Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/96680 
Year of Publication: 
2014
Series/Report no.: 
IZA Discussion Papers No. 8084
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
In this paper we study doubly robust estimators of various average treatment effects under unconfoundedness. We unify and extend much of the recent literature by providing a very general identification result which covers binary and multi-valued treatments; unnormalized and normalized weighting; and both inverse-probability weighted (IPW) and doubly robust estimators. We also allow for subpopulation-specific average treatment effects where subpopulations can be based on covariate values in an arbitrary way. Similar to Wooldridge (2007), we then discuss estimation of the conditional mean using quasi-log likelihoods (QLL) from the linear exponential family.
Subjects: 
double robustness
inverse-probability weighting (IPW)
multi-valued treatments
quasi-maximum likelihood estimation (QMLE)
treatment effects
JEL: 
C13
C21
C31
C51
Document Type: 
Working Paper

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