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Preventing COVID-19 Fatalities: State versus Federal Policies

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  • Jean-Paul Renne
  • Guillaume Roussellet
  • Gustavo Schwenkler

Abstract

Are COVID-19 fatalities large when a federal government does not enforce containment policies and instead allow states to implement their own policies? We answer this question by developing a stochastic extension of a SIRD epidemiological model for a country composed of multiple states. Our model allows for interstate mobility. We consider three policies: mask mandates, stay-at-home orders, and interstate travel bans. We fit our model to daily U.S. state-level COVID-19 death counts and exploit our estimates to produce various policy counterfactuals. While the restrictions imposed by some states inhibited a significant number of virus deaths, we find that more than two-thirds of U.S. COVID-19 deaths could have been prevented by late November 2020 had the federal government enforced federal mandates as early as some of the earliest states did. Our results quantify the benefits of early actions by a federal government for the containment of a pandemic.

Suggested Citation

  • Jean-Paul Renne & Guillaume Roussellet & Gustavo Schwenkler, 2020. "Preventing COVID-19 Fatalities: State versus Federal Policies," Papers 2010.15263, arXiv.org, revised Dec 2020.
    • Handle: RePEc:arx:papers:2010.15263
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    References listed on IDEAS

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    1. Fernando Alvarez & David Argente, 2020. "A Simple Planning Problem for COVID-19 Lockdown," Working Papers 2020-34, Becker Friedman Institute for Research In Economics.
    2. Jacek Rothert, 2020. "Optimal federal redistribution during the uncoordinated response to a pandemic," Departmental Working Papers 64, United States Naval Academy Department of Economics.
    3. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
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    5. Saidi, Farzad & Alfaro, Laura & Faia, Ester & Lamersdorf, Nora, 2020. "Social Interactions in Pandemics: Fear, Altruism, and Reciprocity," CEPR Discussion Papers 14716, C.E.P.R. Discussion Papers.
    6. Luís M A Bettencourt & Ruy M Ribeiro, 2008. "Real Time Bayesian Estimation of the Epidemic Potential of Emerging Infectious Diseases," PLOS ONE, Public Library of Science, vol. 3(5), pages 1-9, May.
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    Cited by:

    1. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CESifo Working Paper Series 8977, CESifo.
    2. Jacek Rothert, 2021. "Optimal federal transfers during uncoordinated response to a pandemic," GRAPE Working Papers 58, GRAPE Group for Research in Applied Economics.
    3. Rebucci, Alessandro & Elenev, Vadim & , & Simeonova, Emilia, 2021. "Direct and Spillover Effects from Staggered Adoption of Health Policies: Evidence from Covid-19 Stay-at-Home Orders," CEPR Discussion Papers 16649, C.E.P.R. Discussion Papers.
    4. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    5. Jacek Rothert, 2022. "Optimal federal transfers during uncoordinated response to a pandemic," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 1124-1153, October.
    6. Jonas E. Arias & Jesús Fernández-Villaverde & Juan Rubio Ramírez & Minchul Shin, 2021. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," NBER Working Papers 28617, National Bureau of Economic Research, Inc.
    7. Hansen, Niels-Jakob H. & Mano, Rui C., 2023. "Mask mandates save lives," Journal of Health Economics, Elsevier, vol. 88(C).

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