Examining Policies to Reduce Homelessness Using a General Equilibrium Model of the Housing Market

Erin Mansur, University of California at Berkeley
John M. Quigley, University of California at Berkeley
Steven Raphael, University of California at Berkeley
Eugene Smolensky, University of California at Berkeley

Abstract

In this paper, we use a general equilibrium simulation model of the housing market to assess the potential to reduce the incidence of homelessness of various housing-market policy interventions. A version of the model developed by Anas and Arnott is extended and adapted to study homelessness and is calibrated to the four largest metropolitan areas in California. Using data from the Census of Population and Housing for 1980 and 1990 and the American Housing Survey for various years, we explore several alternative simulations. First, we calibrate the model for each metropolitan area to observed housing market and income conditions in 1980 and assess how well the model predicts observed changes in rents during the decade of the 1980s. Next, using models calibrated to 1990 conditions, we assess the effects on homelessness of changes in the income distribution similar to those that occurred during the 1980s. Finally, we explore the welfare consequences and the effects on homelessness of three housing market policy interventions: extending housing vouchers to all low-income households, subsidizing all landlords, and subsidizing those landlords who supply low-income housing. Our results suggest that a very large fraction of homelessness can be eliminated through increased reliance upon well-known housing subsidy policies.