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Initial economic damage from the COVID-19 pandemic in the United States is more widespread across ages and geographies than initial mortality impacts

Author

Listed:
  • Maria Polyakova

    (Center for Health Policy, Department of Medicine, Stanford University School of Medicine, Stanford University, Stanford, CA 94305)

  • Geoffrey Kocks

    (Department of Economics, Massachusetts Institute of Technology, Cambridge, MA 02142)

  • Victoria Udalova

    (Enhancing Health Data Program, Demographic Directorate, US Census Bureau, Washington, DC 20233)

  • Amy Finkelstein

    (Department of Economics, Massachusetts Institute of Technology, Cambridge, MA 02142)

Abstract

The economic and mortality impacts of the COVID-19 pandemic have been widely discussed, but there is limited evidence on their relationship across demographic and geographic groups. We use publicly available monthly data from January 2011 through April 2020 on all-cause death counts from the Centers for Disease Control and Prevention and employment from the Current Population Survey to estimate excess all-cause mortality and employment displacement in April 2020 in the United States. We report results nationally and separately by state and by age group. Nationally, excess all-cause mortality was 2.4 per 10,000 individuals (about 30% higher than reported COVID deaths in April) and employment displacement was 9.9 per 100 individuals. Across age groups 25 y and older, excess mortality was negatively correlated with economic damage; excess mortality was largest among the oldest (individuals 85 y and over: 39.0 per 10,000), while employment displacement was largest among the youngest (individuals 25 to 44 y: 11.6 per 100 individuals). Across states, employment displacement was positively correlated with excess mortality (correlation = 0.29). However, mortality was highly concentrated geographically, with the top two states (New York and New Jersey) each experiencing over 10 excess deaths per 10,000 and accounting for about half of national excess mortality. By contrast, employment displacement was more geographically spread, with the states with the largest point estimates (Nevada and Michigan) each experiencing over 16 percentage points employment displacement but accounting for only 7% of the national displacement. These results suggest that policy responses may differentially affect generations and geographies.

Suggested Citation

  • Maria Polyakova & Geoffrey Kocks & Victoria Udalova & Amy Finkelstein, 2020. "Initial economic damage from the COVID-19 pandemic in the United States is more widespread across ages and geographies than initial mortality impacts," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(45), pages 27934-27934, November.
    • Handle: RePEc:nas:journl:v:117:y:2020:p:27934-27934
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    Citations

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    Cited by:

    1. Lackner, Mario & Sunde, Uwe & Winter-Ebmer, Rudolf, 2021. "COVID-19 and the Forces behind Social Unrest," IZA Discussion Papers 14884, Institute of Labor Economics (IZA).
    2. Gallo, Edoardo & Barak, Darija & Langtry, Alastair, 2023. "Social distancing in networks: A web-based interactive experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    3. Mario Lackner & Uwe Sunde & Rudolf Winter-Ebmer, 2023. "The Forces Behind Social Unrest: Evidence from the Covid-19 Pandemic," Economics working papers 2023-07, Department of Economics, Johannes Kepler University Linz, Austria.
    4. Natalie Nitsche & Ansgar Hudde, 2022. "Countries embracing maternal employment opened schools sooner after Covid-19 lockdowns," MPIDR Working Papers WP-2022-008, Max Planck Institute for Demographic Research, Rostock, Germany.
    5. Chen, Simiao & Prettner, Klaus & Kuhn, Michael & Bloom, David E., 2021. "The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach," The Journal of the Economics of Ageing, Elsevier, vol. 20(C).
    6. Wang, Wei & Miao, Wei & Liu, Yongdong & Deng, Yiting & Cao, Yunfei, 2022. "The impact of COVID-19 on the ride-sharing industry and its recovery: Causal evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 128-141.
    7. Lin William Cong & Ke Tang & Bing Wang & Jingyuan Wang, 2021. "An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States," Papers 2109.10009, arXiv.org.
    8. Li, Han & Liu, Haibo & Tang, Qihe & Yuan, Zhongyi, 2023. "Pricing extreme mortality risk in the wake of the COVID-19 pandemic," Insurance: Mathematics and Economics, Elsevier, vol. 108(C), pages 84-106.
    9. Hurwitz, Abigail & Mitchell, Olivia S. & Sade, Orly, 2022. "Testing methods to enhance longevity awareness," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 466-475.
    10. Liao, Liping & Du, Minzhe, 2024. "How digital finance shapes residents' health: Evidence from China," China Economic Review, Elsevier, vol. 87(C).
    11. Marcella Alsan & Amitabh Chandra & Kosali Simon, 2021. "The Great Unequalizer: Initial Health Effects of COVID-19 in the United States," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 25-46, Summer.
    12. Almeida Fernando, 2021. "Open Data’s Role in Social Innovation Initiatives to Fight COVID-19," Journal of Management and Business Administration. Central Europe, Sciendo, vol. 29(3), pages 2-19, September.
    13. M. Kate Bundorf & Jill DeMatteis & Grant Miller & Maria Polyakova & Jialu L. Streeter & Jonathan Wivagg, 2021. "Risk Perceptions and Protective Behaviors: Evidence from COVID-19 Pandemic," NBER Working Papers 28741, National Bureau of Economic Research, Inc.

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