Community structure in the World Trade Network based on communicability distances

Paolo Bartesaghi (), Gian Paolo Clemente () and Rosanna Grassi ()
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Paolo Bartesaghi: University of Milano - Bicocca
Gian Paolo Clemente: Università Cattolica del Sacro Cuore
Rosanna Grassi: University of Milano - Bicocca

Journal of Economic Interaction and Coordination, 2022, vol. 17, issue 2, No 2, 405-441

Abstract: Abstract In this paper, we investigate the mesoscale structure of the World Trade Network. In this framework, a specific role is assumed by short- and long-range interactions, and hence by any suitably defined network-based distance between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network. The proposed methodology aims at finding the distance threshold that maximizes a specific quality function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities. The numerical analysis highlights peculiar relationships between countries and provides a rich set of information that can hardly be achieved within alternative clustering approaches.

Keywords: Network analysis; Communicability distance; Community detection; World Trade Network (search for similar items in EconPapers)
JEL-codes: D57 F40 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11403-020-00309-y

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