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.

Bartesaghi, P., Clemente, G. P., Grassi, R., Community structure in the World Trade Network based on communicability distances, <<JOURNAL OF ECONOMIC INTERACTION AND COORDINATION>>, N/A; (N/A): N/A-N/A. [doi:10.1007/s11403-020-00309-y] [http://hdl.handle.net/10807/164907]

Community structure in the World Trade Network based on communicability distances

Clemente, Gian Paolo
Secondo
;
2020

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.
2020
Inglese
Bartesaghi, P., Clemente, G. P., Grassi, R., Community structure in the World Trade Network based on communicability distances, <<JOURNAL OF ECONOMIC INTERACTION AND COORDINATION>>, N/A; (N/A): N/A-N/A. [doi:10.1007/s11403-020-00309-y] [http://hdl.handle.net/10807/164907]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/164907
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