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Explaining Trade Flows: Traditional and New Determinants of Trade Patterns

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  • Julien Gourdon

    (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

Abstract

An empirical tradition in international trade seeks to establish whether the predictions of factor abundance theory match with the data. The relation between factor endowments and trade in goods (commodity version of Hecksher-Ohlin) provide mildly encouraging empirical results. But in the analysis of factor service trade and factor endowments (factor content version of HO), the results show that it performs poorly and reject strict HOV models in favor of modifications that allow for technology differences, consumer's preferences differences, increasing returns to scale or cost of trade. In this paper we test if these "new" determinants help us to improve our estimation of trade patterns in commodities. Since the commodity version allows obtaining a large panel data we also compare two periods, pre and post 1980. We use a Heckman procedure to allow for non linearity in the relation between factors endowments and net exports and between trade intensity and net exports. The results show that adding the "new" determinants of factor content studies help us to improve the prediction of being specialized in the different manufactured products. However specialization according to factor endowments is stronger than ever, especially concerning the specialization according to human capital endowment. Trade patterns are also determined by trade intensity. Here differences in technology, trade policy, transport and transaction costs, explain the difference in trade intensity.

Suggested Citation

  • Julien Gourdon, 2011. "Explaining Trade Flows: Traditional and New Determinants of Trade Patterns," CERDI Working papers halshs-00557125, HAL.
  • Handle: RePEc:hal:cdiwps:halshs-00557125
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00557125
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    Cited by:

    1. Mohd Alsaleh & Abdul Samad Abdul-Rahim, 2018. "The Economic Determinants of Bioenergy Trade Intensity in the EU-28: A Co-Integration Approach," Sustainability, MDPI, vol. 10(2), pages 1-20, February.
    2. Regolo, Julie, 2013. "Export diversification: How much does the choice of the trading partner matter?," Journal of International Economics, Elsevier, vol. 91(2), pages 329-342.
    3. Sadok ACHOUR & Dr. Fatima HADJI, 2021. "Determinants of trade flows to Agadir Agreement countries: gravity model three-way approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(627), S), pages 125-134, Summer.
    4. Hanousek, Jan & Kočenda, Evžen, 2014. "Factors of trade in Europe," Economic Systems, Elsevier, vol. 38(4), pages 518-535.
    5. Amadeo Navarro Zapata & María Arrazola & José Hevia, 2024. "Determinants of High-tech Exports: New Evidence from OECD Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1103-1117, March.
    6. Ndubuisi, Gideon & Avenyo, Elvis, 2018. "Estimating the effects of robotization on exports," MERIT Working Papers 2018-046, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

    More about this item

    Keywords

    international trade; Hecksher-Ohlin Model;

    JEL classification:

    • F2 - International Economics - - International Factor Movements and International Business
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • F11 - International Economics - - Trade - - - Neoclassical Models of Trade

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