Employment, property offenses, and homelessness: a quantitative analysis of structural disadvantage and arrest outcomes
Year: 2026
Type: article
Abstract: The annual Point-in-Time count indicates homelessness in the US increased by 18% between 2023 and 2024. Because this count is completed in January, it does not consider those who are homeless for less than 30 days during other parts of the year. Acute homelessness is intimately connected with mental illness, criminal arrests, and poverty. Employment is a viable means through which persons experiencing homelessness can escape this cycle. Utilizing the 2016 Survey of Prison Inmates as data and General Strain Theory as an interpretive lens, this study examines the extent to which different types of acute homelessness impact property offense arrests and the moderating role of employment. Respondents who were living in a vehicle 30 days before their arrest had significantly greater odds of being arrested for a property offense at 85% (OR = 1.85, 95% CI [1.34, 2.55]). Those living in a shelter or on the streets had significantly higher odds at 156% (OR = 2.56, 95% CI [1.95, 3.36]) of being arrested for a property offense. Among respondents who were living in a car 30 days before their arrest, being employed significantly reduced the odds of committing a property offense by 41% (OR = 0.59, 95% CI [0.36, 0.96]). The findings provide evidence that acute homelessness is associated with increased property offending, and employment moderates this association, consistent with GST. Our interaction finding that employment significantly reduced property offense odds among vehicle-dwelling individuals points toward economic integration as a more effective lever than enforcement.
Source: Crime Law and Social Change
Authors: Tremaine Sails-Dunbar, Serita Whiting
Institutions: University of South Carolina, Prairie View A&M University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
OpenAlex ID: W7225561722
