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Nonparametric Kernel Estimation for Semiparametric Models

Published online by Cambridge University Press:  11 February 2009

Donald W.K. Andrews
Donald W.K. Andrews
Affiliation:
Cowles Foundation for Research in Economics, Yale University
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Abstract

This paper presents a number of consistency results for nonparametric kernel estimators of density and regression functions and their derivatives. These results are particularly useful in semiparametric estimation and testing problems that rely on preliminary nonparametric estimators, as in Andrews (1994, Econometrica 62, 43–72). The results allow for near-epoch dependent, nonidentically distributed random variables, data-dependent bandwidth sequences, preliminary estimation of parameters (e.g., nonparametric regression based on residuals), and nonparametric regression on index functions.

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Articles
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Econometric Theory , Volume 11 , Issue 3 , June 1995 , pp. 560 - 586
Copyright
Copyright © Cambridge University Press 1995

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