TY  - RPRT
        AU  - Rothe, Christoph
AU  - Firpo, Sergio
        TI  - Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions
        PY  - 2013/Aug/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 7564
        UR  - https://www.iza.org/index.php/publications/dp7564
        AB  - 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.
        KW  - semiparametric model
KW  - missing data
KW  - treatment effects
KW  - doubly robust estimation
KW  - higher order asymptotics
        ER  -