Evaluation of Language Training Programs in Luxembourg using Principal Stratification

Michela Bia, Alfonso Flores-Lagunes, Andrea Mercatanti

Research output: Contribution to journalArticlepeer-review

Abstract

In a world increasingly globalized, multiple language skills can create more employment opportu-nities. Several countries include language training programs in active labor market programs for the unemployed. We analyze the effects of a language training program on the re-employment probability and hourly wages simultaneously, using high-quality administrative data from Luxem-bourg. We address selection into training with an unconfoundedness assumption and account for the complication that wages are “truncated” by unemployment by adopting a principal stratification framework. Estimation is undertaken with a mixture model likelihood-based approach. To improve inference, we use the individual’s hours worked as a secondary outcome and a stochastic dominance assumption. These two features considerably ameliorate the multimodality problem commonly encountered in mixture models. We also conduct a sensitivity analysis to assess the unconfoundedness assumption. Our results suggest a positive effect (of up to 12.7 percent) of the language training programs on the re-employment probability, but no effects on wages for those who are observed employed regardless of training participation.

Original languageEnglish (US)
JournalObservational Studies
Volume8
Issue number1
DOIs
StatePublished - 2022

Keywords

  • Language Training Programs
  • Mixture Models
  • Policy Evaluation
  • Principal Stratification
  • Sensitivity Analysis
  • Unconfoundedness

ASJC Scopus subject areas

  • Applied Mathematics
  • Numerical Analysis
  • Statistics and Probability
  • Computer Science Applications
  • Modeling and Simulation

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