A0159
Title: A forecast-error taxonomy facing multiple shifts
Authors: David Hendry - University of Oxford (United Kingdom) [presenting]
Jennifer L Castle - Oxford University (United Kingdom)
Jurgen Doornik - University of Oxford (United Kingdom)
Abstract: Distributional shifts occur frequently, with detrimental impacts on forecast accuracy. Almost all econometric forecasting models are equilibrium correcting, so they are susceptible to systematic forecast failure after equilibrium mean shifts, which could be direct or induced. Unanticipated out-of-sample shifts are a well-known cause of forecast failure, but they later become in-sample shifts and require handling. Previous forecast error taxonomies are extended to include shifts both in-sample and after the forecast origin. The taxonomy reveals which shifts do and do not lead to forecast failure, facing both in-sample and post-forecast origin shifts, also highlighting what features are amenable to rapid correction.
