TY - JOUR
T1 - Evaluation of Language Training Programs in Luxembourg using Principal Stratification
AU - Bia, Michela
AU - Flores-Lagunes, Alfonso
AU - Mercatanti, Andrea
N1 - Funding Information:
FUNDING: European Social Fund Project: “Evaluation of Active Labor Market Policies in Luxembourg” – EvaLab4Lux, cofunded by the Ministry of Labour, Employment and the Social and Solidarity Economy of Luxembourg and LISER. CONFLICT OF INTEREST: the authors declare that they have no conflict of interest.
Funding Information:
Part of this work was done when Andrea Mercatanti worked as Researcher at LISER and at the Bank of Italy. Michela Bia and Andrea Mercatanti acknowledge financial support from the European Social Fund Project: “Evaluation of Active Labor Market Policies in Luxembourg” – EvaLab4Lux, cofunded by the Ministry of Labour, Employment and the Social and Solidarity Economy of Luxembourg and LISER.
Publisher Copyright:
© 2022 Michela Bia, Alfonso Flores-Lagunes and Andrea Mercatanti.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Language Training Programs
KW - Mixture Models
KW - Policy Evaluation
KW - Principal Stratification
KW - Sensitivity Analysis
KW - Unconfoundedness
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U2 - 10.1353/obs.2022.0001
DO - 10.1353/obs.2022.0001
M3 - Article
AN - SCOPUS:85133455295
SN - 2767-3324
VL - 8
JO - Observational Studies
JF - Observational Studies
IS - 1
ER -