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Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 Across U.S. States and Selected Countries

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  • Johnsson, I.
  • Pesaran, M. H.
  • Yang, C. F.

Abstract

This paper proposes a structural econometric approach to estimating the basic reproduction number (R0) of Covid-19. This approach identifies R0 in a panel regression model by filtering out the effects of mitigating factors on disease diffusion and is easy to implement. We apply the method to data from 48 contiguous U.S. states and a diverse set of countries. Our results reveal a notable concentration of R0 estimates with an average value of 4.5. Through a counterfactual analysis, we highlight a significant underestimation of the R0 when mitigating factors are not appropriately accounted for.

Suggested Citation

  • Johnsson, I. & Pesaran, M. H. & Yang, C. F., 2023. "Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 Across U.S. States and Selected Countries," Cambridge Working Papers in Economics 2360, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:2360
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    References listed on IDEAS

    as
    1. M. Hashem Pesaran & Cynthia Fan Yang, 2022. "Matching theory and evidence on Covid‐19 using a stochastic network SIR model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1204-1229, September.
    2. Isabella Locatelli & Bastien Trächsel & Valentin Rousson, 2021. "Estimating the basic reproduction number for COVID-19 in Western Europe," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-9, March.
    3. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
    4. Jonas E. Arias & Jesús Fernández- Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2023. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 287-319, July.
    5. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    7. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    8. Lu Tang & Yiwang Zhou & Lili Wang & Soumik Purkayastha & Leyao Zhang & Jie He & Fei Wang & Peter X.‐K. Song, 2020. "A Review of Multi‐Compartment Infectious Disease Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 462-513, August.
    9. Gabriel G Katul & Assaad Mrad & Sara Bonetti & Gabriele Manoli & Anthony J Parolari, 2020. "Global convergence of COVID-19 basic reproduction number and estimation from early-time SIR dynamics," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-22, September.
    10. Luís M A Bettencourt & Ruy M Ribeiro, 2008. "Real Time Bayesian Estimation of the Epidemic Potential of Emerging Infectious Diseases," PLOS ONE, Public Library of Science, vol. 3(5), pages 1-9, May.
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    More about this item

    Keywords

    basic reproduction number; Covid-19; panel threshold regression model;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy

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