Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/56748
Year of Publication: 
2010
Series/Report no.: 
SFB 649 Discussion Paper No. 2010-059
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
We analyze the properties of non- and semiparametric estimation procedures involving nonparametric regression with generated covariates. Such estimators appear in numerous econometric applications, including nonparametric estimation of simultaneous equation models, sample selection models, treatment effect models, and censored regression models, but so far there seems to be no unified theory to establish their statistical properties. Our paper provides such results, allowing to establish asymptotic properties like rates of consistency or asymptotic normality for a wide range of semi- and nonparametric estimators. We also show how to account for the presence of nonparametrically generated regressors when computing standard errors.
Subjects: 
empirical process
propensity score
control variable methods
semiparametric estimation
JEL: 
C14
C31
Document Type: 
Working Paper

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