Home values and race have an intimate connection in Durham, NC. From 1940 to 2020, if mean home values in Black-majority Census tracts had appreciated at rates equal to those in white Census tracts, the mean home value for homes in Black tracts would be $94,642 higher than it is.
That’s the disappointing, but perhaps not shocking, finding of a Duke Data+ team.
Because housing accounts for the biggest portion of wealth for families that fall outside of the top 10% of wealth in the U.S., this figure on home values represents a pervasive racial divide in wealth.
What started as a Data+ project in the summer of 2020 has expanded into an ongoing exploration of the connection between persistent wealth disparities across racial lines through housing. Omer Ali (Ph.D.), a postdoctoral associate with The Samuel Dubois Cook Center on Social Equity, is leading undergraduates Nicholas Datto and Pei Yi Zhuo in the continuation of their initial work. The trio presented an in-depth analysis of their work and methods Friday, February 5th during a Data Dialogue.
The team used a multitude of data to conduct their analyses, including the 1940 Census, Durham County records, CoreLogic data for home sales and NC voter registrations. Aside from the nearly $100,000 difference between mean home values between Black census tracts (defined as >50% Black homeowners from 1940-2020) and white census tracts (defined as >50% white homeowners from 1940-2020), Ali, Datto, and Zhou also found that over the last 10 years, home values have risen in Black neighborhoods as they have been losing Black residents. Within Census tracts, the team said that Black home-buyers in Durham occupy the least valuable homes.
Datto introduced the concept of redlining — systemic housing discrimination — and explained how this historic issue persists. From 1930-1940, the Home Owners’ Loan Corporation (HOLC) and Federal Housing Administration (FHA) designated certain neighborhoods unsuitable for mortgage lending. Neighborhoods were given a desirability grade from A to D, with D being the lowest.
In 1940, no neighborhoods with Black residents were designated as either A or B districts. That meant areas with non-white residents were considered more risky and thus less likely to receive FHA-guaranteed mortgages.
Datto explained that these historic classifications persist because the team found significant differences in the amount of accumulated home value over time by neighborhood rating. We are “seeing long-lasting effects of these redlined maps on homeowners in Durham, “ said Datto, with even “significant differences between white [and non-white] homeowners, even in C and D neighborhoods.”
Zhou explained the significance of tracking the changes of each Census tract – Black, white, or integrated – over the last 50 years. The “white-black disparity [in home value] has grown by 287%” in this time period, he said. Homes of comparable structural design and apparent worth are much less valuable for simply existing in Black neighborhoods and being owned by Black people. And the problem has only expanded.
Along with differences in home value, both Black and white neighborhoods have seen a decline in Black homeowners in the 21st Century, pointing to a larger issue at hand. Though the work done so far merely documents these trends, rather than looking for correlation that may get at the underlying causes of the home-value disparity, the trends pair closely with other regions across the country being impacted by gentrification.
“Home values are going up in Black neighborhoods, but the number of Black people in those neighborhoods is going down,” said Datto.
Ali pointed out that there are evaluation practices that include evaluation of the neighborhood “as opposed to the structural properties of the home.” When a house is being evaluated, he said a home of similar structure owned by white homeowners would never be chosen as a comparator for a Latinx- or Black-owned home. This perpetuates historical disparities, as “minority neighborhoods have been historically undervalued” it is a compounding, systemic cycle.
The team hopes to export their methodology to a much larger scale. Thus far, this has presented some back-end issues with data and computer science, however “there is nothing in the analysis itself that couldn’t be [applied to other geographical locations,” they said.
Large socioeconomic racial disparities prevail in the U.S., from gaps in unemployment to infant mortality to incarceration rates to life expectancy itself. Though it should come as no surprise that home-values represent another area of inequity, work like Ali, Datto, and Zhou are conducting needs more traction, support, and expansion.
Post by Cydney Livingston