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Effectiveness of sequences of classroom training for welfare recipients: what works best in West Germany?

Author

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  • Katharina Dengler

Abstract

Sequences of active labour market programmes (ALMPs) may be part of an intensified activation strategy targeting hard-to-place unemployed individuals. Such sequences are very common among welfare recipients in Germany, but most studies only evaluate either single ALMPs or unemployed individuals’ first ALMP. I analyse the effects of different sequences of classroom training for West German men and women on different labour market outcomes. Using rich administrative data and a dynamic causal model, I can control for dynamic selection problems that occur during a sequence. The results show that two classroom trainings are more effective than two periods of welfare receipt in helping welfare recipients find regular employment, especially among West German women. Moreover, immediately assigning individuals to classroom training is more effective than waiting and assigning them to classroom training in the second period. However, in some cases, avoiding participation in multiple programmes is preferable.Abbreviations: ALMP, active labour market programme; CIA, Conditional Independence Assumption; CSR, Common Support Requirement; DATET, dynamic average treatment effect on the treated; IEB, Integrated Employment Biographies; IPW, inverse probability weighting; LHG, UBII-Receipt History (Leistungshistorik Grundsicherung); MSB, mean standardized absolute bias; SUTVA, Stable Unit Treatment Value Assumption; UBII, unemployment benefit II; UBI, unemployment benefit I; WDCIA, Weak Dynamic Conditional Independence Assumption

Suggested Citation

  • Katharina Dengler, 2019. "Effectiveness of sequences of classroom training for welfare recipients: what works best in West Germany?," Applied Economics, Taylor & Francis Journals, vol. 51(1), pages 1-46, January.
  • Handle: RePEc:taf:applec:v:51:y:2019:i:1:p:1-46
    DOI: 10.1080/00036846.2018.1489110
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    Cited by:

    1. Garloff, Alfred, 2016. "Side effects of the new German minimum wage on (un-)employment : first evidence from regional data," IAB-Discussion Paper 201631, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Fabian Muny, 2025. "Evaluating Program Sequences with Double Machine Learning: An Application to Labor Market Policies," Papers 2506.11960, arXiv.org.
    3. Dauth, Christine, 2016. "Gender gaps of the unemployed - What drives diverging labor market outcomes?," IAB-Discussion Paper 201627, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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