 Forecast combination when outcomes are difficult to predictEmpirical Economics, 2017, vol. 53, issue 1, No 2, 7-20 Abstract: Abstract We show that when outcomes are difficult to forecast in the sense that forecast errors have a large common component that (a) optimal weights are not affected by this common component, and may well be far from equal to each other but (b) the relative mean square error loss from averaging over optimal combination can be small. Hence, researchers could well estimate combining weights that indicate that correlations could be exploited for better forecasts only to find that the difference in terms of loss is negligible. The results then provide an additional explanation for the commonly encountered practical situation of the averaging of forecasts being difficult to improve upon. Keywords: Forecasting; Forecast combination; Average forecasts (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-017-1253-2 Ordering information: This journal article can be ordered from DOI: 10.1007/s00181-017-1253-2 Access Statistics for this article Empirical Economics is currently edited by Robert M. Kunst, Arthur H.O. van Soest, Bertrand Candelon, Subal C. Kumbhakar and Joakim Westerlund More articles in Empirical Economics from Springer |
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