On winning forecasting competitions in economics

• Autores: David F. Hendry, Michael P. Clements
• Localización: Spanish economic review, ISSN 1435-5469, Vol. 1, Nº 2, 1999, págs. 123-160
• Idioma: alemán
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• Resumen

  • Abstract. 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.