Nonparametric M-Estimation with Long-Memory Errors

We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind this study is illustrated with an example.

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Year of publication:	2000-06
Authors:	Beran, Jan ; Gosh, Sucharita ; Sibbertsen, Philipp
Institutions:	Zentrum für Finanzen und Ökonometrie, Fachbereich Wirtschaftswissenschaften

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Extent:	application/pdf
Series:	CoFE Discussion Paper.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 00-19 9 pages longPages
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005357905