On winning forecasting competitions in economics

Clements, M. P. ORCID: https://orcid.org/0000-0001-6329-1341 and Hendry, D. F. (1999) On winning forecasting competitions in economics. Spanish Economic Review, 1 (2). pp. 123-160. ISSN 1435-5477 doi: 10.1007/s101080050006

Abstract/Summary

To explain which methods might win forecasting competitions on economic time series, we consider forecasting in an evolving economy subject to structural breaks, using mis-specified, data-based models. ‘Causal’ models need not win when facing deterministic shifts, a primary factor underlying systematic forecast failure. We derive conditional forecast biases and unconditional (asymptotic) variances to show that when the forecast evaluation sample includes sub-periods following breaks, non-causal models will outperform at short horizons. This suggests using techniques which avoid systematic forecasting errors, including improved intercept corrections. An application to a small monetary model of the UK illustrates the theory.