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The Labour Market Consequences of the COVID-19 Pandemic in the European Union Countries: Selected Issues

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Modern Classification and Data Analysis (SKAD 2021)

Abstract

The massive lockdowns of economies as a result of the COVID-19 pandemic are unprecedented on a global scale. Such actions have unfortunately had their negative consequences for the labour market. This is expressed, among other things, through the deterioration of labour market indicators. The aim of the presented study is to assess the size of differences in changes in selected labour market indicators across EU countries over the period 2019–2020 and to assess the heterogeneity of EU countries due to the responses of these indicators. Given that EU countries have used isolation strategies and job support with different intensities, and that their labour markets are characterised by quite different elasticities, the response of these markets is characterised by considerable heterogeneity. In the analysis, we consider labour market characteristics such as economic activity, employment level, share of part-time workers, share of temporary workers or share of self-employed. The k-means algorithm is applied as a research tool. In turn, we use the silhouette index to assess the quality of the obtained divisions. The results obtained indicate a diverse response of national labour markets to the restrictions introduced as a result of COVID-19. The largest negative changes we observe in the group includes PIIGS countries (Portugal, Ireland, Italy, Greece and Spain) and Bulgaria, Czech Republic, and Slovakia. The countries in the group in which Luxembourg, Hungary and the Netherlands are classified have done relatively well, where apart from a reduction in the number of temporary workers, changes in other characteristics are positive.

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Correspondence to Aleksandra Matuszewska-Janica .

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Matuszewska-Janica, A. (2022). The Labour Market Consequences of the COVID-19 Pandemic in the European Union Countries: Selected Issues. In: Jajuga, K., Dehnel, G., Walesiak, M. (eds) Modern Classification and Data Analysis. SKAD 2021. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-031-10190-8_24

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