期刊名称：DIW Diskussionspapiere / Deutsches Institut für Wirtschaftsforschung, Berlin
出版年度：2007
卷号：2007
出版社：Deutsches Institut für Wirtschaftsforschung, Berlin
摘要：Matching 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.
