Evaluation of Further Training Programmes with an Optimal Matching Algorithm
Eva Reinowski, Birgit Schultz, Jürgen Wiemers
Swiss Journal of Economics and Statistics,
2005
Abstract
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Evaluation of Further Training Programmes with an Optimal Matching Algorithm
Eva Reinowski, Birgit Schultz, Jürgen Wiemers
IWH Discussion Papers,
No. 188,
2004
Abstract
This study evaluates the effects of further training on the individual unemployment duration of different groups of persons representing individual characteristics and some aspects of the economic environment. The Micro Census Saxony enables us to include additional information about a person's employment history to eliminate the bias resulting from unobservable characteristics and to avoid Ashenfelter's Dip. In order to solve the sample selection problem we employ an optimal full matching assignment, the Hungarian algorithm. The impact of participation in further training is evaluated by comparing the unemployment duration between participants and non-participants using the Kaplan-Meier-estimator. Overall, we find empirical evidence that participation in further training programmes results in even longer unemployment duration.
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