Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/153711
Authors: 
Genre, Véronique
Kenny, Geoff
Meyler, Aidan
Timmermann, Allan
Year of Publication: 
2010
Series/Report no.: 
ECB Working Paper 1277
Abstract: 
In this paper, we explore the potential gains from alternative combinations of the surveyed forecasts in the ECB Survey of Professional Forecasters. Our analysis encompasses a variety of methods including statistical combinations based on principal components analysis and trimmed means, performance-based weighting, least squares estimates of optimal weights as well as Bayesian shrinkage. We provide a pseudo real-time out-of-sample performance evaluation of these alternative combinations and check the sensitivity of the results to possible data-snooping bias. The latter robustness check is also informed using a novel real time meta selection procedure which is not subject to the data-snooping critique. For GDP growth and the unemployment rate, only few of the forecast combination schemes are able to outperform the simple equal-weighted average forecast. Conversely, for the inflation rate there is stronger evidence that more refined combinations can lead to improvement over this benchmark. In particular, for this variable, the relative improvement appears significant even controlling for data snooping bias.
Subjects: 
data snooping
forecast combination
forecast evaluation
real-time data
Survey of Professional Forecasters
JEL: 
C22
C53
Document Type: 
Working Paper

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