Nonparametric M-Estimation with Long-Memory Errors
Jan Beran,
Sucharita Gosh and
Philipp Sibbertsen
No 00/19, CoFE Discussion Papers from University of Konstanz, Center of Finance and Econometrics (CoFE)
Abstract:
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.
Date: 2000
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https://www.econstor.eu/bitstream/10419/85219/1/dp00-19.pdf (application/pdf)
Related works:
Working Paper: Nonparametric M-estimation with long-memory errors (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:cofedp:0019
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