Evaluation of Language Training Programs in Luxembourg using Principal Stratification

Michela Bia, Alfonso Flores-Lagunes, Andrea Mercatanti
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引用次数: 1

Abstract

Abstract:In a world increasingly globalized, multiple language skills can create more employment opportunities. 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 Luxembourg. 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.
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用校长分层法评价卢森堡语言培训项目
摘要:在一个日益全球化的世界里,多种语言技能可以创造更多的就业机会。一些国家将语言培训项目纳入了针对失业者的活跃劳动力市场项目中。我们利用卢森堡的高质量行政数据,同时分析了语言培训计划对再就业概率和时薪的影响。我们以一种无根据的假设来解决培训的选择问题,并通过采用一个主要的分层框架来解释失业“截断”工资的复杂性。使用基于混合模型似然的方法进行估计。为了改进推理,我们使用个人的工作时间作为次要结果和随机优势假设。这两个特征大大改善了混合模型中常见的多模态问题。我们还进行了敏感性分析,以评估无根据性假设。我们的研究结果表明,语言培训项目对再就业概率有积极影响(高达12.7%),但对那些被观察到就业的人的工资没有影响,无论他们是否参加培训。
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