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A hybrid forecasting approach for piece-wise stationary time series

Author

Listed:
  • Ronald Bewley

    (School of Economics, University of New South Wales, Sydney, Australia)

  • Minxian Yang

    (School of Economics, University of New South Wales, Sydney, Australia)

Abstract

We consider the problem of forecasting a stationary time series when there is an unknown mean break close to the forecast origin. Based on the intercept-correction methods suggested by Clements and Hendry (1998) and Bewley (2003), a hybrid approach is introduced, where the break and break point are treated in a Bayesian fashion. The hyperparameters of the priors are determined by maximizing the marginal density of the data. The distributions of the proposed forecasts are derived. Different intercept-correction methods are compared using simulation experiments. Our hybrid approach compares favorably with both the uncorrected and the intercept-corrected forecasts. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Ronald Bewley & Minxian Yang, 2006. "A hybrid forecasting approach for piece-wise stationary time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 513-527.
    • Handle: RePEc:jof:jforec:v:25:y:2006:i:7:p:513-527
    DOI: 10.1002/for.1003
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    References listed on IDEAS

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    1. D. W. K. Andrews, 2003. "End-of-Sample Instability Tests," Econometrica, Econometric Society, vol. 71(6), pages 1661-1694, November.
    2. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423.
    3. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    4. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
    5. Phillips, Peter C B, 1996. "Econometric Model Determination," Econometrica, Econometric Society, vol. 64(4), pages 763-812, July.
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