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New and Corrected Estimates of California Migration Patterns Suggest Slowing of Pandemic-Era Trends

Berkeley, CA, April 14, 2022 — The number of people leaving California for other states appears to have slowed during the last quarter of 2021, while the number of people moving into the state appears to be rebounding, according to new estimates released today by the nonpartisan California Policy Lab (CPL) using credit-bureau data through the end of 2021. These trends are especially pronounced in the Bay Area counties that originally saw the largest pandemic-era shifts in domestic migration, like San Francisco. CPL also released a corrected version of its December 2021 Pandemic Patterns report, which corrects an error that led CPL to significantly undercount the number of people moving into California since 2020.

“The changes in domestic migration we’ve seen since the pandemic began appear to be slowing and perhaps even reversing,” explains co-author Natalie Holmes, a Research Fellow at the California Policy Lab and a PhD student at the Goldman School of Public Policy at UC Berkeley. “In the Bay Area, in particular, exits are down and entrances are up during the last quarter of 2021 – though they remain significantly different than before the pandemic – which suggests that pandemic migration shifts may be weakening.”

The updated brief that CPL released today corrects earlier estimates of entrances. Exits were not affected. CPL’s errata provides more background on the error and a table summarizing the main corrections.

“We are glad to correct the record and release these updated estimates of how many people moved into California since the start of the pandemic,” explains co-author Evan White, Executive Director of the California Policy Lab’s UC Berkeley site. “One of the biggest takeaways from our corrected research is that while domestic migration into California did decrease between the start of the pandemic in 2020, and the end of the third quarter of 2021, it was only an 8% decrease, not the 38% decrease that we had originally estimated.”

Additional Background
CPL’s analysis uses the University of California Consumer Credit Panel (UC-CCP), a dataset created through a partnership between the California Policy Lab, the Student Borrower Protection Center, and the Student Loan Law Initiative. The UC-CCP consists of data from one of the nationwide three credit bureaus, and contains longitudinal information about adults with a credit history who have lived in California since 2004. Data includes each person’s ZIP code of residence, as reported by creditors, and credit information at a quarterly frequency. We define moves as changes in ZIP codes from one quarter to the next. The analysis is focused on reported moves, defined as the date when that move is reported to financial institutions and shows up in the dataset, which we expect to lag behind actual moves. More information about methodology is included in the report.

While this data is one of the best ways to measure mobility in near-real-time, it has some limits. Because the sample consists of adults with credit histories (nearly 90 percent of adults, according to the Consumer Financial Protection Bureau), it is slightly older, more financially advantaged, and less racially and ethnically diverse than the overall adult population. As such, these results are less able to capture patterns of residential mobility among lower-income Californians and among racial and ethnic minorities. Also, because children are not included in the sample, the volume of movers are underestimates of the true volume.

The California Policy Lab creates data-driven insights for the public good. Our mission is to partner with California’s state and local governments to generate scientific evidence that solves California’s most urgent issues, including homelessness, poverty, criminal justice reform, and education inequality. We facilitate close working partnerships between policymakers and researchers at the University of California to help evaluate and improve public programs through empirical research and technical assistance.

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