International comparisons of COVID-19 pandemic management: What can be learned from activity analysis techniques?

Víctor Giménez, Diego Prior, Claudio Thieme and Emili Tortosa-Ausina

Omega, 2024, vol. 122, issue C

Abstract: The global spread of COVID-19 since early 2020 has resulted in significant humanitarian costs. The pandemic has affected most countries to varying degrees, and governments have implemented diverse policies to minimise the impact on public health. However, these policies have varied across regions and even within countries. This study proposes a nonparametric activity analysis methodology to assess how different countries have managed the pandemic. Specifically, we assess the effectiveness of 61 countries nine months into the pandemic using a robust directional Benefit of Doubt (BoD) model according to expert opinion and conditional on country contextual factors. We then estimate the marginal impact of structural and discretionary contextual variables on effectiveness using nonparametric regression analysis, which shows that effectiveness is strongly influenced by socioeconomic and cultural factors. The results reveal three main groups of countries according to their level of effectiveness in pandemic management, suggesting that an accurate assessment of countries’ management of the pandemic benefits greatly from operations research methods, as we obtain benchmarks and find out how these benchmarks (or best practices) vary when contextual factors are included in the analysis.

Keywords: Data envelopment analysis; COVID-19; Composite indicators; Assurance region; Robust conditional convex frontier models (search for similar items in EconPapers)
JEL-codes: C61 H51 I18 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Working Paper: International comparisons of the COVID-19 pandemic management: What can be learned from activity analysis techniques? (2021)
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DOI: 10.1016/j.omega.2023.102966

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