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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
  • Kirill Glavatskiy
  • Michael S. Harr'e
  • Mikhail Prokopenko

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. Harr'e & Mikhail Prokopenko, 2020. "The impact of social influence in Australian real-estate: market forecasting with a spatial agent-based model," Papers 2009.06914, arXiv.org, revised Feb 2021.
    • Handle: RePEc:arx:papers:2009.06914
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    References listed on IDEAS

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    1. Dallas Rogers & Chyi Lin Lee & Ding Yan, 2015. "The Politics of Foreign Investment in Australian Housing: Chinese Investors, Translocal Sales Agents and Local Resistance," Housing Studies, Taylor & Francis Journals, vol. 30(5), pages 730-748, July.
    2. Bahadir, Berrak & Mykhaylova, Olena, 2014. "Housing market dynamics with delays in the construction sector," Journal of Housing Economics, Elsevier, vol. 26(C), pages 94-108.
    3. J. Raimbault & J. Broere & M. Somveille & J. M. Serna & E. Strombom & C. Moore & B. Zhu & L. Sugar, 2020. "A spatial agent based model for simulating and optimizing networked eco-industrial systems," Papers 2003.14133, arXiv.org.
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    Cited by:

    1. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
    2. Adrian Carro & Marc Hinterschweiger & Arzu Uluc & J Doyne Farmer, 2023. "Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(2), pages 386-432.
    3. Mérő, Bence & Borsos, András & Hosszú, Zsuzsanna & Oláh, Zsolt & Vágó, Nikolett, 2023. "A high-resolution, data-driven agent-based model of the housing market," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    4. Sidong Zhao & Kaixu Zhao & Ping Zhang, 2021. "Spatial Inequality in China’s Housing Market and the Driving Mechanism," Land, MDPI, vol. 10(8), pages 1-33, August.
    5. Deepeka Garg & Benjamin Patrick Evans & Leo Ardon & Annapoorani Lakshmi Narayanan & Jared Vann & Udari Madhushani & Makada Henry-Nickie & Sumitra Ganesh, 2024. "A Heterogeneous Agent Model of Mortgage Servicing: An Income-based Relief Analysis," Papers 2402.17932, arXiv.org, revised Feb 2024.
    6. Benjamin Patrick Evans & Mikhail Prokopenko, 2021. "Bounded rationality for relaxing best response and mutual consistency: The Quantal Hierarchy model of decision-making," Papers 2106.15844, arXiv.org, revised Mar 2023.
    7. Benjamin Patrick Evans & Mikhail Prokopenko, 2022. "Bounded strategic reasoning explains crisis emergence in multi-agent market games," Papers 2206.05568, arXiv.org.

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