Gollier, Christian
(2020)
Pandemic economics: Optimal dynamic confinement under uncertainty and learning.
Covid Economics, vol. 34 (n° 3).
pp. 1-14.
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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. 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 |
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Language: | English |
Date: | 3 July 2020 |
Refereed: | Yes |
Subjects: | B- ECONOMIE ET FINANCE |
Divisions: | TSE-R (Toulouse) |
Site: | UT1 |
Date Deposited: | 30 Jul 2020 13:33 |
Last Modified: | 15 Jul 2021 09:35 |
OAI Identifier: | oai:tse-fr.eu:124425 |
URI: | https://publications.ut-capitole.fr/id/eprint/41557 |
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- Pandemic economics: Optimal dynamic confinement under uncertainty and learning. (deposited 30 Jul 2020 13:33) [Currently Displayed]