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Model-free asymptotically best forecasting of stationary economic time series

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  • Bierens, H.J.

    (Vrije Universiteit Amsterdam, Faculteit der Economische Wetenschappen en Econometrie (Free University Amsterdam, Faculty of Economics Sciences, Business Administration and Economitrics)

Abstract

Given observations on a stationary economic vector time series process we show that the best h-step ahead forecast (best in the sense of having minimal mean square forecast error) of one of the variables can be consistently estimated by nonparametric regression on an ARMA memory index. Our approach is based on a combination of the ARMA memory index modeling approach of Bierens [7] with a modification to time series of the nonparametric kernel regression approach of Devroye and Wagner [16]. This approach is truly model-free, as no explicit specification of the distribution of the data generating process is needed.
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Suggested Citation

  • Bierens, H.J., 1986. "Model-free asymptotically best forecasting of stationary economic time series," Serie Research Memoranda 0032, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    • Handle: RePEc:vua:wpaper:1986-32
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    References listed on IDEAS

    as
    1. Bierens, Herman J., 1987. "Armax model specification testing, with an application to unemployment in the Netherlands," Journal of Econometrics, Elsevier, vol. 35(1), pages 161-190, May.
    2. White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-161, January.
    3. Shiller, Robert J., 1978. "Rational expectations and the dynamic structure of macroeconomic models : A critical review," Journal of Monetary Economics, Elsevier, vol. 4(1), pages 1-44, January.
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