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Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2019

Persistent link: https://www.econbiz.de/10012098947

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2020

Propensity Score Matching-Schätzer sind ein zentrales Tool, um Wirkungen aktiver Arbeitsmarktpolitik mit …Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation … of average treatment effects on the treated using a radius matching framework. Considering two popular methods, the …

Persistent link: https://www.econbiz.de/10012165548

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2019

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation … of average treatment effects on the treated using a radius matching framework. Considering two popular methods, the …

Persistent link: https://www.econbiz.de/10012060603

The finite sample performance of inference methods for propensity score matching and weighting estimators

Bodory, Hugo; Camponovo, Lorenzo; Huber, Martin; … - 2016

Persistent link: https://www.econbiz.de/10011717677

Decomposing a matching estimation : correlated unobserved non-random selection, substitution, and causal effects in a large scale ALMP Program in Germany ; conference paper

Brändle, Tobias; Fervers, Lukas; Webel, Carina - 2014 - Preliminary version

perform matching estimations to analyse the treatment effect on the treated. In the cross-section estimation, we find …-participants. Therefore, we combine matching with difference-in-difference estimation (to control for unobserved heterogeneity), Doing so, we … matching estimation can be decomposed into a causal effect (6%-points), correlated unobserved heterogeneity and negative spill …

Persistent link: https://www.econbiz.de/10010487257

The effectiveness of public sponsored training revisited : the importance of data and methodological choices

Biewen, Martin; Fitzenberger, Bernd; Osikominu, Aderonke; … - 2012

effects in the early 2000s. We employ a stratified propensity score matching approach to address dynamic selection into …

Persistent link: https://www.econbiz.de/10011345874

Evaluation of active labour market policy : methodological concepts and empirical estimates

Hujer, Reinhard; Caliendo, Marco - 2000

Persistently high unemployment, tight government budgets and the growing scepticism regarding the effects of active labour market policies (ALMP) are the basis for a growing interest in evaluating these measures. This paper intends to explain the need for evaluation on the micro- and...

Persistent link: https://www.econbiz.de/10011339682

Understanding program complementarities : estimating the dynamic effects of a training program with multiple alternatives

Dalla-Zuanna, Antonio; Liu, Kai - 2019

In this paper we estimate the causal effect of a training program for disadvantaged youths on their long-run labor market outcomes. Individuals receive lottery offers to participate in the program, but are allowed to choose when to leave the program and to participate in alternative programs. We...

Persistent link: https://www.econbiz.de/10012147080

Essays on causal inference in observational studies

Diamond, Alexis - 2008

Persistent link: https://www.econbiz.de/10010249157

Aktive Arbeitsmarktpolitik in Deutschland und der Schweiz : eine Gegenüberstellung

Behncke, Stefanie; Frölich, Markus; Lechner, Michael - 2006

Persistent link: https://www.econbiz.de/10003335645