期刊名称：Zbornik radova Ekonomskog fakulteta u Rijeci, Časopis za ekonomsku teoriju praksu
印刷版ISSN：1331-8004
出版年度：2022
卷号：40
期号：1
页码：177-200
DOI：10.18045/zbefri.2022.1.177
语种：German
出版社：University of Rijeka Faculty of Economics
摘要：Starting from the fact that the rapid spread of the SARS-CoV-2 virus and the implementation of social distancing strategies have dramatically affected all aspects of human lives at global, national, and micro levels, this paper focuses on examining the impact of the COVID-19 pandemic on the economic performance of selected European countries. To perceive and understand this impact, the authors applied a complex research methodology based on the combined application of suitable univariate and multivariate methods of statistical analysis. The classification of 40 European countries into different groups, in terms of the selected set of COVID-19 indicators in 2020, was performed through hierarchical agglomerative cluster analysis, while statistical evaluation of the quality of the obtained solution of a non-hierarchical procedure, based on the k-means method, was implemented. The classification consists of four clusters of countries identified as the “optimal” clustering solution. The authors conducted the analysis and comparison of profiles of the formed clusters of countries in terms of their average GDP growth rates in 2020 using the statistical methods of descriptive analysis and hypothesis testing. This study reveals that a cluster of countries with a relatively “lower” severity of the COVID-19 health consequences recorded a higher average GDP growth rate compared to groups of countries that suffered more serious consequences and vice versa. The obtained results, which indicate the connection between the magnitude of the negative health and economic consequences of the COVID-19 pandemic, can serve as additional support to policymakers in making decisions aimed at mitigating pandemic impacts and crisis management.
