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Network Analysis of International Trade between 2001 and 2016

Student: Alina Roman

Supervisor: Fuad T. Aleskerov

Faculty: Faculty of Social Sciences

Educational Programme: Public Administration (Bachelor)

Year of Graduation: 2020

Recent research has concentrated on network analysis of international trade, but none of these studies analyzed indirect interactions in the world trade network. This paper addresses the research gap by a simultaneous exploration of direct and indirect interactions between countries, dependent territories, and special areas of geographic interest. In order to identify the most influential and most exposed to external influence trade participants, we employ classical centrality indices (different degree centralities, eigenvector centrality) and novel centrality indices (short-range interaction centrality, long-range interaction centrality, bundle influence in-degree index, pivotal influence in-degree index). Our analysis reveals that the largest importers and exporters of goods are both the most influential and most exposed to external influence participants of international trade, although different centrality measures treat various characteristics as significant. Keywords: international trade, influential countries, network analysis, centrality indices

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