COVID-19 Pandemic and Lockdown Fine Optimality

Niavis, Spyros and Kallioras, Dimitris and Vlontzos, George and Duquenne, Marie-Noelle (2021) COVID-19 Pandemic and Lockdown Fine Optimality. Economies, 9 (1). p. 36. ISSN 2227-7099

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Abstract

The first stream of economic studies on public policy responses during the COVID-19 pandemic focused on the stringency, the effectiveness, and the impact of the countries’ interventions and paid rather little attention to the corresponding means used to support them. The present paper scrutinizes the lockdown measures and, particularly, examines the optimality of the lockdown fines imposed by countries worldwide towards ensuring citizens’ compliance. Initially, a triad of fine stringency indicators are compiled, and the stringency of fines is evaluated in a comparative context, among the countries considered. Consequently, the fine stringency is incorporated into a regression analysis with various epidemiological, socioeconomic, and policy factors to reveal any drivers of fine variability. Finally, theoretical approaches behind fine optimality are capitalized and real data are used towards estimating the optimal fine for each country considered. The objectives of the paper are, first, to check for any drivers of fine stringency around the world and, second, to develop and test a formula that could be used in order to assist policy makers to formulate evidence-based fines for confronting the pandemic. The findings of the paper highlight that fines do not seem to have been imposed with any sound economic reasoning and the majority of countries considered imposed larger real fines, compared to the optimal ones, to support the lockdowns. The paper stresses the need for the imposition of science-based fines that reflect the social cost of non-compliance with the lockdown measures.

Item Type: Article
Subjects: Scholar Eprints > Multidisciplinary
Depositing User: Managing Editor
Date Deposited: 24 Jun 2023 05:11
Last Modified: 05 Jun 2024 10:36
URI: http://repository.stmscientificarchives.com/id/eprint/2178

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