The International Trade Network: weighted network analysis and modelling

By K. Bhattacharya, G. Mukherjee, J. Saramaki, Kimmo K. Kaski, S. S. Manna. 2007

220 citations recorded by the source corpus.

Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the ‘rich-club’ coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world’s trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN.

Subfields: Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/70c853b1306b1eabebacfb9e626ea7a2e5ec7381

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Citations in the corpus

The evolution of the world trade web: a weighted-network analysis (2010, methodology): “A similar approach has been adopted by Li et al. (2003), Bhattacharya et al. (2007b), Bhattacharya et al. (2007a) and Serrano et al. (2007).”
The statistical physics of real-world networks (2018, background): “In order to reconstruct sparse weighted networks, both of them are required [47, 49], as in the ECM [41].”
Uncovering space-independent communities in spatial networks (2010, background): “It has been shown for systems as diverse as the International Trade Market [16], human migration [17], traﬃc ﬂows [18] or mobile communication between cities [19, 20] that the volume of interaction between distant locations is successfully modeled by where N i measures the importance of location i…”
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.”
Universal patterns of inequality (2009, background): “The analogy between energy and money is mentioned in some physics textbooks [7], but not developed in detail.”
The World Trade Network (2011, unknown): “For an analysis of the weighted trade network see Bhattacharya et al. (2008) and Fagiolo et al. (2007a, 2007b). in section 2.4.”
Socio-Spatial Properties of Online Location-Based Social Networks (2011, background): “An interesting possibility is related to gravity models, which have long been used to model connections in spatial networks such as trade flows across countries (Bhattacharya et al. 2008).”