Model-free Asymptotically Best Forecasting of Stationary Economic Time Series

Herman J. Bierens

Econometric Theory, 1990, vol. 6, issue 03, pages 348-383

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.

Date: 1990

Downloads: (external link)
http://journals.cambridge.org/abstract_S0266466600005314 link to article abstract page (text/html)

Related works:
Working Paper: Model-free asymptotically best forecasting of stationary economic time series (1986)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:6:y:1990:i:03:p:348-383_00

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press
Address: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Series data maintained by Mike Eden ().