Combining the forecasts in the ECB survey of professional forecasters: can anything beat the simple average?

Geoff Kenny, Veronique Genre, Aidan Meyler and Allan Timmermann

No 1277, Working Paper Series from European Central Bank

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. JEL Classification: C22, C53

Keywords: data snooping; forecast combination; forecast evaluation; real-time data; Survey of Professional Forecasters (search for similar items in EconPapers)
Date: 2010-12
New Economics Papers: this item is included in nep-cba, nep-eec, nep-for and nep-mon
Note: 339061
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20101277

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