Measuring Integration in Affordable Housing with Location Data

• In Event: Studying Integrated Spaces and the Policies that Support Them

Abstract

This project will evaluate a selection of longstanding hypotheses about spatial integration through a national and comparative examination of mobility patterns. A novel human mobility dataset from our study year of 2023, enables us to quantitatively examine, over time and space, the actual sites visited by anonymized individuals and develop descriptions of experienced integration. By examining the actual movements of individuals at a national scale, the project will test the tension between theories emerging from quantitative work on the power of proximity and opportunity for individual outcomes and those drawn from case studies documenting persistent patterns of experienced segregation and exclusion inside mixed-income areas. Moving people to ‘better’ places to correct social inequality is a central logic of contemporary affordable housing policy in the US, and has resulted in tens of thousands of low-income residents in higher-income areas. Building off findings from case studies that ask where, when, and under what historical and institutional conditions, residents of subsidized housing use the same services as other residents of ‘opportune’ areas. We use cell phone data to look at subsidized housing residents by sampling block groups in which the vast majority of housing is subsidized affordable housing and compare the distance traveled, time spent, and types of places visited by this group with a selection of ‘control’ block groups. Given the various scales of physical isolation – at the neighborhood and metropolitan level – we uncovered from our case study analysis, we hypothesize that, while subsidized residents in “opportune” block groups do not necessarily travel longer distances nor visit fewer places, they are nevertheless socially isolated from their neighbors and more socially isolated from comparable naturally occurring affordable housing in less “opportune” areas.

Author

• Wenfei Xu, University of California, Santa Barbara
  Presenting Author