On winning forecasting competitions in economics
Michael Clements and
David Hendry ()
Spanish Economic Review, 1999, vol. 1, issue 2, 123-160
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.
Keywords: Forecasting; structural breaks; differencing; intercept corrections (search for similar items in EconPapers)
JEL-codes: C32 C53 (search for similar items in EconPapers)
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