Can a stochastic cusp catastrophe model explain housing market crashes?

Cees Diks, Juanxi Wang

Research output: Contribution to journalArticle

19 Citations (Scopus)

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.

LanguageEnglish
Pages68-88
Number of pages21
JournalJournal of Economic Dynamics and Control
Volume69
Early online date19 May 2016
DOIs
Publication statusPublished - 20 Aug 2016

Fingerprint

Catastrophe
Crash
Cusp
Euler
Interest Rates
Discretization
Multiple Equilibria
Discretization Method
Stock Market
Long-run
Model
Stochastic models
Time series
Predict
Market
Market crash
Housing market
Prediction

Keywords

  • housing market
  • instability
  • multiple equilibria
  • stochastic catastrophe

Cite this

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title = "Can a stochastic cusp catastrophe model explain housing market crashes?",
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.",
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Can a stochastic cusp catastrophe model explain housing market crashes? / Diks, Cees; Wang, Juanxi.

In: Journal of Economic Dynamics and Control, Vol. 69, 20.08.2016, p. 68-88.

Research output: Contribution to journalArticle

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