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Interplay between topology and dynamics in the World Trade Web

Author

Listed:
  • D. Garlaschelli
  • T. Di Matteo
  • T. Aste
  • G. Caldarelli
  • M. I. Loffredo

Abstract

We present an empirical analysis of the network formed by the trade relationships between all world countries, or World Trade Web (WTW). Each (directed) link is weighted by the amount of wealth flowing between two countries, and each country is characterized by the value of its Gross Domestic Product (GDP). By analysing a set of year-by-year data covering the time interval 1950-2000, we show that the dynamics of all GDP values and the evolution of the WTW (trade flow and topology) are tightly coupled. The probability that two countries are connected depends on their GDP values, supporting recent theoretical models relating network topology to the presence of a `hidden' variable (or fitness). On the other hand, the topology is shown to determine the GDP values due to the exchange between countries. This leads us to a new framework where the fitness value is a dynamical variable determining, and at the same time depending on, network topology in a continuous feedback.

Suggested Citation

  • 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.
  • Handle: RePEc:arx:papers:physics/0701030
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    Citations

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    Cited by:

    1. Theophilos Papadimitriou & Periklis Gogas & Georgios Sarantitis, 2016. "Convergence of European Business Cycles: A Complex Networks Approach," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 97-119, February.
    2. 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.
    3. 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.
    4. Assaf Almog & Rhys Bird & Diego Garlaschelli, 2015. "Enhanced Gravity Model of trade: reconciling macroeconomic and network models," Papers 1506.00348, arXiv.org, revised Mar 2017.
    5. Antonakakis, Nikolaos & Gogas, Periklis & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2016. "International business cycle synchronization since the 1870s: Evidence from a novel network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 286-296.
    6. 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.
    7. Alexander M. Petersen & Boris Podobnik & Davor Horvatic & H. Eugene Stanley, 2010. "Scale invariant properties of public debt growth," Papers 1002.2491, arXiv.org.
    8. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    9. Song, Dong-Ming & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2009. "Statistical properties of world investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2450-2460.
    10. Tiziano Squartini & Diego Garlaschelli, 2012. "Triadic motifs and dyadic self-organization in the World Trade Network," Papers 1201.1215, arXiv.org, revised Jan 2012.
    11. 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.
    12. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    13. Zhong, Weiqiong & An, Haizhong & Shen, Lei & Dai, Tao & Fang, Wei & Gao, Xiangyun & Dong, Di, 2017. "Global pattern of the international fossil fuel trade: The evolution of communities," Energy, Elsevier, vol. 123(C), pages 260-270.
    14. 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.
    15. Periklis Gogas & Rangan Gupta & Stephen M. Miller & Theophilos Papadimitriou & Georgios Antonios Sarantitis, 2015. "Income Inequality: A State-by-State Complex Network Analysis," Working Papers 201534, University of Pretoria, Department of Economics.
    16. Annika Birch & Tomaso Aste, 2014. "Systemic Losses Due to Counter Party Risk in a Stylized Banking System," Papers 1402.3688, arXiv.org.
    17. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
    18. repec:eee:enepol:v:106:y:2017:i:c:p:22-31 is not listed on IDEAS
    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. repec:ebl:ecbull:eb-17-00361 is not listed on IDEAS
    21. repec:eee:phsmap:v:483:y:2017:i:c:p:423-437 is not listed on IDEAS
    22. Pau Erola & Albert Diaz-Guilera & Sergio Gomez & Alex Arenas, 2012. "Modeling international crisis synchronization in the World Trade Web," Papers 1201.2024, arXiv.org.
    23. 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.

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