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COVID-19 over Time and across States: Predictions from a Statistical Model

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Abstract

We discuss a statistical time series model to capture and forecast the dynamics of COVID-19 in the fifty U.S. states and Washington, D.C. We design the model to replicate the typical pattern of infections during a pandemic. We rely on Bayesian methods, which provide a straightforward way to quantify the uncertainty surrounding our estimates and forecasts. In this brief, we focus on North Carolina and Washington, D.C., since they have experienced different trajectories of COVID-19 and may have different implications for the efficacy of our approach.

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  • Paul Ho & Thomas A. Lubik & Christian Matthes, 2020. "COVID-19 over Time and across States: Predictions from a Statistical Model," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, vol. 20(10), September.
    • Handle: RePEc:fip:fedreb:92714
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    Keywords

    Regional and Urban Economics;

    Statistics

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