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Enhanced Gravity Model of trade: reconciling macroeconomic and network models

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  • Assaf Almog
  • Rhys Bird
  • Diego Garlaschelli

Abstract

The structure of the International Trade Network (ITN), whose nodes and links represent world countries and their trade relations respectively, affects key economic processes worldwide, including globalization, economic integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The traditional Gravity Model (GM) successfully reproduces the volume of trade between connected countries, using macroeconomic properties such as GDP, geographic distance, and possibly other factors. However, it predicts a network with complete or homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the ITN. On the other hand, recent maximum-entropy network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Here we integrate these two currently incompatible approaches via the introduction of an Enhanced Gravity Model (EGM) of trade. The EGM is the simplest model combining the GM with the network approach within a maximum-entropy framework. Via a unified and principled mechanism that is transparent enough to be generalized to any economic network, the EGM provides a new econometric framework wherein trade probabilities and trade volumes can be separately controlled by any combination of dyadic and country-specific macroeconomic variables. The model successfully reproduces both the global topology and the local link weights of the ITN, parsimoniously reconciling the conflicting approaches. It also indicates that the probability that any two countries trade a certain volume should follow a geometric or exponential distribution with an additional point mass at zero volume.

Suggested Citation

  • Assaf Almog & Rhys Bird & Diego Garlaschelli, 2015. "Enhanced Gravity Model of trade: reconciling macroeconomic and network models," Papers 1506.00348, arXiv.org, revised Feb 2019.
  • Handle: RePEc:arx:papers:1506.00348
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    References listed on IDEAS

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    1. Giorgio Fagiolo & Javier Reyes & Stefano Schiavo, 2010. "The evolution of the world trade web: a weighted-network analysis," Journal of Evolutionary Economics, Springer, vol. 20(4), pages 479-514, August.
    2. Fagiolo, Giorgio & Reyes, Javier & Schiavo, Stefano, 2008. "On the topological properties of the world trade web: A weighted network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3868-3873.
    3. D. Garlaschelli & T. Di Matteo & T. Aste & G. Caldarelli & M. I. Loffredo, 2007. "Interplay between topology and dynamics in the World Trade Web," Papers physics/0701030, arXiv.org.
    4. Stefano Schiavo & Javier Reyes & Giorgio Fagiolo, 2010. "International trade and financial integration: a weighted network analysis," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 389-399.
    5. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. I. A binary network analysis," Papers 1103.1243, arXiv.org, revised Nov 2011.
    6. Giorgio Fagiolo, 2006. "Directed or Undirected? A New Index to Check for Directionality of Relations in Socio-Economic Networks," Economics Bulletin, AccessEcon, vol. 3(34), pages 1-12.
    7. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2013. "Null models of economic networks: the case of the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 75-107, April.
    8. repec:hal:spmain:info:hdl:2441/9771 is not listed on IDEAS
    9. Rossana Mastrandrea & Squartini Tiziano & Giorgio Fagiolo & Diego Garlaschelli, 2014. "Reconstructing the world trade multiplex: the role of intensive and extensive biases," Post-Print hal-01113938, HAL.
    10. Tiziano Squartini & Diego Garlaschelli, 2011. "Exact maximum-likelihood method to detect patterns in real networks," LEM Papers Series 2011/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. II. A weighted network analysis," Papers 1103.1249, arXiv.org, revised Nov 2011.
    12. Raja Kali & Javier Reyes, 2010. "Financial Contagion On The International Trade Network," Economic Inquiry, Western Economic Association International, vol. 48(4), pages 1072-1101, October.
    13. V. Zlatic & G. Bianconi & A. Díaz-Guilera & D. Garlaschelli & F. Rao & G. Caldarelli, 2009. "On the rich-club effect in dense and weighted networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 271-275, February.
    14. repec:lmu:muenar:20646 is not listed on IDEAS
    15. Gabriel J Felbermayr & Wilhelm Kohler, 2014. "Exploring the Intensive and Extensive Margins of World Trade," World Scientific Book Chapters, in: European Economic Integration, WTO Membership, Immigration and Offshoring, chapter 4, pages 115-148, World Scientific Publishing Co. Pte. Ltd..
    16. Giorgio Fagiolo, 2010. "The international-trade network: gravity equations and topological properties," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(1), pages 1-25, June.
    17. Luca De Benedictis & Lucia Tajoli, 2011. "The World Trade Network," The World Economy, Wiley Blackwell, vol. 34(8), pages 1417-1454, August.
    18. D. Garlaschelli & T. Di Matteo & T. Aste & G. Caldarelli & M. I. Loffredo, 2007. "Interplay between topology and dynamics in the World Trade Web," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 159-164, May.
    19. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    20. M. Serrano & Marián Boguñá & Alessandro Vespignani, 2007. "Patterns of dominant flows in the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 111-124, December.
    21. Francesco Picciolo & Tiziano Squartini & Franco Ruzzenenti & Riccardo Basosi & Diego Garlaschelli, 2012. "The role of distances in the World Trade Web," Papers 1210.3269, arXiv.org, revised Oct 2012.
    22. M. Angeles Serrano & Marian Boguna & Alessandro Vespignani, 2007. "Patterns of dominant flows in the world trade web," Papers 0704.1225, arXiv.org.
    23. Raja Kali & Javier Reyes, 2007. "The architecture of globalization: a network approach to international economic integration," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 38(4), pages 595-620, July.
    24. Garlaschelli, Diego & Loffredo, Maria I., 2005. "Structure and evolution of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 138-144.
    25. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
    26. D. Garlaschelli & M. I. Loffredo, 2005. "Structure and Evolution of the World Trade Network," Papers physics/0502066, arXiv.org, revised May 2005.
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    5. Jošić Hrvoje & Žmuk Berislav, 2022. "A Machine Learning Approach to Forecast International Trade: The Case of Croatia," Business Systems Research, Sciendo, vol. 13(3), pages 144-160, October.
    6. Berislav ZMUK, 2021. "Investigating the impact of GDP and distance variables in the gravity model using sign and rank tests," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 12, pages 5-30, June.
    7. Michael Lebacher & Paul W. Thurner & Göran Kauermann, 2021. "Censored regression for modelling small arms trade volumes and its ‘Forensic’ use for exploring unreported trades," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 909-933, August.
    8. Tamaş Anca, 2020. "Why should the gravity model be taught in business education?," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 14(1), pages 422-433, July.

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