Combining expert forecasts: Can anything beat the simple average?
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- 作者：Vé ; ronique Genre<sup>asup>Author Vitae ; Geoff Kenny<sup>asup><sup> ; sup><sup>geoff.kenny@ecb.europa.eusup>Author Vitae ; Aidan Meyler<sup>asup>Author Vitae ; Allan Timmermann<sup>bsup>Author Vitae
- 关键词：Forecast combination ; Forecast evaluation ; Multiple model comparisons ; Real-time data ; Survey of Professional Forecasters
- 刊名：International Journal of Forecasting
- 出版年：2013
- 出版时间：January-March, 2013
- 年：2013
- 卷：29
- 期：1
- 页码：108-121
- 全文大小：2171 K
文摘
This paper explores the gains from combining expert forecasts from the ECB Survey of Professional Forecasters (SPF). The analysis encompasses combinations based on principal components and trimmed means, performance-based weighting, and least squares estimates of optimal weights, as well as Bayesian shrinkage. For GDP growth and the unemployment rate, only few of the individual forecast combination schemes outperform the simple equally weighted average forecast in a pseudo-out-of-sample analysis, while there is stronger evidence of improvement over this benchmark for the inflation rate. Nonetheless, when we account for the effect of multiple model comparisons through White¡¯s reality check, the results caution against any assumption that the improvements identified would persist in the future.