Displaced and unsafe: The legacy of settler-colonial racial capitalism in the U.S. rental market

ABSTRACT

Unsafe rental units are disproportionately located in communities of color, resulting in numerous detrimental effects for residents’ health and socioeconomic well-being. Yet, scholars disagree regarding the mechanisms driving this phenomenon. Exogenous capitalism theories emphasize socioeconomic factors while setter-colonial racial capitalism theories emphasize the racist policies and practices that incentivize unequal investment and maintenance. We empirically adjudicate between these mechanisms by merging restricted-access versions of the American Housing Survey, the Rental Housing Finance Survey, and the American Community Survey at a Census Restricted Data Center. Our findings demonstrate neighborhood White proportion is a key mechanism shaping the condition of rental units even when controlling for neighborhood socioeconomic status, property features, and renter demographics. We argue these results support settler-colonial racial capitalism theories and discuss the implications of these findings for future research and housing policy.

KEYWORDS:

• Housing quality
• settler colonialism
• racial capitalism
• rental housing
• neighborhood inequality

Acknowledgments

The authors would like to thank Hajar Yazdiha for providing helpful feedback on a previous version of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Disclaimer

Views expressed in this article are those of the authors and not those of the U.S. Census Bureau. The Census Bureau’s Disclosure Review Board and Disclosure Avoidance Officers have reviewed this information product for unauthorized disclosure of confidential information and have approved the disclosure avoidance practices applied to this release. This research was performed at a Federal Statistical Research Data Center under FSRDC Project Number 2080. (CBDRB-FY21-P2080-R9105).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1. Aligning with the terminology recommendations of the National Congress of American Indians, we use American Indian/Alaska Native (AI/AN) throughout the paper in reference to communities whose ancestors lived in the Americas before European settler colonizers invaded the land. This includes people of Tribal Nations who resided in the continental United States (American Indians) and Tribal Nations and Villages of Alaska (Alaska Natives).

2. In the 1930s, Asian and Latinx communities were less common than Black and AI/AN neighborhoods. Thus, less attention has been brought to the role HOLC classifications had on these communities. For an example, see the HOLC map of San Antonio: https://digital.utsa.edu/digital/collection/p16018coll12/id/78/rec/3.

3. The survey is nationally representative with an oversample of the 15 largest metropolitan areas.

4. The AHS is collected from May to September of odd number years and the corresponding RHFS is administered the following year. We used the most recent available data: the 2017 AHS (n = 82,591 households) and the 2018 RHFS (n = 4,330 units).

5. Wires not enclosed in a wall, metal, or plastic covering were defined as exposed. Broken furnaces included instances where the primary heating stopped working during winter months. Broken toilets included toilets that stopped working in the last 3 months. Interrupted water supply was defined as losing running water in the last 3 months. Sewage failures entailed an unusable system in the prior 3 months. Infestations were defined as visual evidence of rodents or insects within the last 6 months. Foundation, roof, and window damage included visible holes, cracks, crumbling, missing shingles, and sagging. Unstable walls and floors were defined as those with cracks or holes at least 4 inches across and deeper than 3 inches or visible buckling, leaning, or sloping. Mold covered an area larger than an 8.5 by 11-inch piece of paper.

6. Our variable mirrors HUD’s classification of inadequate housing units. Like our variable, HUD counts the number and type of plumbing, heating, electric, wiring, and upkeep (defined as external and internal water leaks, holes and cracks in the walls, ceilings, or floors, peeling or broken plaster, and rats) problems, but they create quality categories (e.g., severely inadequate). Although the substantive results of the two measures are comparable, we maintain a continuous variable to reflect how more problems gradually make the unit more unlivable.

7. In supplemental models, we used alternative definitions of racial neighborhood composition to empirically confirm our theoretical assertion that the White proportion drive neighborhood inequality (see also Goetz et al., 2020; Howell & Korver-Glenn, 2021; Howell, 2019a).

8. Most complexes were built in 1 year. However, for the few multiyear, multibuilding projects, we are unable to identify the AHS respondent’s building. To produce conservative results, we use the oldest building as the property’s age. In a couple of cases, owners only report the age of their newest building. For these cases, we used this year to reduce the missing data.

9. Some owners did not report potential or market rate rent. For these respondents, we used the received rent across all units as a proxy for potential rent.

10. Building off Howell & Emerson’s (2017) findings, we classify all respondents into one of five categories. Specifically, Latinx renters are all Hispanic respondents. White renters are monoracial non-Hispanic White respondents. Black renters are monoracial and all multiracial non-Hispanic Black respondents. AI/AN renters are monoracial non-Hispanic AI/AN respondents and multiracial non-Hispanic AI/AN respondents who do not identify as Black. Asian renters are monoracial non-Hispanic Asian and/or Pacific Islander respondents and multiracial non-Hispanic Asian and/or Pacific Islander respondents who do not identify as Black or AI/AN.

11. Couples include married and unmarried romantic partners. Parents refer to primary caregivers of children under 18 years of age.

12. Education was defined as less than high school, some high school, high school (diploma, GED, or equivalent), some college, associate’s degree (diploma or vocational certificate), bachelor’s degree, and graduate degree.

13. Both education and income were standardized and then their mean was calculated. We then used a natural logarithm transformation to adjust for the rightward skew. Supplemental models with educational attainment and annual household income as separate variables produced comparable results. We present the combined measure because it is more parsimonious.

14. Since some landlords include utilities (e.g., water) in rent while others do not, the AHS creates a comparable variable by adding together rent, electricity, natural gas, oil, wood, coal, kerosene, or other fuel, water and sewage, and garbage and trash collection for all respondents. We used the RHFS variable discussed above for the property’s potential rent. We applied a square root transformation to this ratio to adjust for its skew.

15. Single-family homes are all detached single unit dwellings. A square root transformation was used to adjust for the total population rightward skew.

16. Renters in communities of color are slightly more likely to live in multiunit complexes and have professionally managed units than renters in White neighborhoods. Yet, these differences are statistically insignificant and substantively small, especially compared to the notable differences in neighborhood and renter demographics.

17. Concentration is defined as a resident’s own racial group consisting of a larger proportion of their neighborhood than their racial group’s proportion in the U.S. population.

18. See also Denetdale (2016) and Huyser et al. (2018), who find that AI/AN people who live away from their reservation lands and the supports these lands provide experience particularly acute consequences of settler colonialism.

Additional information

Funding

This research uses data from the Census Bureau’s Longitudinal Employer Household Dynamics Program, which was partially supported by the following National Science Foundation [Grants SES-9978093, SES-0339191 and ITR-0427889]; National Institute on Aging [Grant AG018854]; and grants from the Alfred P. Sloan Foundation. This specific project was also funded by the Russell Sage Foundation and the University of New Mexico ADVANCE program and the UNM Office of the Vice President for Research.

Notes on contributors

Elizabeth Korver-Glenn

Elizabeth Korver-Glenn is assistant professor of sociology at Washington University in St. Louis. Dr. Korver-Glenn’s scholarship, which has been supported by the Russell Sage Foundation and the Swedish Research Council, among other external and internal grants, examines the causes and consequences of racial, class, and gender inequalities in urban contexts and how policy can mitigate these inequities.

Sofia Locklear

Sofia Locklear is an enrolled citizen of the Lumbee Tribe of North Carolina and currently an Assistant Professor at Western University. Dr. Locklear’s research investigates racial inequities, Whiteness, and the racialization of Indigenous people.

Junia Howell

Junia Howell is an is an urban sociologist and race scholar who uses quantitative and qualitative tools to identify and dismantle the specific policies, processes, and practices that uphold White supremacy. Currently, her work focuses on the housing industry and disaster relief. Dr. Howell currently holds a faculty position at the University of Illinois Chicago.

Ellen Whitehead

Ellen Whitehead is an assistant professor of sociology at Ball State University who specializes in family sociology, social inequality, and race and ethnicity. Dr. Whitehead’s research has been supported through grants from the Russell Sage Foundation, the National Institute of Food and Agriculture, and the Aspire Program at Ball State.