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

该奖项资助的研究将创新性地利用档案数据来检验一个重要的经济理论。这项研究包括创建一个新的数据集，供跨学科的学者小组研究美国农村和城市地区各种各样的社会经济问题。该项目利用了非裔美国人在吉姆·克劳（Jim Crow）时代使用的一种重要的历史工具：《黑人驾驶绿皮书》（Negro Motorist Green Books）。从1936年到1964年，这些目录列出了对非裔美国人客户友好的酒店、企业、餐馆和其他公共场所，在那个时候，旅行可能不舒服，往好里说，最坏的情况是危险。它将利用绿皮书机构的全新、完整的数字化和地理编码，以及其他新的数据集，来研究在1964年《民权法案》禁止公共场所的种族歧视之前，消费者偏好的变化如何影响非歧视性企业的数量。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经济学理论。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设施，推进了重要的社会目标。由于数据相对稀少，人们对公共设施隔离的经济学和直接决定因素或企业歧视倾向知之甚少。基于品味的歧视的传统模型（如Becker， 1971）表明，即使在没有政府干预的情况下，竞争也会降低歧视企业的市场份额。然而，如果非少数族裔客户因招揽非歧视性业务而产生负效用，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风格化的模型，该模型捕捉了服务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本质。该模型预测，在少数族裔人口中，歧视公司的数量正在减少。为了测试该模型的含义，该团队将创建一个独特的县级绿皮书建立计数数据集，以代表非歧视性公司的数量，然后利用二战死亡率对白人壮年人口造成的外生冲击，看看不断变化的消费者人口统计是否与非歧视性公司的数量有关。与白人消费者的歧视为公司提供了歧视动机这一观点相一致的是，初步结果表明，二战中白人伤亡人数最多的县，其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。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.