生活色彩:亲自筛选会影响谁被录用吗?

John M. Barrios, Laura M. Giuliano, A. Leone
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引用次数: 1

摘要

在招聘新员工时,雇主通常会筛选大量的书面申请,然后再选择一小部分进行成本更高的面对面面试。大量文献表明,信息摩擦导致筛选不完美的质量信号——例如,教育背景和基于网络的推荐——这些做法会使劳动力市场的不平等永久化。理论上,降低现场筛查的成本可以减少对某些群体不利的生硬信号的使用,从而提高效率和公平性。我们通过研究劳动力市场中介的引入来检验这一假设,会计新秀训练营(ARC)极大地促进了劳动力市场对会计师博士的亲自筛选。我们使用了一个包含11年来新博士、招聘人员和市场结果信息的新数据集,估计了利用ARC采用时间变化的差异中的差异模型。我们发现,学位课程排名和顾问联系是初始就业安排的有力预测因素,但它们的影响因参与ARC而显着降低。结果表明,节目声誉和顾问网络的历史回报部分受到其信号价值的驱动,而ARC创建的新信息渠道降低了信号价值。他们还指出,在某些方面,采用ARC有助于促进招聘的更大多样性。同时,我们没有发现任何证据表明ARC减少了现有的性别分配差距,只有微弱的证据表明它有利于未被充分代表的少数民族。最后,使用人名来预测国籍和母语,我们发现ARC导致母语与英语差异很大的候选人的排名更差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Living Color: Does In-Person Screening Affect Who Gets Hired?
When hiring new workers, employers often screen large numbers of written applications before selecting a subset for more costly, in-person interviews. A large literature suggests that information frictions lead to screening on imperfect quality signals - e.g., educational pedigree and network-based referrals - and that these practices can perpetuate labor-market inequities. In theory, a reduction in the cost of in-person screening could lead to improvements in both efficiency and equity by reducing the use of blunt signals that disadvantage certain groups. We test this hypothesis by studying the introduction of a labor-market intermediary, the Accounting Rookie Camp (ARC), that greatly facilitated in-person screening in the labor market for PhD accountants. Using a novel data set with information on new PhDs, recruiters and market outcomes over 11 years, we estimate difference-in-difference models that leverage variation in the timing of ARC adoption. We find that degree program rank and adviser connectedness are strong predictors of initial job placements, but that their impacts are significantly reduced by participation in ARC. The results suggest that the historical returns to program reputation and adviser networks were driven partly by their signaling values, which were reduced by new the information channels created by ARC. They also indicate that in some respects, ARC adoption helped foster greater diversity in hiring. At the same time, we find no evidence that ARC reduced existing disparities in placements by gender and only weak evidence that it benefited under-represented minorities. Finally, using names to predict nationality and native language, we find that ARC led to worse placements for candidates whose native language is very different from English.
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