equal to 25 p.p. results from our treatment of unbound products (see text)

Fig. 3

Source: Authors’ calculations based on MAcMap-HS6 database (CEPII-ITC), WTO and national sources. Note: Share in world imports (in %) are on the x-axis, preferential margin (in percentage points) on the y-axis. The figure represents the distribution of preferential margin in world trade, based on import share. Reading: point (90, 2) of the curve for 2013, for instance, means that 90% of imports were made in products in which the preferential margin, i.e. the difference between the MFN applied and the preferential applied tariff was lower than 2%

Fig. 4

Source: Author’s calculations based on BACI database (CEPII), WTO and national sources

Fig. 5

Source: Authors’ calculations, MAcMap-HS6 database. Weighted average using MAcMap-HS6 methodology

Fig. 6

Source: Authors’ simulations based on a perfect competition version of the Mirage model

Fig. 7

Source: Authors’ simulations based on Mirage model

Fig. 8

Source: Authors’ simulations based on Mirage model


  1. 1.

    In usual WTO conventions (, Regional Trade Agreement (RTA) refers to reciprocal trade agreements. However, in this paper, we use the term PTA in line with the trade policy literature [For example, Baldwin and Freund (2011), Krishna (2012) and Caliendo et al. (2016)].

  2. 2.

    For instance, while Hufbauer and DeRosa (2007) emphasize that “global tariff-cutting over the past decade was dominated by preferential trade agreements”, Krishna (2012) concludes instead that “the actual amount of liberalization that has been achieved through PTAs is actually quite limited”.

  3. 3.

    For instance through ad valorem equivalent (AVE) estimations (Kee et al. 2009 is an example), assessment of the NTM provisions in PTAs (e.g. Cadot and Gourdon 2015), and by estimating the firm-level impact of NTMs on exports (Fontagné et al. 2015).

  4. 4.

    In particular, the World Bank’s Temporary Trade Barriers database has vastly improved the quality and consistency of information available in this regard.

  5. 5.

    “Unilateralism” refers here to liberalization at a country’s own initiative.

  6. 6.

    Even though the US withdrew from the TPP, we consider here this agreement in its original configuration, which can be considered as an upper bound of what is likely to happen in practice.

  7. 7.

    Partners that are not members of the WTO sometimes apply tariffs higher than the MFN. This non-MFN tariff is taken into account in this case.

  8. 8.

    PTAs are reciprocal arrangements, whereby partner countries sign mutually binding commitments. By contrast, non-reciprocal preferential schemes, such as Generalized Systems of Preferences (GSPs) and their special schemes for least developed countries, are granted unilaterally and do not bind the countries granting them with respect to their partners. In this sense, they are not contractual in nature. They are set unilaterally and driven by development-oriented motivations.

  9. 9.

    For post-DDA tariffs, we use as a reference the latest draft modalities circulated by the Trade Negotiations Committee chairman, namely revision 4 of the 2008 modalities for agricultural and non-agricultural market access (WTO 2008a, b). For each HS6 product, the relevant tariff-cutting formula is applied to the existing bound tariff to compute the new bound. The new applied tariff is then the minimum between the formerly applied tariff and this new bound. This is done taking into account each country’s status (developed, developing, LDCs, {very} recently acceded members, small and vulnerable economies, etc). In accordance with the modalities, 4% sensitive products (selected using the Jean et al. 2011 method) are entitled to more flexible treatment for developed countries, and a third more for developing countries. Special products are also taken into account in accordance with modalities. Quotas open in compensation for these sensitive of special products are not taken into consideration.

  10. 10.

    Even though countries that are not members of the WTO are not bound by the MFN principle, they usually apply the same duty rate to their partners, outside PTAs. If different rates are applied, we take into account the higher one applied to at least three different partners.

  11. 11.

    Using computations based on average statistics over the 2001–2013 period instead does not alter significantly the results.

  12. 12.

    Stipulating that at least three different partners apply this same level allows preventing an exceptional regime from being considered as the MFN duty.

  13. 13.

    Looking for any specific pattern would make little sense for countries with a very low number of PTAs.

  14. 14.

    The five-year period is chosen so as to limit the influence of the phasing-in period, while keeping a large-enough number of agreements for each country.

  15. 15.

    This gap is also frequently referred to as tariff water.

  16. 16.

    See, e.g.,

  17. 17.

    As explicitly formulated, for example, in Robert B. Zoellick’s statement to the Committee on Finance of the US Senate, Washington, DC, 21 June 2001.

  18. 18.

    Chile is the most extreme example of this strategy, with bilateral agreements covering 60 partners (EU member states are counted individually) and more than 90% of its imports. Mexico, Singapore and, to a lesser extent, Association of Southeast Asian Nations (ASEAN) countries can also be considered as having applied such a strategy.

  19. 19.

    Broad Economic Categories. See

  20. 20.

    Details of the model can be found in the “Appendix”.

  21. 21.

    The GTAP database provides social accounting matrixes for 140 regions, with 57 sectors. See

  22. 22.

    Note, however, that unilaterally applied duties also take non-reciprocal trade preferences into account.

  23. 23.

    The correlation is less straightforward when tariffs are cut as a result of commitments to trading partners, in which case countries may be tempted to use other protection instruments instead, as evidenced by Bown and Crawley (2013) in the case of temporary trade barriers.

  24. 24.

    The model is also documented in an interactive wiki-based website. See


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Bureau and Jean benefited from support by the European Union’s Seventh Framework Programme FP7/2007–2011 under Grant Agreement 290693 Foodsecure. The authors only are responsible for any omissions or deficiencies. Neither the Foodsecure project partner organizations nor any organization of the European Union are accountable for the content of this paper. The authors are indebted to Mondher Mimouni and Xavier Pichot for making tariff protection data available to them, and for helpful discussions. They would like to thank the editor Gerald Willmann and two anonymous referees for their valuable suggestions.

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A1. Results of ANOVA regressions

Importer R-square Coeff. of variation RootMSE Number of RTAs
Japan 1.00 23.89 0.01 5
Switzerland 1.00 31.03 0.02 15
Iceland 1.00 25.40 0.03 15
South Korea 0.99 37.41 0.04 5
Norway 0.99 18.16 0.11 15
European Union 0.99 47.11 0.01 21
Israel 0.98 68.18 0.05 6
Turkey 0.95 79.98 0.06 11
USA 0.95 178.90 0.01 10
Mexico 0.92 186.38 0.05 13
Costa Rica 0.92 189.01 0.02 5
Morocco 0.89 216.66 0.06 6
El Salvador 0.70 245.70 0.03 5
Former Yugoslav Republic 0.67 244.60 0.04 6
Jordan 0.67 232.42 0.08 6
India 0.58 120.59 0.08 6
Tunisia 0.47 215.96 0.06 5
China 0.47 146.82 0.05 6
Guatemala 0.43 212.27 0.03 5
Egypt 0.27 833.36 0.26 5
Albania 0.16 225.69 0.04 5
Chile 0.13 226.06 0.02 12
  1. These statistics refer to Least-Square Dummy Variable (LSDV) regressions carried out separately for each country. The dependent variable is the product-level preferential duty rate applied bilaterally to each partner with which the country has a PTA in force. In each regression, the only independent variables taken into account are product dummies. The R-square of such regression indicates to what extent the product dimension alone explains the structure of preferential tariffs applied by each country. Source: Authors’ calculations. MAcMap-HS6 database

A2. The tariff ladder from 2001 onward for selected countries

See Fig. 9.

Fig. 9

The tariff ladder from 2001 onward for selected countries (AVE, world average)

A3. Additional results on the decomposition of changes in average applied and MFN tariff duty between 2001 and 2013

See Tables 6 and 7.

Table 6 Decomposition of changes in average MFN tariff duty between 2001 and 2013, for selected countries (AVE in %, variation in p.p.)
Table 7 Decomposition of changes in average applied tariff duty between 2001 and 2013, for selected countries (AVE in  %, variation in p.p.)

A4. Sectoral and geographical aggregation

See Tables 8 and 9.

Table 8 Sectoral decomposition used in the analysis
Table 9 Region aggregates used in counterfactual simulations

A5. The model

As a complement to the short description given in the main text, the main elements of the model’s structure are sketched below. The model used here is the perfect competition version of the Mirage model, as documented in Fontagné et al. (2013).Footnote 24

Supply side

On the supply side, each sector in Mirage is modeled as a representative firm, which combines value-added and intermediate consumption in fixed shares. Value-added is a CES bundle of imperfectly substitutable primary factors (capital, skilled and unskilled labor, land and natural resources). Firms’ demand for production factors is organized as a CES aggregation of land, natural resources, unskilled labor, and a bundle of the remaining factors. This bundle is a nested CES aggregate of skilled labor and capital (which are considered as relatively more complementary).

Mirage assumes full employment of primary factors, of which the growth rates are set exogenously, based on the macro projections on a yearly step, as detailed below. Population, participation in the labor market and human capital evolve in each country (or region of the world economy) according to the demographics embedded in the macro projections. This determines the labor force as well as its skill composition (skilled/unskilled). Skilled and unskilled labor is perfectly mobile across sectors, but immobile between countries. Natural resources are sector-specific, while land is mobile between agricultural sectors. Natural resources for the mining sector and land for agricultural sectors are set at their 2011 levels: prices adjust demand to this fixed supply. In the baseline, natural resources for fossil-fuel production sectors adjust to match the exogenous price target that is imposed (IEA 2015) for coal, oil and gas, and according to the energy demand projected by the model. By contrast, in the simulations, changes in demand for fossil energy sources influence their price, while natural resources are fixed at their baseline level.

Installed capital is assumed to be immobile (sector-specific), while investments are allocated across sectors according to their rates of return. The overall stock of capital evolves by combining capital formation and a constant depreciation rate of capital of 6% that is the same as in the long-term growth models. Gross investment is determined by the combination of saving (the saving rate from the growth model, applied to the national income) and the current account. Finally, while total investment is savings-driven, its allocation is determined by the rate of return on investment in the various activities. For simplicity, and because we lack reliable data on foreign direct investment at country of origin, host and sectoral levels, international capital flows only appear through the current account imbalances, and are not explicitly modeled.

Demand side

On the demand side, a representative consumer from each country/region maximizes instantaneous utility under a budget constraint and saves a part of its income, determined by saving rates projected in our first-step exercise. Expenditure is allocated to commodities and services according to a LES–CES (Linear Expenditure System–Constant Elasticity of Substitution) function. This implies that, above a minimum consumption of goods produced by each sector, consumption choices among goods produced by different sectors are made according to a CES function. This representation of preferences is well suited to our purpose as it is flexible enough to deal with countries at different levels of development.

Within each sector, goods are differentiated by their origin. A nested CES function allows for a particular status for domestic products according to the usual Armington hypothesis (Armington 1969): consumers’ and firms’ choices are biased towards domestic production, and therefore domestic and foreign goods are imperfectly substitutable, using a CES specification. We use Armington elasticities provided by the GTAP database (Global Trade Analysis Project) and estimated by Hertel et al. (2007). Total demand is built from final consumption, intermediate consumption and investment in capital goods.


Efficiency in the use of primary factors and intermediate inputs is based on the combination of four mechanisms. First, agricultural productivity is projected separately, as detailed in Fontagné et al. (2013). Second, energy efficiency computed from the aggregate growth models is imposed on Mirage. Third, a 2 p.p growth difference between TFP in manufactures and services is assumed (as in Van der Mensbrugghe 2005). Fourth, given the agricultural productivity and the relation between productivity in manufacturing and services, Mirage recovers endogenously country-specific TFP from the exogenous GDP and production factors. Notice that TFP thus recovered from the baseline projections is subsequently set as exogenous in the alternative scenarios. Therefore, GDP becomes endogenous in such scenarios.

Dynamics in Mirage is implemented in a sequentially recursive way. That is, the equilibrium can be solved successively for each period, given the exogenous variations of GDP, savings, current accounts, active population and skill level coming from the growth models, as described above. Simulations extend up to 2025. Finally, Mirage is calibrated on the GTAP dataset version 9PR1, with 2011 as a base year.

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Bureau, JC., Guimbard, H. & Jean, S. Competing liberalizations: tariffs and trade in the twenty-first century. Rev World Econ 155, 707–753 (2019).

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  • Regional trade agreements
  • Unilateral liberalization
  • Doha development agenda
  • WTO
  • Global value chains

JEL Classification

  • F10
  • F13
  • F14