Nonparametric Regression with Nonparametrically Generated Covariates
نویسندگان
چکیده
In this paper, we analyze the properties of nonparametric estimators of a regression function when some covariates are not directly observed, but have only been estimated by some nonparametric procedure. We provide general results that can be used to establish rates of consistency or asymptotic normality in numerous econometric applications, including nonparametric estimation of simultaneous equation models, sample selection models, treatment effect models, and censored regression models. JEL Classification: C14, C31
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