Robustness to Parametric Assumptions in Missing Data Models
We consider estimation of population averages when data are missing at random. If some cells contain few observations, there can be substantial gains from imposing parametric restrictions on the cell means, but there is also a danger of misspecification. We develop a simple empirical Bayes estimator, which combines parametric and unadjusted estimates of cell means in a data-driven way. We also consider ways to use knowledge of the form of the propensity score to increase robustness. We develop an empirical Bayes extension of a double robust estimator. In a small simulation study, the empirical Bayes estimators perform well. They are similar to fully nonparametric methods and robust to misspecification when cells are moderate to large in size, and when cells are small they maintain the benefits of parametric methods and can have lower sampling variance.
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Volume (Year): 101 (2011)
Issue (Month): 3 (May)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lee, David S. & Card, David, 2008.
"Regression discontinuity inference with specification error,"
Journal of Econometrics,
Elsevier, vol. 142(2), pages 655-674, February.
- David S. Lee & David Card, 2006. "Regression Discontinuity Inference with Specification Error," NBER Technical Working Papers 0322, National Bureau of Economic Research, Inc.
- Guido M. Imbens & Jeffrey M. Wooldridge, 2008.
"Recent Developments in the Econometrics of Program Evaluation,"
NBER Working Papers
14251, National Bureau of Economic Research, Inc.
- Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
- Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute for the Study of Labor (IZA).
- Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
- Guido Imbens & Jeffrey Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Joshua Angrist & Jinyong Hahn, 2004. "When to Control for Covariates? Panel Asymptotics for Estimates of Treatment Effects," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 58-72, February.
- Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2008.
"Inverse Probability Tilting for Moment Condition Models with Missing Data,"
NBER Working Papers
13981, National Bureau of Economic Research, Inc.
- Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," Review of Economic Studies, Oxford University Press, vol. 79(3), pages 1053-1079.
- Wooldridge, Jeffrey M., 2007.
"Inverse probability weighted estimation for general missing data problems,"
Journal of Econometrics,
Elsevier, vol. 141(2), pages 1281-1301, December.
- Jeffrey M. Wooldridge, 2004. "Inverse probability weighted estimation for general missing data problems," CeMMAP working papers CWP05/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chen, Xiaohong & Hong, Han & Tarozzi, Alessandro, 2008.
"Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects,"
42, Yale University, Department of Economics.
- Xiaohong Chen & Han Hong & Alessandro Tarozzi, 2008. "Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects," Cowles Foundation Discussion Papers 1644, Cowles Foundation for Research in Economics, Yale University.
- Weihua Cao & Anastasios A. Tsiatis & Marie Davidian, 2009. "Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data," Biometrika, Biometrika Trust, vol. 96(3), pages 723-734.
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