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Community structure in the World Trade Network based on communicability distances
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Community structure in the World Trade Network based on communicability distances

Author

Listed:
  • Paolo Bartesaghi

    (University of Milano - Bicocca)

  • Gian Paolo Clemente

    (Università Cattolica del Sacro Cuore)

  • Rosanna Grassi

    (University of Milano - Bicocca)

Abstract

In this paper, we investigate the mesoscale structure of the World Trade Network. In this framework, a specific role is assumed by short- and long-range interactions, and hence by any suitably defined network-based distance between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network. The proposed methodology aims at finding the distance threshold that maximizes a specific quality function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities. The numerical analysis highlights peculiar relationships between countries and provides a rich set of information that can hardly be achieved within alternative clustering approaches.

Suggested Citation

  • Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2022. "Community structure in the World Trade Network based on communicability distances," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 405-441, April.
  • Handle: RePEc:spr:jeicoo:v:17:y:2022:i:2:d:10.1007_s11403-020-00309-y
    DOI: 10.1007/s11403-020-00309-y
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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. Javier Reyes & Stefano Schiavo & Giorgio Fagiolo, 2008. "Assessing The Evolution Of International Economic Integration Using Random Walk Betweenness Centrality: The Cases Of East Asia And Latin America," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(05), pages 685-702.
    6. Estrada, Ernesto & Hatano, Naomichi, 2010. "A vibrational approach to node centrality and vulnerability in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3648-3660.
    7. Freddy Cepeda-López & Fredy Gamboa-Estrada & Carlos León & Hernán Rincón-Castro, 2019. "The evolution of world trade from 1995 to 2014: A network approach," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 28(4), pages 452-485, May.
    8. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
    9. 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.
    10. Barigozzi, Matteo & Fagiolo, Giorgio & Mangioni, Giuseppe, 2011. "Identifying the community structure of the international-trade multi-network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2051-2066.
    11. Tilak Abeysinghe & Kristin Forbes, 2005. "Trade Linkages and Output‐Multiplier Effects: a Structural VAR Approach with a Focus on Asia," Review of International Economics, Wiley Blackwell, vol. 13(2), pages 356-375, May.
    12. Zhen Zhu & Federica Cerina & Alessandro Chessa & Guido Caldarelli & Massimo Riccaboni, 2014. "The Rise of China in the International Trade Network: A Community Core Detection Approach," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-8, August.
    13. Hausmann, Ricardo & Hidalgo, Cesar, 2014. "The Atlas of Economic Complexity: Mapping Paths to Prosperity," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262525429, April.
    14. Zhen Zhu & Federica Cerina & Alessandro Chessa & Guido Caldarelli & Massimo Riccaboni, 2014. "The rise of China in the international trade network: a community core detection approach," Working Papers 4/2014, IMT School for Advanced Studies Lucca, revised Apr 2014.
    15. I. Tzekina & K. Danthi & D. Rockmore, 2008. "Evolution of community structure in the world trade web," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 63(4), pages 541-545, June.
    16. Luca De Benedictis & Lucia Tajoli, 2011. "The World Trade Network," The World Economy, Wiley Blackwell, vol. 34(8), pages 1417-1454, August.
    17. Roy Cerqueti & Gian Paolo Clemente & Rosanna Grassi, 2019. "A Network-Based Measure of the Socio-Economic Roots of the Migration Flows," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 187-204, November.
    18. Luis M. Varela & Giulia Rotundo & Marcel Ausloos & Jesús Carrete, 2015. "Complex Network Analysis in Socioeconomic Models," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 209-245, Springer.
    19. 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.
    20. Carlo Piccardi & Lucia Tajoli, 2018. "Complexity, centralization, and fragility in economic networks," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-13, November.
    21. Rita María del Río-Chanona & Jelena Grujić & Henrik Jeldtoft Jensen, 2017. "Trends of the World Input and Output Network of Global Trade," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-14, January.
    22. Li, Xiang & Ying Jin, Yu & Chen, Guanrong, 2003. "Complexity and synchronization of the World trade Web," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 328(1), pages 287-296.
    23. Gian Paolo Clemente & Marco Fattore & Rosanna Grassi, 2018. "Structural comparisons of networks and model-based detection of small-worldness," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 117-141, April.
    24. Natalia Victorovna Kuznetsova & Ekaterina Victorovna Kocheva & Nikolay Anatolievich Matev, 2016. "The Analysis of Foreign Trade Activities of Russia and Asia-pacific Region," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 736-744.
    25. Fan, Ying & Ren, Suting & Cai, Hongbo & Cui, Xuefeng, 2014. "The state's role and position in international trade: A complex network perspective," Economic Modelling, Elsevier, vol. 39(C), pages 71-81.
    26. M. Angeles Serrano & Marian Boguna & Alessandro Vespignani, 2007. "Patterns of dominant flows in the world trade web," Papers 0704.1225, arXiv.org.
    27. 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.
    28. 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.
    29. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
    30. 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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    More about this item

    Keywords

    Network analysis; Communicability distance; Community detection; World Trade Network;
    All these keywords.

    JEL classification:

    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General

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