IDEAS home Printed from https://ideas.repec.org/a/spr/jeicoo/v14y2019i4d10.1007_s11403-019-00267-0.html
   My bibliography  Save this article

Dissecting the myth of the house price in Chinese metropolises: allowing for behavioral heterogeneity among investors

Author

Listed:
  • Ling Zhang

    (Guangdong University of Finance)

  • Wenlong Bian

    (Sungkyunkwan University)

  • Hao Zhang

    (Guangdong University of Foreign Studies
    Southern China Institute of Fortune Management Research)

Abstract

This paper aims to demystify the housing boom in Chinese metropolises by allowing for behavioral heterogeneity among investors. We construct an agent-based model where investors are categorized into two groups: fundamentalists and chartists. In addition, the investment strategy switching is allowed between these two groups contingent on the historical performance. Using the data of five Chinese metropolises over the period 2008–2014, the results suggest that chartists dominate the housing market and make the house price maintain an upward trend, while fundamentalists play a stabilizing role. Specifically, fundamentalists can serve as a “price anchor” in the market, because the proportion of the fundamentalists is negatively associated with both the growth rate of the house price and the deviation relative to the fundamental value. Overall, the impact of the chartists on the house price is much greater than that of the fundamentalists, which contributes to the ever-increasing house price in Chinese metropolises.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:jeicoo:v:14:y:2019:i:4:d:10.1007_s11403-019-00267-0
    DOI: 10.1007/s11403-019-00267-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11403-019-00267-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11403-019-00267-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
    2. Dieci, Roberto & Westerhoff, Frank, 2016. "Heterogeneous expectations, boom-bust housing cycles, and supply conditions: A nonlinear economic dynamics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 21-44.
    3. 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.
    4. Thomas Lux & Michele Marchesi, 2000. "Volatility Clustering In Financial Markets: A Microsimulation Of Interacting Agents," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 675-702.
    5. Cars Hommes, 2013. "Reflexivity, expectations feedback and almost self-fulfilling equilibria: economic theory, empirical evidence and laboratory experiments," Journal of Economic Methodology, Taylor & Francis Journals, vol. 20(4), pages 406-419, December.
    6. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    7. Hommes, C.H. & Bao, T., 2015. "When Speculators Meet Constructors: Positive and Negative Feedback in Experimental Housing Markets," CeNDEF Working Papers 15-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    8. John M. Quigley, 1999. "Real Estate Prices and Economic Cycles," International Real Estate Review, Global Social Science Institute, vol. 2(1), pages 1-20.
    9. Goetzmann, William Nelson, 1993. "The Single Family Home in the Investment Portfolio," The Journal of Real Estate Finance and Economics, Springer, vol. 6(3), pages 201-222, May.
    10. 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.
    11. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    12. Kouwenberg, Roy & Zwinkels, Remco, 2014. "Forecasting the US housing market," International Journal of Forecasting, Elsevier, vol. 30(3), pages 415-425.
    13. 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.
    14. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    15. Gian Italo Bischi & Carl Chiarella & Iryna Sushko (ed.), 2013. "Global Analysis of Dynamic Models in Economics and Finance," Springer Books, Springer, edition 127, number 978-3-642-29503-4, December.
    16. Zhang, Hao & Huang, Yuyuan & Yao, Haixiang, 2016. "Heterogeneous expectation, beliefs evolution and house price volatility," Economic Modelling, Elsevier, vol. 53(C), pages 409-418.
    17. Christian Hott & Pierre Monnin, 2008. "Fundamental Real Estate Prices: An Empirical Estimation with International Data," The Journal of Real Estate Finance and Economics, Springer, vol. 36(4), pages 427-450, May.
    18. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    19. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    20. Sommervoll, Dag Einar & Borgersen, Trond-Arne & Wennemo, Tom, 2010. "Endogenous housing market cycles," Journal of Banking & Finance, Elsevier, vol. 34(3), pages 557-567, March.
    21. 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.
    22. Karl E. Case & Robert J. Shiller, 2003. "Is There a Bubble in the Housing Market?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(2), pages 299-362.
    23. Roberto Dieci & Frank Westerhoff, 2012. "A simple model of a speculative housing market," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 303-329, April.
    24. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    25. Zeeman, E. C., 1974. "On the unstable behaviour of stock exchanges," Journal of Mathematical Economics, Elsevier, vol. 1(1), pages 39-49, March.
    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. Hu, Chunhua & Feng, Huarong, 2024. "Kinetic model for asset allocation with strategy switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).

    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. 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.
    2. Zhang, Hao & Huang, Yuyuan & Yao, Haixiang, 2016. "Heterogeneous expectation, beliefs evolution and house price volatility," Economic Modelling, Elsevier, vol. 53(C), pages 409-418.
    3. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. Noemi Schmitt & Frank Westerhoff, 2022. "Speculative housing markets and rent control: insights from nonlinear economic dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 141-163, January.
    5. Zheng, Min & Wang, Hefei & Wang, Chengzhang & Wang, Shouyang, 2017. "Speculative behavior in a housing market: Boom and bust," Economic Modelling, Elsevier, vol. 61(C), pages 50-64.
    6. 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.
    7. Chen, Zhenxi, 2016. "Regimes dependent speculative trading: Evidence from the United States housing market," FinMaP-Working Papers 66, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    8. 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.
    9. Alessio Emanuele Biondo, 2019. "Order book modeling and financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 469-489, September.
    10. He, Xue-Zhong & Li, Youwei & Zheng, Min, 2019. "Heterogeneous agent models in financial markets: A nonlinear dynamics approach," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 135-149.
    11. 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.
    12. 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.
    13. Majewski, Adam A. & Ciliberti, Stefano & Bouchaud, Jean-Philippe, 2020. "Co-existence of trend and value in financial markets: Estimating an extended Chiarella model," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    14. Biondo, Alessio Emanuele, 2018. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-21.
    15. Alessio Emanuele Biondo, 2018. "Order book microstructure and policies for financial stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 35(1), pages 196-218, March.
    16. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
    17. 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.
    18. Biondo, Alessio Emanuele, 2017. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics Discussion Papers 2017-104, Kiel Institute for the World Economy (IfW Kiel).
    19. Chiarella, Carl & He, Xue-Zhong & Zwinkels, Remco C.J., 2014. "Heterogeneous expectations in asset pricing: Empirical evidence from the S&P500," Journal of Economic Behavior & Organization, Elsevier, vol. 105(C), pages 1-16.
    20. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.

    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:spr:jeicoo:v:14:y:2019:i:4:d:10.1007_s11403-019-00267-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.