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Randomizing world trade. I. A binary network analysis

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Author Info

  • Tiziano Squartini
  • Giorgio Fagiolo
  • Diego Garlaschelli

Abstract

The international trade network (ITN) has received renewed multidisciplinary interest due to recent advances in network theory. However, it is still unclear whether a network approach conveys additional, nontrivial information with respect to traditional international-economics analyses that describe world trade only in terms of local (first-order) properties. In this and in a companion paper, we employ a recently proposed randomization method to assess in detail the role that local properties have in shaping higher-order patterns of the ITN in all its possible representations (binary/weighted, directed/undirected, aggregated/disaggregated by commodity) and across several years. Here we show that, remarkably, the properties of all binary projections of the network can be completely traced back to the degree sequence, which is therefore maximally informative. Our results imply that explaining the observed degree sequence of the ITN, which has not received particular attention in economic theory, should instead become one the main focuses of models of trade.

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File URL: http://arxiv.org/pdf/1103.1243
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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number 1103.1243.

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Date of creation: Mar 2011
Date of revision: Nov 2011
Publication status: Published in Phys. Rev. E 84, 046117 (2011)
Handle: RePEc:arx:papers:1103.1243

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Web page: http://arxiv.org/

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Cited by:
  1. Lomi, Alessandro & Conaldi, Guido & Tonellato, Marco & Pallotti, Francesca, 2014. "Participation motifs and the emergence of organization in open productions," Structural Change and Economic Dynamics, Elsevier, Elsevier, vol. 29(C), pages 40-57.
  2. Marco Duenas & Giorgio Fagiolo, 2011. "Modeling the International-Trade Network: A Gravity Approach," Papers 1112.2867, arXiv.org.
  3. Pau Erola & Albert Diaz-Guilera & Sergio Gomez & Alex Arenas, 2012. "Modeling international crisis synchronization in the World Trade Web," Papers 1201.2024, arXiv.org.
  4. Marco Duenas & Giorgio Fagiolo, 2013. "Global Trade Imbalances: A Network Approach," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy 2013/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  5. Riccardo Chiarucci & Franco Ruzzenenti & Maria I. Loffredo, 2013. "Detecting spatial homogeneity in the world trade web with Detrended Fluctuation Analysis," Papers 1308.0526, arXiv.org, revised Nov 2013.
  6. 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, Elsevier, vol. 401(C), pages 1-7.

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