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The double role of GDP in shaping the structure of the International Trade Network

Author

Listed:
  • Assaf Almog
  • Tiziano Squartini
  • Diego Garlaschelli

Abstract

The International Trade Network (ITN) is the network formed by trade relationships between world countries. The complex structure of the ITN impacts important economic processes such as globalisation, competitiveness, and the propagation of instabilities. Modelling the structure of the ITN in terms of simple macroeconomic quantities is therefore of paramount importance. While traditional macroeconomics has mainly used the gravity model to characterise the magnitude of trade volumes, modern network theory has predominantly focused on modelling the topology of the ITN. Combining these two complementary approaches is still an open problem. Here we review these approaches and emphasise the double role played by gross domestic product (GDP) in empirically determining both the existence and the volume of trade linkages. Moreover, we discuss a unified model that exploits these patterns and uses only the GDP as the relevant macroeconomic factor for reproducing both the topology and the link weights of the ITN.

Suggested Citation

  • Assaf Almog & Tiziano Squartini & Diego Garlaschelli, 2017. "The double role of GDP in shaping the structure of the International Trade Network," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(4), pages 381-398.
    • Handle: RePEc:ids:ijcome:v:7:y:2017:i:4:p:381-398
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    Citations

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    Cited by:

    1. Lucio Biggiero & Roberto Urbani, 2022. "Testing the convergence hypothesis: a longitudinal and cross-sectional analysis of the world trade web through social network and statistical analyses," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(3), pages 713-777, July.
    2. Abdullah Bin Zafar, 2024. "Impact of Selected Factors on International Trade of Bangladesh: An Empirical Analysis," International Journal of Science and Business, IJSAB International, vol. 35(1), pages 30-47.
    3. Di Vece, Marzio & Garlaschelli, Diego & Squartini, Tiziano, 2023. "Reconciling econometrics with continuous maximum-entropy network models," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    4. Felipe Chávez-Bustamante & Elliott Mardones-Arias & Julio Rojas-Mora & Jaime Tijmes-Ihl, 2023. "A Forgotten Effects Approach to the Analysis of Complex Economic Systems: Identifying Indirect Effects on Trade Networks," Mathematics, MDPI, vol. 11(3), pages 1-20, January.

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