Gollier, Christian (2020) Pandemic economics: optimal dynamic confinement under uncertainty and learning. Geneva Risk and Insurance Review, vol. 45 (n° 2). pp. 80-93.

This is the latest version of this item.

[thumbnail of uncertainty_covideconomics34.pdf]
Preview
Text
Download (472kB) | Preview
Identification Number : 10.1057/s10713-020-00052-1

Abstract

Most integrated models of the covid pandemic have been developed under the assumption that the policy-sensitive reproduction number is certain. The decision to exit from the lockdown has been made in most countries without knowing the reproduction number that would prevail after the deconfinement. In this paper, I explore the role of uncertainty and learning on the optimal dynamic lockdown policy. I limit the analysis to suppression strategies where the SIR dynamics can be approximated by an exponential infection decay. In the absence of uncertainty, the optimal confinement policy is to impose a constant rate of lockdown until the suppression of the virus in the population. I show that introducing uncertainty about the reproduction number of deconfined people reduces the optimal initial rate of confinement.

Item Type: Article
Language: English
Date: September 2020
Refereed: Yes
Place of Publication: Norwell, MA
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 25 Mar 2021 09:54
Last Modified: 01 Sep 2021 01:00
OAI Identifier: oai:tse-fr.eu:125161
URI: https://publications.ut-capitole.fr/id/eprint/42278

Available Versions of this Item

View Item

Downloads

Downloads per month over past year