Vital Signs: Displacement Risk - by metro
VITAL SIGNS INDICATOR
Displacement Risk (EQ3)
FULL MEASURE NAME
Share of lower-income households living in tracts at risk of displacement
LAST UPDATED
December 2018
DESCRIPTION
Displacement risk refers to the share of lower-income households living in neighborhoods that have been losing lower-income residents over time, thus earning the designation “at risk”. While “at risk” households may not necessarily be displaced in the short-term or long-term, neighborhoods identified as being “at risk” signify pressure as reflected by the decline in lower-income households (who are presumed to relocate to other more affordable communities). The dataset includes metropolitan area, regional, county and census tract tables.
DATA SOURCE
U.S. Census Bureau: Decennial Census
1980-1990
Form STF3
https://nhgis.org
U.S. Census Bureau: Decennial Census
2000
Form SF3a
https://nhgis.org
U.S. Census Bureau: Decennial Census
1980-2010
Longitudinal Tract Database
http://www.s4.brown.edu/us2010/index.htm
U.S. Census Bureau: American Community Survey
2010-2015
Form S1901
5-year rolling average
http://factfinder2.census.gov
U.S. Census Bureau: American Community Survey
2010-2017
Form B19013
5-year rolling average
http://factfinder2.census.gov
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
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.
Querying over HTTP
Splitgraph serves as an HTTP API that lets you run SQL queries directly on
this data to power Web applications. For example:
curl https://data.splitgraph.com/sql/query/ddn \
-H "Content-Type: application/json" \
-d@-<<EOF
{"sql": "
SELECT *
FROM \"bayareametro-gov/vital-signs-displacement-risk-by-metro-wx2e-8w6i\".\"vital_signs_displacement_risk_by_metro\"
LIMIT 100
"}
EOFSee the Splitgraph documentation
for more information.
