How resilient was international trade to Covid-19? Insights from clusters of European countries

  • Olivera Kostoska University St. Kliment Ohridski - Bitola, Faculty of Economics - Prilep
  • Marjan Angeleski University St. Kliment Ohridski - Bitola, Faculty of Economics - Prilep
  • Ljupco Kocarev Macedonian Academy of Sciences and Arts
Keywords: International trade, cluster analysis, Covid-19, Europe, programming models


The Covid-19 crisis spread around the world at lightning speed mainly due to the interconnectedness of today's economies as evidenced by major disruptions in international trade. This article aims at assessing the possible shifts that coronavirus disease has triggered in trade activity of European countries in two particularly affected sectors, that is food and machinery and transport equipment. In this process, exploratory data analysis is conducted in order to accurately explain the patterns lying behind the observed variations in trade values. Furthermore, cluster analysis is performed to the sample of European countries by applying hierarchical and K-means clustering algorithms using Python's libraries. By examining clusters of countries with similar trade profiles, this article contributes to discussions on global value chains, and to which extent there is data-based evidence to indicate systemic changes and reconfiguration of global production processes.


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