ABSTRACT This paper develops a dynamic model of minority labor market discrimination. Employers repeatedly decide to hire either minority or majority job candidates whose productivities are unobservable beforehand. Hiring decisions are based on productivity expectations derived from the observable productivity of employers’ previously hired workers. If employers have fewer minority workers initially—a plausible assumption for (numerical) minorities—they discriminate against minority workers over time. Discrimination results from more dispersed minority expectations across the employer population and stronger effects of additional productivity observations on minority expectations. Both effects are a direct consequence of the minority’s initial underrepresentation in firms. I demonstrate the emergence of minority discrimination formally in a two-period hiring model and show simulation results for longer time frames.

中文翻译：

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劳动力市场代表性不足导致少数族裔歧视：雇主学习的动态招聘模式

摘要 本文开发了少数民族劳动力市场歧视的动态模型。雇主一再决定雇佣少数或多数的求职者，他们的生产力事先无法观察到。招聘决定是基于从雇主以前雇用的工人的可观察生产力得出的生产力预期。如果雇主最初拥有较少的少数族裔工人——这是（数字上的）少数族裔的合理假设——他们会随着时间的推移歧视少数族裔工人。歧视源于雇主群体中更分散的少数群体期望，以及额外的生产力观察对少数群体期望的更大影响。这两种影响都是少数族裔最初在公司中代表性不足的直接后果。