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Market structure and the link between migration and trade

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Abstract

Many recent studies have looked at the impact of international migration on trade and found a significant effect. They posit that migration fosters trade by lowering costs or by means of a preference bias. However, to my knowledge, market structure has not as yet been considered. Using data from Switzerland, this paper empirically assesses the extent to which migration affects trade, taking goods differentiation into account. A monopolistic model with a multisector economy (Chaney in Am Econ Rev 98(41):1707–1721, 2008) is then empirically estimated. The findings show that market structure explains the different channels through which migration affects trade.

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Notes

  1. See Rauch (2001) for a survey of these mechanisms.

  2. Source: United Nations Demographic and Social Statistics http://unstats.un.org/unsd/demographic/products/dyb/DYB2002/Table03.pdf.

  3. http://ec.europa.eu/youreurope/nav/fr/citizens/working/free-circulation/index.html.

  4. See Melo et al. (2002), Sect. 3 for an overview of Switzerland’s immigration policy.

  5. In keeping with the 2006 World Bank classification in which 53 countries are ranked as low-income economies (GNI per capita of $905 or less), 96 countries as middle-income economies (GNI per capita of $906 to $11,115) and 60 countries as high-income economies (GNI per capita of $11,116 or more). Source: http://web.worldbank.org.

  6. Head and Ries (1998) present the most significant difference of the effect of migration on exports and imports (they are statistically different at the 95% level).

  7. See Sect. 2 for a justification.

  8. The colony variable does not apply to Switzerland.

  9. For the sake of clarity, sector h indices are omitted henceforth.

  10. For more details, see Anderson and van Wincoop (2003), Feenstra (2004), and Santos Silva and Tenreyro (2006).

  11. Source: INSEE, National Institute for Statistics and Economic Studies, France.

  12. A total of 10.1% of imports and 18% of exports were deleted from the sector-based analysis for other reasons. Some NBER trade data sectors do not match with the elasticities data: 3.8% of imports and 11.7% of exports. In the case of exports, one code (900) alone accounts for 7.8% of this 11.7%. The authors of the trade database assume that the breakdown of Sect. 9 is essentially meaningless and reflects the reporting country’s unwillingness to provide the product detail and, in some cases, partner detail as well. Therefore, these data are not included in the estimations.

  13. http://www.cepii.fr/anglaisgraph/bdd/distances.htm.

  14. These databases are: Swiss people abroad, foreigners in France and French people abroad.

  15. These outliers can considerably disrupt the findings. Since the estimates are made based on σ’s interaction, the “leverage” of these points on σ is high. Moreover, the spread is too diffuse: there are four points (counting by integer σ) in the interval from σ = 9 to σ = 33. No regression could be representative in this case.

  16. A test to the power of 3 (not reported) failed this same test.

  17. Relative behaviour between complementary elasticities does not change for any value of β.

  18. Still considering the reference regression (3) in Table 4.

  19. 3.87 is the point maximizing the impact of migration on trade, determined by Eq. 21. It is where \( \tfrac{{\partial \tau_{a} }}{\partial \sigma }\alpha_{m} = \tfrac{{\partial \alpha_{m} }}{\partial \sigma }\tau_{a} \) and \( \tfrac{{\partial \tau_{f} }}{\partial \sigma }\varphi_{m} = \tfrac{{\partial \varphi_{m} }}{\partial \sigma }\tau_{f} \).

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Acknowledgments

Thanks are extended to Elisabeth Aebischer (Swiss Federal Statistics Office), Karin Schär (Swiss Federal Department of Foreign Affairs) and Bernard Gentil (French Ministry of Foreign and European Affairs) for kindly supplying data; professors Robert C. Feenstra and Robert E. Lipsey for their explanations regarding the trade data; professors Thierry Verdier, Lionel Fontagné and Thierry Mayer for their guidance; and Vincent Rebeyrol, Fabian Gouret, Julien Vauday, Lysu Paez, Rémi Bazillier, Gautier Duflos, José de Sousa and Vincent Vicard for their help and suggestions. The author is grateful to CIREM/CEPII for their financial support.

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  1. Paris School of Economics, Université Paris 1 Panthéon, Sorbonne, 106-112 Blvd de l’Hopital, 75647, Paris, France

    Silvio H. T. Tai

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Correspondence to Silvio H. T. Tai.

Appendix

Appendix

Table 5 Instrumental variable for immigrants in Switzerland
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Tai, S.H.T. Market structure and the link between migration and trade. Rev World Econ 145, 225–249 (2009). https://doi.org/10.1007/s10290-009-0012-7

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