Abstract
The aim of this work is to employ theoretical and empirical analysis on the role of special interest groups in the determination of the EU trade policy. We build a two-stage game model of trade policy formation in a multisector-multicountry framework. We obtain the level of protection as a function of industry characteristics, in addition to political and economic factors at member state and European levels. The model is then tested by 2SLS estimation using data for 15 countries and 41 sectors. The econometric output suggests empirical support to model’s predictions as it highlights an important role for both national and European groups in trade policy making.
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Acknowledgements
This work is part of the Research Program of National Scientific Relevance (PRIN) on “The new multilateral trade negotiations within the World Trade Organization (Doha Round): liberalisation prospects and the impact of the Italian economy”. Financial support by the Italian Ministry of Universities and Scientific Research is gratefully acknowledged. We would like to thank Carl-Johan Belfrage and Betina V. Dimaranan for useful suggestions. Usual disclaimers apply.
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Appendix:
Appendix:
1.1 A: Mathematical appendix
1.2 A.1 Proof of Eq. 14:
To obtain Eq. 14, we maximize (∀j∈M):
The first order condition is:
Whence:
1.3 A.2 Proof of Eq. 15:
To find Eq. 15 for each member country, we need to find \(\widetilde{t}_{jk}\) such that the following two conditions are met:
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1
\(\widetilde{\mathbf{t}}_{k}=\underset{\widetilde{\mathbf{t}}_{k}}{\arg \max }\left( W_{ik}-C_{ik}\right) ,\)∀i∈L;
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2
\(\widetilde{\mathbf{t}}_{k}=\underset{\widetilde{\mathbf{t}}_{k}}{\arg \max }\left( W_{jk}-C_{jk}\right) +b\sum_{i\in E}C_{ik}+\sum_{i\in S}C_{ik}+aW_{k},\)∀j∈L.
From 1., we get (∀j∈L and k∈K):
and, from 2.:
Summing Eq. 22 over j, and combining with Eq. 23, it follows:
where \(W_{ik}\left( \mathbf{p}\right) \equiv l_{ik}+\pi _{ik}\left( p_{i}\right) +\alpha _{ik}N_{k}\left[ r\left( \mathbf{p}\right) +s\left( \mathbf{p}\right) \right] \). Since \(t_{j}=\left( p_{j}-p_{j}^{\mathbf{\ast } }\right) \) and \(p_{j}^{\mathbf{\ast }}\) is exogenous, we can derive with respect to p j (notice that some mathematical details are skipped for reasons of space). We have:
where we have used the fact that: \(m_{jk}\left( p_{j}\right) -N_{k}d_{jk}\left( p_{j}\right) =-y_{jk}\left( p_{j}\right) ,\) α i =α ik ∀k∈K and \(u^{\prime }\left[ d_{jk}\left( p_{j}\right) \right] =p_{j}.\) Separating national from European lobbies, it follows that:
where δ jS =1 if i∈S and =0 otherwise, whereas η jE =1 if i∈E and =0 otherwise. Then, aggregating Eqs. 28 and 29 over i∈L, the first two terms of the summation in Eq. 24 turn out to be (with j∈M):
where \(I_{i}^{E}\equiv \sum_{i\in E}\eta _{iE}=1\) if i∈E and =0 otherwise, \(I_{ik}^{S}\equiv \sum_{i\in S}\delta _{iS}=1\) if i∈S in country k and =0 otherwise. For simplicity we set α L =α S +bα E , where α S ≡∑i∈S α iS ( α E ≡∑i∈E α iE ) is the fraction of total population of voters represented by an organized national (European) group. We derive now W k with respect to p j and get (with k∈K and j∈M):
Thus, combining Eqs. 30 and 31 in Eq. 24, we have:
that is the tariff platform for country k. From Eq. 21 and substituting \(\widetilde{t}_{jk}\) for Eq. 32, we can finally write:
Dividing both sides of Eq. 33 by p j , defining \(e_{jk}=-m_{jk}^{ \prime }p_{j}/m_{jk}\), and using the fact that:
we obtain Eq. 17.
1.4 B: Appendix to the empirical analysis
1.5 B.1 List of sectors included in the analysis:
1—Paddy rice; 2—Wheat; 3—Cereal grains nec; 4—Vegetables, fruit, nuts; 5—Oil seeds; 6—Sugar cane, sugar beet; 7—Plant-based fibers; 8—Crops nec; 9—Bovine cattle, sheep and goats, horses; 10—Animal products nec; 12—Wool, silk-worm cocoons; 13—Forestry; 14—Fishing; 15—Coal; 16—Oil; 17—Gas; 18—Minerals nec; 19—Bovine cattle, sheep and goat, horse meat prods; 20—Meat products nec; 21—Vegetable oils and fats; 22—Dairy products; 23—Processed rice; 24—Sugar; 25— Food products nec; 26—Beverages and tobacco products; 27—Textiles; 28—Wearing apparel; 29—Leather products; 30—Wood products; 31—Paper products, publishing; 32—Petroleum, coal products; 33—Chemical, rubber, plastic products; 34—Mineral products nec; 35—Ferrous metals; 36—Metals nec; 37—Metal products; 38—Motor vehicles and parts; 39—Transport equipment nec; 40—Electronic equipment; 41—Machinery and equipment nec; 42—Manufactures nec.
Source:http://www.gtap.agecon.purdue.edu/.
Note: All the services are excluded. Furthermore we do not include in the analysis those sectors where market prices comparisons among countries would be misleading. The criterion (suggested by Belfrage 2004) is not to include in the analysis sectors for whom concordance with the international classification system for tradable goods (SITC/HS) is not available. This leads us to exclude the raw milk sector.
1.6 B.2 List of countries and relative political weights:
1—Austria (4); 2—Belgium (5); 3—Denmark (3); 4—Finland (3); 5—France (10); 6—Germany (10); 7—Greece (5); 8—Ireland (3); 9—Italy (10); 10—Luxembourg (2); 11—Netherlands (5); 12—Portugal (5); 13—Spain (8); 14—Sweden (4); and the 15—UK (10).
Source: http://europa.eu.int/
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Belloc, M., Guerrieri, P. Special Interest Groups and Trade Policy in the EU. Open Econ Rev 19, 457–478 (2008). https://doi.org/10.1007/s11079-007-9012-1
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DOI: https://doi.org/10.1007/s11079-007-9012-1