Abstract
This paper investigates the effects of preferential trade agreements (PTAs) on bilateral trade using a comprehensive data base of PTAs in force and a detailed matrix of world trade. Total trade between PTA partners is a poor proxy for preferential trade (trade in tariff lines where preferences are likely to matter): while the former was one-third of global trade in 2000–2002, the latter was between one-sixth and one-tenth. Gravity model estimates indicate that using total trade to assess the impacts of PTAs leads to a significant downward bias in the PTA coefficient: the semi-elasticity of trade with respect to PTA membership rises from 87% for total trade to 119% for preferential trade. Product exclusions and long phase-in periods significantly limit preferential trade; the marginal impact of South-South agreements on preferential trade is much higher than North-South PTAs, while the effect of North-North agreements is insignificantly different from zero.
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Notes
This paper will not take up the estimation of general equilibrium feedback effects, as raised in Anderson and van Wincoop (2003).
This estimate counts the 25-member EU as a single agreement. The main reason for this approach is that the EU negotiates all of its PTAs with outside countries as a single body, with new members becoming automatic signatories to earlier agreements. Since I am interested in the number of PTAs in force rather than their historical evolution, other methods of dealing with the EU, such as regarding each round of accession as a new agreement, would lead to double-counting.
For example, Russia (the largest country in the world that is not a WTO member) participates in two regional PTAs and is actively negotiating several others.
For example, the WTO data base does not include the Southern African Development Community (SADC) and Southern African Customs Union (SACU) agreements in Africa, even though a WTO member (South Africa) is party to both. Similarly, the India-Nepal and India-Bhutan bilateral agreements in South Asia remain unreported despite India’s membership in the WTO. Additional details on the unreported agreements, including the data sources used in their identification, will be provided later in this section.
As before, this estimate counts the EU-25 as a single agreement. If EU-15 is treated as a single agreement instead (implying that all PTAs between the EU and the new accession countries, as well as between the accession countries themselves, are included in the estimate), the number of unnotified agreements remains the same, but the number of notified PTAs rises to 155.
Therefore, trade that takes place under unilateral preference schemes such as General System of Preferences (GSP), USA’s African Growth and Opportunity Act (AGOA) or EU’s Everything but Arms (EBA) will not be considered preferential. There are several reasons for this choice of definition. First, unilateral preferences lie outside the WTO definition of PTAs because preferences are not mutual. Second, these schemes are of limited duration and require periodic renewal, which is not guaranteed. Third, because preferences granted under these scheme are essentially one-sided “concessions,” they tend to exclude important export products, leading to concentration of production in low value-added activities and slow development (see Panagariya 2002; Lamy 2002).
UN definitions of “partner” and “reporter” correspond in this case to importer and exporter, respectively.
This is equivalent to estimating the shares as import-weighted averages, therefore allowing countries with large trade volumes to dominate the results.
Currently, China, India, and Japan are all involved in PTA negotiations with ASEAN. If these countries join the ASEAN FTA, the importance of preferential trade for the region and the world as a whole may increase as a result.
I use the word “potential” here because the analysis does not take into account product exclusions. With exclusions, the share would be even lower.
Rose (2004b) notes that under symmetry, a single set of fixed effects may serve the estimation purposes equally well. An alternative strategy, employed in Rose (2004a), relies on pair-wise fixed effects, which, in addition to the unobserved price indices, control for any other characteristic specific to a given pair of countries.
Note also that σ > 1 by assumption.
Both the regional and income dummies are defined in accordance with World Bank classifications. North is high-income OECD.
This is calculated as \(\left(e^{\beta_{\rm PTA}} - 1\right).\)
Consider the Consider the Frankel (1997) approach of using two PTA dummies: one for intra-bloc trade, and one for the bloc members’ trade with third countries. Suppose I am interested in the effects of NAFTA on US imports. Under this framework, the first dummy will equal one when the US trades with Canada and Mexico, and zero otherwise. The second dummy will equal one when the US trades with countries other than its NAFTA partners. Now, allow the US to participate in the US-Chile FTA and construct the same set of dummy variables for this agreement. I now find that the NAFTA extra-bloc dummy and the US-Chile intra-bloc dummy are perfectly collinear for Chile’s exports to the US. A similar argument can be applied to the three dummy variable approach of Soloaga and Winters (2001), where identification of intra- and extra-bloc effects becomes even more difficult.
For a linear regression with a conventionally estimated variance-covariance matrix, the Chow test is equivalent to the Wald test.
The same holds true even if I control for differences in sample size by re-estimating the total imports model only for countries with a positive trade value in tariff lines above 3% MFN.
The actual number of GSP beneficiaries is higher because several countries classified as high income by the UN and the World Bank, such as Bahrain or the United Arab Emirates, are also eligible for the EU GSP scheme.
These include the Andean Pact, EFTA, the EU, LAIA, MERCOSUR, NAFTA, SPARTECA, Australia-New Zealand, EU-Switzerland, Chile-Colombia, Chile-Mexico, US-Israel, Australia-Papua New Guinea, Singapore-New Zealand, Chile-MERCOSUR, EU-Egypt, EU-Poland, and AFTA. Since the EU is treated as a single country in the model, I do not use the EU score.
In other words, the gravity model will estimate a larger coefficient for a larger percentage change in the dependent variable, even if that change is from a very low base and therefore small in absolute terms.
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Acknowledgments
The author is deeply grateful to Robert Blecker, Paul Brenton, Jeff Lewis, Kara Reynolds, Hans Timmer, the editor, and an anonymous referee for valuable comments and suggestions. All remaining errors are his own.
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Medvedev, D. Preferential trade agreements and their role in world trade. Rev World Econ 146, 199–222 (2010). https://doi.org/10.1007/s10290-010-0054-x
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DOI: https://doi.org/10.1007/s10290-010-0054-x