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...

In the context of the ongoing reforms on European labour markets the keyword 'flexicurity' is presently gaining prominence. We therefore want to explore the importance of the flexicurity-concept on the example of the German Hartzreforms. Starting from the frequently used definition as a...

The European Commission declared 2022 the "European Year of Youth." Apart from the obvious aim to enhance its visibility and political legitimacy, the Commission responded to the fact that COVID-19 badly affected especially young people, manifested in the rise of youth unemployment and of youth...