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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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Citations: View citations in EconPapers (1)

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https://www.econstor.eu/bitstream/10419/85219/1/dp00-19.pdf (application/pdf)

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Working Paper: Nonparametric M-estimation with long-memory errors (2000) Downloads
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