Advanced Search
Article Contents
Article Contents

Modeling international crisis synchronization in the world trade web

Abstract Related Papers Cited by
  • Trade is a fundamental pillar of economy and a form of social organization. Its empirical characterization at the worldwide scale is represented by the World Trade Web (WTW), the network built upon the trade relationships between the different countries. Several scientific studies have focused on the structural characterization of this network, as well as its dynamical properties, since we have registry of the structure of the network at different times in history. In this paper we study an abstract scenario for the development of global crises on top of the structure of connections of the WTW. Assuming a cyclic dynamics of national economies and the interaction of different countries according to the import-export balances, we are able to investigate, using a simple model of pulse-coupled oscillators, the synchronization phenomenon of crises at the worldwide scale. We focus on the level of synchronization measured by an order parameter at two different scales, one for the global system and another one for the mesoscales defined through the topology. We use the WTW network structure to simulate a network of Integrate-and-Fire oscillators for six different snapshots between years 1950 and 2000. The results reinforce the idea that globalization accelerates the global synchronization process, and the analysis at a mesoscopic level shows that this synchronization is different before and after globalization periods: after globalization, the effect of communities is almost inexistent.
    Mathematics Subject Classification: Primary: 05C82, 91B60; Secondary: 91C20.


    \begin{equation} \\ \end{equation}
  • [1]

    A. Arenas, A. Díaz-Guilera, J. Kurths, Y. Moreno and C. Zhou, Synchronization in complex networks, Phys. Rep., 469 (2008), 93-153.doi: 10.1016/j.physrep.2008.09.002.


    A. Arenas, J. Duch, A. Fernández and S. Gómez, Size reduction of complex networks preserving modularity, New J. Phys., 9 (2007), 1-176.


    A. Arenas, A. Fernández and S. Gómez, Analysis of the structure of complex networks at different resolution levels, New J. Phys., 10 (2008), 053039.doi: 10.1088/1367-2630/10/5/053039.


    E. T. Bell, Exponential numbers, Am. Math. Mon., 41 (1934), 411-419.doi: 10.2307/2300300.


    U. Brandes, D. Delling, M. Gaertler, R. Goerke, M. Hoefer, Z. Nikoloski and D. Wagner, On modularity clustering, IEEE T. Knowl. Data En., 20 (2008), 172-188.doi: 10.1109/TKDE.2007.190689.


    S. R. Campbell, D. L. L. Wang and C. Jayaprakash, Synchrony and desynchrony in integrate-and-fire oscillators, Neural Comput., 11 (1999), 1595-1619.doi: 10.1162/089976699300016160.


    A. Clauset, M. E. J. Newman and C. Moore, Finding community structure in very large networks, Phys. Rev. E, 70 (2004), 066111.doi: 10.1103/PhysRevE.70.066111.


    A. V. Deardorff, "Terms of Trade: Glossary of International Economics,'' World Scientific, Singapore, 2006.


    J. Duch and A. Arenas, Community identification using extremal optimization, Phys. Rev. E, 72 (2005), 027104.doi: 10.1103/PhysRevE.72.027104.


    G. Fagiolo, J. Reyes and S. Schiavo, World-trade web: Topological properties, dynamics, and evolution, Phys. Rev. E, 79 (2009), 036115.doi: 10.1103/PhysRevE.79.036115.


    D. Garlaschelli, T. Di Matteo, T. Aste, G. Caldarelli and M. I. Loffredo, Interplay between topology and dynamics in the World Trade Web, Eur. Phys. J. B, 57 (2007), 159-164.doi: 10.1140/epjb/e2007-00131-6.


    R. Guimerà and L. A. N. Amaral, Cartography of complex networks: modules and universal roles, J. Stat. Mech., (2005), P02001.


    K. S. Gleditsch, Expanded Trade and GDP data, J. Conflict Resolut., 46 (2002), 712-724.doi: 10.1177/002200202236171.


    J. He and M. W. Deem, Structure and response in the World Trade Network, Phys. Rev. Lett., 105 (2010), 198701.doi: 10.1103/PhysRevLett.105.198701.


    M. A. Kose, C. Otrok and E. S. Prasad, Global business cycles: Convergence or decoupling?, Nat. Bureau of Economic Research, Working Paper, 14292 (2008).


    H. P. Minsky, "Stabilizing an Unstable Economy,'' Yale University Press, New Haven and London, 1986.


    H. P. Minsky, The financial instability hypothesis, The Jerome Levy Economics Institute, Working Paper, 74 (1992).


    R. E. Mirollo and S. H. Strogatz, Synchronization of pulse-coupled biological oscillators, SIAM J. Appl. Math., 50 (1990), 1645-1662.doi: 10.1137/0150098.


    M. E. J. Newman, Analysis of weighted networks, Phys. Rev. E, 70 (2004), 056131.doi: 10.1103/PhysRevE.70.056131.


    M. E. J. Newman, Fast algorithm for detecting community structure in networks, Phys. Rev. E, 69 (2004), 066133.doi: 10.1103/PhysRevE.69.066133.


    M. E. J. Newman, Modularity and community structure in networks, P. Natl. Acad. Sci. USA, 103 (2006), 8577-8582.doi: 10.1073/pnas.0601602103.


    X. Li, Y. Y. Jin and G. Chen, Complexity and synchronization of the world trade web, Physica A, 328 (2003), 287-296.doi: 10.1016/S0378-4371(03)00567-3.


    J. M. Pujol, J. Béjar and J. Delgado, Clustering algorithm for determining community structure in large networks, Phys. Rev. E, 74 (2006), 016107.doi: 10.1103/PhysRevE.74.016107.


    A. Rothkegel and K. Lehnertz, Recurrent events of synchrony in complex networks of pulse-coupled oscillators, Europhys. Lett., 95 (2011), 38001.doi: 10.1209/0295-5075/95/38001.


    M. A. Serrano and M. Boguñá, Topology of the world trade web, Phys. Rev. E, 68 (2003), 015101.doi: 10.1103/PhysRevE.68.015101.


    T. Squartini, G. Fagiolo and D. Garlaschelli, Randomizing world trade. I. A binary network analysis, Phys. Rev. E, 84 (2011), 046117.doi: 10.1103/PhysRevE.84.046118.


    M. Timme, F. Wolf and T. Geisel, Coexistence of regular and irregular dynamics in complex networks of pulse-coupled oscillators, Phys. Rev. Lett, 89 (2002), 258701.doi: 10.1103/PhysRevLett.89.258701.

  • 加载中

Article Metrics

HTML views() PDF downloads(47) Cited by(0)

Access History



    DownLoad:  Full-Size Img  PowerPoint