中文摘要
我研究由雇主因与工人群体的个体经历而产生的歧视。我提出一个模型，其中雇主对两个群体中某一群体的生产率存在不确定性，并通过雇佣进行学习。积极的经历会导致正向偏差，这种偏差会通过带来更多雇佣和学习而自我纠正。消极的经历会减少雇佣和学习，从而维持负向偏差，并可能导致持续性歧视。该模型将偏见解释为不正确的统计性歧视，并产生了新颖的预测和政策含义。随后，我在一个实验性劳动力市场中展示了基于经验的歧视，发现研究结果支持关键模型预测。（JEL D83, J23, J24, J31, J71, M51）
Abstract
I study discrimination arising from individual experiences of employers with worker groups. I present a model in which employers are uncertain about the productivity of one of two groups and learn through hiring. Positive experiences lead to positive biases, which correct themselves by leading to more hiring and learning. Negative experiences decrease hiring and learning, preserving negative biases, which can cause persistent discrimination. The model explains prejudice as incorrect statistical discrimination and generates novel predictions and policy implications. I then illustrate experience-based discrimination in an experimental labor market, finding support for key model predictions. (JEL D83, J23, J24, J31, J71, M51)