The Impact of Housing Programs on Unsheltered Homeless Population: An Agent-Based Approach

Abstract

This article presents an Agent-Based Modeling approach to simulate the cascading effect that community-based health care services and two temporary housing programs would have on the unsheltered homeless population in Los Angeles. Our model overcomes the challenge that traditional research using aggregated data isn’t sufficient to provide satisfying explanations. We incorporate micro, meso, and macro level components, to uncover the step-by-step changes introduced by integrated program that synchronizes health services and housing programs, including the feedback loop between homeless population and the socio-economic environment they live in. Using key policy levers, we explore the impact of various policies on the unsheltered homeless population. Particularly, we assess the Rapid Re-Housing program, which is one important component of the Housing-First policy, as well as the transitional housing program, which especially aims to support chronically unsheltered homeless people through an aggregate program that conflates the temporary housing and supportive services. To achieve our objective, we use sensitivity analysis to estimate the impact of the number of social workers, effectiveness of policy level, and community-based special care services for mentally ill homeless on macroscopic phenomena. We also conduct two scenario analyses to evaluate two major temporary housing programs on unsheltered homeless. The regression result based on simulation data suggests that the Rapid Re-Housing program is neither effective nor efficient in reducing unsheltered homeless. However, the result illuminates that social workers play vital roles in building relationship with unsheltered homeless people and facilitating chronical unsheltered homeless to receive needed treatment and to be stabilized by housing programs.