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Measuring Housing Stability With Consumer Reference Data.

David C Phillips1

  • 1Wilson Sheehan Lab for Economic Opportunities, Department of Economics, University of Notre Dame, 3060 Jenkins Nanovic Hall, South Bend, IN, 46556, USA. david.phillips.184@nd.edu.

Demography
|June 26, 2020
PubMed
Summary
This summary is machine-generated.

Consumer data offer a novel way to measure housing instability for low-income renters. This method enhances research on housing policies and tracks moves during critical events like natural disasters or public housing demolition.

Keywords:
Administrative dataHomelessnessHousing stabilityInternal migration

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Area of Science:

  • Social Sciences
  • Urban Studies
  • Public Policy

Background:

  • Housing instability disproportionately affects low-income renters, yet research is limited by measurement challenges.
  • Understanding housing instability is crucial for developing effective housing stabilization policies.

Purpose of the Study:

  • To demonstrate the utility of consumer reference data for measuring housing instability among vulnerable populations.
  • To expand research capabilities on housing policy effectiveness.

Main Methods:

  • Utilizing address histories from consumer reference data to track housing moves across the United States.
  • Analyzing consumer data to identify patterns of extreme housing instability for low-income groups.

Main Results:

  • Consumer data can accurately measure housing stability for groups with very low incomes and high rates of residential mobility.
  • The data allow for tracking housing moves during natural disasters, public housing demolition, and gentrification.
  • Consumer data provide a more granular and cost-effective alternative to surveys and some administrative data.

Conclusions:

  • Consumer reference data represent a valuable, scalable resource for studying housing instability.
  • This approach can significantly improve the quantity and quality of research on housing policies for low-income renters.
  • Future research can leverage these data to better understand and address the complexities of housing instability.