Information and Search on the Housing Market: An Agent-based Model

We simulate a closed rental housing market with search and matching frictions, in which both landlord and tenant agents may be imperfectly informed of the characteristics of the market. The model hypotheses are set so as to match a rent posting search model in the spirit of search models of the labor market. In the simulations, landlords decide what rent to post based on the expected effect of the rent on the time-on-the-market (TOM) required to find a tenant. Each tenant observes their idiosyncratic preference for a random offer and decides whether to accept the offer or continue searching, based on their imperfect knowledge of the distribution of offered rents. The steady state to which the simulation evolves shows price dispersion, nonzero search times and vacancies. We further assess the effects of altering the level of information for landlords. Landlords are better off when they have less information. In that case they underestimate the TOM and so the steady-state of the market moves to higher rents. However, when landlords with different levels of information are present on the market, the better informed are consistently better off. The model setup also allows the analysis of market dynamics. It is observed that dynamic shocks to the discount rate can provoke overshoots in rent adjustments due in part to landlords use of outdated information in their rent posting decision.