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Activity Number:
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531
- Urban Analytics: Modeling and Analysis of High Resolution Urban Data
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Type:
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Invited
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Date/Time:
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Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
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Sponsor:
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Social Statistics Section
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Abstract #309214
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Title:
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Inflection Points in Community-Level Homeless Rates
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Author(s):
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Dennis Culhane* and Thomas Byrne and Chris Glynn
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Companies:
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University of Pennsylvania and Boston University and University of New Hampshire
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Keywords:
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homelessness;
housing affordability;
Bayesian nonparametrics;
Ewens-Pitman;
Mixture model
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Abstract:
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Statistical models of community-level homeless rates typically assume a linear relationship to covariates. This linear model assumption precludes the possibility of inflection points in homeless rates -- thresholds in quantifiable metrics of a community that, once breached, are associated with large increases in homelessness. In this talk, we identify points of structural change in the relationship between homeless rates and community-level measures of housing affordability and extreme poverty. We utilize the Ewens-Pitman attraction distribution to develop a Bayesian nonparametric mixture model in which clusters of communities with similar covariates share common patterns of variation in homeless rates. A main finding of the study is that the expected homeless rate in a community increases sharply once median rental costs exceed 32% of median income, providing statistical evidence for the widely used definition of a housing cost burden at 30% of income. Our analysis also identifies clusters of communities that exhibit distinct geographic patterns and yield insight into the homelessness and housing affordability crisis unfolding on both coasts of the United States.
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Authors who are presenting talks have a * after their name.
