论文标题
统计歧视的搜索模型
A Search Model of Statistical Discrimination
论文作者
论文摘要
我们提供了统计歧视的搜索理论模型，在该模型中，公司根据职业选择不平等地对待相同的群体。该模型接受了对称平衡，其中忽略了组特征，但也不对称一个群体在统计上被歧视，即使在对称平衡是唯一的情况下。此外，强大的可能性是当引入群体特征时，对称平衡变得不稳定。与大多数以前的文献不同，我们的模型可以证明平权行动是合理的，因为它消除了不对称的平衡而不会扭曲激励措施。
We offer a search-theoretic model of statistical discrimination, in which firms treat identical groups unequally based on their occupational choices. The model admits symmetric equilibria in which the group characteristic is ignored, but also asymmetric equilibria in which a group is statistically discriminated against, even when symmetric equilibria are unique. Moreover, a robust possibility is that symmetric equilibria become unstable when the group characteristic is introduced. Unlike most previous literature, our model can justify affirmative action since it eliminates asymmetric equilibria without distorting incentives.
