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Combining expert forecasts: Can anything beat the simple average?

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Author Info

  • Genre, Véronique
  • Kenny, Geoff
  • Meyler, Aidan
  • Timmermann, Allan

Abstract

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.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 29 (2013)
Issue (Month): 1 ()
Pages: 108-121

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Handle: RePEc:eee:intfor:v:29:y:2013:i:1:p:108-121

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Web page: http://www.elsevier.com/locate/ijforecast

Related research

Keywords: Forecast combination; Forecast evaluation; Multiple model comparisons; Real-time data; Survey of Professional Forecasters;

References

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  1. Clemon, Robert T & Winkler, Robert L, 1986. "Combining Economic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 4(1), pages 39-46, January.
  2. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
  3. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, Econometric Society, vol. 68(5), pages 1097-1126, September.
  4. Raffaella Giacomini & Halbert White, 2003. "Tests of Conditional Predictive Ability," Econometrics, EconWPA 0308001, EconWPA.
  5. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier, Elsevier.
  6. Diebold, Francis X. & Pauly, Peter, 1990. "The use of prior information in forecast combination," International Journal of Forecasting, Elsevier, Elsevier, vol. 6(4), pages 503-508, December.
  7. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, School of Economics and Management, University of Aarhus.
  8. Giannone, Domenico & Henry, Jérôme & Lalik, Magdalena & Modugno, Michele, 2010. "An area-wide real-time database for the euro area," Working Paper Series 1145, European Central Bank.
  9. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
  10. Benalal, Nicholai & Diaz del Hoyo, Juan Luis & Landau, Bettina & Roma, Moreno & Skudelny, Frauke, 2004. "To aggregate or not to aggregate? Euro area inflation forecasting," Working Paper Series 0374, European Central Bank.
  11. Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca, 2010. "Short-Term Inflation Projections: a Bayesian Vector Autoregressive approach," CEPR Discussion Papers 7746, C.E.P.R. Discussion Papers.
  12. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
  13. Jeremy Smith & Kenneth F. Wallis, 2009. "A Simple Explanation of the Forecast Combination Puzzle," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 331-355, 06.
  14. Juan Angel Garcia, 2003. "An introduction to the ECB’s survey of professional forecasters," Occasional Paper Series 08, European Central Bank.
  15. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  16. Carlos Bowles & Roberta Friz & Veronique Genre & Geoff Kenny & Aidan Meyler & Tuomas Rautanen, 2010. "An Evaluation of the Growth and Unemployment Forecasts in the ECB Survey of Professional Forecasters," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2010(2), pages 1-28.
  17. Carlos Bowles & Roberta Friz & Veronique Genre & Geoff Kenny & Aidan Meyler & Tuomas Rautanen, 2007. "The ECB survey of professional forecasters (SPF) – A review after eight years’ experience," Occasional Paper Series 59, European Central Bank.
  18. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, Elsevier, vol. 5(4), pages 559-583.
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Citations

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Cited by:
  1. Katarzyna Maciejowska & Jakub Nowotarski & Rafal Weron, 2014. "Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology HSC/14/09, Hugo Steinhaus Center, Wroclaw University of Technology.
  2. Makram El-Shagi & Sebastian Giesen & A. Jung, 2012. "Does Central Bank Staff Beat Private Forecasters?," IWH Discussion Papers, Halle Institute for Economic Research 5, Halle Institute for Economic Research.
  3. Jakub Nowotarski & Eran Raviv & Stefan Trueck & Rafal Weron, 2013. "An empirical comparison of alternate schemes for combining electricity spot price forecasts," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology HSC/13/07, Hugo Steinhaus Center, Wroclaw University of Technology.
  4. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, Elsevier, vol. 30(1), pages 43-54.
  5. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
  6. Julieta Fuentes & Pilar Poncela & Julio Rodríguez, 2014. "Selecting and combining experts from survey forecasts," Statistics and Econometrics Working Papers, Universidad Carlos III, Departamento de Estadística y Econometría ws140905, Universidad Carlos III, Departamento de Estadística y Econometría.
  7. Jakub Nowotarski & Rafal Weron, 2013. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology HSC/13/12, Hugo Steinhaus Center, Wroclaw University of Technology.
  8. Smets, Frank & Warne, Anders & Wouters, Raf, 2013. "Professional forecasters and the real-time forecasting performance of an estimated new keynesian model for the euro area," Working Paper Series 1571, European Central Bank.
  9. Tao Hong & Katarzyna Maciejowska & Jakub Nowotarski & Rafal Weron, 2014. "Probabilistic load forecasting via Quantile Regression Averaging of independent expert forecasts," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology HSC/14/10, Hugo Steinhaus Center, Wroclaw University of Technology.

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