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Detecting spatial homogeneity in the World Trade Web with Detrended Fluctuation Analysis

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  • Chiarucci, Riccardo
  • Ruzzenenti, Franco
  • Loffredo, Maria I.
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    Abstract

    In a spatially embedded network, that is a network where nodes can be uniquely determined in a system of coordinates, links’ weights might be affected by metric distances coupling every pair of nodes (dyads). In order to assess to what extent metric distances affect relationships (link’s weights) in a spatially embedded network, we propose a methodology based on DFA (Detrended Fluctuation Analysis). DFA is a well developed methodology to evaluate autocorrelations and estimate long-range behavior in time series. We argue it can be further extended to spatially ordered series in order to assess autocorrelations in values. A scaling exponent of 0.5 (uncorrelated data) would thereby signal a perfect homogeneous space embedding the network. We apply the proposed methodology to the World Trade Web (WTW) during the years 1949–2000 and we find, in some contrast with predictions of gravity models, a declining influence of distances on trading relationships.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 401 (2014)
    Issue (Month): C ()
    Pages: 1-7

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    Handle: RePEc:eee:phsmap:v:401:y:2014:i:c:p:1-7

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: DFA analysis; Distance puzzle; Spatially embedded networks; Spatial homogeneity; Exponential random graphs;

    References

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    1. 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.
    2. Ruzzenenti, F. & Basosi, R., 2009. "Evaluation of the energy efficiency evolution in the European road freight transport sector," Energy Policy, Elsevier, vol. 37(10), pages 4079-4085, October.
    3. Stanley, H.E. & Buldyrev, S.V. & Goldberger, A.L. & Goldberger, Z.D. & Havlin, S. & Mantegna, R.N. & Ossadnik, S.M. & Peng, C.-K. & Simons, M., 1994. "Statistical mechanics in biology: how ubiquitous are long-range correlations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 205(1), pages 214-253.
    4. Yotov, Yoto, 2012. "A Simple Solution to the Distance Puzzle in International Trade," School of Economics Working Paper Series 2012-6, LeBow College of Business, Drexel University.
    5. Buch, Claudia M. & Kleinert, Jorn & Toubal, Farid, 2004. "The distance puzzle: on the interpretation of the distance coefficient in gravity equations," Economics Letters, Elsevier, vol. 83(3), pages 293-298, June.
    6. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. I. A binary network analysis," Papers 1103.1243, arXiv.org, revised Nov 2011.
    7. Marco Duenas & Giorgio Fagiolo, 2011. "Modeling the International-Trade Network: A Gravity Approach," Papers 1112.2867, arXiv.org.
    8. Kantelhardt, Jan W & Koscielny-Bunde, Eva & Rego, Henio H.A & Havlin, Shlomo & Bunde, Armin, 2001. "Detecting long-range correlations with detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 441-454.
    9. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
    10. D. Garlaschelli & M. I. Loffredo, 2005. "Structure and Evolution of the World Trade Network," Papers physics/0502066, arXiv.org, revised May 2005.
    11. Lin, Faqin & Sim, Nicholas C.S., 2012. "Death of distance and the distance puzzle," Economics Letters, Elsevier, vol. 116(2), pages 225-228.
    12. 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.
    13. Lin, Faqin, 2013. "Are distance effects really a puzzle?," Economic Modelling, Elsevier, vol. 31(C), pages 684-689.
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