ABSTRACT
Two different city-level homelessness data types have been used by many homelessness studies in the United States: intercity data and intracity data. Intercity homelessness data are collected through cross-sectional surveys to estimate the number of persons experiencing homelessness in each city or metropolitan area. Intracity homelessness data are collected through prior address information reported by persons experiencing homelessness within a city’s jurisdiction. This article reviews and compares both city-level homelessness data types. The comparison of intercity and intracity data offers insight into the strength and weaknesses of each data type in identifying the causes of homelessness and the characteristics associated with a high risk of homelessness. Intercity homelessness data examine the effect of policy and institutional variables and community-level variables that vary across cities on the prevalence of homelessness. Meanwhile, intracity homelessness data focus on the spatial variation of demographic, socioeconomic, housing, and other neighborhood factors that contribute to the incidence of homelessness within a jurisdiction that has the same policy and institutional variables. The findings from intracity and intercity homelessness data are not contradictory but complementary. The complementary findings between intercity and intracity homelessness data provide important information for planners to address homelessness at local levels.
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No potential conflict of interest was reported by the author.
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Deden Rukmana
Deden Rukmana is Professor and Chair of the Department of Community and Regional Planning at Alabama A&M University. He received a PhD degree in Urban and Regional Planning from Florida State University and completed master’s degrees from the University of Southern California as well as Bandung Institute of Technology. His research centers on health disparities, homelessness and poverty in the United States, and spatial planning, housing and development challenges in Indonesia.