Abstract:
While models based on well-established theoretical understanding and available evidence are crucial to viable policymaking in observational-data disciplines, shifts in distributions can lead to systematic mis-forecasting. This column argues that there is an important role for short-term forecasts using adaptive data-based models that are `robust’ after distributional shifts, and discusses an approach to doing so for the Covid-19 pandemic.
Citation:
Castle, J.L., Doornik, J.A. & Hendry, D.F. (2020). ‘Short-term forecasting of the coronavirus pandemic’. VoxEU, 24 April.