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Applying a Racial Equity Lens to Housing Policy Analysis

In June, the Housing Matters editorial team, spurred by the national uprisings against police brutality and anti-Black structural racism, and the uneven effects of COVID-19 pledged a renewed commitment to racial equity. To manifest this promise, we committed to “reexamine evidence and assumptions in order to advance antiracist housing policy and practice,” and as a first step, we are reviewing five years of Housing Matters content to identify gaps and shortcomings in the work we’ve featured. In our role as research translators, we aim to arm our readers with the research and policy analysis necessary to advance antiracist housing policy and practice in communities and governments across the US.

In much of the research featured on Housing Matters, researchers disaggregate data by race to determine whether Black people, Indigenous people, and other people of color (BIPOC)[1] are disproportionately affected by the negative effects of programs and policies or whether they have less access to benefits provided through policies and programs. This disaggregation provides policymakers with the insights they need to develop targeted solutions to ensure more equitable outcomes. It can also help policymakers evaluate whether a law, regulation, or practice is helping reduce racial inequities or perpetuating them. Importantly, disaggregated data that is shared within a robust racial equity frame, acknowledging and fully engaging with historic, structural, and systemic drivers of inequitable outcomes, is essential to ensure that policymakers are equipped with the context necessary to develop antiracist interventions that redress harm and promote equitable outcomes for all impacted by a specific policy issue.  

While reviewing Housing Matters content, we realized we missed several opportunities to apply a racial equity lens to our research translation by failing to include these disaggregated data, even though the researchers featured did investigate racially disparate impacts. This observation led us to consider: What do policymakers miss when research translators and advocacy organizations don’t apply a racial equity lens to housing policy analysis?  As stated, equity-focused public policy work extends beyond the mere inclusion of racially disaggregated data. Meaningful work in this space requires significant power shifts and critical reevaluations of racist assumptions and systems. However, for research translators, a key entry point to this work is the inclusion of racially disaggregated data coupled with critical structural racism framings of these data that adequately acknowledge the historic and systemic drivers of inequitable outcomes.

Guided by this question, we returned to those analyses to gain insight into how our failure to include racially disaggregated data and structural racism framings in our policy analysis obscured valuable takeaways that illustrate why racial equity should be a core objective when developing housing policies.  Below, we share a selection of these to show what we missed across domains. Though these examples are derived from Housing Matters, they illustrate the need for an intentional, sustained racial equity lens across research translators, advocacy organizations, and other policy intermediaries.

The value of applying a racial equity lens to housing policy analysis relating to…


Although eviction affects people of all races and ethnicities, in some communities—especially those that are densely populated and where home prices are rising—it affects Black and Hispanic people at much greater rates. Policy intermediaries’ discussions of eviction should align with this knowledge and center eviction’s impact on BIPOC. In a Q&A with Evicted author Matt Desmond published on March 2, 2016, Desmond explained that eviction causes poverty in cities across America. During the interview, we did not inquire about the disparate effects eviction has on Black and Hispanic[2] people in Milwaukee, despite the strong evidence of these impacts presented in the book. In one of the most poignant quotes of the book, Desmond writes, “If incarceration had come to define the lives of men from impoverished black neighborhoods, eviction was shaping the lives of women. Poor black men were locked up. Poor black women were locked out.” [3]

In Evicted, Desmond shares data about eviction’s impact on people of different races and ethnicities:

  • “Women from black neighborhoods made up 9 percent of Milwaukee’s population and 30 percent of its evicted tenants.”
  • “Hispanic and African American neighborhoods had been targeted by the subprime lending industry: renters were lured into buying bad mortgages, and homeowners were encouraged to refinance under riskier terms.… Between 2007 and 2010, the average white family experienced an 11 percent reduction in wealth, but the average black family lost 31 percent of its wealth. The average Hispanic family lost 44 percent.”
  • “Among Milwaukee renters, over 1 in 5 black women report having been evicted in their adult life, compared with 1 in 12 Hispanic women and 1 in 15 white women.”

These data expand on the specific effects of eviction on Black and Hispanic residents of Milwaukee and prompt a deeper discussion of how structural racism produces financial instability, compounded by unequal access to employment, healthy food, and health care, among other inequities, that puts BIPOC at a higher risk of losing their homes. For policymakers to proactively encourage housing stability in their localities, they need to examine access to services and housing and the ability to accumulate wealth by race and ethnicity. Having racially disaggregated data not only better explains findings in a particular city or state but also equips decisionmakers with a better understanding of funding gaps to help them target solutions.

Socioeconomic mobility

When we discuss economic mobility without an integrated analysis of structural racism, we miss an opportunity to explore the well-documented connections between racism and capitalism. On May 7, 2015, we highlighted the work of Raj Chetty and Nathaniel Hendren’s Equality of Opportunity project. Their research, which included a dataset of more than five million US families, disaggregated data on race for all outcomes. However, we did not include these data in our write-up, and we did not spotlight how limited opportunities worsened BIPOC’s, specifically Black people’s, well-being. For disaggregated data that are not contextualized in structural factors, such as those highlighted in the excerpts below, policy analysts must do the work of situating data to ensure the “why” of such inequities is clear.

  • “We also find that areas with a larger African American population tend to have lower rates of upward mobility. These spatial differences amplify racial inequality across generations: we estimate that roughly one-fifth of the gap in earnings between blacks and whites can be attributed to the counties in which they grow up.”
  • “The evidence here validates the hypothesis that, on average, African Americans live in neighborhoods that cause lower outcomes for children in low-income families.… On average, African Americans live in counties that produce 1.69 percentile lower outcomes. Scaling this to percentage changes in incomes, it suggests the counties in which African Americans live cause incomes to be 5.3% lower relative to the counties in which non-African Americans live.”

When policy translators include data that illuminate racial disparities, we are positioned to identify the structural factors that create generational racial disparities in income, access, and opportunity. Chetty and Hendren’s research provides data that allow us to push back on racist assertions that such disparities are innate and, instead, affirm gaps between Black and white people’s socioeconomic mobility are driven by structural, environmental factors that can be changed.


Racially and ethnically disaggregated education data (PDF) also allow decisionmakers to precisely target student and community support services, which creates more impactful, efficient resource allocation.

On January 20, 2016, we published an article highlighting research that explored how housing policy can be a path to educational opportunity for children from low-income families. This piece featured research on the impacts of socioeconomically integrated housing, inclusionary zoning, housing mobility vouchers, and school choice on children from low-income families. The original article mentions that “socioeconomic and racial segregation [are] commonplace in both neighborhoods and schools” but fails to describe the impacts of segregation on educational access and opportunity. Though most of the scholarship referenced in this piece highlights how Black and Hispanic students from low-income families are differentially affected, we did not include the following takeaways in our write-up:

  • From Heather Schwartz (PDF): “To test whether affluent schools or neighborhoods improve low-income students’ academic achievement, this study examined all elementary school–age children of families who lived in public housing during the 2001–07 school years in Montgomery County. These families comprised some of the very poorest households living in the county; their average income was $21,000, 72 percent were African American, and 87 percent of these families were headed by females.”
  • From Center for Research on Education Outcomes (PDF): “Black and Hispanic students, students in poverty, English language learners, and students receiving special education services all see stronger growth in urban charters than their matched peers in urban traditional public schools.”

It is essential to disaggregate by race and ethnicity when discussing students’ academic performance to ensure these policies equitably benefit children and families of color. If data show a policy only benefits white students from low-income families, researchers, policy advisors, and advocates should communicate this clearly to not obscure how current policies and programs are insufficient in addressing the needs of students of color.


When policymakers are armed with a better understanding of how social determinants cause health inequities among people of different races and ethnicities, they will be better positioned to create innovative treatment plans that go beyond medical care (to include other supports like rental assistance and increased access to fresh food) and will be able to better select and direct their investments in social determinants of health. In a research review summarizing the negative health consequences of spending too much on housing published May 22, 2019, we omitted data from the studies which demonstrate that Black families are more likely to be affected by housing-cost challenges and therefore experience negative health impacts:

  • In their research on the Michigan recession and recovery, Burgard, Seefeldt and Zelner found that “respondents reporting multiple moves, moves for cost, doubling up or homelessness were significantly younger than those with stable housing and more likely to be African American.”
  • In an examination into health insurance gaps, Carroll and colleagues found “children who were unstably housed were significantly more likely to have gaps in health insurance coverage than children who were stably housed.… They were more likely to be non-Hispanic black and to reside in English-speaking households.”

By omitting data like these, translators miss an opportunity to emphasize the importance of centering racially disparate health impacts to policymakers. More than housing’s effects on health (and inversely, health’s on housing), consistent engagement with a racial equity lens opens the door for policy that addresses medical racism. As described in the original research review, many hospitals and health systems are starting to invest in the creation and maintenance of affordable housing and in the social determinants of health more broadly.

Housing assistance

Housing discrimination and racial wealth disparities resulting from structural inequities, including redlining, impact racially disparate outcomes in housing assistance programs. In a research abstract of a study analyzing how long households stayed in housing programs assisted by US Department of Housing and Urban Development published January 4, 2018, we excluded disaggregated data on the experiences of residents of color.

  • “Racial and ethnic minorities seem to stay for longer periods of time within the HCV (Housing Choice Vouchers) program, but the influence of race and ethnicity is less within the public housing and the Section 8 project based housing programs.”
  • “Minority households, especially Black households, tend to stay longer but also tend to make greater use of portability moves within the HCV program.”
  • “In all [HCV] cases, the length of stay at the median was greater for minority households compared with White households. Comparing the 2015 with the 2000 cohort of exiters, median stays increased more for Black and Hispanic households than for White and Other Non-Hispanic households.”

The length of stay cannot be isolated in a vacuum, and policy translators should appropriately center these data within broader research on racist housing policies and programs. Housing discrimination and racial wealth disparities resulting from structural inequities, including redlining, contextualize why Black households were seen to stay longer in HCV programs. This context is essential to work toward housing assistance programs that address the specific needs of BIPOC, and it’s bolstered when we share disaggregated data.

What policymakers miss when research intermediaries don’t apply a racial equity lens to policy analysis

As our Urban colleagues Leah Hendey and Daniel Fowler wrote, “What gets measured gets addressed.” Although we agree with this statement, in our role as research translators and policy analysts, we understand the important role of organizations like ours in assisting policymakers with policy analysis and would add one more caveat to the phrase: “What gets measured and explicitly named gets addressed.” When we, as translators, don’t apply a racial equity lens to analyze housing policy and fail to include racially disaggregated data, we have the potential to break a key link that policymakers rely on to understand, acknowledge, and address racial inequities in housing policy and practice and risk obscuring and perpetuating structural racism.

Through revisiting prior Housing Matters work, we see the opportunities we missed to elevate data that support our mission to advance antiracist housing policy and explore how this reflects a broader need within policy translation to be intentional about racial equity framings. Moving forward, we are exploring best practices to ensure this intentionality is present across our platform. Importantly, these data should be framed in a way that explicitly names and explores how structural racism causes these inequities, and these data should not be presented in isolation. Through policy intermediaries’ work to elucidate the specific housing and neighborhood experiences of BIPOC, we hope the housing field will understand the full pictured presented in the data to craft targeted, antiracist policy solutions and make meaningful progress toward racially equitable housing outcomes.


[1] Although the terms “BIPOC” and “POC” are the subjects of substantial critique, as they group together racial and ethnic minority groups, obscuring the specific experiences of each, the Housing Matters team chooses to use BIPOC when generally referring to nonwhite people and communities. When discussing a specific demographic group or identity, we opt to name them as specifically as possible. We welcome your thoughts on this terminology.

[2] In this piece, we opt to use the term “Hispanic” throughout to align with language used in the source materials.

[3] With direct source quotes, we keep the capitalization of racial groups the same as in the original text. However, the Urban Institute capitalizes Black when describing people of African origin.

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