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A Simple Planning Problem for COVID-19 Lockdown

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  • Lippi, Francesco
  • Alvarez, Fernando
  • Argente, David

Abstract

We study the optimal lockdown policy for a planner who controls the fatalities of a pandemic while minimizing the output costs of the lockdown. The policy depends on the fraction of infected and susceptible in the population, prescribing a severe lockdown beginning two weeks after the outbreak, covering 60% of the population after a month, and gradually withdrawing to 20% of the population after 3 months. The intensity of the optimal lockdown depends on the gradient of the fatality rate with respect to the infected, and the availability of antibody testing that yields a welfare gain of 2% of GDP.

Suggested Citation

  • Lippi, Francesco & Alvarez, Fernando & Argente, David, 2020. "A Simple Planning Problem for COVID-19 Lockdown," CEPR Discussion Papers 14658, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:14658
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    2. Facundo Piguillem & Liyan Shi, 2022. "Optimal Covid-19 Quarantine and Testing Policies," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2534-2562.
    3. Andrew Atkeson, 2020. "What Will be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios," Staff Report 595, Federal Reserve Bank of Minneapolis.
    4. Robert J. Barro & José F. Ursua & Joanna Weng, 2020. "The Coronavirus and the Great Influenza Epidemic - Lessons from the "Spanish Flu" for the Coronavirus's Potential Effects on Mortality and Economic Activity," CESifo Working Paper Series 8166, CESifo.
    5. repec:aei:rpaper:1008560098 is not listed on IDEAS
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    Keywords

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    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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