Forecast Combinations

Allan Timmermann

No 5361, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models? forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where the numbers of models is large relative to the available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts.

Keywords: Forecast combinations; Pooling and trimming; Shrinkage methods; Model misspecification; Diversification gains (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Date: 2005-11
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Citations: View citations in EconPapers (14)

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Related works:
Working Paper: Forecast Combinations (2010)
Working Paper: Forecast Combinations (2010)
Chapter: Forecast Combinations (2006)
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