Estimating Residential Displacement in the Central Puget Sound Region using Household Survey Data

Abstract

Housing instability is a persistent challenge faced by households in cities across the United States. In worst-case scenarios, households are displaced from their residences and forced to start anew. In an effort to mitigate the harms of residential displacement, local policymakers have an interest in monitoring residential displacement within their communities. In this work, we propose a new strategy to estimate sub-county residential displacement within the Central Puget Sound Region using data from three household survey programs. We first estimate residential displacement between 2016-2023 from a local household travel survey using a Bayesian spatiotemporal model, and poststratify with data from the American Community Survey. We then benchmark these estimates to the American Housing Survey to ensure consistency across sources. The results reveal east-west and north-south differences in residential displacement rates within the region as well as a temporary moderation of displacement in the 2020-2021 cohort of movers. Our estimates are publicly available for interested stakeholders to further study trends in residential displacement in the Central Puget Sound Region, and our methodology is transportable to other jurisdictions with similar data contexts.

Figures (4)

• Figure 1: Maps of the number of recent movers sampled by each wave of the HTS organized by move cohort and PUMA. For many move cohort and PUMA combinations, the number of samples is small, precluding direct estimation of residential displacement.
• Figure 2: Maps of the posterior median estimates of the residential displacement rates for each move cohort. County borders are displayed by the thick grey lines and PUMA borders are displayed by the thin grey lines. The PUMA boundaries for the 2016-2017, 2018-2019, and 2020-2021 move cohorts correspond to the 2010 census definitions whereas the PUMA boundaries for the 2022-2023 move cohort correspond to the 2020 census definitions.
• Figure 3: Maps of the 95% credible interval widths for the residential displacement rates for each move cohort. Darker shades of green correspond to wider credible intervals (i.e., greater uncertainty). County borders are displayed by the thick grey lines and PUMA borders are displayed by the thin grey lines. The PUMA boundaries for the 2016-2017, 2018-2019, and 2020-2021 move cohorts correspond to the 2010 census definitions whereas the PUMA boundaries for the 2022-2023 move cohort correspond to the 2020 census definitions.
• Figure 4: Results of the benchmarking stage of our residential displacement rate estimation workflow. Panel (a) plots the PUMA-level unbenchmarked posterior median estimates against the benchmarked posterior estimates, coloured by move cohort, as well as the identity line in black. The points track the line closely, implying that the unbenchmarked estimates are largely aligned with the AHS-derived estimates of residential displacement for all of the Central Puget Sound Region. Panel (b) plots the PUMA-level unbenchmarked posterior standard deviations against the benchmarked posterior standard deviations, coloured by move cohort, as well as the identity line in black. For three of the four move cohorts, the points lie below the line, implying that overall, benchmarking increases the precision of our residential displacement risk estimates.