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On the Optimal Size and Composition of Customs Unions: An Evolutionary Approach

Author

Listed:
  • Takfarinas Saber

    (National University of Ireland Galway)

  • Dominik Naeher

    (University of Goettingen)

  • Philippe Lombaerde

    (Neoma Business School
    United Nations University Institute on Comparative Regional Integration Studies (UNU-CRIS))

Abstract

Customs unions enable countries to freely access each other’s markets, which is thought to increase intra-regional trade and economic growth. However, accession to a customs union also comes with the condition that all members need to consent to a common external trade policy. Especially if countries feature different economic structures, this may act as a force against the creation of large customs unions. In this paper, we propose a new mathematical approach to model the optimal size and composition of customs unions in the form of a bi-objective combinatorial non-linear problem. We also use a multi-objective evolutionary algorithm (NSGA-II) to search for the best (non-dominated) configurations using data on the trade flows and economic characteristics of 200 countries. Our algorithm identifies 445 different configurations that are strictly preferable, from a global perspective, to the real-world landscape of customs unions. However, many of these non-dominated configurations have the feature that they improve outcomes for the world as a whole, on average, but not for all individual countries. The best configurations tend to favour the creation of a few large customs unions and several smaller ones.

Suggested Citation

  • Takfarinas Saber & Dominik Naeher & Philippe Lombaerde, 2023. "On the Optimal Size and Composition of Customs Unions: An Evolutionary Approach," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1457-1479, December.
    • Handle: RePEc:kap:compec:v:62:y:2023:i:4:d:10.1007_s10614-022-10307-w
    DOI: 10.1007/s10614-022-10307-w
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    References listed on IDEAS

    as
    1. De Lombaerde, Philippe & Naeher, Dominik & Saber, Takfarinas, 2021. "Regional Integration Clusters and Optimum Customs Unions: A Machine-Learning Approach," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 36(2), pages 262-281.
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    More about this item

    Keywords

    Regional integration; Customs unions; Multi-objective optimisation; Evolutionary algorithm;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • F13 - International Economics - - Trade - - - Trade Policy; International Trade Organizations
    • F15 - International Economics - - Trade - - - Economic Integration
    • F60 - International Economics - - Economic Impacts of Globalization - - - General

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