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摘要翻译：
我们系统地研究了失业工人求职方案的效果异质性。为了研究可能的异质性就业效应，我们将非实验因果经验模型与拉索型估计量相结合。实证分析是基于瑞士社会保障记录中丰富的行政数据。我们只在训练开始后的前六个月发现相当大的异质性。与以往文献的结果一致，就业机会较少的失业者从参加这些方案中获益较多。此外，我们还证明了居住身份对就业的异质性影响。最后，我们展示了易于实施的方案参与规则对于改善这些活跃劳动力市场方案的平均就业效果的潜力。
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英文标题：
《Heterogeneous Employment Effects of Job Search Programmes: A Machine
Learning Approach》
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作者：
Michael Knaus, Michael Lechner, Anthony Strittmatter
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最新提交年份：
2018
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分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
We systematically investigate the effect heterogeneity of job search programmes for unemployed workers. To investigate possibly heterogeneous employment effects, we combine non-experimental causal empirical models with Lasso-type estimators. The empirical analyses are based on rich administrative data from Swiss social security records. We find considerable heterogeneities only during the first six months after the start of training. Consistent with previous results of the literature, unemployed persons with fewer employment opportunities profit more from participating in these programmes. Furthermore, we also document heterogeneous employment effects by residence status. Finally, we show the potential of easy-to-implement programme participation rules for improving average employment effects of these active labour market programmes.
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PDF链接：
https://arxiv.org/pdf/1709.10279
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