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Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs

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  • Fernández-Villaverde, Jesús
  • Arias, Jonas
  • Rubio-Ramírez, Juan Francisco
  • Shin, Minchul
Abstract
We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely on a Markov chain Monte Carlo to sample from the posterior distribution. We show how to use the posterior simulation outputs as inputs for exercises in causality assessment. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. Our estimated time-varying-parameters SIRD model captures the data dynamics very well, including the three waves of infections. We use the estimated (true) number of new cases and the time-varying effective reproduction number from the epidemiological model as information for structural vector autoregressions and local projections. We document how additional government-mandated mobility curtailments would have reduced deaths at zero cost or a very small cost in terms of output.

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  • Fernández-Villaverde, Jesús & Arias, Jonas & Rubio-Ramírez, Juan Francisco & Shin, Minchul, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CEPR Discussion Papers 15951, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:15951
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    Cited by:

    1. 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).
    2. Masashige Hamano & Munechika Katayama, 2021. "Epidemics and Macroeconomic Dynamics," Working Papers e162, Tokyo Center for Economic Research.
    3. INOUE Tomoo & OKIMOTO Tatsuyoshi, 2022. "Exploring the Dynamic Relationship between Mobility and the Spread of COVID-19, and the Role of Vaccines," Discussion papers 22011, Research Institute of Economy, Trade and Industry (RIETI).
    4. Gächter, Martin & Huber, Florian & Meier, Martin, 2022. "A shot for the US economy," Finance Research Letters, Elsevier, vol. 47(PA).
    5. David Turner & Balázs Égert & Yvan Guillemette & Jarmila Botev, 2021. "The tortoise and the hare: The race between vaccine rollout and new COVID variants," OECD Economics Department Working Papers 1672, OECD Publishing.

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    More about this item

    Keywords

    Bayesian estimation; Epidemiological models; Causality; Policy interventions;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • I1 - Health, Education, and Welfare - - Health

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