Journal Article

Inverse Probability Tilting for Moment Condition Models with Missing Data

Bryan S. Graham, Cristine Campos De Xavier Pinto and Daniel Egel

in The Review of Economic Studies

Published on behalf of Review of Economic Studies Ltd

Volume 79, issue 3, pages 1053-1079
Published in print July 2012 | ISSN: 0034-6527
Published online April 2012 | e-ISSN: 1467-937X | DOI: http://dx.doi.org/10.1093/restud/rdr047
Inverse Probability Tilting for Moment Condition Models with Missing Data

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  • Econometric and Statistical Methods and Methodology: General
  • Labour Discrimination
  • Demographic Economics
  • Single Equation Models; Single Variables

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We propose a new inverse probability weighting (IPW) estimator for moment condition models with missing data. Our estimator is easy to implement and compares favourably with existing IPW estimators, including augmented IPW estimators, in terms of efficiency, robustness, and higher-order bias. We illustrate our method with a study of the relationship between early Black–White differences in cognitive achievement and subsequent differences in adult earnings. In our data set, the early childhood achievement measure, the main regressor of interest, is missing for many units.

Keywords: Missing data; Semiparametric efficiency; Double robustness; (Augmented) Inverse probability; weighting (IPW); Higher-order comparisons; Black–White gap; Causal inference; Average treatment effect (ATE); C14; C21; C23; J15; J70

Journal Article.  10702 words.  Illustrated.

Subjects: Econometric and Statistical Methods and Methodology: General ; Labour Discrimination ; Demographic Economics ; Single Equation Models; Single Variables

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