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Forecast Combination With Entry and Exit of Experts

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  • Capistrán, Carlos
  • Timmermann, Allan

Abstract

Combination of forecasts from survey data is complicated by the frequent entry and exit of individual forecasters which renders conventional least squares regression approaches infeasible. We explore the consequences of this issue for existing combina- tion methods and propose new methods for bias-adjusting the equal-weighted forecast or applying combinations on an extended panel constructed by back-filling missing ob- servations using an EM algorithm. Through simulations and an application to a range of macroeconomic variables we show that the entry and exit of forecasters can have a large effect on the real-time performance of conventional combination methods. The bias-adjusted combination method is found to work well in practice.

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File URL: http://pubs.amstat.org/doi/abs/10.1198/jbes.2009.07211
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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 27 (2009)
Issue (Month): 4 ()
Pages: 428-440

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Handle: RePEc:bes:jnlbes:v:27:i:4:y:2009:p:428-440

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References

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  1. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
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  3. Heejoon Kang, 1986. "Unstable Weights in the Combination of Forecasts," Management Science, INFORMS, vol. 32(6), pages 683-695, June.
  4. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, School of Economics and Management, University of Aarhus.
  5. Pesaran, M. Hashem & Timmermann, Allan, 2004. "Real Time Econometrics," IZA Discussion Papers 1108, Institute for the Study of Labor (IZA).
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Citations

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Cited by:
  1. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
  2. Sancetta, Alessio, 2009. "Nearest neighbor conditional estimation for Harris recurrent Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2224-2236, November.
  3. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
  4. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
  5. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers 624, Queen Mary, University of London, School of Economics and Finance.
  6. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
  7. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2011. "Scoring rules and survey density forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 379-393.
  8. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
  9. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, School of Economics and Management, University of Aarhus.
  10. Carlos Capistrán & Gabriel López-Moctezuma, 2010. "Forecast Revisions of Mexican Inflation and GDP Growth," Working Papers 2010-11, Banco de México.
  11. Olivier Coibion & Yuriy Gorodnichenko, 2012. "Information Rigidity and the Expectations Formation Process," IMF Working Papers 12/296, International Monetary Fund.
  12. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), August.
  13. Frank A.G. den Butter & Pieter W. Jansen, 2008. "Beating the Random Walk: a Performance Assessment of Long-term Interest Rate Forecasts," Tinbergen Institute Discussion Papers 08-102/3, Tinbergen Institute.
  14. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
  15. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
  16. Hoornweg, V., 2013. "Some Tools for Robustifying Econometric Analyses," Econometric Institute Research Papers 50163, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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