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Combining forecasts using optimal combination weight and generalized autoregression

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  • Jeong-Ryeol Kurz-Kim

    (Deutsche Bundesbank, Frankfurt am Main, Germany)

Abstract

In this paper, we consider a combined forecast using an optimal combination weight in a generalized autoregression framework. The generalized autoregression provides not only a combined forecast but also an optimal combination weight for combining forecasts. By simulation, we find that short- and medium-horizon (as well as partly long-horizon) forecasts from the generalized autoregression using the optimal combination weight are more efficient than those from the usual autoregression in terms of the mean-squared forecast error. An empirical application with US gross domestic product confirms the simulation result. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Jeong-Ryeol Kurz-Kim, 2008. "Combining forecasts using optimal combination weight and generalized autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 419-432.
  • Handle: RePEc:jof:jforec:v:27:y:2008:i:5:p:419-432
    DOI: 10.1002/for.1069
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    File URL: http://hdl.handle.net/10.1002/for.1069
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    References listed on IDEAS

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    1. Gourieroux,Christian & Monfort,Alain, 1997. "Time Series and Dynamic Models," Cambridge Books, Cambridge University Press, number 9780521423083.
    2. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
    3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    4. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
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    Cited by:

    1. Chai, Jian & Zhang, Zhong-Yu & Wang, Shou-Yang & Lai, Kin Keung & Liu, John, 2014. "Aviation fuel demand development in China," Energy Economics, Elsevier, vol. 46(C), pages 224-235.

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