Increase the visibility of your scientific production by authorizing the export of your publications to HAL!

Pandemic economics: Optimal dynamic confinement under uncertainty and learning

Gollier, Christian (2020) Pandemic economics: Optimal dynamic confinement under uncertainty and learning. Covid Economics (34). pp. 1-14.

Download (407kB) | Preview
Official URL:


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
Language: English
Date: 3 July 2020
Refereed: Yes
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 30 Jul 2020 13:33
Last Modified: 30 Jul 2020 13:33
["eprint_fieldname_oai_identifier" not defined]:

Actions (login required)

View Item View Item


Downloads per month over past year