IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2004.07571.html
   My bibliography  Save this paper

Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large scale agent-based model

Author

Listed:
  • Kirill S. Glavatskiy
  • Mikhail Prokopenko
  • Adrian Carro
  • Paul Ormerod
  • Michael Harre

Abstract

Urban housing markets, along with markets of other assets, universally exhibit periods of strong price increases followed by sharp corrections. The mechanisms generating such non-linearities are not yet well understood. We develop an agent-based model populated by a large number of heterogeneous households. The agents' behavior is compatible with economic rationality, with the trend-following behavior found to be essential in replicating market dynamics. The model is calibrated using several large and distributed datasets of the Greater Sydney region (demographic, economic and financial) across three specific and diverse periods since 2006. The model is not only capable of explaining price dynamics during these periods, but also reproduces the novel behavior actually observed immediately prior to the market peak in 2017, namely a sharp increase in the variability of prices. This novel behavior is related to a combination of trend-following aptitude of the household agents (rational herding) and their propensity to borrow.

Suggested Citation

  • 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.
    • Handle: RePEc:arx:papers:2004.07571
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2004.07571
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
    3. Andrea Mazzocchetti & Marco Raberto & Andrea Teglio & Silvano Cincotti, 2018. "Securitization and business cycle: an agent-based perspective," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 1091-1121.
    4. Andrea Teglio & Marco Raberto & Silvano Cincotti, 2012. "The Impact Of Banks' Capital Adequacy Regulation On The Economic System: An Agent-Based Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-27.
    5. Lauretta, Eliana, 2018. "The hidden soul of financial innovation: An agent-based modelling of home mortgage securitization and the finance-growth nexus," Economic Modelling, Elsevier, vol. 68(C), pages 51-73.
    6. Dosi, Giovanni & Fagiolo, Giorgio & Napoletano, Mauro & Roventini, Andrea, 2013. "Income distribution, credit and fiscal policies in an agent-based Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1598-1625.
    7. John Geanakoplos & Robert Axtell & J. Doyne Farmer & Peter Howitt & Benjamin Conlee & Jonathan Goldstein & Matthew Hendrey & Nathan M. Palmer & Chun-Yi Yang, 2012. "Getting at Systemic Risk via an Agent-Based Model of the Housing Market," American Economic Review, American Economic Association, vol. 102(3), pages 53-58, May.
    8. Cardaci, Alberto, 2018. "Inequality, household debt and financial instability: An agent-based perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 434-458.
    9. Reinhart, Karmen & Rogoff, Kenneth, 2009. ""This time is different": panorama of eight centuries of financial crises," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 77-114, March.
    10. 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.
    11. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    12. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    13. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    14. Erlingsson, Einar Jon & Teglio, Andrea & Cincotti, Silvano & Stefansson, Hlynur & Sturlusson, Jon Thor & Raberto, Marco, 2014. "Housing market bubbles and business cycles in an agent-based credit economy," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-42.
    15. Baptista, Rafa & Farmer, J. Doyne & Hinterschweiger, Marc & Low, Katie & Tang, Daniel & Uluc, Arzu, 2016. "Macroprudential policy in an agent-based model of the UK housing market," Bank of England working papers 619, Bank of England.
    16. Marco Raberto & Bulent Ozel & Linda Ponta & Andrea Teglio & Silvano Cincotti, 2019. "From financial instability to green finance: the role of banking and credit market regulation in the Eurace model," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 429-465, March.
    17. Opeoluwa Banwo & Paul Harrald & Francesca Medda, 2019. "Understanding the consequences of diversification on financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 273-292, June.
    18. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    19. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    20. Assenza, Tiziana & Delli Gatti, Domenico & Grazzini, Jakob, 2015. "Emergent dynamics of a macroeconomic agent based model with capital and credit," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 5-28.
    21. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    22. Corrado Di Guilmi, 2017. "The Agent†Based Approach To Post Keynesian Macro†Modeling," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1183-1203, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Benjamin Patrick Evans & Mikhail Prokopenko, 2021. "A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback," Papers 2102.09180, arXiv.org, revised May 2021.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Teglio, Andrea & Mazzocchetti, Andrea & Ponta, Linda & Raberto, Marco & Cincotti, Silvano, 2019. "Budgetary rigour with stimulus in lean times: Policy advices from an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 59-83.
    4. 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.
    5. Michael S. Harr'e, 2018. "Multi-agent Economics and the Emergence of Critical Markets," Papers 1809.01332, arXiv.org.
    6. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    7. Lamperti, Francesco & Bosetti, Valentina & Roventini, Andrea & Tavoni, Massimo & Treibich, Tania, 2021. "Three green financial policies to address climate risks," Journal of Financial Stability, Elsevier, vol. 54(C).
    8. repec:hal:spmain:info:hdl:2441/5bnglqth5987gaq6dhju3psjn3 is not listed on IDEAS
    9. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    10. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    11. Giovanni Dosi & Andrea Roventini, 2017. "Agent-Based Macroeconomics and Classical Political Economy: Some Italian Roots," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 261-283, November.
    12. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    13. Mauro Napoletano, 2018. "A Short Walk on the Wild Side: Agent-Based Models and their Implications for Macroeconomic Analysis," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(3), pages 257-281.
    14. Erlingsson, Einar Jon & Teglio, Andrea & Cincotti, Silvano & Stefansson, Hlynur & Sturlusson, Jon Thor & Raberto, Marco, 2014. "Housing market bubbles and business cycles in an agent-based credit economy," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-42.
    15. 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).
    16. Furtado, Bernardo Alves & Eberhardt, Isaque Daniel Rocha, 2015. "Modelo espacial simples da economia: uma proposta teórico-metodológica [A simple spatial economic model: a proposal]," MPRA Paper 67005, University Library of Munich, Germany.
    17. 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.
    18. Lilit Popoyan, 2020. "Macroprudential Policy: a Blessing or a Curse?," Review of Economics and Institutions, Università di Perugia, vol. 11(1-2).
    19. Tang, Yinan & Chen, Ping, 2015. "Transition probability, dynamic regimes, and the critical point of financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 11-20.
    20. Eugenio Caverzasi & Alberto Russo, 2018. "Toward a new microfounded macroeconomics in the wake of the crisis," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 999-1014.
    21. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2020. "Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2004.07571. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.