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Randomizing world trade. I. A binary network analysis

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  • Tiziano Squartini
  • Giorgio Fagiolo
  • Diego Garlaschelli

Abstract

The international trade network (ITN) has received renewed multidisciplinary interest due to recent advances in network theory. However, it is still unclear whether a network approach conveys additional, nontrivial information with respect to traditional international-economics analyses that describe world trade only in terms of local (first-order) properties. In this and in a companion paper, we employ a recently proposed randomization method to assess in detail the role that local properties have in shaping higher-order patterns of the ITN in all its possible representations (binary/weighted, directed/undirected, aggregated/disaggregated by commodity) and across several years. Here we show that, remarkably, the properties of all binary projections of the network can be completely traced back to the degree sequence, which is therefore maximally informative. Our results imply that explaining the observed degree sequence of the ITN, which has not received particular attention in economic theory, should instead become one the main focuses of models of trade.

Suggested Citation

  • Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. I. A binary network analysis," Papers 1103.1243, arXiv.org, revised Nov 2011.
    • Handle: RePEc:arx:papers:1103.1243
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    Cited by:

    1. Monica Billio & Roberto Casarin & Matteo Iacopini & Sylvia Kaufmann, 2023. "Bayesian Dynamic Tensor Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 429-439, April.
    2. Chiarucci, Riccardo & Ruzzenenti, Franco & Loffredo, Maria I., 2014. "Detecting spatial homogeneity in the World Trade Web with Detrended Fluctuation Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 1-7.
    3. Lomi, Alessandro & Conaldi, Guido & Tonellato, Marco & Pallotti, Francesca, 2014. "Participation motifs and the emergence of organization in open productions," Structural Change and Economic Dynamics, Elsevier, vol. 29(C), pages 40-57.
    4. 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.
    5. Riccardo Chiarucci & Franco Ruzzenenti & Maria I. Loffredo, 2013. "Detecting spatial homogeneity in the world trade web with Detrended Fluctuation Analysis," Papers 1308.0526, arXiv.org, revised Nov 2013.
    6. Di Vece, Marzio & Garlaschelli, Diego & Squartini, Tiziano, 2023. "Reconciling econometrics with continuous maximum-entropy network models," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    7. Hao Xiao & Tianyang Sun & Bo Meng & Lihong Cheng, 2017. "Complex Network Analysis for Characterizing Global Value Chains in Equipment Manufacturing," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-22, January.
    8. Matthieu Cristelli & Andrea Gabrielli & Andrea Tacchella & Guido Caldarelli & Luciano Pietronero, 2013. "Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-20, August.
    9. Xu, Helian & Cheng, Long, 2016. "The QAP weighted network analysis method and its application in international services trade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 91-101.
    10. Amir Maghssudipour & Marco Bellandi & Annalisa Caloffi, 2023. "The role of language in international trade and the “made in Italy”," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 50(3), pages 677-702, September.
    11. 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.
    12. Shaowei Chen & Qiang (Patrick) Qiang, 2020. "The Trade Network Structure of the “One Belt and One Road” and Its Environmental Effects," Sustainability, MDPI, vol. 12(9), pages 1-21, April.
    13. 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.
    14. Marco Dueñas & Giorgio Fagiolo, 2014. "Global Trade Imbalances: A Network Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(03n04), pages 1-29.
    15. Luu, Duc Thi & Lux, Thomas, 2018. "Multilayer overlaps and correlations in the bank-firm credit network of Spain," Economics Working Papers 2018-04, Christian-Albrechts-University of Kiel, Department of Economics.
    16. Michael Lebacher & Paul W. Thurner & Göran Kauermann, 2021. "A dynamic separable network model with actor heterogeneity: An application to global weapons transfers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 201-226, January.
    17. Pau Erola & Albert Diaz-Guilera & Sergio Gomez & Alex Arenas, 2012. "Modeling international crisis synchronization in the World Trade Web," Papers 1201.2024, arXiv.org.
    18. Nicole Palan & Nadia Simoes & Nuno Crespo, 2021. "Measuring fifty years of trade globalisation," The World Economy, Wiley Blackwell, vol. 44(6), pages 1859-1884, June.
    19. Hoppe, K. & Rodgers, G.J., 2015. "A microscopic study of the fitness-dependent topology of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 64-74.
    20. Vittorio Carlei & Francesca Affortunato & Alessandro Marra & Marco Brogi, 2019. "Does centrality of importing countries affect export prices in the global trade?," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 529-551, January.
    21. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    22. Zhang, Xiaohang & Cui, Huiyuan & Zhu, Ji & Du, Yu & Wang, Qi & Shi, Wenhua, 2017. "Measuring the dissimilarity of multiplex networks: An empirical study of international trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 380-394.
    23. Vincenza Carchiolo & Marco Grassia & Michele Malgeri & Giuseppe Mangioni, 2022. "Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers," Future Internet, MDPI, vol. 14(6), pages 1-15, June.
    24. Luu, Duc Thi & Lux, Thomas & Yanovski, Boyan, 2017. "Structural correlations in the Italian overnight money market: An analysis based on network configuration models," Economics Working Papers 2017-02, Christian-Albrechts-University of Kiel, Department of Economics.
    25. Hempfing, Alexander & Mundt, Philipp, 2022. "Tie formation in global production chains," BERG Working Paper Series 181, Bamberg University, Bamberg Economic Research Group.

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