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

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  • Khismatullina, Marina
  • Vogt, Michael

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.

Suggested Citation

  • Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    • Handle: RePEc:eee:econom:v:232:y:2023:i:1:p:87-108
    DOI: 10.1016/j.jeconom.2021.04.010
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    Cited by:

    1. Otilia Boldea & Adriana Cornea-Madeira & João Madeira, 2023. "Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: a dynamic intensity model," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 444-466.

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    More about this item

    Keywords

    Simultaneous hypothesis testing; Multiscale test; Time trend; Panel data; COVID-19;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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