Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79567 
Year of Publication: 
2012
Series/Report no.: 
SFB 649 Discussion Paper No. 2012-042
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
In many applications, covariates are not observed but have to be estimated from data. We outline some regression-type models where such a situation occurs and discuss estimation of the regression function in this context.We review theoretical results on how asymptotic properties of nonparametric estimators differ in the presence of generated covariates from the standard case where all covariates are observed. These results also extend to settings where the focus of interest is on average functionals of the regression function.
Subjects: 
Nonparametric estimation
generated covariates
JEL: 
C14
C31
Document Type: 
Working Paper

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