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Measuring the Economic Risk of COVID‐19

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  • Ilan Noy
  • Nguyen Doan
  • Benno Ferrarini
  • Donghyun Park

Abstract

We measure the economic risk of COVID‐19 at a geo‐spatially detailed resolution. In addition to data about the current prevalence of confirmed cases, we use data from 2014–2018 and a conceptual disaster risk model to compute measures for exposure, vulnerability, and resilience of the local economy to the shock of the epidemic. Using a battery of proxies for these four concepts, we calculate the hazard, the principal components of exposure and vulnerability to it, and of the economy’s resilience (i.e. its ability of the recover rapidly from the shock). We find that the economic risk of this pandemic is particularly high in most of Sub‐Saharan Africa, South Asia, and Southeast Asia. These results are consistent when comparing an ad hoc equal weighting algorithm for the four components of the index, an algorithm that assumes equal hazard for all countries, and one based on estimated weights using previous aggregated disability‐adjusted life years losses associated with communicable diseases.

Suggested Citation

  • Ilan Noy & Nguyen Doan & Benno Ferrarini & Donghyun Park, 2020. "Measuring the Economic Risk of COVID‐19," Global Policy, London School of Economics and Political Science, vol. 11(4), pages 413-423, September.
    • Handle: RePEc:bla:glopol:v:11:y:2020:i:4:p:413-423
    DOI: 10.1111/1758-5899.12851
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    1. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2020. "COVID-19 and The Macroeconomic Effects of Costly Disasters," NBER Working Papers 26987, National Bureau of Economic Research, Inc.
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    Cited by:

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    2. KATO-VIDAL Enrique L., 2022. "Industrial Variety, Firms And Resilience," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 17(2), pages 141-159, August.
    3. Naeher, Dominik & Narayanan, Raghavan & Ziulu, Virginia, 2024. "The relevance of development policies to confront crisis situations: World Bank’s early response to Covid-19," Journal of Policy Modeling, Elsevier, vol. 46(5), pages 847-866.
    4. Per G. Fredriksson & Aatishya Mohanty, 2022. "COVID-19 Regulations, Political Institutions, and the Environment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(2), pages 323-353, February.
    5. Sándor Kovács & Mohammad Fazle Rabbi & Domicián Máté, 2021. "Global Food Security, Economic and Health Risk Assessment of the COVID-19 Epidemic," Mathematics, MDPI, vol. 9(19), pages 1-16, September.
    6. Viral Acharya & Zhengyang Jiang & Robert J. Richmond & Ernst-Ludwig von Thadden, 2020. "Divided We Fall: International Health and Trade Coordination During a Pandemic," CRC TR 224 Discussion Paper Series crctr224_2020_248, University of Bonn and University of Mannheim, Germany.
    7. Fisayo Fagbemi & Tolulope T. Osinubi & Olufemi S. Olatunde, 2022. "COVID-19 and Unemployment: Showcasing Sub-Saharan African Experience," Jindal Journal of Business Research, , vol. 11(1), pages 24-33, June.
    8. Nana Liu & Zeshui Xu & Marinko Skare, 2021. "The research on COVID-19 and economy from 2019 to 2020: analysis from the perspective of bibliometrics," Oeconomia Copernicana, Institute of Economic Research, vol. 12(2), pages 217-268, June.
    9. Vu Nguyen Doan & Ilan Noy, 2021. "A Comprehensive Measure of Lifeyears Lost due to COVID‐19 in 2020: A Comparison across Countries and with Past Disasters," Global Policy, London School of Economics and Political Science, vol. 12(4), pages 553-561, September.

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    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General

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