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Assessing Targeted Containment Policies to Fight COVID-19

Author

Listed:
  • Checo Ariadne

    (Central Bank of the Dominican Republic, Santo Domingo, Dominican Republic)

  • Grigoli Francesco

    (International Monetary Fund, Washington, USA)

  • Mota Jose M.

    (Economics, University of Houston, Houston, USA)

Abstract

The large economic costs of full-blown lockdowns in response to COVID-19 outbreaks, coupled with heterogeneous mortality rates across age groups, led to question non-discriminatory containment measures. In this paper we provide an assessment of the targeted approach to containment. We propose a SIR-macro model that allows for heterogeneous agents in terms of mortality rates and contact rates, and in which the government optimally bans people from working. We find that under a targeted policy, the optimal containment reaches a larger portion of the population than under a blanket policy and is held in place for longer. Compared to a blanket policy, a targeted approach results in a smaller death count. Yet, it is not a panacea: the recession is larger under such approach as the containment policy applies to a larger fraction of people, remains in place for longer, and herd immunity is achieved later. Moreover, we find that increased interactions between low- and high-risk individuals effectively reduce the benefits of a targeted approach to containment.

Suggested Citation

  • Checo Ariadne & Grigoli Francesco & Mota Jose M., 2022. "Assessing Targeted Containment Policies to Fight COVID-19," The B.E. Journal of Macroeconomics, De Gruyter, vol. 22(1), pages 159-196, January.
    • Handle: RePEc:bpj:bejmac:v:22:y:2022:i:1:p:159-196:n:5
    DOI: 10.1515/bejm-2020-0260
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    JEL classification:

    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • H00 - Public Economics - - General - - - General
    • I10 - Health, Education, and Welfare - - Health - - - General

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