By Jochen Kluve, David Card, Michael Fertig, Marek Góra, Lena Jacobi, Peter Jensen, Reelika Leetmaa, Leonhard Nima, Eleonora Patacchini, Sandra Schaffner, Christoph M. Schmidt, Bas van der Klaauw, Andrea Weber
Measures of lively hard work marketplace coverage - similar to education, salary subsidies, public employment measures, and activity seek advice - are normal in ecu nations to wrestle unemployment. Little, although, is understood approximately what every one nation can examine from stories in different nations. This research offers novel perception in this vital coverage factor through discussing the function of the ecu Commission's Employment method, reviewing the studies made in eu states, and giving the 1st ever quantitative evaluation of the present cross-country facts, answering the query "what exertions industry application works for what objective crew lower than what (economic and institutional) circumstances?". utilizing an cutting edge meta-analytical process, the authors locate that instead of contextual elements equivalent to hard work marketplace associations or the company cycle, it's nearly completely this system style that issues for application effectiveness: whereas direct employment courses within the public region look dangerous, salary subsidies and "Services and Sanctions" may be powerful in expanding members' employment probability.
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Additional info for Active Labor Market Policies in Europe: Performance and Perspectives
In addition, ALMPs may reallocate the work force from low-pro- 32 Chapter 2: An overview of Active Labor Market Policies ductivity sectors to high-productivity sectors (Calmfors et al. 2002). Furthermore, active measures may have a positive impact on labor force participation. They may maintain the size of the labor force by reducing the risk of long-term unemployed leaving the labor force. In addition to the positive effects, labor market interventions might have some unintended and detrimental effects not only on participants but also on non-treated individuals.
Comparison of exact matches The principal idea of exact matching is to assign to one or more of the individuals i in the treatment sample as matching partners one or more individuals from the non-experimental control sample who are similar in terms of their observed individual characteristics. That is, the exact match procedure specifies the most general possible model of post-intervention outcomes in terms of the observable data (pre-intervention histories and education, say). The central identification assumption is that for individuals that are characterized by any specific configuration of observable characteristics, the participation decision is independent of any unobservable determinant of the post-intervention outcome4, (5) 4 E(Yt | X , Yt' , D = 1) = E(Yt | X , Yt' , D = 0).
Its validity facilitates a manageable formal setup; nevertheless, in practical applications it is frequently questionable whether it holds. Unfortunately, and this is the core of the evaluation problem, we can never observe Yti and Yti + ∆ i simultaneously for a given individual – a worker can either participate in the training or not. Instead, only one of these two outcome variables can actually be observed for each individual i. That is, the outcome Yti is the counterfactual outcome for those individuals who do participate in the program (Di = 1), whereas Yti + ∆ i is the counterfactual outcome for non-participants (Di = 0).