A Graph-Based Network Analysis of Global Coffee Trade—The Impact of COVID-19 on Trade Relations in 2020

Zsuzsanna Bacsi (), Mária Fekete-Farkas and Muhammad Imam Ma’ruf
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Zsuzsanna Bacsi: Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary
Mária Fekete-Farkas: Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary
Muhammad Imam Ma’ruf: Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, 2100 Godollo, Hungary

Sustainability, 2023, vol. 15, issue 4, 1-32

Abstract: International trade relations have been considerably affected by the coronavirus pandemic. Our analysis was aimed at identifying its effect on the global trade network of green coffee beans, comparing the COVID-year 2020 to the pre-COVID year 2018. The methodology applied was that of social network analysis using trade value data for the above two years. Our results show that between the pre-pandemic and the pandemic years, the role of some major actors considerably changed, and many trade relationships were disrupted. Overall trade value decreased, and the number of trade connections also changed—some countries gained, but more countries lost compared to their former positions. The network measures, i.e., degree distribution, betweenness, closeness and eigenvector centralities, modularity-based clustering and the minimum spanning tree, were suitable for quantifying these changes and identifying differences between affected countries. The changes found between the two years are assumed to be due to the effects of the pandemic, but further analysis is needed to reveal the actual mechanisms leading to these results.

Keywords: coffee; global trade; social network analysis; Gephi; centrality; minimal spanning tree (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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