New evidence on the finite sample properties of propensity score reweighting and matching estimators

Review of Economics and Statistics

Volumn 96, Issue 5, 2014, Pages 885-897

  Busso, Matias ^a   DiNardo, John ^b,c   McCrary, Justin ^c,d  

^a INTER AMERICAN DEVELOPMENT BANK   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c NATIONAL BUREAU OF ECONOMIC RESEARCH   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84919832679     PISSN: 00346535     EISSN: 15309142     Source Type: Journal    
DOI: 10.1162/REST_a_00431     Document Type: Article

References (32)

1. Abadie, Alberto, and Guido W. Imbens, "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica 74 (2006)(1), 235-267.
2. Abadie, Alberto, "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business and Economic Statistics 2 (2011), 1-11.
3. Abadie, Alberto, "Matching on the Estimated Propensity Score," Harvard University working paper (2012).
4. Abadie, Alberto, David Drukker, Jane Leber Herr, and Guido Imbens, "Implementing Matching Estimators for Average Treatment Effects in STATA," Stata Journal 4 (2004), 290-311.
5. Black, Dan A., and Jeffrey A. Smith, "How Robust Is the Evidence on the Effects of College Quality? Evidence from Matching," Journal of Econometrics 121 (2004), 99-124.
6. Dehejia, Rajeev H., and Sadek Wahba, "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," in Rajeev H. Dehejia, ed., Econometric Methods for Program Evaluation (Cambridge, MA: Harvard University, 1997).
7. Dehejia, Rajeev H., "Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs," Journal of the American Statistical Association 448a (1999), 1053-1062.
8. Drake, Christiana, "Effects of Misspecification of the Propensity Score on Estimators of Treatment Effect," Biometrics 49 (1993), 1231-1236.
9. Flossmann, Anton, "Empirical Bias Bandwidth Choice for Local Polynomial Matching Estimators," University of Konstanz working paper (2007).
10. Flossmann, Anton, "Optimal Bandwidth Choice for Matching Estimators by Double Smoothing," University of Konstanz working paper (2008).
11. Frölich, Markus, "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," this review 86 (2004), 77-90.
12. Galdo, Jose, Jeffrey Smith, and Dan Black, "Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data," Annals of Economics and Statistics 91-92 (2008), 189-216.
13. Graham, Bryan S., Cristine Campos de Xavier Pinto, and Daniel Egel, "Inverse Probability Tilting for Moment Condition Models with Missing Data," Review of Economic Studies 79 (2012), 1053-1079.
14. Heckman, James J., Hidehiko Ichimura, and Petra Todd, "Matching as an Econometric Evaluation Estimator," Review of Economic Studies 65 (1998), 261-294.
15. Hirano, Keisuke, Guido W. Imbens, and Geert Ridder, "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica 71 (2003), 1161-1189.
16. Horvitz, Daniel G., and Donovan J. Thompson, "A Generalization of Sampling without Replacement from a Finite Universe," Journal of the American Statistical Association 47 (1952), 663-685.
17. Huber, Martin, Michael Lechner, and Conny Wunsch, "How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score," IZA discussion paper 5268 (2010).
18. Huber, Martin, "The Performance of Estimators Based on the Propensity Score," Journal of Econometrics 175 (2013), 1-21.
19. Imbens, Guido W., "Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review," Review of Economics and Statistics 86 (2004), 4-29.
20. Kang, Joseph D. Y., and Joseph L. Schafer, "Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data," Statistical Science 22 (2007), 523-539.
21. Khan, Shakeeb, and Elie Tamer, "Irregular Identification, Support Conditions and Inverse Weight Estimation," Econometrica 78 (2010), 2021-2042.
22. Lunceford, Jared K., and Marie Davidian, "Stratification and Weighting via the Propensity Score in Estimation of Causal Treatment Effects: A Comparative Study," Statistics in Medicine 23 (2004), 2937-2960.
23. Robins, James M., Andrea Rotnitzky, and Lue Ping Zhao, "Estimation of Regression Coefficients When Some Regressors Are Not Always Observed," Journal of the American Statistical Association 89 (1994), 846-866.
24. Robins, James, Mariela Sued, Quanhong Lei-Gomez, and Andrea Rotnitzky, "Comment: Performance of Double-Robust Estimators When Inverse Probability Weights Are Highly Variable," Statistical Science 22 (2007), 544-559.
25. Rosenbaum, Paul R., "Model-Based Direct Adjustment," Journal of the American Statistical Association 82 (1987), 387-394.
26. Rosenbaum, Paul R., and Donald B. Rubin, "The Central Role of the Propensity Score in Observational Studies for Causal Effects," Biometrika 70 (1983), 41-55.
27. Rubin, Donald B., "Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies," Journal of Educational Psychology 66 (1974), 688-701.
28. Seifert, Burkhardt, and Theo Gasser, "Data Adaptive Ridging in Local Polynomial Regression," Journal of Computational and Graphical Statistics 9 (2000), 338-360.
29. Smith, Jeff, and Petra Todd, "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?" Journal of Econometrics 125 (2005), 305-353.
30. Tan, Zhiqiang, "Bounded, Efficient, and Doubly Robust Estimation with Inverse Weighting," Biometrika 97 (2010), 661-682.
31. Wooldridge, Jeffrey M., Econometric Analysis of Cross Section and Panel Data (Cambridge, MA: MIT Press, 2002).
32. Wooldridge, Jeffrey M., "Inverse Probability Weighted Estimation for General Missing Data Problems," Journal of Econometrics 141 (2007), 1281-1301.