Fighting COVID-19: Patterns in International Data, Expanded
Roberto Mariano and
Suleyman Ozmucur
PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania
Abstract:
This paper provides an empirical evaluation of countries’ performance in fighting COVID-19, utilizing a performance index (which we call the Disaster Index) based on four health and economic indicators: deaths per population size, deaths per confirmed cases, and quarterly real GDP and monthly unemployment rate relative to pre-pandemic values. International data patterns are studied for these four indicators and the Disaster index to analyze trends and basic empirical relationships. The approach is descriptive and primarily based on graphs, scatter diagrams, and correlation analysis. The ten best performers based on the Disaster Index for the first half of 2020 were (best #1 to #10): Singapore, Taiwan, Belarus, Korea, New Zealand, Japan, Norway, Israel, Czechia, and Lithuania. The worst twelve performers were (bad to worst): Sweden, US, Canada, Philippines, France, Columbia, Spain, Belgium, United Kingdom, Ecuador, Italy, and Peru. Thus, high-income Asian countries performed relatively better than low-income Asian countries, European, and American countries in the first half of 2020. Reasons for this geographical divide are very important and must be studied more carefully and closely, as successful methods in better performing countries will provide some lessons for other countries. It also would be interesting to see how this Disaster Index profile shifts in 2021 as vaccination and economic relief accelerate in countries like the United States. The pandemic exhibited the vulnerabilities in the world and reemphasized the vital significance of international coordination and cooperation in a globalized world. Recent trends show that most countries still have a long way to go to control the virus. Vaccination is a reassuring fresh hope, a potential game-changer, though requiring careful, painstaking, and timely implementation.
Keywords: COVID-19; Disaster Index; Data Patterns; Trends; Correlations; Cluster Analysis (search for similar items in EconPapers)
JEL-codes: C00 E00 F00 I1 O57 (search for similar items in EconPapers)
Pages: 86 pages
Date: 2021-03-21
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