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Endogenous Price Bubbles in a Multi-Agent System of the Housing Market

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  • Roy Kouwenberg
  • Remco C J Zwinkels

Abstract

Economic history shows a large number of boom-bust cycles, with the U.S. real estate market as one of the latest examples. Classical economic models have not been able to provide a full explanation for this type of market dynamics. Therefore, we analyze home prices in the U.S. using an alternative approach, a multi-agent complex system. Instead of the classical assumptions of agent rationality and market efficiency, agents in the model are heterogeneous, adaptive, and boundedly rational. We estimate the multi-agent system with historical house prices for the U.S. market. The model fits the data well and a deterministic version of the model can endogenously produce boom-and-bust cycles on the basis of the estimated coefficients. This implies that trading between agents themselves can create major price swings in absence of fundamental news.

Suggested Citation

  • Roy Kouwenberg & Remco C J Zwinkels, 2015. "Endogenous Price Bubbles in a Multi-Agent System of the Housing Market," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
    • Handle: RePEc:plo:pone00:0129070
    DOI: 10.1371/journal.pone.0129070
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    References listed on IDEAS

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    1. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
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    14. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
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    Cited by:

    1. Martin, Carolin & Schmitt, Noemi & Westerhoff, Frank, 2021. "Heterogeneous expectations, housing bubbles and tax policy," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 555-573.
    2. Ling Zhang & Wenlong Bian & Hao Zhang, 2019. "Dissecting the myth of the house price in Chinese metropolises: allowing for behavioral heterogeneity among investors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 721-740, December.
    3. Martin, Carolin & Schmitt, Noemi & Westerhoff, Frank, 2022. "Housing Markets, Expectation Formation And Interest Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 26(2), pages 491-532, March.
    4. Dieci, Roberto & Schmitt, Noemi & Westerhoff, Frank, 2018. "Interactions between stock, bond and housing markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 43-70.
    5. 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.
    6. 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.
    7. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harre, 2020. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large scale agent-based model," Papers 2004.07571, arXiv.org.
    8. Hommes, Cars & Vroegop, Joris, 2019. "Contagion between asset markets: A two market heterogeneous agents model with destabilising spillover effects," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 314-333.
    9. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    10. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    11. 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).
    12. Diks, Cees & Wang, Juanxi, 2016. "Can a stochastic cusp catastrophe model explain housing market crashes?," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 68-88.
    13. Saskia ter Ellen & Willem F. C. Verschoor, 2018. "Heterogeneous Beliefs and Asset Price Dynamics: A Survey of Recent Evidence," Dynamic Modeling and Econometrics in Economics and Finance, in: Fredj Jawadi (ed.), Uncertainty, Expectations and Asset Price Dynamics, pages 53-79, Springer.
    14. Saskia ter Ellen & Willem F.C. Verschoor, 2017. "Heterogeneous beliefs and asset price dynamics: a survey of recent evidence," Working Paper 2017/22, Norges Bank.

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