More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors

Zhijie Xiao, Oliver Linton, Raymond J. Carroll and Enno Mammen
Additional contact information
Raymond J. Carroll: Texas A&M Univ.

No 1375, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: We propose a modification of kernel time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that has to be estimated from the data. We establish the asymptotic distribution of our estimator under weak dependence conditions. It is shown that the proposed estimation procedure is more efficient than the conventional kernel method. We also provide simulation evidence to suggest that gains can be achieved in moderate sized samples.

Keywords: Time series regression; Nonparametric regression; Kernel; Efficiency (search for similar items in EconPapers)
Pages: 49 pages
Date: 2002-06
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Journal of Econometrics (February 2010), 154(2): 186-202

Downloads: (external link)
https://cowles.yale.edu/sites/default/files/files/pub/d13/d1375.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
Working Paper: More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors (2002)
Working Paper: More efficient kernel estimation in nonparametric regression with autocorrelated errors (2002)
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: https://EconPapers.repec.org/RePEc:cwl:cwldpp:1375

Ordering information: This working paper can be ordered from
Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
The price is None.

Access Statistics for this paper

More papers in Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University Yale University, Box 208281, New Haven, CT 06520-8281 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Brittany Ladd ().