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Time Series Models for Forecasting: Testing or Combining?

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Author Info

  • Chen Zhuo

    ()
    (University of Chicago)

  • Yang Yuhong

    ()
    (University of Minnesota)

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.

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File URL: http://www.degruyter.com/view/j/snde.2007.11.1/snde.2007.11.1.1385/snde.2007.11.1.1385.xml?format=INT
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Bibliographic Info

Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 11 (2007)
Issue (Month): 1 (March)
Pages: 56-90

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Handle: RePEc:bpj:sndecm:v:11:y:2007:i:1:n:3

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References

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  1. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-55, December.
  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.
  3. Elliott, Graham & Timmermann, Allan G, 2004. "Optimal Forecast Combination Under Regime Switching," CEPR Discussion Papers 4649, C.E.P.R. Discussion Papers.
  4. 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.
  5. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
  6. Yang Y., 2001. "Adaptive Regression by Mixing," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 574-588, June.
  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. Swanson, Norman R & Zeng, Tian, 2001. "Choosing among Competing Econometric Forecasts: Regression-Based Forecast Combination Using Model Selection," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 425-40, September.
  9. Pötscher, B.M., 1991. "Effects of Model Selection on Inference," Econometric Theory, Cambridge University Press, vol. 7(02), pages 163-185, June.
  10. Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, February.
  11. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
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Cited by:
  1. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.

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