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Forecast Combination With Entry and Exit of Experts

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  • Carlos Capistrán
  • Allan Timmermann

    ()
    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

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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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-55.

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Length: 25
Date of creation: 19 Sep 2008
Date of revision:
Handle: RePEc:aah:create:2008-55

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Real-time Data; Survey of Professional Forecasters; Bias-adjustment; EM Algorithm.;

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References

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Citations

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Cited by:
  1. Sancetta, Alessio, 2009. "Nearest neighbor conditional estimation for Harris recurrent Markov chains," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2224-2236, November.
  2. 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.
  3. 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.
  4. 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.
  5. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, School of Economics and Management, University of Aarhus.
  6. Olivier Coibion & Yuriy Gorodnichenko, 2010. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," Working Papers 102, Department of Economics, College of William and Mary.
  7. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
  8. 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, April.
  9. Jan J. J. Groen & George Kapetanios, 2008. "Revisiting useful approaches to data-rich macroeconomic forecasting," Staff Reports 327, Federal Reserve Bank of New York.
  10. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
  11. Carlos Capistrán & Gabriel López-Moctezuma, 2010. "Forecast Revisions of Mexican Inflation and GDP Growth," Working Papers 2010-11, Banco de México.
  12. 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.
  13. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
  14. 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.
  15. Hoornweg, V., 2013. "Some Tools for Robustifying Econometric Analyses," Econometric Institute Research Papers 50163, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  16. 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.

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