Econ Papers Daily / 期刊论文
失业对劳动者、企业和市场收入的异质性影响
The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets
摘要
Using rich Swedish administrative data, we apply causal machine learning methods to study how earnings losses after job displacement vary with observable characteristics that may be relevant for targeting policy interventions for workers. Heterogeneity in effects is as large within as across worker groups defined by age and schooling, and as large within as across establishments. A substantial portion of cross-establishment heterogeneity can be explained by industry and local labor market characteristics, suggesting a role for place- and industry-based targeting. The largest losses are concentrated among already vulnerable workers, indicating that well-designed targeting policies can improve both efficiency and equity.
中文摘要
利用丰富的瑞典行政数据，我们运用因果机器学习方法研究失业后收入损失如何随可观测特征变化，这些特征可能与针对工人的政策干预定位相关。效应的异质性在由年龄和 schooling 定义的工人群体内部与群体之间一样大，在企业内部与企业之间也一样大。跨企业异质性的很大一部分可由行业和当地劳动力市场特征解释，这表明基于地点和行业的定位可能发挥作用。最大的损失集中在已经处于弱势的工人中，这表明设计良好的定位政策可以提高效率和公平性。