Nonparametric Kernel Estimation for Semiparametric Models
- 1 June 1995
- journal article
- research article
- Published by Cambridge University Press (CUP) in Econometric Theory
- Vol. 11 (3) , 560-586
- https://doi.org/10.1017/s0266466600009427
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.Keywords
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