How to Go Viral: A Covid-19 Model with Endogenously Time-Varying Parameters

35 Pages Posted: 2 Oct 2020 Last revised: 23 Oct 2020

See all articles by Paul Ho

Paul Ho

Federal Reserve Banks - Federal Reserve Bank of Richmond

Thomas Lubik

Federal Reserve Banks - Federal Reserve Bank of Richmond

Christian Matthes

Federal Reserve Bank of Richmond

Date Written: August, 2020

Abstract

This paper estimates 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. The paper's 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.

JEL Classification: C32, C51

Suggested Citation

Ho, Paul and Lubik, Thomas and Matthes, Christian, How to Go Viral: A Covid-19 Model with Endogenously Time-Varying Parameters (August, 2020). FRB Richmond Working Paper No. 20-10, Available at SSRN: https://ssrn.com/abstract=3701996 or http://dx.doi.org/10.21144/wp20-10

Paul Ho (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

Thomas Lubik

Federal Reserve Banks - Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

Christian Matthes

Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

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