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标题：Combining the forecasts in the ECB survey of professional forecasters: can anything beat the simple average?
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作者：Véronique Genre ; Geoff Kenny ; Aidan Meyler 等
期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2010
出版社：European Central Bank
摘要：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.
关键词：forecast combination; forecast evaluation; data snooping; real-time data; Survey of;Professional Forecasters