Propensity score matching provides an estimate of the effect of a treatment variable on an outcome variable that is largely free of bias arising from an association between treatment status and observable variables. However, matching methods are not robust against hidden bias arising from...

Aufgrund ihrer Nähe zum Konzept kontrafaktischer Kausalität haben nichtparametrische Matchingverfahren in der neueren statistischen und ökonometrischen Literatur zur Kausalanalyse an Bedeutung gewonnen. Vor diesem Hintergrund führt der Beitrag das Rubin Causal Model (RCM) in die...

Propensity score matching provides an estimate of the effect of a 'treatment' variable on an outcome variable that is largely free of bias arising from an association between treatment status and observable variables. However, matching methods are not robust against 'hidden bias' arising from...

Having close linkages with the counterfactual concept of causality, nonparametric matching estimators have recently gained in popularity in the statistical and econometric literature on causal analysis. Introducing key concepts of the Rubin causal model (RCM), the paper discusses the...