The Long-run Effects of the 1930s Redlining Maps on Children

Abstract

We estimate the long-run effects of the 1930s Home Owners Loan Corporation (HOLC) redlining maps by linking children in the full count 1940 Census to 1) the universe of IRS tax data in 1974 and 1979 and 2) the long form 2000 Census. We use two identification strategies to estimate the potential long-run effects of differential access to credit along HOLC boundaries. The first strategy compares cross-boundary differences along HOLC boundaries to a comparison group of boundaries that had statistically similar pre-existing differences as the actual boundaries. A second approach only uses boundaries that were least likely to have been chosen by the HOLC based on our statistical model. We find that children living on the lower-graded side of HOLC boundaries had significantly lower levels of educational attainment, reduced income in adulthood, and lived in neighborhoods during adulthood characterized by lower educational attainment, higher poverty rates, and higher rates of single-headed households.*We thank Adriana Lleras-Muney and Shari Eli for many helpful comments. We also thank Raven Molloy, Trevon Logan and Sun Kyoung Lee for reading and discussing our paper at conferences. We thank participants at the Federal Reserve System Committee on Regional Analysis Conference, the NBER Economics of Mobility Workshop and the Race, Ethnicity, Gender, and Economic Justice Virtual Symposium held at Yale University. The views expressed are those of the authors and do not necessarily represent the views of the U.S. Census Bureau, the Federal Reserve Bank of Chicago, the Board of Governors of the Federal Reserve System, or its staff. This research was conducted as part of an Internal Census Project. All results using internal data have been reviewed to ensure that no confidential information is disclosed (DRB clearance numbers CBDRB-FY22-CES17-001 and CBDRB-FY22-115).which they could have retained for future use or shared with others. Some have also argued that the HOLC had a broad influence on the appraisal process used by private lenders nationwide by creating new standardized practices that emphasized the characteristics of neighborhoods. For example, some banks created their own version of the HOLC maps. Finally, the maps were shared with the Federal Housing Administration (FHA), which drew their own appraisal maps shortly after the HOLC, and the HOLC maps could have influenced FHA activity. The FHA played a critical role in the housing market by deciding whether to insure mortgages and were notorious for following discriminatory practices (Fishback et al 2021). Each of these potential avenues raise the prospect that the content of the HOLC maps, along with the broader use of a government-backed appraisal system, may have either directly or indirectly influenced access to credit for households in many urban neighborhoods. Although historical research on these different channels remains active, and we discuss some of this work further below, we may never fully know which of these mechanisms were the most pertinent.Several stud...

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“…The 32nd United States (US) President Franklin D. Roosevelt's New Deal was the government's response to the Great Depression, and its Home Owners' Loan Corporation (HOLC) aimed to stabilize the nation's mortgage lending system. To help reduce the risk that government‐backed loans would default, the HOLC drew residential “security” maps for 239 cities between 1935 and 1940 and completed more than 5 million appraisals that were assessed using criteria first established by the government‐sponsored HOLC (Aaronson et al, 2020; Hillier, 2003; Jan, 2018). In the imagined city at the beginning of this article, the characteristics and descriptors you chose have minimal to no consequence.…”

“…Scholars who have studied the effects of racial residential segregation in the United States, including these neighborhood characterizations and redlining, find that these practices led to reduced home ownership rates, home values, and today, those same neighborhoods suffer not only from reduced wealth and greater poverty, but from lower life expectancy and higher incidence of chronic diseases that are risk factors for poor health outcomes, and increased exposure to environmental hazards (Aaronson et al, 2020;Bravo et al, 2016;Hoffman et al, 2020;Lynch et al, 2021;Morello-Frosch & Jesdale, 2006;Nardone et al, 2020Nardone et al, , 2021Richardson et al, 2020). The National Community Reinvestment Coalition found that historically redlined neighborhoods have a greater prevalence of risk factors for coronavirus disease 2019 (COVID-19), such as high levels of exposure to air pollution (Richardson et al, 2020).…”

Neighborhood Blighted Property Removal and 311 Calls for Non‐Emergency Services: A Test of a Marker of Social Control

“…Representativeness is often influenced by the extent to which residents trust the capacity and will of local government to act on their behalf and respond to a call for service or complaint in a just way. Given the historic structural exclusion and exploitation people of color in the United States through municipally enacted policies like mortgage redlining and discriminatory policing (Aaronson, Hartley, and Mazumder 2020 ; Jacoby et al 2018 ; Zenou and Boccard 2000 ), the representativeness of such data may be a substantial concern in effected communities. Others have suggested that although 311 data may not be an ideal marker for political engagement or participation when interpreted absent of the context of neighborhood conditions, these data can be used as broader marker for the extent of service demands that residents make and expect of city governments (White and Trump 2018 ).…”

Gender-Targeted Job Ads in the Recruitment Process: Evidence from China

“…Motivated by evidence of high levels of gender segregation across occupations (Blau et al 2013), across firms (Card et al 2016) and across jobs within firms (Bielby and Baron 1984), we wish to assess the contribution of the explicit job labels (F, N and M) to gender segregation across all these partitions of the labor market. As noted, measuring the contribution of explicit gender designations for jobs to gender segregation is mathematically analogous to the measuring the association of red-lining with urban residential segregation (Aaronson et al, 2017), a practice which in some cases gave official government sanction to explicit racial categorization of neighborhoods. 22 In our case, neighborhoods that would be categorized as black, mixed, or white are directly analogous to employers' explicit designation of jobs as F, N or M. In the urban context, these labels presumably allocated home seekers to neighborhoods both by directing where home seekers search for housing (compliance) and via landlords' and home sellers' refusals to transact with 'race-mismatched' persons who offer to purchase or rent a home (enforcement).…”

“…If so, does their role reflect mostly workers' compliance or firm's enforcement actions? Conceptually, these questions are isomorphic to quantifying the role of 'red lining' practices -the historic designation of U.S. urban neighborhoods by race --in residential racial segregation (Aaronson et al, 2017). Abstracting from gendered job labels, we can pose an additional question about workplace gender segregation that to our knowledge has not been answered: does the observed level of gender segregation across all jobs -not just the gender-targeted ones--result mostly from workers' self-sorting in deciding where to apply, or from employers' active selection among applicants?…”