Anatomy of Lifetime Earnings Inequality: Heterogeneity in Job-Ladder Risk versus Human Capital

Serdar Ozkan, Jae Song, Fatih Karahan
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Abstract

We study the determinants of lifetime earnings (LE) inequality in the United States by focusing on latent heterogeneity in job-ladder dynamics and on-the-job learning. We use administrative data to document a novel set of moments on job mobility and earnings growth across the LE distribution. We then estimate a structural model featuring a rich set of worker types and firm heterogeneity. We find vast ex ante differences in job-loss, job-finding, and contact rates across worker types. These differences account for 75% of the lifetime wage growth differential among the bottom half of the LE distribution. Above the median, almost all lifetime wage growth differences are a result of Pareto-distributed learning ability.
终身收入不平等剖析:工作阶梯风险与人力资本的异质性
我们通过关注工作阶梯动态和在职学习的潜在异质性来研究美国终身收入不平等的决定因素。我们使用管理数据来记录整个LE分布中工作流动性和收入增长的一系列新时刻。然后,我们估计了一个具有丰富的工人类型和企业异质性的结构模型。我们发现,不同类型的工人在失业、找工作和接触率方面存在巨大的事前差异。这些差异占了收入分配后一半人群终生工资增长差异的75%。在中位数以上,几乎所有的终生工资增长差异都是帕累托分布学习能力的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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