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International Conference on Complex Networks and their Applications

COMPLEX NETWORKS 2017: Complex Networks & Their Applications VI pp 1111–1123Cite as

Multiplex Dynamics on the World Trade Web

Part of the Studies in Computational Intelligence book series (SCI,volume 689)

Abstract

The network of international trade, where countries are represented with nodes and trade relations are represented by directed, weighted edges is an important economic model. In this paper, we consider a multiplex version of this system, wherein nations are connected by multiple edges, representing different commodities, based on a new approach for multilayer network models. The central idea behind this method is to use a network dynamics interpretation of the commodity flows to construct a single operator representing the entire system. This allows us to study the global structure of the trade network as a single object instead of as a disjoint collection of layers. We analyze centralities and communities determined by this model and show that studying the multiplex as a whole allows us to uncover structure not evident in the individual layers or the aggregate network.

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References

  1. Adarov, A., Kali, R., Reyes, J.: Exploring multi-layer flow network of international trade based on flow distances. Preprint p. 37 (2009)

    Google Scholar 

  2. Banerjee, A., Chandrasekhar, A.G., Duflo, E., Jackson, M.O.: The diffusion of microfinance. Science 341(6144), (2013). https://doi.org/10.1126/science.1236498

  3. Barigozzi, M., Fagiolo, G., Garlaschelli, D.: Multinetwork of international trade: a commodity-specific analysis. Phys. Rev. E 81, 046,104–046,127 (2010)

    CrossRef  Google Scholar 

  4. Barigozzi, M., Fagiolo, G., Mangioni, G.: Community Structure in the Multi-network of International Trade. vol. 116, pp. 163–175. Springer, Berlin (2011)

    Google Scholar 

  5. Barigozzi, M., Fagiolo, G., Mangioni, G.: Community Structure in the Multi-network of International Trade. In: Costa, L.D.F., Evsukoff, A., Mangioni, G., Menezes, R. (eds.) Complex Networks. Communications in Computer and Information Science, vol. 116, pp. 163–175. Springer, Berlin (2011)

    Google Scholar 

  6. Caccioli, F., Farmer, J.D., Foti, N., Rockmore, D.: Overlapping portfolios, contagion, and financial stability. J. Econ. Dyn. Control 51, 50–63 (2015)

    CrossRef  MathSciNet  Google Scholar 

  7. Chinazzi, M., Fagiolo, G., Reyes, J.A., Schiavo, S.: Post-mortem examination of the international financial network. J. Econ. Dyn. Control 37(8), 1692–1713 (2013)

    CrossRef  MathSciNet  MATH  Google Scholar 

  8. De Domenico, M., Sole-Ribalta, A., Cozzo, E., Kivela, M., Moreno, Y., Porter, M.A., Gomez, S., Arenas, A.: Mathematical formulation of multilayer networks. Phys. Rev. X 3(4), 041,022 (2013)

    Google Scholar 

  9. De Domenico, M., Sole-Ribalta, A., Omodei, E., Gomez, S., Arenas, A.: Centrality in interconnected multilayer networks. Nat. Commun. 6, 6868 (2015). arXiv:1311.2906

    CrossRef  MATH  Google Scholar 

  10. DeFord, D.R., Pauls, S.D.: A new framework for dynamical models on multiplex networks. J. Complex Netw. (to appear) (2017)

    Google Scholar 

  11. DeFord, D.R., Pauls, S.D.: Spectral clustering methods for multiplex networks. ArXiv (2017)

    Google Scholar 

  12. Deguchi, T., Takahashi, K., Takayasu, H., Takayasu, M.: Hubs and authorities in the world trade network using a weighted HITS algorithm. PLOS ONE 9(7), e100,338 (2014)

    CrossRef  Google Scholar 

  13. Domenico, M.D., Nicosia, V., Arenas, A., Latora, V.: Structural reducibility of multilayer networks. Nat. Commun. 6, 6864 (2015)

    CrossRef  Google Scholar 

  14. Domenico, M.D., Sole-Ribalta, A., Gomez, S., Arenas, A.: Navigability of interconnected networks under random failures. Proc. Natl. Acad. Sci. 111(23), 8351–8356 (2014)

    CrossRef  MathSciNet  MATH  Google Scholar 

  15. Duenas, M., Fagiolo, G.: Global trade imbalances: a network approach. Adv. Complex Syst. 17(03n04), 1450,014 (2014)

    CrossRef  MathSciNet  Google Scholar 

  16. Fagiolo, G.: The international-trade network: gravity equations and topological properties. J. Econ. Interact. Coord. 5(1), 1–25 (2010)

    CrossRef  Google Scholar 

  17. Fagiolo, G., Reyes, J., Schiavo, S.: On the topological properties of the world trade web: a weighted network analysis. Phys. A: Stat. Mech. Appl. 387(15), 3868–3873 (2008). https://doi.org/10.1016/j.physa.2008.01.050. Applications of Physics in Financial AnalysisSelected papers from the 6th International Conference Applications of Physics in Financial Analysis (APFA6), Lisbon, Portugal, 47 July 2007 Applications of Physics in Financial Analysis

  18. Fagiolo, G., Reyes, J., Schiavo, S.: Dynamics and Evolution of the International Trade Network. In: S. Fortunato, G. Mangioni, R. Menezes, V. Nicosia (eds.) Complex Networks. Studies in Computational Intelligence, vol. 207, pp. 1–13, Springer, Berlin (2009)

    Google Scholar 

  19. Fagiolo, G., Reyes, J.: World-trade web: topological properties, dynamics, and evolution. Phys. Rev. E 79(3), 036,115 (2009)

    CrossRef  MathSciNet  Google Scholar 

  20. Fagiolo, G., Reyes, J., Schiavo, S.: The evolution of the world trade web: a weighted-network analysis. J. Evol. Econ. 20(4), 479–514 (2010). https://doi.org/10.1007/s00191-009-0160-x

    CrossRef  Google Scholar 

  21. Feenstra, R., Lipsey, R., Deng, H., Ma, A.C., Mo, H.: World Trade Flows: 1962–2000. NBER Working Paper 11040, National Bureau of Economic Research, Inc (2005)

    Google Scholar 

  22. Foti, N.J., Pauls, S., Rockmore, D.N.: Stability of the world trade web over time an extinction analysis. J. Econ. Dyn. Control 37(9), 1889–1910 (2013)

    CrossRef  MathSciNet  Google Scholar 

  23. Garlaschelli, D., Loffredo, M.: Structure and evolution of the world trade network. Phys. A 355(188,701), 138–44 (2005)

    CrossRef  MathSciNet  Google Scholar 

  24. Garlaschelli, D., Loffredo, M.: Fitness–dependent topological properties of the world trade web. Phys. Rev. Lett. 93, 188,701 (2004)

    CrossRef  Google Scholar 

  25. Hubert, L., Arabie, P.: Comparing partitions. J. Classif. 2(1), 193–218 (1985)

    CrossRef  MATH  Google Scholar 

  26. Jackson, M.O.: Social and Economic Networks, unknown edn. Princeton University Press, Princeton (2010)

    MATH  Google Scholar 

  27. Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J.P., Moreno, Y., Porter, M.A.: Multilayer networks. J. Complex Netw. cnu016 (2014)

    Google Scholar 

  28. Leibon, G., Pauls, S., Rockmore, D., Savell, R.: Topological structures in the equities market network. Proc. Natl. Acad. Sci. 105(52), 20589–20594 (2008)

    CrossRef  MathSciNet  MATH  Google Scholar 

  29. Input-Output Economics. Oxford University Press, Oxford (1986)

    Google Scholar 

  30. Luxburg, U.: A Tutorial on Spectral Clustering. Stat. Computing 17(4), 395–416 (2007). https://doi.org/10.1007/s11222-007-9033-z

    CrossRef  MathSciNet  Google Scholar 

  31. Newman, M.E.J.: A measure of betweenness centrality based on random walks. Soc. Netw. 27(1), 39–54 (2005)

    CrossRef  MathSciNet  Google Scholar 

  32. Schweitzer, F., Fagiolo, G., Sornette, D., Vega-Redondo, F., Vespignani, A., White, D.R.: Economic networks: the new challenges. Science 325(5939), 422–425 (2009)

    MathSciNet  MATH  Google Scholar 

  33. Serrano, M.A., Boguñá, M.: Topology of the world trade web. Phys. Rev. E 68(1), 015,101 (2003)

    CrossRef  Google Scholar 

  34. Sgrignoli, P.: The World Trade Web: a multiple-network perspective (2014)

    Google Scholar 

  35. Shen, B., Zhang, J., Li, Y., Zheng, Q., Li, X.: International trade modelling using open flow networks: a flow-distance based analysis. PLoS ONE 10(11) (2015)

    Google Scholar 

  36. Sol-Ribalta, A., De Domenico, M., Gmez, S., Arenas, A.: Random walk centrality in interconnected multilayer networks. Phys. D: Nonlinear Phenom. 323–324, 73–79 (2016)

    CrossRef  MathSciNet  MATH  Google Scholar 

  37. Squartini, T., Fagiolo, G., Garlaschelli, D.: Randomizing world trade. II. A weighted network analysis. Phys. Rev. E 84(4), 046,118 (2011)

    CrossRef  Google Scholar 

  38. Squartini, T., Fagiolo, G., Garlaschelli, D.: Rewiring world trade part 1. a binary network analysis. Phys. Rev. E 84, 046,118 (2011)

    CrossRef  Google Scholar 

  39. Taylor, D., Caceres, R.S., Mucha, P.J.: Detectability of small communities in multilayer and temporal networks: eigenvector localization, layer aggregation, and time series discretization. arXiv:1609.04376 [physics] (2016)

  40. Taylor, D., Shai, S., Stanley, N., Mucha, P.J.: Enhanced detectability of community structure in multilayer networks through layer aggregation. Phys. Rev. Lett. 116(22), 228,301 (2016)

    CrossRef  Google Scholar 

  41. Trpevski, I., Stanoev, A., Koseska, A., Kocarev, L.: Discrete-time distributed consensus on multiplex networks. New J. Phys. 16(11), 113,063 (2014)

    CrossRef  Google Scholar 

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Acknowledgments

The author would like to thank Dan Rockmore, Scott Pauls, and Tommy Khoo for helpful discussions and advice.

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Authors and Affiliations

  1. Department of Mathematics Dartmouth College, Hanover, NH, 03755, USA

    Daryl R. DeFord

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  1. Daryl R. DeFord
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Correspondence to Daryl R. DeFord .

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Editors and Affiliations

  1. University of Lyon 2, Lyon, France

    Chantal Cherifi

  2. University of Burgundy, Dijon, France

    Hocine Cherifi

  3. École Normale Supérieure de Lyon, Lyon, France

    Márton Karsai

  4. University College London, London, United Kingdom

    Mirco Musolesi

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DeFord, D.R. (2018). Multiplex Dynamics on the World Trade Web. In: Cherifi, C., Cherifi, H., Karsai, M., Musolesi, M. (eds) Complex Networks & Their Applications VI. COMPLEX NETWORKS 2017. Studies in Computational Intelligence, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-72150-7_90

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  • DOI: https://doi.org/10.1007/978-3-319-72150-7_90

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