We use a new and exceptionally rich administrative data set for Germany to evaluate the employment effects of a variety of public sponsored training programs in the early 2000s. Building on the work of Sianesi (2003, 2004), we employ propensity score matching methods in a dynamic, multiple...

New administrative data have recently permitted a differentiated and dynamic evaluation of the employment effects of measures of further vocational training in Germany which have been conducted in the context of active labour market policy. The data available for this purpose include firstly...

We use a new and exceptionally rich administrative data set for Germany to evaluate the employment effects of a variety of public sponsored training programs in the early 2000s. Building on the work of Sianesi (2003, 2004), we employ propensity score matching methods in a dynamic, multiple...

We use a new and exceptionally rich administrative data set for Germany to evaluate theemployment effects of a variety of public sponsored training programs in the early 2000s.Building on the work of Sianesi (2003, 2004), we employ propensity score matching methodsin a dynamic, multiple...

"New administrative data have recently permitted a differentiated and dynamic evaluation of the employment effects of measures of further vocational training in Germany which have been conducted in the context of active labour market policy. The data available for this purpose include firstly...

We use a new and exceptionally rich administrative data set for Germany to evaluate the employment effects of a variety of public sponsored training programs in the early 2000s. Building on the work of Sianesi (2003, 2004), we employ propensity score matching methods in a dynamic, multiple...

We use a new and exceptionally rich administrative data set for Germany to evaluate the employment effects of a variety of public sponsored training programs in the early 2000s. Building on the work of Sianesi (2003, 2004), we employ propensity score matching methods in a dynamic, multiple...