Sensitivity analysis for average treatment effects
Based on the conditional independence or unconfoundedness assump- tion, matching has become a popular approach to estimate average treatment effects. Checking the sensitivity of the estimated results with respect to devia- tions from this identifying assumption has become an increasingly important topic in the applied evaluation literature. If there are unobserved variables that affect assignment into treatment and the outcome variable simultaneously, a hidden bias might arise to which matching estimators are not robust. We address this prob- lem with the bounding approach proposed by Rosenbaum (Observational Studies, 2nd ed., New York: Springer), where mhbounds lets the researcher determine how strongly an unmeasured variable must influence the selection process to undermine the implications of the matching analysis. Copyright 2007 by StataCorp LP.
Volume (Year): 7 (2007)
Issue (Month): 1 (February)
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- DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, Social Science Research Center Berlin (WZB).
- Manski, C.F., 1992. "Identification Problems in the Social Sciences," Working papers 9217, Wisconsin Madison - Social Systems.
- Caliendo, Marco & Kopeinig, Sabine, 2005.
"Some Practical Guidance for the Implementation of Propensity Score Matching,"
IZA Discussion Papers
1588, Institute for the Study of Labor (IZA).
- Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, 02.
- Marco Caliendo & Sabine Kopeinig, 2005. "Some Practical Guidance for the Implementation of Propensity Score Matching," Discussion Papers of DIW Berlin 485, DIW Berlin, German Institute for Economic Research.
- James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998.
"Characterizing Selection Bias Using Experimental Data,"
NBER Working Papers
6699, National Bureau of Economic Research, Inc.
- James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
- Tommaso Nannicini, 2006.
"A Simulation-Based Sensitivity Analysis for Matching Estimators,"
North American Stata Users' Group Meetings 2006
6, Stata Users Group.
- Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
- Tommaso Nannicini, 2009. "A simulation-based sensitivity analysis for matching estimators," Italian Stata Users' Group Meetings 2008 05, Stata Users Group.
- A. Smith, Jeffrey & E. Todd, Petra, 2005.
"Does matching overcome LaLonde's critique of nonexperimental estimators?,"
Journal of Econometrics,
Elsevier, vol. 125(1-2), pages 305-353.
- Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20035, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Caliendo, Marco & Hujer, Reinhard & Thomsen, Stephan L., 2005. "The Employment Effects of Job Creation Schemes in Germany: A Microeconometric Evaluation," IZA Discussion Papers 1512, Institute for the Study of Labor (IZA).
- Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
- Ichino, Andrea & Mealli, Fabrizia & Nannicini, Tommaso, 2006.
"From Temporary Help Jobs to Permanent Employment: What Can We Learn from Matching Estimators and their Sensitivity?,"
IZA Discussion Papers
2149, Institute for the Study of Labor (IZA).
- Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
- Ichino, Andrea & Mealli, Fabrizia & Nannicini, Tommaso, 2006. "From Temporary Help Jobs to Permanent Employment: What Can We Learn from Matching Estimators and their Sensitivity?," CEPR Discussion Papers 5736, C.E.P.R. Discussion Papers.
- Manski, Charles F, 1990.
"Nonparametric Bounds on Treatment Effects,"
American Economic Review,
American Economic Association, vol. 80(2), pages 319-23, May.
- LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
- Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
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