Epidemic Responses Under Uncertainty

45 Pages Posted: 29 May 2020 Last revised: 27 Apr 2021

See all articles by Michael Barnett

Michael Barnett

Arizona State University (ASU) - Finance Department

Greg Buchak

Stanford University Graduate School of Business

Constantine Yannelis

University of Chicago, Booth School of Business, Finance, Students

Multiple version iconThere are 2 versions of this paper

Date Written: August 30, 2020

Abstract

We examine how policymakers react to a pandemic with uncertainty regarding key epidemiological parameters by embedding a macroeconomic SIR model in a robust control framework. We find that optimal policy under uncertainty generates optimal mitigation responses that are asymmetric with respect to the initial estimate of the pandemic’s severity. When underestimating the severity, the robust control approach leads to a harsher quarantine, closer to the true optimal level, compared to a naive approach. When overestimating, the planner initially implements a policy similar to the true optimal policy but fails to relax it as the pandemic abates.

Keywords: COVID-19, Coronavirus, Model Uncertainty, Dynamic General Equilibrium

JEL Classification: E1, H0, I1

Suggested Citation

Barnett, Michael and Buchak, Greg and Yannelis, Constantine, Epidemic Responses Under Uncertainty (August 30, 2020). University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2020-72, Available at SSRN: https://ssrn.com/abstract=3610905 or http://dx.doi.org/10.2139/ssrn.3610905

Michael Barnett

Arizona State University (ASU) - Finance Department ( email )

W. P. Carey School of Business
PO Box 873906
Tempe, AZ 85287-3906
United States

Greg Buchak

Stanford University Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States
6507214004 (Phone)
94305 (Fax)

Constantine Yannelis (Contact Author)

University of Chicago, Booth School of Business, Finance, Students ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

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