Fitness-dependent topological properties of the world trade web.

By Diego Garlaschelli, M. I. Loffredo. Physical Review Letters, 2004

326 citations recorded by the source corpus.

Among the proposed network models, the hidden variable (or good get richer) one is particularly interesting, even if an explicit empirical test of its hypotheses has not yet been performed on a real network. Here we provide the first empirical test of this mechanism on the world trade web, the network defined by the trade relationships between world countries. We find that the power-law distributed gross domestic product can be successfully identified with the hidden variable (or fitness) determining the topology of the world trade web: all previously studied properties up to third-order correlation structure (degree distribution, degree correlations, and hierarchy) are found to be in excellent agreement with the predictions of the model. The choice of the connection probability is such that all realizations of the network with the same degree sequence are equiprobable.

Subfields: Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/f17d69309184b93b87e3d9f09134a6600a3cd0c2

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Citations in the corpus

Networks of Value Added Trade (2017, unknown): “…by providing new opportunities for developing countries to integrate into the world economy by joining a supply chain.10 8 Given that the networks of value-added trade have a time-varying density, panel (d) of Figure 1 presents the measure of reciprocity of Garlaschelli and Loffredo (2004b).”
International trade and financial integration: a weighted network analysis (2010, methodology): “While a large literature exists describing trade relationships in terms of a network (see for instance Li et al. 2003, Serrano and Boguñá 2003, Garlaschelli and Loffredo 2004, Bhattacharya et al. 2008, to quote just a few recent examples), this is the first time bilateral *Corresponding author.”
The statistical physics of real-world networks (2018, background): “[52] D.”
The evolution of the world trade web: a weighted-network analysis (2010, methodology): “13 For instance, Serrano and Bogu˜n´a (2003) and Garlaschelli and Loﬀredo (2004a) study the WTW using binary undirected and directed graphs.”