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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.

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.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:401:y:2014:i:c:p:1-7
    DOI: 10.1016/j.physa.2014.01.019
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    References listed on IDEAS

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    Cited by:

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    2. Alvarez-Ramirez, J. & Rodriguez, E., 2018. "AR(p)-based detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 49-57.
    3. Zhang, Shuhong & Wang, Lin & Liu, Zhixin & Wang, Xiaofan, 2016. "Evolution of international trade and investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 752-763.
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    5. Franco Ruzzenenti, 2018. "The Prism of Elasticity in Rebound Effect Modelling: An Insight from the Freight Transport Sector," Sustainability, MDPI, vol. 10(8), pages 1-13, August.
    6. 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.
    7. Xinghua Fan & Xuxia Li & Jiuli Yin & Jiaochen Liang, 2019. "Temporal Characteristics and Spatial Homogeneity of Virtual Water Trade: A Complex Network Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(4), pages 1467-1480, March.

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