We estimate the short‐, medium‐, and long‐term effects of different types of government‐sponsored training in West Germany using particularly rich data that allows us to control for selectivity by matching methods and to measure interesting outcome variables over eight years after a program's start. We use distance‐weighted radius matching together with a bias removal procedure based on weighted regressions in order to increase the precision and robustness of standard matching estimators. We find negative employment effects in the short term for all program types, effects whose magnitude and persistence is directly related to program duration. In the longer term, training seems to increase employment rates by 10–20 percentage points. For most programs the longer‐term positive effects seem to be sustainable over the eight‐year observation period.

We investigate the finite sample properties of a large number of estimators for the average treatment effect on the treated that are suitable when adjustment for observed covariates is required, like inverse probability weighting, kernel and other variants of matching, as well as different parametric models. The simulation design used is based on real data usually employed for the evaluation of labour market programmes in Germany. We vary several dimensions of the design that are of practical importance, like sample size, the type of the outcome variable, and aspects of the selection process. We find that trimming individual observations with too much weight as well as the choice of tuning parameters are important for all estimators. A conclusion from our simulations is that a particular radius matching estimator combined with regression performs best overall, in particular when robustness to misspecifications of the propensity score and different types of outcome variables is considered an important property.

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We provide new evidence on the effectiveness of West German labour market programmes by evaluating training and employment programmes that have been conducted 2000-2002 after the first large reform of German labour market policy in 1998. We employ exceptionally rich administrative data that allow us to use microeconometric matching methods and to estimate interesting effects for different types of programmes and participants at a rather disaggregated level. We find that, on average, all programmes fail to improve their participants' chances of finding regular, unsubsidised employment. Rather, participants accumulate 2-13 more months of unemployment than nonparticipants over the 2.5 years following programme start, which, in addition to direct programme costs, induces net costs in terms of benefit payments and wage subsidies amounting to, on average, 1500-7000 EUR per participant. However, we show that there is some scope for improvements in mean employment rates as well as potential for considerable cost savings by a reallocation of participants and nonparticipants to the different programmes. Copyright 2008 Blackwell Publishing Ltd..