Land banks and community land trusts are finding new ways to work together in light of the ongoing housing affordability crisis and the new economic pressures of the COVID-19 pandemic.
Emma Zehner reports on the latest collaborations between community land trusts and land banks to address systemic racism and expand affordable housing opportunities.
The first example examined in the article: the New Home Development Program (NHDP), a collaboration of the city of Houston, the Houston Land Bank, and the Houston Community Land Trust (HCLT).
"Launched in 2018, NHDP was created to provide newly constructed, affordable single-family homes to homebuyers with a household income of 80 percent or less of area median income (AMI)," according to Zehner. "The program is working to address systemic racial disparities and discriminatory practices that have shut Black people and other people of color out of homeownership opportunities."
The Houston model is found in other cities around the country, like Portland and Atlanta, coalescing in the 36-month Catalytic Land Cohort, a program run by the Grounded Solutions Network and the Center for Community Progress, with initial funding from Wells Fargo.
Zehner offers insight into what makes these recent collaborations so innovative: "Land banks and community land trusts haven’t historically coordinated their work: land banks typically purchase properties in weak markets with the goal of bringing them back to productive use, while community land trusts have focused on ensuring affordability in hot markets. But by joining together, these entities can serve as an important tool in expanding homeownership opportunities."
The article also includes a history of community land trusts in addition to deeply reported partnership case studies from Albany, New York, and Richmond, Virginia, in addition to the New Home Development Program in Houston and examples from Atlanta and Portland.
As for next steps for the Catalytic Land Cohort, Zehner reports that the collaboration is seeking funding support to scale the model up to the regional level.
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