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Can a stochastic cusp catastrophe model explain housing market crashes?

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  • Diks, Cees
  • Wang, Juanxi

Abstract

Like stock market prices, housing prices often exhibit temporary booms and busts. A possible explanation for the observed abrupt changes is offered by the stochastic catastrophe model. This paper addresses the question whether the catastrophe model can describe and predict the dynamics of housing markets. We fit a stochastic cusp catastrophe model to empirical housing market data for six OECD countries, US, JP, UK, NL, SE and BE. Two different estimation approaches are considered – Cobb׳s method and Euler discretization. The analysis shows that while Cobb׳s approach describes the long-run stationary density better, Euler discretization is more tailored for time series, as it provides better one-step-ahead predictions. Proceeding using the Euler discretization method we discuss the dynamics of housing markets in terms of the multiple equilibria cusp catastrophe model. By considering the long-term interest rate as an exogenous variable we obtain new insights into the policy implications of interest rate levels, in particular concerning the stability of housing markets.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:dyncon:v:69:y:2016:i:c:p:68-88
    DOI: 10.1016/j.jedc.2016.05.008
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    Cited by:

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    2. 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.
    3. Huang, Wencheng & Zhang, Rui & Xu, Minhao & Yu, Yaocheng & Xu, Yifei & De Dieu, Gatesi Jean, 2020. "Risk state changes analysis of railway dangerous goods transportation system: Based on the cusp catastrophe model," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    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. 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.
    6. Bolgorian, Meysam, 2019. "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers 2019-2, Kiel Institute for the World Economy (IfW Kiel).
    7. Schmitt, Noemi & Westerhoff, Frank, 2017. "On the bimodality of the distribution of the S&P 500's distortion: Empirical evidence and theoretical explanations," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 34-53.
    8. Martin Carolin & Westerhoff Frank, 2019. "Regulating Speculative Housing Markets via Public Housing Construction Programs: Insights from a Heterogeneous Agent Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(4), pages 627-660, August.
    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. Zhang, Wenjun & Zhang, Yingjun & Zhang, Chuang, 2024. "Research on risk assessment of maritime autonomous surface ships based on catastrophe theory," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    12. Mostafa, Mohamed M., 2022. "Five decades of catastrophe theory research: Geographical atlas, knowledge structure and historical roots," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

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    More about this item

    Keywords

    Stochastic catastrophe; Housing market; Instability; Multiple equilibria;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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