资历
分类
收益
分布(数学)
工资
人口经济学
业务
聚类分析
口译(哲学)
劳动经济学
经济
政治学
会计
计算机科学
机器学习
人工智能
数学分析
程序设计语言
法学
数学
作者
Jaime Arellano-Bover,Fernando Saltiel
摘要
We present evidence consistent with large disparities across firms in the on-the-job learning their young employees experience, using administrative datasets from Brazil and Italy. We categorize firms into discrete classes using a clustering methodology which groups together firms with similar distributions of unexplained earnings growth. Equipped with this categorization of firms-which our conceptual framework interprets as skill-learning classes-we document three main results. First, Mincerian returns to experience vary substantially across experiences acquired in different firm classes, and the magnitude of this heterogeneity is associated with significant shifts across the distribution of early-career wage growth. Second, past experience at firms with better on-the-job learning is associated with subsequent jobs featuring greater non-routine task content. Third, firms' observable characteristics only mildly predict on-the-job learning opportunities. Our findings hold among involuntarily displaced workers who have no seniority at their new jobs, which is consistent with a portable skills interpretation.
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