The name is absent

mhbounds - Sensitivity Analysis for Average
Treatment Effects

Working Paper

Abstract. Matching has become a popular approach to estimate average treat-
ment effects. It is based on the conditional independence or unconfoundedness
assumption. Checking the sensitivity of the estimated results with respect to de-
viations 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 hid-
den 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.

Keywords: matching, treatment effects, sensitivity analysis, unobserved hetero-
geneity

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