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COVID19: Erroneous Modelling and Its Policy Implications

Author

Listed:
  • Yinon Bar-On

    (Weizmann Institute of Science)

  • Tatiana Baron

    (Ben Gurion University)

  • Ofer Cornfeld

    (BFI)

  • Ron Milo

    (Weizmann Institute of Science)

  • Eran Yashiv

    (Tel Aviv University
    Centre for Macroeconomics (CFM)
    London School of Economics (LSE)
    Centre for Economic Policy Research (CEPR))

Abstract

Research in Economics on COVID19 typically posits an economy subject to a model of epidemiological dynamics. We place this model on the foundations of an epidemiological analysis of the SARS-CoV-2 transmission timescales. We formulate a full model with both epidemiologically based and clinically based parameterization. Doing so, we are able to study the dynamic properties of the epidemic. We show that there is often serious mis-specification of the model, erroneously characterizing a relatively slow-moving disease, thereby distorting the policymaker decisions. This leads to a higher death toll and potentially also to higher loss of output.

Suggested Citation

  • Yinon Bar-On & Tatiana Baron & Ofer Cornfeld & Ron Milo & Eran Yashiv, 2020. "COVID19: Erroneous Modelling and Its Policy Implications," Discussion Papers 2030, Centre for Macroeconomics (CFM).
    • Handle: RePEc:cfm:wpaper:2030
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    References listed on IDEAS

    as
    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. Andrew B. Abel & Stavros Panageas, 2020. "Social Distancing, Vaccination and the Paradoxical Optimality of an Endemic Equilibrium," NBER Working Papers 27742, National Bureau of Economic Research, Inc.
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    4. Moll, Benjamin & Kaplan, Greg & Violante, Giovanni, 2020. "The Great Lockdown and the Big Stimulus: Tracing the Pandemic Possibility Frontier for the U.S," CEPR Discussion Papers 15256, C.E.P.R. Discussion Papers.
    5. 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).
    6. Yinon Bar-On & Tatiana Baron & Ofer Cornfeld & Eran Yashiv, 2023. "When to Lock, Not Whom: Managing Epidemics Using Time-Based Restrictions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 292-321, December.
    7. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "An Economist's Guide to Epidemiology Models of Infectious Disease," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 79-104, Fall.
    8. Daniel Stadlbauer & Jessica Tan & Kaijun Jiang & Matthew M. Hernandez & Shelcie Fabre & Fatima Amanat & Catherine Teo & Guha Asthagiri Arunkumar & Meagan McMahon & Christina Capuano & Kathryn Twyman &, 2021. "Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City," Nature, Nature, vol. 590(7844), pages 146-150, February.
    9. Glenn Ellison, 2020. "Implications of Heterogeneous SIR Models for Analyses of COVID-19," NBER Working Papers 27373, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Facundo Piguillem & Liyan Shi, 2022. "Optimal Covid-19 Quarantine and Testing Policies," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2534-2562.

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    More about this item

    Keywords

    epidemiological dynamics; COVID19; transmission timescales; optimal policy; public health; disease dynamics and scale; misspecification;
    All these keywords.

    JEL classification:

    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J17 - Labor and Demographic Economics - - Demographic Economics - - - Value of Life; Foregone Income

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