Generated covariates in nonparametric estimation: A short review

Enno Mammen, Christoph Rothe and Melanie Schienle

No 2012-042, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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.

Keywords: Nonparametric estimation; generated covariates (search for similar items in EconPapers)
JEL-codes: C14 C31 (search for similar items in EconPapers)
Date: 2012
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