Everybody’s got to learn sometime? A causal machine learning evaluation of training programmes for jobseekers in France
用改进因果森林方法评估法国三种职业培训对求职者重返就业的异质性影响，发现短期存在负锁定效应，仅资格培训有积极中期效果，且对外国出生者等群体更有效。
This paper estimates the heterogeneous impact of three types of vocational training- preparation, qualifying, and combined – on jobseekers’ return to employment using the Modified Causal Forest method. Analysing data from 33,699 individuals over 24 months, it reveals a short-term negative lock-in effect for all programmes, persisting in the medium term for combined training. Only qualifying training shows a positive medium-term effect. Seniors, low-skilled, foreign-born, and those with poor job histories benefit most, while youth and higher education levels benefit less. Targeting foreign-born individuals could significantly enhance programme effectiveness, as indicated by the clustering analysis and optimal policy trees.