In the second part of the 1990?s Switzerland conducted an ambitious active labour market policy (ALMP) encompassing a wide variety of programmes. We evaluate the effects of these programmes on the individual employment probability of potential participants. Our econometric analysis uses...

This paper investigates the link between variation in the supply of workers who participate in specific types of active labour market policies (ALMPs) and firm performance using a new exceptionally informative German employer-employee data base. For identification we exploit that German local...

Based on new, exceptionally informative and large German linked employer-employee administrative data, we investigate the question whether the omission of important control variables in matching estimation leads to biased impact estimates of typical active labour market programs for the...

We analyse the effects of government-sponsored training for the unemployed conducted during East German transition. For the microeconometric analysis, we use a new, large and informative administrative database that allows us to use matching methods to reduce potential selection bias, to study...

Using exceptionally rich linked administrative and survey information on German welfare recipients we investigate the health effects of transitions from welfare to employment and of assignments to welfare-to-work programmes. Applying semi-parametric propensity score matching estimators we find...

We estimate short, medium, and long-run individual labor market effects of training programs for unemployed by following program participation on a monthly basis over a ten-year period. Since analyzing the effectiveness of training over such a long period is impossible with experimental data, we...

Uncovering the heterogeneity of causal effects of policies and business decisions at various levels of granularity provides substantial value to decision makers. This paper develops new estimation and inference procedures for multiple treatment models in a selection-on-observables frame-work by...

We investigate heterogenous employment effects of Flemish training programmes. Based on administrative individual data, we analyse programme effects at various aggregation levels using Modified Causal Forests (MCF), a causal machine learning estimator for multiple programmes. While all...

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...

We evaluate a randomized experiment of a statistical support system developed to assistcaseworkers in Swiss employment offices in choosing appropriate active labour marketprogrammes for their unemployed clients. This statistical support system predicted the labourmarket outcome for each...