当前位置: X-MOL 学术Journal of Human Resources › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach
Journal of Human Resources ( IF 5.784 ) Pub Date : 2020-03-26 , DOI: 10.3368/jhr.57.2.0718-9615r1
Michael C. Knaus , Michael Lechner , Anthony Strittmatter

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.

中文翻译:

求职计划的异质就业效应:一种机器学习方法

我们系统地调查了失业工人求职计划的影响异质性。为了研究可能的异质就业效应,我们将非实验因果经验模型与套索型估计量相结合。实证分析基于来自瑞士社会保障记录的丰富行政数据。我们仅在训练开始后的前六个月发现了相当大的异质性。与之前的文献结果一致,就业机会较少的失业者从参与这些计划中获益更多。此外,我们还记录了居住身份的异质就业影响。最后,我们展示了易于实施的计划参与规则在改善这些活跃劳动力市场计划的平均就业影响方面的潜力。
更新日期:2020-03-26
down
wechat
bug