Residential Instability in the Bay Area through the COVID-19 Pandemic


Jackelyn Hwang, Stanford University; Becky Liang, Stanford University; Vasudha Kumar, Stanford University; and Jason Vargo, Federal Reserve Bank of San Francisco

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July 11, 2022

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Executive Summary

This report draws on a unique, longitudinal dataset of over 250,000 San Francisco Bay Area residents to examine residential instability—including moving, crowding, and financial health—in the Bay Area during the pandemic. Our research finds a substantial decrease in moving during the pandemic, particularly for residents of extremely low socioeconomic status (SES). At the same time, we report a concerning rise in residents living in crowded conditions and experiencing declining credit scores. These trends suggest that COVID-19 rent relief programs and eviction moratoria may be successful in reducing displacement; however, alternative strategies may be necessary to address other forms of residential instability, like crowding, especially in Black and low-income neighborhoods. This report concludes with recommendations to address residential instability in the Bay Area.

Key Takeaways

During the first year of the pandemic, people were moving less but increasingly living in crowded housing and experiencing declines in their financial health. We count a move as an individual moving out of their block group.* In the context of COVID-19 job loss, it is likely that people moved into shared living spaces with friends or family members who live nearby (i.e., within the same census-designated block group) to reduce and share expenses. Additionally, young adults living in other parts of the country may also have moved back home to the Bay Area at the onset of the pandemic.

In places hit hardest by COVID-19, more households started living in crowded conditions (i.e., transitioned from low-density to high-density households), gained new delinquencies, and experienced declines in their financial health. We report significant correlations between case rates and these residential instability outcomes.

Trends are unequal across neighborhoods by racial composition: Neighborhoods with at least a 10 percent Black population (i.e., Mixed-Black neighborhoods) experienced the largest decrease in moving rates during the pandemic. Although low-moderate-SES residents moved more in Majority White neighborhoods, they moved less in Mixed-Black neighborhoods. Residents in Mixed-Black neighborhoods also saw the largest increase in people living in crowded conditions.

Moves into crowded conditions, new delinquencies, and declines in financial health were concentrated in the southeast parts of San Francisco (including Bayview/Hunters Point), the eastern and northern parts of the North Bay (including Vallejo and Calistoga), Deep East Oakland, the northeast of the East Bay (including Pittsburg and Antioch), central San Jose (in Naglee Park and Little Saigon), and central South Bay (including Menlo Park and East Palo Alto).

*Note: A census block group is a cluster of blocks and contains approximately 600–3,000 residents. Refer to Appendix B (pdf) for additional information.

The views expressed in this report are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of San Francisco or the Federal Reserve System.


We would like to thank AJ Nadel, Ruben Anguiano, Brooke Tran, and Alisha Zhao for their fantastic research assistance on this project and the Vice Provost for Undergraduate Education Urban Studies Summer Fellow Program at Stanford University for supporting Stanford University in this work. We are also grateful to Karen Chapple, Laura Choi, Naomi Cytron, Lizzy Mattiuzzi, and Carolina Reid for their generous input in improving this report, to Crystal Ejanda for editorial guidance, and to the SF Fed Creative Team for graphic design.

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Article Citation

Hwang, Jackelyn, Jason Vargo, Becky Liang, and Vasudha Kumar. 2022. “Residential Instability in the Bay Area Through the COVID-19 Pandemic.” Federal Reserve Bank of San Francisco Community Development Research Brief 2022-04. doi: 10.24148/cdrb2022-4.