Nonparametric comparison of epidemic time trends: The case of COVID-19

Marina Khismatullina; Michael Vogt

doi:10.1016/j.jeconom.2021.04.010

Nonparametric comparison of epidemic time trends: The case of COVID-19

Marina Khismatullina, Michael Vogt

Econometrics

Research output: Contribution to journal › Article › Academic › peer-review

2 Citations (Scopus)

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Abstract

The COVID-19 pandemic is one of the most pressing issues at present. A question which is particularly important for governments and policy makers is the following: Does the virus spread in the same way in different countries? Or are there significant differences in the development of the epidemic? In this paper, we devise new inference methods that allow to detect differences in the development of the COVID-19 epidemic across countries in a statistically rigorous way. In our empirical study, we use the methods to compare the outbreak patterns of the epidemic in a number of European countries.

Original language	English
Pages (from-to)	87-108
Number of pages	22
Journal	Journal of Econometrics
Volume	232
Issue number	1
DOIs	https://doi.org/10.1016/j.jeconom.2021.04.010
Publication status	Published - Jan 2023

Bibliographical note

Funding Information:
Financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Germany – grant VO 2503/1-1, project number 430668955 – is gratefully acknowledged.

Publisher Copyright:
© 2021

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10.1016/j.jeconom.2021.04.010

1-s2.0-S030440762100155X-mainFinal published version, 694 KBLicence: Article 25fa Dutch Copyright Act

Cite this

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Nonparametric comparison of epidemic time trends: The case of COVID-19

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