INFLECTION POINTS IN COMMUNITY-LEVEL HOMELESS RATES

• 成果类型: Article
• 署名作者: Glynn, Chris; Byrne, Thomas H.; Culhane, Dennis P.
• 署名单位: Boston University; University of Pennsylvania
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/20-AOAS1414
• 发表日期: 2021
• 页码: 1037-1053
• 关键词: regression; inference; MODEL

摘要

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 paper 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 (EPA) distribution to develop a Bayesian nonparametric regression 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 begins to quickly increase once median rental costs exceed 30% of median income, providing a statistical link between homelessness and the U.S. government's definition of a housing cost burden. Our analysis also identifies clusters of communities that exhibit distinct geographic patterns and yields insight into the homelessness and housing affordability crisis unfolding on both coasts of the United States.