Download This PaperTesting the Predictive Accuracy of COVID-19 Forecasts
35 Pages Posted: 10 Aug 2021
Date Written: July 1, 2021
Abstract
We test the predictive accuracy of forecasts of the number of COVID-19 fatalities produced by several forecasting teams and collected by the United States Centers for Disease Control and Prevention during the first and second waves of the epidemic in the United States. We find three main results. First, at the short horizon (1-week ahead) no forecasting team outperforms a simple time-series benchmark. Second, at longer horizons (3- and 4-week ahead) forecasters are more successful and sometimes outperform the benchmark, in particular during the first wave of the epidemic. Third, one of the best performing forecasts is the Ensemble forecast, that combines all available predictions using uniform weights. In view of these results, collecting a wide range of forecasts and combining them in an ensemble forecast may be a superior approach for health authorities, rather than relying on a small number of forecasts.
Note: Funding: None to declare.
Declaration of Interests: None to declare.
Keywords: Forecast evaluation, Forecasting tests, Epidemic
JEL Classification: C12, C53, I18
Suggested Citation: Suggested Citation
Alessia Paccagnini (Contact Author)
University College Dublin (UCD) - Michael Smurfit Graduate School of Business ( email )
Blackrock, Co. Dublin
Ireland
Australian National University (ANU) - Crawford School of Public Policy ( email )
ANU College of Asia and the Pacific
J.G. Crawford Building, #132, Lennox Crossing
Canberra, Australian Capital Territory 0200
Australia