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The impact of social influence in Australian real estate: market forecasting with a spatial agent-based model

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Listed:
  • Benjamin Patrick Evans

    (The University of Sydney)

  • Kirill Glavatskiy

    (The University of Sydney)

  • Michael S. Harré

    (The University of Sydney)

  • Mikhail Prokopenko

    (The University of Sydney)

Abstract

Housing markets are inherently spatial, yet many existing models fail to capture this spatial dimension. Here, we introduce a new graph-based approach for incorporating a spatial component in a large-scale urban housing agent-based model (ABM). The model explicitly captures several social and economic factors that influence the agents’ decision-making behaviour (such as fear of missing out, their trend-following aptitude, and the strength of their submarket outreach), and interprets these factors in spatial terms. The proposed model is calibrated and validated with the housing market data for the Greater Sydney region. The ABM simulation results not only include predictions for the overall market, but also produce area-specific forecasting at the level of local government areas within Sydney as arising from individual buy and sell decisions. In addition, the simulation results elucidate agent preferences in submarkets, highlighting differences in agent behaviour, for example, between first-time home buyers and investors, and between both local and overseas investors.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jeicoo:v:18:y:2023:i:1:d:10.1007_s11403-021-00324-7
    DOI: 10.1007/s11403-021-00324-7
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    Cited by:

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    2. Richard Bläse & Matthias Filser & Sascha Kraus & Kaisu Puumalainen & Petra Moog, 2024. "Non‐sustainable buying behavior: How the fear of missing out drives purchase intentions in the fast fashion industry," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 626-641, February.
    3. Carro, Adrian, 2023. "Taming the housing roller coaster: The impact of macroprudential policy on the house price cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 156(C).

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    More about this item

    Keywords

    Agent-based modelling; Spatial models; Housing markets; Decision-making; Social influence; Trend following;
    All these keywords.

    JEL classification:

    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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