Tenant-based subsidized housing location planning under uncertainty

Abstract

Subsidized housing policy in the United States must increasingly account for a greater use of tenant-based housing subsidies in place of traditional high-rise public housing. This paper focuses on design of policies to assist families relocating from high-rise public housing to rent-subsidized market-rate housing that, in principle, offers more flexibility in consumption and mobility. These policies must incorporate uncertainty in the residential choices of families already using tenant-based subsidies. A multi-objective stochastic integer program for relocation planning is formulated where it is shown that the model can be made linear and solved using chance-constrained programming. Preliminary computational results show that this model, while requiring significant amounts of information on housing mobility and housing markets, can be solved in a straightforward way. Model outputs clearly display tradeoffs between competing objectives and provide decisionmakers with more realistic alternatives for policy development.