Impact of COVID-19-Related Lockdown Measures on Economic and Social Outcomes in Lithuania

Jurgita Markevičiūtė, Jolita Bernatavičienė, Rūta Levulienė, Viktor Medvedev, Povilas Treigys and Julius Venskus
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Jurgita Markevičiūtė: Institute of Applied Mathematics, Vilnius University, Naugarduko St. 24, LT-03225 Vilnius, Lithuania
Jolita Bernatavičienė: Institute of Data Science and Digital Technologies, Vilnius University, Akademijos Str. 4, LT-08412 Vilnius, Lithuania
Rūta Levulienė: Institute of Applied Mathematics, Vilnius University, Naugarduko St. 24, LT-03225 Vilnius, Lithuania
Viktor Medvedev: Institute of Data Science and Digital Technologies, Vilnius University, Akademijos Str. 4, LT-08412 Vilnius, Lithuania
Povilas Treigys: Institute of Data Science and Digital Technologies, Vilnius University, Akademijos Str. 4, LT-08412 Vilnius, Lithuania
Julius Venskus: Institute of Applied Mathematics, Vilnius University, Naugarduko St. 24, LT-03225 Vilnius, Lithuania

Mathematics, 2022, vol. 10, issue 15, 1-20

Abstract: The current world crisis caused by the COVID-19 pandemic has transformed into an economic crisis, becoming a problem and a challenge not only for individual national economies but also for the world economy as a whole. The first global lockdown, which started in mid-March of 2020 and lasted for three months in Lithuania, affected the movement and behavior of the population, and had an impact on the economy. This research presents results on the impact of lockdown measures on the economy using nonparametric methods in combination with parametric ones. The impact on unemployment and salary inequality was estimated. To assess the impact of lockdown on the labor market, the analysis of the dynamics of the unemployment rate was performed using the results of the cluster analysis. The Lithuanian data were analyzed in the context of other countries, where the dynamics of the spread of the virus were similar. The salary inequality was measured by the Gini coefficient and analyzed using change point analysis, functional data analysis and linear regression. The study found that the greatest impact of the closure restrictions on socio-economic indicators was recorded in 2020, with a lower impact in 2021. The proposed multi-step approach could be applied to other countries and to various types of shocks and interventions, not only the COVID-19 crisis, in order to avoid adverse economic and social outcomes.

Keywords: COVID-19; nonparametric analysis; Gini index; unemployment; cluster analysis; panel data; change point detection; functional data; multidimensional data; lockdown consequences (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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