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Comparing predictive accuracy I: an asymptotic test

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  • Francis X. Diebold
  • Roberto S. Mariano

Abstract

We propose and evaluate an explicit test of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic, and need not even be symmetric), and forecast errors can be non-Gaussian, nonzero mean, serially correlated and contemporaneously correlated.

Suggested Citation

  • Francis X. Diebold & Roberto S. Mariano, 1991. "Comparing predictive accuracy I: an asymptotic test," Discussion Paper / Institute for Empirical Macroeconomics 52, Federal Reserve Bank of Minneapolis.
  • Handle: RePEc:fip:fedmem:52
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    References listed on IDEAS

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    7. 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. West, Kenneth D. & Cho, Dongchul, 1995. "The predictive ability of several models of exchange rate volatility," Journal of Econometrics, Elsevier, vol. 69(2), pages 367-391, October.
    2. Lin, Wen-Ling, 1995. "Market closure and predictability of intradaily stock returns in the United States and Japan," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 19-44, March.
    3. Chan Huh, 1998. "Forecasting industrial production using models with business cycle asymmetry," Economic Review, Federal Reserve Bank of San Francisco, pages 29-41.
    4. Roy H. Webb & Tazwell S. Rowe, 1995. "An index of leading indicators for inflation," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 75-96.

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    Keywords

    Econometrics;

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