mhbounds - Sensitivity Analysis for Average Treatment Effects
AbstractMatching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly important topic in the applied evaluation literature. If there are unobserved variables which affect assignment into treatment and the outcome variable simultaneously, a hidden bias might arise to which matching estimators are not robust. We address this problem with the bounding approach proposed by Rosenbaum (2002), where mhbounds allows the researcher to determine how strongly an unmeasured variable must influence the selection process in order to undermine the implications of the matching analysis.
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Bibliographic InfoPaper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 659.
Length: 13 p.
Date of creation: 2007
Date of revision:
Publication status: Published in: The Stata Journal 7(2007) Iss.1, 71-83
matching; treatment effects; sensitivity analysis; unobserved heterogeneity;
Other versions of this item:
- Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
- Becker, Sascha O. & Caliendo, Marco, 2007. "mhbounds – Sensitivity Analysis for Average Treatment Effects," IZA Discussion Papers 2542, Institute for the Study of Labor (IZA).
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-01-28 (All new papers)
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