Market Competition, Consumer Discrimination, and Public Accommodations: Evidence From Green Books

该奖项资助的研究将创新地利用档案数据来测试一个重要的经济理论。该研究包括创建一个新的数据集，将提供给一个跨学科的学者小组，以研究美国农村和城市地区的各种社会经济问题。该项目利用了一个重要的历史工具，非洲裔美国人在导航隔离在吉姆克劳时代：黑人司机绿色书籍。 从1936年到1964年，这些目录列出了酒店，企业，餐馆和其他对非裔美国人客户友好的公共住宿，在旅行可能不舒服的时候，在最好的情况下，在最坏的情况下，危险。它将利用绿色图书机构和其他新数据集的全新完整数字化和地理编码，研究在1964年民权法案禁止公共场所种族歧视之前，消费者偏好的变化如何影响非歧视性企业的数量。该研究小组将创建一个独特的县级数据集，并将使用这些数据来测试市场竞争如何受到歧视和种族隔离影响的理论经济理论。 该项目通过帮助我们了解商业竞争是否以及如何导致公平获得公共住宿来推进重要的社会目标。由于数据相对稀少，人们对公共场所隔离的经济学和直接决定因素或企业歧视倾向知之甚少。传统的基于品味的歧视模式（例如，Becker，1971）表明，即使在没有政府干预的情况下，竞争也会压低歧视性公司的市场份额。然而，如果非少数群体客户在招揽非歧视性业务时产生负效用，则存在一个不随时间变化的歧视性公司的稳定均衡。研究小组建立并分析了一个程式化的模型，该模型捕捉了服务于少数群体成员的公司份额与该群体在人口中所占份额之间关系的性质。该模型预测，歧视性公司的数量在少数民族人口中所占的份额正在减少。 为了测试该模型的影响，该团队将创建一个独特的县级数据集的绿色书建立计数代理的非歧视性公司的数量，然后利用外源冲击的白色黄金年龄人口造成的第二次世界大战的死亡率，看看是否不断变化的消费者人口与非歧视性公司的数量。 与白色消费者的歧视为公司提供了歧视激励的概念相一致，初步结果表明，二战中白色伤亡人数最多的县，非歧视性公司的比例增加幅度更大。完成的项目将促进我们对歧视和种族隔离的理论和经验证据的理解。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

This award funds research that will make innovative use of archival data to test an important economic theory. The research includes creating a new data set that will be available to an interdisciplinary group of scholars to study a wide variety of socioeconomic issues in rural and urban areas of the United States. The project makes use of an important historical tool used by African Americans in navigating segregation in the Jim Crow era: The Negro Motorist Green Books. From 1936 to 1964, these directories listed hotels, businesses, restaurants, and other public accommodations that were friendly towards African American clients during a time when travel could be uncomfortable, at best, and dangerous, at worst. It will leverage a new, complete digitization and geocoding of Green Book establishments and other new data sets to examine how changing preferences of consumers influenced the number of non-discriminatory businesses before the Civil Rights Act of 1964 barred racial discrimination in public accommodations. The research team will create a unique county-level dataset and will use the data to test theories economic theories of how market competition is affected by discrimination and racial segregation. This project advances important societal goals by helping us understand whether and how business competition will result in equitable access to public accommodations. Due to a relative sparsity of data, little is known about the economics and proximate determinants of segregation of public accommodations or the propensity for businesses to discriminate. Traditional models of taste-based discrimination (e.g., Becker, 1971) suggest that competition will drive down the market share of discriminatory firms even in the absence of government intervention. If non-minority clients have a disutility from soliciting non-discriminatory businesses, however, there is a stable equilibrium of discriminatory firms that does not change over time. The research team builds and analyzes a stylized model that captures the nature of the relationship between the share of firms that serve members of the minority group and that group's share of the population. The model predicts that the number of discriminatory firms is decreasing in the share of the minority population. To test the model’s implications, the team will create a unique county-level data set of Green Book establishment counts to proxy for the number of non-discriminatory firms and then exploit exogenous shocks to the white prime-aged population caused by World War II mortality to see if changing consumer demographics are related to the number of non-discriminatory firms. Consistent with the notion that discrimination on the part of white consumers provided firms with incentives to discriminate, preliminary results show that counties with the highest number of white casualties in WWII had larger increases in the share of non-discriminatory firms. The completed project will advance our understanding of the theory and empirical evidence of discrimination and racial segregation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.