An Agent-Based Simulation of Rental Housing Markets

We simulate a closed rental housing market with search and matching frictions, in which both landlord and tenant agents are imperfectly informed. Homogeneous landlords set rents to maximise revenue, using information on the market to estimate the relationship between posted rent and time-on-the-market (TOM). Tenants, heterogeneous in income, engage in undirected search accepting residences based on their idiosyncratic tastes for housing and a disagreement point derived from information on the distribution of offers. The steady state to which the simulation evolves shows price dispersion, nonzero search times and vacancies.The main results concern the effects of increasing information on either side of the market. When tenants see a greater percentage of the distribution of offers, tenants learn to refuse high rents and so the population rises and tenants' utilities rise as does overall welfare. Conversely, when landlords have less information, their utility can rise as over estimations in best posting rent move the market to higher rents.