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Unstable Weights in the Combination of Forecasts

Author

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  • Heejoon Kang

    (Graduate School of Business, Indiana University, Bloomington, Indiana 47405)

Abstract

The weights used in the combination of forecasts are shown to be very unstable. They are generally so unstable that the combined forecasts often do not perform better than some of the individual forecasts or a simple average of the forecasts in practice. The instability is found from a series of Monte Carlo experiments as well as from the nominal GNP forecasts from four well-known macro forecasters. The Monte Carlo experiments also show that when the underlying models are known, a composite forecast from a composite model is generally more accurate than the combination of the individual forecasts. A simple average is shown to be the best technique to use in practice, because the weights in the combination are so unstable.

Suggested Citation

  • Heejoon Kang, 1986. "Unstable Weights in the Combination of Forecasts," Management Science, INFORMS, vol. 32(6), pages 683-695, June.
  • Handle: RePEc:inm:ormnsc:v:32:y:1986:i:6:p:683-695
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    File URL: http://dx.doi.org/10.1287/mnsc.32.6.683
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    Cited by:

    1. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
    2. Kamstra, Mark & Kennedy, Peter, 1998. "Combining qualitative forecasts using logit," International Journal of Forecasting, Elsevier, vol. 14(1), pages 83-93, March.
    3. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
    4. repec:oup:jfinec:v:15:y:2017:i:2:p:247-285. is not listed on IDEAS
    5. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    6. Blanc, Sebastian M. & Setzer, Thomas, 2016. "When to choose the simple average in forecast combination," Journal of Business Research, Elsevier, vol. 69(10), pages 3951-3962.
    7. P. J. Lamberson & Scott E. Page, 2012. "Optimal Forecasting Groups," Management Science, INFORMS, vol. 58(4), pages 805-810, April.
    8. Webby, Richard & O'Connor, Marcus, 1996. "Judgemental and statistical time series forecasting: a review of the literature," International Journal of Forecasting, Elsevier, vol. 12(1), pages 91-118, March.
    9. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    10. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier.
    11. Keunkwan Ryu & Kuo-yuan Liang, 1992. "Relationship of Forecast Encompassing to Composite Forecasts with Simulations and an Application," UCLA Economics Working Papers 668, UCLA Department of Economics.
    12. Issler, João Victor & Lima, Luiz Renato, 2009. "A panel data approach to economic forecasting: The bias-corrected average forecast," Journal of Econometrics, Elsevier, vol. 152(2), pages 153-164, October.
    13. Zhao, Weigang & Wang, Jianzhou & Lu, Haiyan, 2014. "Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model," Omega, Elsevier, vol. 45(C), pages 80-91.
    14. Mostaghimi, Mehdi, 1996. "Combining ranked mean value forecasts," European Journal of Operational Research, Elsevier, vol. 94(3), pages 505-516, November.
    15. Guidolin, Massimo & Timmermann, Allan, 2009. "Forecasts of US short-term interest rates: A flexible forecast combination approach," Journal of Econometrics, Elsevier, vol. 150(2), pages 297-311, June.
    16. Blattenberger, Gail & Fowles, Richard, 1995. "Road closure to mitigate avalanche danger: a case study for Little Cottonwood Canyon," International Journal of Forecasting, Elsevier, vol. 11(1), pages 159-174, March.
    17. Maines, Laureen A., 1996. "An experimental examination of subjective forecast combination," International Journal of Forecasting, Elsevier, vol. 12(2), pages 223-233, June.

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    Keywords

    forecasting;

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