Abstract
We construct a new, global tariff dataset and apply it to a multi-sector quantitative trade model with heterogeneous firms, including nearly all countries of the world. The impact of the Uruguay Round tariff reductions over 1990–2010 is analyzed, as well as the further cuts in Preferential tariffs and the impact of moving to complete free trade. We find that the Uruguay Round tariff cuts led to large welfare gains (2%–3% relative to 1990 for the world, higher in Emerging and Developing countries), but that Preferential tariff cuts led to only small further gains (0%–1%). Surprisingly, the hypothetical movement to free trade leads to the greatest gains (5% relative to 1990, almost 10% in Emerging and Developing countries), which implies that there is strong scope for gains from future multilateral tariff reductions, especially for Emerging and Developing economies. These gains are large relative to prior estimates in the literature and we attribute about nearly one-half of our measured gains to selection effects in our heterogeneous-firm model, which are influenced by the scale of production and by two-tier Armington aggregation.
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Notes
See the description of the ITA in Feenstra et al. (2013).
See note 33 for countries omitted from the quantitative analysis.
We unify tariff schedules from four different sources. With more than 1 million observations per year in the 1980s, rising to 2 million by the 2000s, with our tariff data we can perform tariff policy experiments which could not be explored before now.
For simplicity, we refer to this entire set of MFN tariff cuts as the “Uruguay Round,” though it includes tariff liberalization that occurred prior to 1994 during the negotiations of that round, and also the ITA, for example, which occurred during and after the implementation of that round.
The former authors model a single aggregate heterogeneous-firm sector with additional competitive sectors based on the Global Trade Analysis Project (GTAP) (Dimaranan 2006), with the country data aggregated into 12 regions. CR use the World Input–Output Database (WIOD) (Timmer 2012; Timmer et al. 2015), which has 27 EU countries and 13 other major countries. While these cover a large part of world output and trade, many smaller countries of the world are omitted.
Entry effects in the CR model are examined by Felbermayr et al. (2015), who make the distinction between applying tariffs to the variable production cost of imports versus applying them to the revenue-cost of imports, inclusive of markups. In Appendix A we find that there are some notable theoretical differences in these two cases: in particular, regarding whether changes in tariffs affect entry in a one-sector model. We believe that modeling tariffs as applying to the revenue-cost of imports is the realistic choice that matches customs practices, and is also a theoretically parsimonious benchmark case, so we will focus only on that case here.
See Costinot and Rodríguez-Clare (2014), Table 4.3, p. 232.
They find (p. 95) that “Taking the simple-average welfare change across regions the Melitz structure indicates welfare gains from liberalization that are four times larger than in a standard trade policy simulation [with perfect competition].”
Spearot (2016) relies on a quadratic utility function, but because he does not assume an outside good, he argues that the results are similar to using a CES utility function.
This result is obtained in a one sector Melitz–Chaney model with fixed factor supply, provided that tariff revenue is redistributed to consumers (see Appendix A).
These simple averages are obtained from the columns in Spearot (2016, Table 6, p. 158).
The average loss of those six countries is \(2.9\%\), while the average gains of the other 173 countries is \(9.1\%\).
A second reason for larger welfare gains from tariff removal in our paper as compared to CR is that we introduce two-tier Armington aggregation, i.e., a lower elasticity of substitution between home and foreign varieties than between varieties within a country (see Feenstra et al. 2018). Specifically, we use the “Rule of Two” for the ratio of these two elasticities (see Hillberry and Hummels 2013), as explained in Sect. 4.
Theoretical contributions here include, among others, Haaland and Venables (2016), Beshkar and Ahmad (2020), Costinot et al. (2020), Lashkaripour and Lugovsky (2020), Lashkaripour (2021). Recently, Balistreri and Tarr (2022) analyze a quantitative model with input–output linkages under the Armington, Krugman, and Melitz market structures, for both global tariff cuts and optimal tariffs (which they find are low under monopolistic competition).
This nested structure is also used by Feenstra et al. (2018). We use this nested structure here because Kucheryavyy et al. (2016) have shown the potential for corner solutions in multi-sector monopolistic competition models. That potential is offset by adding the extra upper-level curvature in the nested CES structure.
See Appendix A for a discussion of this alternative way of modeling “cost-based” tariffs, and a comparison to the “revenue-based” tariff that we adopt here in the main text.
In contrast, if tariffs are applied only to the costs of imported products, then they would have exactly the same effect on the zero-cutoff-profit condition as do iceberg trade costs \(\tau _{ij,s}\), and would appear only as multiplying those trade costs above [i.e., as in the final terms in (9)]. Under our maintained assumption that tariffs are applied to the sales revenue, they have the “extra” impact of effectively reduced fixed costs, too.
See Appendix B.4.
See note 11 and Appendix A.
We stress that the source of these generic gains are quite different in the Krugman and Melitz models, however. In the Krugman model, our discussion above has emphasized the gains from domestic and imported product variety. But in the Melitz model, the “generic gains” are due at least in part to the selection of firms, as emphasized by Melitz and Redding (2015). Of course, “generic gains” of this form can also arise in the Armington and other competitive models, as emphasized by ACR, but in those cases there is no entry, so the entry-adjustment part of the formula does not arise.
di Giovanni and Levchenko (2013) consider the case where \(\theta _{s} \rightarrow \sigma _{s}-1\) so the selection effect nearly vanishes. In that case, they argue that the gains from trade depend on the intensive margin of very large firms.
See (37) and (38) in the Appendix.
The potential benefits from expanding entry into industries with forward production linkages is an old idea in trade and development (Hirschman 1958), and is found in modern macroeconomics, too (Jones 2011). The decomposition in (27) shows how this idea arises from our multi-sector Melitz–Chaney model with input–output linkages.
To see this, recall our discussion of the Krugman model just after (20). There, the effective domestic price is \(N_{i,s}^{-1/(\sigma _s - 1)}\). With two-tier Armington aggregation, the “new” import varieties reduce the overall price index in sector s according to the domestic share of expenditure \(\lambda _{ii,s}\) raised to \(1/(\omega _s - 1)\), so the overall price is \(\lambda _{ii,s}^{1/(\omega _s - 1)}/N_{i,s}^{1/(\sigma _s - 1)}\). Expressed in log changes we obtain \(\frac{1}{(\omega _s - 1)}\ln {\hat{\lambda }} _{ii,s} - \frac{1}{(\sigma _s - 1)}{\hat{N}}_{i,s}\). That is identical to the term in braces for sector s on the second line of (30), once we replace \(\theta _s\) with \(\sigma _s - 1\) and simplify using \(\frac{1}{(\sigma _s - 1)}+\frac{(\sigma _s - \omega _s)}{(\sigma _s - 1)(\omega _s - 1)} = \frac{1}{(\omega _s - 1)}\).
As explained in note 22, the “generic gains” from trade in the Melitz model arise at least in part from selection effects. We are therefore taking a conservative approach to measuring the contribution of selection to our quantitative results, by only counting the terms appearing in the final three rows of (30).
Most tariff schedules can be fairly readily matched to the SITC classification.
Multiple preferential tariffs may be applicable for trade in a particular product between two countries. Since the most favorable one may change over time, we keep track of each potentially applicable tariff program.
Readers may wonder why the number of tariff line observations grows in the tariff database, since the number of product categories is fixed and the number of countries only grows slightly. The key reason is that we are only summarizing tariff observations where there is a matching trade observation, and the number of country-pair observations with positive trade grows substantially. Because we are ignoring zero-trade observations that might have high tariffs, this approach may lead us to understate the decline in MFN tariffs.
Tariffs are aggregated using trade weights as discussed in Appendix E.
Please refer to http://worldmrio.com/ for more information.
Countries omitted from our quantitative analysis because their input–output tables in Eora were judged to be unreliable are: Azerbaijan (AZE), Belarus (BLR), Guyana (GUY), Moldova (MDA), Sudan (SDN), South Sudan (SSD), and Tajikistan (TJK), while Netherlands Antilles (ANT), and Former USSR (USR) overlap with other included countries. Two other countries omitted because of missing trade data in 1990 were Liechtenstein (LIE) and the Palestine Occupied Territory (PSE).
Several parameters from our model are directly observable, like value added shares and input–output coefficients. However, there are a large number of parameters, like fixed entry, production, and exports costs, that are not observed.
This idea was first advanced by Dekle et al. (2008) in the context of a Ricardian trade model. Caliendo and Parro (2015) and Ossa (2014) show that one can use this method to analyze the effects of tariff policy. CR show how it works for a variety of trade models, including a multi-county, multi-industry Melitz model similar to the one we use here. We apply it with a nested CES structure with Armington and for the case of revenue-based tariffs.
This estimate comes from their working paper, Gervais and Jensen (2013).
This calculation is available on request.
Specifically, we set the 2010 tariff equal to minimum of the 1990 preferential tariff and the 2010 MFN tariff.
These data are from the WTO’s Regional Trade Agreements Database.
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We thank Federico Esposito, Anna Ignatenko, and Mingzhi Xu for excellent research assistance. For their helpful comments we thank Andres Rodríguez-Clare, Kyle Bagwell, Fernando Parro, Stephen Redding, Esteban Rossi-Hansberg, Ina Simonovska, many seminar participants, the editor, and two anonymous referees. Romalis acknowledges support from the Australian Research Council. The usual disclaimer applies.
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Caliendo, L., Feenstra, R.C., Romalis, J. et al. Tariff Reductions, Heterogeneous Firms, and Welfare: Theory and Evidence for 1990–2010. IMF Econ Rev 71, 817–851 (2023). https://doi.org/10.1057/s41308-022-00194-4
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DOI: https://doi.org/10.1057/s41308-022-00194-4
Keywords
- Trade policy
- Monopolistic competition
- Gains from trade
- Input–output linkages
- Multilateralism
- Bilateralism