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How to go viral: A COVID-19 model with endogenously time-varying parameters

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  • Ho, Paul
  • Lubik, Thomas A.
  • Matthes, Christian

Abstract

We estimate a panel model with endogenously time-varying parameters for COVID-19 cases and deaths in U.S. states. The functional form for infections incorporates important features of epidemiological models but is flexibly parameterized to capture different trajectories of the pandemic. Daily deaths are modeled as a spike-and-slab regression on lagged cases. Our Bayesian estimation reveals that social distancing and testing have significant effects on the parameters. For example, a 10 percentage point increase in the positive test rate is associated with a 2 percentage point increase in the death rate among reported cases. The model forecasts perform well, even relative to models from epidemiology and statistics.

Suggested Citation

  • Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2023. "How to go viral: A COVID-19 model with endogenously time-varying parameters," Journal of Econometrics, Elsevier, vol. 232(1), pages 70-86.
    • Handle: RePEc:eee:econom:v:232:y:2023:i:1:p:70-86
    DOI: 10.1016/j.jeconom.2021.01.001
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    Cited by:

    1. Bognanni, Mark & Hanley, Doug & Kolliner, Daniel & Mitman, Kurt, 2020. "Economics and Epidemics: Evidence from an Estimated Spatial Econ-SIR Model," IZA Discussion Papers 13797, Institute of Labor Economics (IZA).
    2. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    3. Zubarev, Andrei & Kirillova, Maria, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.

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    More about this item

    Keywords

    Bayesian estimation; Panel; Time-varying parameters;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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