Journal
JOURNAL OF ECONOMETRICS
Volume 141, Issue 2, Pages 1281-1301Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2007.02.002
Keywords
inverse probability weighting; sample selection; M-estimator; censored duration; average treatment effect
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Funding
- Economic and Social Research Council [RES-544-28-5001] Funding Source: researchfish
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I study inverse probability weighted M-estimation under a general missing data scheme. Examples include M-estimation with missing data due to a censored survival time, propensity score estimation of the average treatment effect in the linear exponential family, and variable probability sampling with observed retention 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 a general characterization of a double robustness result due to Scharfstein et al. [1999. Rejoinder. Journal of the American Statistical Association 94, 1135-1146]. (c) 2007 Elsevier B.V. All rights reserved.
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