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House Price Changes: A Perspective of Inhomogeneous Multiple Structural Breaks

Author

Listed:
  • Fenglin Tian
  • Yanpeng Li
  • Boping Tian

Abstract

This article proposes an inhomogeneous multiple structural breaks model, with unknown mean changes or variance changes in observations. The asymptotic properties of the likelihood ratio statistics are demonstrated, which converge to a Gumbel distribution. Furthermore, the rule of information criterion and Bayesian model selection are used to detect inhomogeneous multiple change points through the binary segmentation and random interval technique. Extensive simulation experiments are provided to illustrate the promising performance of our method. The real residential property prices for Australia and China are employed in this model for empirical analysis, which illustrates the performance of the proposed model.

Suggested Citation

  • Fenglin Tian & Yanpeng Li & Boping Tian, 2025. "House Price Changes: A Perspective of Inhomogeneous Multiple Structural Breaks," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 58(4), pages 277-288, December.
    • Handle: RePEc:bla:ausecr:v:58:y:2025:i:4:p:277-288
    DOI: 10.1111/1467-8462.70007
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    References listed on IDEAS

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    1. Bai, Jushan, 1999. "Likelihood ratio tests for multiple structural changes," Journal of Econometrics, Elsevier, vol. 91(2), pages 299-323, August.
    2. Jie Chen & Arjun K. Gupta, 2012. "Parametric Statistical Change Point Analysis," Springer Books, Springer, edition 0, number 978-0-8176-4801-5, January.
    3. Fryzlewicz, Piotr, 2014. "Wild binary segmentation for multiple change-point detection," LSE Research Online Documents on Economics 57146, London School of Economics and Political Science, LSE Library.
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