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

In: Progress in Artificial Economics

Author

Listed:
  • John Mc Breen

    (ENS-LYON
    University of Lyon)

  • Florence Goffette-Nagot

    (Université de Lyon
    CNRS)

  • Pablo Jensen

    (ENS-LYON
    University of Lyon)

Abstract

We simulate a closed rental housing market with search and matching frictions, in which both landlord and tenant agents are imperfectly informed of the characteristics of the market. 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 his idiosyncratic preference for a random offer and decides whether to accept the offer or continue searching, based on their imperfect knowledge on 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 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that dynamic shocks to the discount rate can provoke overshoots in rent adjustments due in part to landlords use of outdated information in their rent posting decision.

Suggested Citation

  • John Mc Breen & Florence Goffette-Nagot & Pablo Jensen, 2010. "Information and Search on the Housing Market: An Agent-Based Model," Lecture Notes in Economics and Mathematical Systems, in: Marco Li Calzi & Lucia Milone & Paolo Pellizzari (ed.), Progress in Artificial Economics, pages 153-164, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-13947-5_13
    DOI: 10.1007/978-3-642-13947-5_13
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    Citations

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    Cited by:

    1. Benjamin Patrick Evans & Kirill Glavatskiy & Michael S. Harré & Mikhail Prokopenko, 2023. "The impact of social influence in Australian real estate: market forecasting with a spatial agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(1), pages 5-57, January.
    2. Dutta, Champa Bati & Das, Debasish Kumar, 2017. "What drives consumers' online information search behavior? Evidence from England," Journal of Retailing and Consumer Services, Elsevier, vol. 35(C), pages 36-45.

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