Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/89964 
Year of Publication: 
2013
Series/Report no.: 
IZA Discussion Papers No. 7564
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step, but retain a fully nonparametric specification in the first step. Such estimators exist in many economic applications, including a wide range of missing data and treatment effect models. We show that these estimators are √n-consistent and asymptotically normal under weaker than usual conditions on the accuracy of the first stage estimates, have smaller first order bias and second order variance, and that their finite-sample distribution can be approximated more accurately by classical first order asymptotics. We argue that because of these refinements our estimators are useful in many settings where semiparametric estimation and inference are traditionally believed to be unreliable. We also illustrate the practical relevance of our approach through simulations and an empirical application.
Subjects: 
semiparametric model
missing data
treatment effects
doubly robust estimation
higher order asymptotics
JEL: 
C14
C21
C31
C51
Document Type: 
Working Paper

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