To address spatial mismatch, housing agencies seek to locate affordable housing proximate or well-connected to jobs and opportunities. At the same time, transit agencies strive to expand access while minimizing operational costs and energy consumption. Both of these efforts are often done at scales that limit the ability to do deep, community-engaged planning around housing and transit needs. The goal of this planning grant is to identify gaps in current methods of estimating spatial mismatch from both a stakeholder and community perspective; to explore and document models based on data from the community; and design internal and community-facing frameworks for cross-sector planning tools. Ultimately, this will enable the creation of an analytical framework for addressing spatial mismatch using quantitative and qualitative approaches and develop transparent scenario planning tools. The project brings together community-engaged planning, housing policy and finance, transportation demand and network modeling, transportation energy-efficiency, and data-driven public policy analysis.
This project aims to build community-informed frameworks representing spatial mismatch, which lay the foundation for planning tools that directly integrate with housing and transportation planning processes. Accessibility is a function of the transit quality experienced by individuals (i.e., travel cost, time, reliability) and the proximity and connectivity to jobs that match a worker’s skills and other opportunities. Existing methods to study spatial mismatch force an inferential structure on low-income traveler choice; additionally, they focus on adjustments to transit while treating housing as fixed, and vice versa. Spatial mismatch is neither a binary nor static metric, nor can it be measured by empirics alone: its measurement requires community input in the form of travel patterns, constraints, and needs, as well as the quality of transit connections. This project aims to develop a framework for probabilistic, non-linear path models of spatial mismatch interventions, that allow for qualitative data to inform quantitative metric construction. The community engagement process will allow for identification of gaps in current planning processes and new variables that belong in the calculation of accessibility. This project is in response to the Civic Innovation Challenge program, Track A— Communities and Mobility: Offering Better Mobility Options to Solve the Spatial Mismatch Between Housing Affordability and Jobs—and is a collaboration between NSF and the Department of Energy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
