Gourieroux, Christian and Jasiak, Joann (2023) Time Varying Markov Process with Partially Observed Aggregate Data: An Application To Coronavirus. Journal of Econometrics, vol. 232 (n°1). pp. 35-51.

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Identification Number : 10.1016/j.jeconom.2020.09.007


A major difficulty in the analysis of Covid-19 transmission is that many infected individuals are asymptomatic. For this reason, the total counts of infected individuals and of recovered immunized individuals are unknown, especially during the early phase of the epidemic. In this paper, we consider a parametric time varying Markov process of Coronavirus transmission and show how to estimate the model parameters and approximate the unobserved counts from daily data on infected and detected individuals and the total daily death counts. This model-based approach is illustrated in an application to French data, performed on April 6, 2020.

Item Type: Article
Language: English
Date: January 2023
Refereed: Yes
Place of Publication: Amsterdam
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 24 Nov 2022 07:28
Last Modified: 05 Sep 2023 13:37
OAI Identifier: oai:tse-fr.eu:124753
URI: https://publications.ut-capitole.fr/id/eprint/43691
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