Detecting intra-urban housing market spillover through a spatial Markov chain model

Daijun Zhang, Xiaoqi Zhang, Yanqiao Zheng, Xinyue Ye, Shengwen Li, Qiwen Dai

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


This study analyzed the spillovers among intra-urban housing submarkets in Beijing, China. Intra-urban spillover imposes a methodological challenge for housing studies from the spatial and temporal perspectives. Unlike the inter-urban spillover, the range of every submarket is not naturally defined; therefore, it is impossible to evaluate the intra-urban spillover by standard time-series models. Instead, we formulated the spillover effect as a Markov chain procedure. The constrained clustering technique was applied to identify the submarkets as the hidden states of Markov chain and estimate the transition matrix. Using a day-by-day transaction dataset of second-hand apartments in Beijing during 2011–2017, we detected 16 submarkets/regions and the spillover effect among these regions. The highest transition probability appeared in the overlapped region of urban core and Tongzhou district. This observation reflects the impact of urban planning proposal initiated since early 2012. In addition to the policy consequences, we analyzed a variety of spillover “types” through regression analysis. The latter showed that the “ripple” form of spillover is not dominant at the intra-urban level. Other types, such as the spillover due to the existence of price depressed regions, play major roles. This observation reveals the complexity of intra-urban spillover dynamics and its distinct driving-force compared to the inter-urban spillover.

Original languageEnglish (US)
Article number60
JournalISPRS International Journal of Geo-Information
Issue number1
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)


  • Constrained clustering
  • Housing price
  • Intra-urban spillover
  • Ripple effect
  • Spatial markov chain


Dive into the research topics of 'Detecting intra-urban housing market spillover through a spatial Markov chain model'. Together they form a unique fingerprint.

Cite this