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Time Series Models for Forecasting: Testing or Combining?

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Author Info
Zhuo Chen (University of Chicago)
Yuhong Yang (University of Minnesota)

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Abstract

In this paper we systematically compare forecasting accuracy of hypothesis testing procedures with that of a model combining algorithm. Testing procedures are commonly used in applications to select a model, based on which forecasts are made. However, besides the well-known difficulty in dealing with multiple tests, the testing approach has a potentially serious drawback: controlling the probability of Type I error at a conventional level (e.g., 0.05) often excessively favors the null, which can be problematic for the purpose of forecasting. In addition, as shown in this paper, testing procedures can be very unstable, which results in high variability in the forecasts.Selecting a candidate forecast by testing and combining forecasts are both useful but for complementary situations. Currently, there seems to be little guidance in the literature on when combining should be preferred to selecting. We propose instability measures that are helpful for a forecaster to gauge the difficulty in selecting a single optimal forecast.Based on empirical evidences and theoretical considerations, we advocate the use of forecast combining when there is considerable instability in model selection by testing procedures. On the other hand, when there is little instability, testing procedures could work well or even better than forecast combining in terms of forecast accuracy.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 11 (2007)
Issue (Month): 1 ()
Pages: 1385-1385
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Handle: RePEc:bep:sndecm:11:2007:1:1385-1385

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Related research
Keywords: forecast combining hypothesis testing instability in model selection model selection

References listed on IDEAS
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  1. Zou, Hui & Yang, Yuhong, 2004. "Combining time series models for forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 69-84. [Downloadable!] (restricted)
  2. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November. [Downloadable!] (restricted)
    Other versions:
  3. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Blackwell Publishing, vol. 17(31), pages 334-55, December.
  4. Graham Elliott & Allan Timmermann, 2005. "Optimal Forecast Combination Under Regime Switching ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1081-1102, November. [Downloadable!] (restricted)
    Other versions:
  5. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, 06. [Downloadable!] (restricted)
    Other versions:
  6. Timmermann, Allan G, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  7. Hall, A D & McAleer, Michael, 1989. "A Monte Carlo Study of Some Tests of Model Adequacy in Time Series Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 95-106, January.
  8. Bessler, David A & Brandt, Jon A, 1981. "Forecasting Livestock Prices with Individual and Composite Methods," Applied Economics, Taylor and Francis Journals, vol. 13(4), pages 513-22, December.
  9. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May. [Downloadable!] (restricted)
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  10. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583. [Downloadable!] (restricted)
  11. Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, March. [Downloadable!]
  12. Fuchun Li & Greg Tkacz, 2004. "Combining Forecasts with Nonparametric Kernel Regressions," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 8(4), pages 1129-1129. [Downloadable!] (restricted)
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This page was last updated on 2008-11-19.


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