Intersectional Housing Inequity: Analyzing Structural Oppression In the US Rental Market

Background & Purpose: The American rental housing landscape has long exemplified the nation’s entrenched social inequities. Landlord-tenant power imbalances and infrastructure shortages among other interlocking dynamics represent a convergence point of social power and oppression, particularly for low-income renters. These inequities can manifest in the form of gendered, racist, and classist disparities in eviction, the disenfranchisement of historically Black neighborhoods through gentrification, and outsized rates of homelessness for transgender, gender diverse, and queer people. While some of these dynamics have been illustrated using traditional statistical methods, debate continues regarding whether these approaches suffice for operationalizing and describing the multiplicative and intersectional effects of structural social forces.

Methods: Intersectional multi-level analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA) offers a promising method for addressing some of the challenges of quantitatively capturing systemic intersectional inequities. Here we used multiple demographic variables (race, gender identity, sexual orientation, and education) to generate a population stratification variable (n=36) that allowed for inequities between unique intersectional social contexts to be analyzed. The data used in this study were compiled from the US Census Bureau’s Household Pulse Survey and the sample consisted of renters with income of $35,000/yr or less (n=50,956). Logistic MAIHDA models were built sequentially and were covaried with age to evaluate differences in chance of being behind on rent between social contexts of relative power and oppression.

Results: Fourteen percent of the total sample were behind on rent. Across the 36 strata, the predicted probabilities of being behind on rent ranged from .031, 95%CI [.31,.33] to .390, 95%CI [.06, .06] and the average household had a 16% chance of being behind on rent. The group with the highest predicted probability of facing housing precarity was sexual minority Black women with high school or less education (p=.03, 95%CI [.31,.33]). All twelve of the strata above the grand mean (M=1.60, 95%CI [.13, .19]) were Black or Hispanic, and most were sexual or gender minorities. In contrast, the groups with the predicted probabilities below the grand mean and its 95%CI ranged from p=.18 to p=.06 and were mostly white of all gender identities and sexual orientations.

Conclusions: Housing precarity for low-income renters in the US is a manifestation of interlocking structural forces of power and oppression. We found that the predicted probabilities of housing precarity tended to be highest for Black sexual and gender diverse renters, while those with the lowest were predominantly white of all genders and sexual orientations. To make sense of this, we follow Patricia Hill Collins’ concept of the “matrix of domination” and interpret our findings from a “both/and conceptual stance”. Black sexual and gender minorities encounter interlocking anti-Black racism, cisgenderism, and heterosexism, leading to a magnified overall experience of structural inequity. Thus, legal housing protections based on single-axis categorizations are insufficient for disrupting structural inequities in housing. To our knowledge, this study represents an initial effort to integrate the I-MAIHDA method into the housing justice research landscape. These findings have additional implications for targeted service delivery, mutual aid efforts, and resource distribution.