Dynamic housing market equilibrium with taste heterogeneity, idiosyncratic perfect foresight, and stock conversions*

A discrete-time, nonstationary dynamic equilibrium model of the housing market is developed in which consumers exhibit taste heterogeneity and investors act with perfect foresight subject to idiosyncratic uncertainty in costs. Housing is treated as a discrete, durable, and differentiated good which is indivisible in consumption and a convertible asset in investment. The dynamic market equilibrium determines the allocation of each consumer type among the housing types, the rent and vacancies of each housing type, the asset prices of housing and land, and the conversions between land and housing and among the stocks of housing of each type. The model relies on probabilistic discrete choice theory, whereby the investor's and consumer's choice probabilities are given the multinomial logit specification. An algorithm is developed which solves for dynamic equilibrium by assuming a relationship between rents and asset prices in the terminal period. The computable model is used to examine the “filtering hypothesis”: that technological progress or government subsidies targeted to the construction of high-quality housing eventually benefit the poor. While this hypothesis is correct when subsidies do not induce stock conversions, it is false if investors demolish sufficient numbers of low-quality housing units in order to construct high-quality housing.

[1]  T. Thibodeau,et al.  Filtering and housing markets: An empirical analysis , 1988 .

[2]  J. Sweeney A commodity hierarchy model of the rental housing market , 1974 .

[3]  K. Small,et al.  Applied Welfare Economics with Discrete Choice Models , 1981 .

[4]  R. Braid The short-run comparative statics of a rental housing market , 1981 .

[5]  Daniel McFadden,et al.  Modelling the Choice of Residential Location , 1977 .

[6]  R. Braid The effects of government housing policies in a vintage filtering model , 1984 .

[7]  Richard Arnott,et al.  Housing Quality, Maintenance and Rehabilitation , 1983 .

[8]  A. Anas Residential location markets and urban transportation : economic theory, econometrics, and policy analysis with discrete choice models , 1982 .

[9]  J. Ohls Public policy toward low income housing and filtering in housing markets , 1975 .

[10]  D. Weinberg,et al.  The demand for rental housing: Evidence from the Housing Allowance Demand Experiment , 1981 .

[11]  I. S. Lowry Filtering and Housing Standards: A Conceptual Analysis , 1960 .

[12]  Alex Anas,et al.  A probabilistic approach to the structure of rental housing markets , 1980 .

[13]  R. Muth,et al.  Cities and Housing. , 1970 .

[14]  D. Pinés,et al.  Spatial aspects of housing quality, density, and maintenance , 1986 .

[15]  D. McFadden,et al.  URBAN TRAVEL DEMAND - A BEHAVIORAL ANALYSIS , 1977 .

[16]  H. Rosen Housing Subsidies: Effects on Housing Decisions, Efficiency, and Equity , 1983 .

[17]  R. Bellman Dynamic programming. , 1957, Science.

[18]  J. Royce Ginn,et al.  Front matter, The Detroit Prototype of the NBER Urban Simulation Model , 1973 .

[19]  R. Struyk,et al.  The Web of Urban Housing: Analyzing Policy with a Market Simulation Model , 1975 .

[20]  E. Hanushek,et al.  An explicit model of intra-metropolitan mobility. , 1978, Land economics.

[21]  R. Struyk,et al.  Exploring the effects of racial preferences on urban housing markets , 1986 .

[22]  R. Struyk,et al.  Analyzing Housing Policies with the Urban Institute Housing Model , 1977 .

[23]  James L. Sweeney,et al.  Quality, Commodity Hierarchies, and Housing Markets , 1974 .