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Efficient Estimation of Data Combination Models by the Method of Auxiliary-to-Study Tilting (AST)

  • Bryan S. Graham
  • Cristine Campos de Xavier Pinto
  • Daniel Egel

We propose a locally efficient estimator for a class of semiparametric data combination problems. A leading estimand in this class is the Average Treatment Effect on the Treated (ATT). Data combination problems are related to, but distinct from, the class of missing data problems analyzed by Robins, Rotnitzky and Zhao (1994) (of which the Average Treatment Effect (ATE) estimand is a special case). Our estimator also possesses a double robustness property. Our procedure may be used to efficiently estimate, among other objects, the ATT, the two-sample instrumental variables model (TSIV), counterfactual distributions, poverty maps, and semiparametric difference-in-differences. In an empirical application we use our procedure to characterize residual Black-White wage inequality after flexibly controlling for 'pre-market' differences in measured cognitive achievement as in Neal and Johnson (1996).

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16928.

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Date of creation: Apr 2011
Date of revision:
Handle: RePEc:nbr:nberwo:16928
Note: LS TWP
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  1. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, Elsevier.
  2. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, 01.
  3. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
  4. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, 07.
  5. 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.
  6. Guido W. Imbens & Judith K. Hellerstein, 1996. "Imposing Moment Restrictions from Auxiliary Data by Weighting," NBER Technical Working Papers 0202, National Bureau of Economic Research, Inc.
  7. Barsky R. & Bound J. & Charles K.K. & Lupton J.P., 2002. "Accounting for the Black-White Wealth Gap: A Nonparametric Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 663-673, September.
  8. Patrick Kline, 2011. "Oaxaca-Blinder as a Reweighting Estimator," American Economic Review, American Economic Association, vol. 101(3), pages 532-37, May.
  9. William A. Darity & Patrick L. Mason, 1998. "Evidence on Discrimination in Employment: Codes of Color, Codes of Gender," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 63-90, Spring.
  10. Neal, Derek A & Johnson, William R, 1996. "The Role of Premarket Factors in Black-White Wage Differences," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 869-95, October.
  11. Dinardo, J. & Fortin, N.M. & Lemieux, T., 1994. "Labor Market Institutions and the Distribution of Wages, 1973-1992: a Semiparametric Approach," Cahiers de recherche 9406, Universite de Montreal, Departement de sciences economiques.
  12. J. Currie & A. Yelowitz, . "Are Public Housing Projects Good For Kids?," Institute for Research on Poverty Discussion Papers 1152-97, University of Wisconsin Institute for Research on Poverty.
  13. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
  14. Bryan S. Graham, 2008. "Efficiency bounds for missing data models with semiparametric restrictions," NBER Working Papers 14376, National Bureau of Economic Research, Inc.
  15. Alessandro Tarozzi & Angus Deaton, 2009. "Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 773-792, November.
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