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Model-free Asymptotically Best Forecasting of Stationary Economic Time Series

Published online by Cambridge University Press:  11 February 2009

Herman J. Bierens
Herman J. Bierens
Affiliation:
Free University, Amsterdam
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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.

Type
Articles
Information
Econometric Theory , Volume 6 , Issue 3 , September 1990 , pp. 348 - 383
Copyright
Copyright © Cambridge University Press 1990

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