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Contemporaneous causality among residential housing prices of ten major Chinese cities

Author

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  • Xiaojie Xu
  • Yun Zhang

Abstract

Purpose - This study aims to investigate dynamic relationships among residential housing price indices of ten major Chinese cities for the years 2005–2021. Design/methodology/approach - Using monthly data, this study uses vector error correction modeling and the directed acyclic graph for characterization of contemporaneous causality among the ten indices. Findings - The PC algorithm identifies the causal pattern and the Linear Non-Gaussian Acyclic Model algorithm further determines the causal path, from which this study conducts innovation accounting analysis. Sophisticated price dynamics are found in price adjustment processes following price shocks, which are generally dominated by the top tiers of cities. Originality/value - This study suggests that policies on residential housing prices in the long run might need to be planned with particular attention paid to these top tiers of cities.

Suggested Citation

  • Xiaojie Xu & Yun Zhang, 2022. "Contemporaneous causality among residential housing prices of ten major Chinese cities," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 16(4), pages 792-811, May.
    • Handle: RePEc:eme:ijhmap:ijhma-03-2022-0039
    DOI: 10.1108/IJHMA-03-2022-0039
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    Cited by:

    1. Xiaojie Xu & Yun Zhang, 2022. "Forecasting the total market value of a shares traded in the Shenzhen stock exchange via the neural network," Economics Bulletin, AccessEcon, vol. 42(3), pages 1266-1279.

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