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An Econometric Panel Data Model of the COVID-19 Pandemic

Author

Listed:
  • Antoine Djogbenou
  • Christian Gouriéroux
  • Joann Jasiak
  • Paul Rilstone

Abstract

New flexible-form and semi-parametric autoregressive non-linear count models for panel data are developed to analyse the spread and containment of the COVID-19 pandemic. The models are based on a discrete time form of the SIR model. These methods lead naturally to estimators of the infection process and daily reproduction numbers by jurisdiction. Two semi-parametric versions of the reproduction numbers are developed corresponding to currently popular parametric estimators. The estimators are applied to a large international data set to estimate these parameters for 221 jurisdictions at both national and subnational levels. Â Â JEL classification numbers: C14, C23, I18.

Suggested Citation

  • Antoine Djogbenou & Christian Gouriéroux & Joann Jasiak & Paul Rilstone, 2022. "An Econometric Panel Data Model of the COVID-19 Pandemic," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 11(1), pages 1-3.
    • Handle: RePEc:spt:stecon:v:11:y:2022:i:1:f:11_1_3
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    References listed on IDEAS

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    More about this item

    Keywords

    COVID-19; Reproduction Numbers; Panel Data; Count Models; Semi-parametric Approach.;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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