Displacement has become a serious regional concern over the past few decades. As recently as 1990, San Francisco was the only Bay Area county with more than 30 percent of its lower-income residents at risk. By 2015, every county except Contra Costa had displacement risk levels in that range. Rising displacement risk has been powered not only by bayside communities becoming increasingly expensive, but also by North Bay counties once seemingly immune to displacement risk now being buffeted by market forces. While San Francisco had the highest displacement risk of any Bay Area county in every decade up to 2010, nearby counties such as Marin and San Mateo have now found themselves eclipsing San Francisco as our region’s top hotspots for displacement risk. In part, this may be attributable to the similarly high housing costs in those locations paired with much more limited affordable housing policy protections than those in the city proper.
As our region’s economy has reached new heights in recent years – with high-paying job growth in San Francisco, Silicon Valley, and beyond – displacement risk has become an increasingly regional problem. Rising housing costs, combined with a lack of tenant protections, can result in families having to relocate to distant, more affordable communities. While it is not possible to quantify the number of households displaced in a given year, displacement risk helps us identify those communities under pressure, providing a “barometer” over time for this critical issue.
Displacement risk has become a regional issue in recent years, through a combination of rising housing prices, scarce affordable housing production, and limited tenant protections in many cities. While urban neighborhoods have long been at risk of displacement via gentrification, the problem can be just as acute in suburban communities such as Concord, El Cerrito, Santa Clara and Santa Rosa. Not surprisingly, cities known for providing affordable options to those displaced – such as Antioch and Vallejo – have relatively few neighborhoods considered at risk, even as they experience rising poverty.
2015 Displacement Risk by Neighborhood
Houston and Dallas have the lowest and second-lowest levels of displacement risk, respectively, among major U.S. metro areas. This speaks not only to their relative affordability – which reduces pressure on lower-income households – but also to the lack of gentrification in these metro areas’ traditional lower-income communities. In contrast to metropolitan areas like Philadelphia, Washington or Los Angeles, Texas metro areas have maintained a 20th century-style pattern of outward development, which has resulted in many higher-income earners continuing to prefer locations at the periphery. In contrast, the metro areas with the highest risk of displacement have seen a much greater shift in homebuyer preferences, resulting in more gentrification and heightened pressure for displacement in renewed walkable urban cores.
U.S. Census Bureau: Decennial Census – via IPUMS National Historical Geographic Information System
Form STF3 – https://nhgis.org (1980-1990)
Form SF3a – https://nhgis.org (2000)
U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database
Spatial Structures in the Social Sciences, Brown University
Population Estimates (1980 - 2010)
U.S. Census Bureau: American Community Survey
Form S1901 (2010-2015)
Form B19013 (2010-2015)
Image: Flickr (Creative Commons license), Photographer: Evan Blaser
Aligning with the approach used for Plan Bay Area 2040, displacement risk is calculated by comparing the analysis year with the most recent year prior to identify census tracts that are losing lower-income households. Historical data is pulled from U.S. Census datasets and aligned with today’s census tract boundaries using crosswalk tables provided by LTDB. Tract data, as well as regional income data, are calculated using 5-year rolling averages for consistency – given that tract data is only available on a 5-year basis. Using household tables by income level, the number of households in each tract falling below the median are summed, which involves summing all brackets below the regional median and then summing a fractional share of the bracket that includes the regional median (assuming a simple linear distribution within that bracket).
Once all tracts in a given county or metro area are synced to today’s boundaries, the analysis identifies census tracts of greater than 500 lower-income people (in the prior year) to filter out low-population areas. For those tracts, any net loss between the prior year and the analysis year results in that tract being flagged as being at risk of displacement, and all lower-income households in that tract are flagged. To calculate the share of households at risk, the number of lower-income households living in flagged tracts are summed and divided by the total number of lower-income households living in the larger geography (county or metro). Minor deviations on a year-to-year basis should be taken in context, given that data on the tract level often fluctuates and has a significant margin of error; changes on the county and regional level are more appropriate to consider on an annual basis instead.