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Turner Center study estimates up to 1.6M Californians may qualify for MyHome/ZIP; Dream For All effect looks large in early analysis
Summary
A Turner Center and California Policy Lab market study presented to CalHFA estimates roughly 1.6 million Californians could realistically be eligible for MyHome/ZIP subordinate financing and about 1.1 million for Dream For All after income adjustments; preliminary randomized evidence shows Dream For All offers increased homeownership by over 45 percentage points at one year.
CalHFA staff and researchers from the Turner Center and the California Policy Lab presented a market study estimating the potential pool of Californians who could utilize CalHFA subordinate financing products.
Ellen Martin introduced Dustin (Turner Center/California Policy Lab) who described a methodology that starts with the University of California Consumer Credit Panel and then trims for age, credit scores, prior homeownership and county income limits to arrive at estimates of program‑eligible borrowers. "Using the credit records alone, we think 4.6 up to 4,600,000 could be eligible for MyHomeNZIP, and 3,600,000 could be eligible for Dream For All," Dustin said. After applying county‑level income and payment capacity limits, Dustin said the refined estimates are closer to "1,600,000 for MyHome/ZIP and 1,100,000 for Dream For All."
Dustin also reported demographic and geographic patterns: Black borrowers are underrepresented in the eligibility pool partly because of credit invisibility and lower average scores, Asian and Pacific Islander borrowers are overrepresented relative to their share of household heads, and the Bay Area is overrepresented in the eligibility pool compared with other regions because of higher credit scores but low housing affordability.
On program evaluation, Dustin highlighted early randomized evidence from Dream For All: "dream for all voucher increases homeownership by over 45 percentage points relative to the control group, 4 quarters after money was allocated," with preliminary analysis showing no adverse effects on credit lines.
Board members discussed how the estimates inform program design, geographic set‑asides and complementary policy work (supply, borrower education and targeted outreach). Staff and researchers acknowledged limitations: inability to observe income directly in credit data, imputed race/ethnicity in the credit panel, and limits on parental homeownership data used to identify first‑generation borrowers.
