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Understanding intracity housing market dynamics: A state-space model with Bayesian nonparametric clustering approach

Author

Listed:
  • Yaopei Wang
  • Yong Tu
  • Wayne Xinwei Wan

Abstract

Understanding the intracity heterogeneities in housing market dynamics across microgeographic areas is important but challenging due to infrequent transactions. Unlike traditional methods that use trend-based clustering to improve the accuracy of local housing price and rent indices, we propose a novel hybrid model that combines the state-space model and the Bayesian nonparametric clustering approach to cluster neighbourhoods according to their temporal price volatility. We show that our methods improve the performance of traditional methods by 10-40%, using over 889,428 housing transactions in Singapore between 2006 and 2018. We also demonstrate a practical application of our method – monitoring neighbourhoods’ distinct market reactions to macroeconomic or policy shocks, which has important implications for urban planning and housing investment.

Suggested Citation

  • Yaopei Wang & Yong Tu & Wayne Xinwei Wan, 2025. "Understanding intracity housing market dynamics: A state-space model with Bayesian nonparametric clustering approach," Environment and Planning B, , vol. 52(7), pages 1601-1617, September.
    • Handle: RePEc:sae:envirb:v:52:y:2025:i:7:p:1601-1617
    DOI: 10.1177/23998083241302373
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    References listed on IDEAS

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