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Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes, Humboldt-Universität Berlin >
Discussion Papers, SFB 373, HU Berlin >
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http://hdl.handle.net/10419/62744
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| Title: | | A nonparametric regression estimator that adapts to error distribution of unknown form  |
| Authors: | | Linton, Oliver Bruce Xiao, Zhijie |
| Issue Date: | | 2001 |
| Series/Report no.: | | Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 2001,33 |
| Abstract: | | We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum likelihood estimator [Staniswalis (1989)], and hence improves on standard kernel estimators when the error distribution is not normal. We investigate the finite sample performance of our procedure on simulated data. |
| Subjects: | | Adaptive Estimation Asymptotic Expansions Efficiency Kernel Local Likelihood Estimation Nonparametrie Regression |
| JEL: | | C13 C14 C24 |
| Persistent Identifier of the first edition: | | urn:nbn:de:kobv:11-10049681 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Discussion Papers, SFB 373, HU Berlin
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