The Green Books and the Geography of Segregation in Public Accommodations
Jim Crow segregated African Americans and whites by law and practice. The causes and implications of the associated de jure and de facto residential segregation have received substantial attention from scholars, but there has been little empirical research on racial discrimination in public accommodations during this time period. We digitize the Negro Motorist Green Books, important historical travel guides aimed at helping African Americans navigate segregation in the pre-Civil Rights Act United States. We create a novel panel dataset that contains precise geocoded locations of over 4,000 unique businesses that provided non-discriminatory service to African American patrons between 1938 and 1966. Our analysis reveals several new facts about discrimination in public accommodations that contribute to the broader literature on racial segregation. First, the largest number of Green Book establishments were found in the Northeast, while the lowest number were found in the West. The Midwest had the highest number of Green Book establishments per black resident and the South had the lowest. Second, we combine our Green Book estimates with newly digitized county-level estimates of hotels to generate the share of non-discriminatory formal accommodations. Again, the Northeast had the highest share of non-discriminatory accommodations, with the South following closely behind. Third, for Green Book establishments located in cities for which the Home Owner’s Loan Corporation (HOLC) drew residential security maps, the vast majority (nearly 70 percent) are located in the lowest-grade, redlined neighborhoods. Finally, Green Book presence tends to correlate positively with measures of material well-being and economic activity.
We would like to thank Rob Clark, Matt Gregg, Taylor Jaworski, Ian Keay, and Anji Redish for valuable comments. We also thank seminar participants at the University of Missouri, Northwestern University, Queen’s University, the University of Victoria, York University, and conference participants at the 2019 NBER Summer Institute (DAE), 2019 CEA meetings, 2019 SSHA meetings, and 2019 SEA meetings for useful feedback. This work would not have been possible without the help of our dedicated team of research assistants: Ashley Brewster, Maddy Conkle, Jack Csokmay, Vi Dinh, Mark Drodz, Matthew Edwards, Alisa Feng, Fahim Hossain, Daniel Lake, Ryan Scott, Daniel Missell, Abby Nenna, Yamini Panagari, Ethan Pointer, Jessica Shakesprere, Morgan Thompson, Julia Uhler, and Lingxuan Yang. We are grateful for the help of Peggy Ann Brown and Kevin Morrow at the Library of Congress. All errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.