Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79298
Authors: 
Wooldridge, Jeffrey M.
Year of Publication: 
2004
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP05/04
Abstract: 
I study inverse probability weighted M-estimation under a general missing data scheme. The cases covered that do not previously appear in the literature include M-estimation with missing data due to a censored survival time, propensity score estimation of the average treatment effect for linear exponential family quasi-log-likelihood functions, and variable probability sampling with observed retainment frequencies. I extend an important result known to hold in special cases: estimating the selection probabilities is generally more efficient than if the known selection probabilities could be used in estimation. For the treatment effect case, the setup allows for a simple characterization of a double robustness result due to Scharfstein, Rotnitzky, and Robins (1999): given appropriate choices for the conditional mean function and quasi-log-likelihood function, only one of the conditional mean or selection probability needs to be correctly specified in order to consistently estimate the average treatment effect.
Subjects: 
Inverse Probability Weighting , Sample Selection , M-Estimator , Censored Duration , Average Treatment Effect
JEL: 
C13
C21
C23
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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