Racial Gaps, Occupational Matching, and Skill Uncertainty

Limor Golan, Carl Sanders
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引用次数: 1

Abstract

White workers in the United States earn almost 30 percent more per hour on average than Black workers, and this wage gap is associated with large racial differences in occupational assignments. In this article, we theoretically and empirically examine the Black-White disparity in occupations. First, we present a model based on Antonovics and Golan (2012) that relates occupational assignments to the incentives workers face while learning about their own unknown ability. Second, we document differences between Black and White workers in both the complexity of skills required in their initial occupations and the growth rates of this complexity over time. To do this, we match panel data from the National Longitudinal Survey of Youth 1979 with the Dictionary of Occupational Titles measures of occupational characteristics and find that, compared with White workers, Black workers start in occupations requiring less-complex skills, see slower growth in job complexity over time, and are relatively more likely to transition to jobs with lower complexity. Finally, we consider the relationship between our model and our empirical findings; for example, discrimination in hiring early in the career can have long-term consequences on the ability of Black workers to learn their best occupational match and explains part of their lower wage growth. We conclude with suggestions for policy and future research directions.
种族差距、职业匹配和技能不确定性
在美国,白人工人每小时的平均收入比黑人工人高出近30%,这种工资差距与职业任务的巨大种族差异有关。在这篇文章中,我们从理论上和实证上考察了黑人和白人在职业上的差异。首先,我们提出了一个基于Antonovics和Golan(2012)的模型,该模型将职业分配与员工在了解自己未知能力时面临的激励联系起来。其次,我们记录了黑人和白人工人在其初始职业所需技能的复杂性以及这种复杂性随时间增长的速度方面的差异。为了做到这一点,我们将1979年全国青年纵向调查的面板数据与职业头衔词典的职业特征测量相匹配,发现与白人工人相比,黑人工人从需要不太复杂技能的职业开始,随着时间的推移,工作复杂性的增长速度较慢,并且相对更有可能过渡到复杂性较低的工作。最后,我们考虑了我们的模型和实证结果之间的关系;例如,在职业生涯早期招聘中的歧视可能会对黑人工人找到最佳职业匹配的能力产生长期影响,并在一定程度上解释了他们工资增长较低的原因。最后提出了政策建议和未来的研究方向。
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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