Pooling of forecasts
David Hendry and
Michael Clements
Econometrics Journal, 2004, vol. 7, issue 1, 1-31
Abstract:
We consider forecasting using a combination, when no model coincides with a non-constant data generation process (DGP). Practical experience suggests that combining forecasts adds value, and can even dominate the best individual device. We show why this can occur when forecasting models are differentially mis-specified, and is likely to occur when the DGP is subject to location shifts. Moreover, averaging may then dominate over estimated weights in the combination. Finally, it cannot be proved that only non-encompassed devices should be retained in the combination. Empirical and Monte Carlo illustrations confirm the analysis. Copyright Royal Economic Socciety 2004
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (227)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Working Paper: Pooling of Forecasts (2001) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:7:y:2004:i:1:p:1-31
Ordering information: This journal article can be ordered from
http://www.ectj.org
Access Statistics for this article
Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms
More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().