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Nonparametric Censored and Truncated Regression
Author(s) -
Lewbel Arthur,
Linton Oliver
Publication year - 2002
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.1111/1468-0262.00304
Subject(s) - nonparametric statistics , econometrics , nonparametric regression , statistics , regression , mathematics , regression analysis , cross sectional regression , censored regression model , economics , polynomial regression
This paper proposes new estimators of the latent regression function in nonparametric censored and truncated regression models. Our estimators are computationally convenient, consisting only of two nonparametric regressions and a univariate integral. We establish consistency and asymptotic normality for an implementation based on local linear kernel estimators. An extension permits estimation in the presence of a general form of heteroscedasticity.