Global Value Chains of COVID-19 Materials: A Weighted Directed Network Analysis
Georgios Angelidis,
Charalambos Bratsas,
Georgios Makris,
Evangelos Ioannidis,
Nikos C. Varsakelis,
Ioannis E. Antoniou
Affiliations
Georgios Angelidis
School of Economics, Faculty of Economic and Political Sciences, Complex Systems Analysis Laboratory (COSAL), Laboratory of Economic Analysis and Policy (LEAP), Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Charalambos Bratsas
School of Mathematics, Faculty of Sciences, Complex Systems Analysis Laboratory (COSAL), Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Georgios Makris
School of Mathematics, Faculty of Sciences, Complex Systems Analysis Laboratory (COSAL), Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Evangelos Ioannidis
School of Economics, Faculty of Economic and Political Sciences, Complex Systems Analysis Laboratory (COSAL), Laboratory of Economic Analysis and Policy (LEAP), Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Nikos C. Varsakelis
School of Economics, Faculty of Economic and Political Sciences, Complex Systems Analysis Laboratory (COSAL), Laboratory of Economic Analysis and Policy (LEAP), Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Ioannis E. Antoniou
School of Mathematics, Faculty of Sciences, Complex Systems Analysis Laboratory (COSAL), Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
The COVID-19 pandemic caused a boom in demand for personal protective equipment, or so-called “COVID-19 goods”, around the world. We investigate three key sectoral global value chain networks, namely, “chemicals”, “rubber and plastics”, and “textiles”, involved in the production of these goods. First, we identify the countries that export a higher value added share than import, resulting in a “value added surplus”. Then, we assess their value added flow diversification using entropy. Finally, we analyze their egonets in order to identify their key affiliates. The relevant networks were constructed from the World Input-Output Database. The empirical results reveal that the USA had the highest surplus in “chemicals”, Japan in “rubber and plastics”, and China in “textiles”. Concerning value added flows, the USA was highly diversified in “chemicals”, Germany in “rubber and plastics”, and Italy in “textiles”. From the analysis of egonets, we found that the USA was the key supplier in all sectoral networks under consideration. Our work provides meaningful conclusions about trade outperformance due to the fact of surplus, trade flow robustness due to the fact of diversification, and trade partnerships due to the egonets analysis.