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What contributes to the rising house prices in Beijing? A decomposition approach

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  • Zhang, Lei
  • Yi, Yimin

Abstract

The average real house price in Beijing rose by roughly 41.8% between 2012 and 2015, and the appreciation differs across low- versus high-priced homes. The rising house price might be caused by changes in the characteristics of housing units, and it might also be induced by the changing returns to housing characteristics in the underlying hedonic price functions. In this paper, we use a comprehensive housing transaction dataset and analyze the changes in the distribution of house prices over time through a decomposition approach. The result of Oaxaca-Blinder mean decomposition suggests that the proportion of the price gap between 2012 and 2015 due to altered returns over time is greater than the proportion caused by changes in housing characteristics. The quantile decomposition shows that the decomposition effects are heterogenous across the complete distribution of house prices. We also find that low-priced homeowners are exposed to a decline in house prices, while there are deteriorating housing conditions from 2012 to 2015. The high-priced homeowners experience an improvement in living conditions, but a rise in house prices.

Suggested Citation

  • Zhang, Lei & Yi, Yimin, 2018. "What contributes to the rising house prices in Beijing? A decomposition approach," Journal of Housing Economics, Elsevier, vol. 41(C), pages 72-84.
    • Handle: RePEc:eee:jhouse:v:41:y:2018:i:c:p:72-84
    DOI: 10.1016/j.jhe.2018.04.003
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    2. Tianzheng Zhang & Yingxiang Zeng & Yingjie Zhang & Yan Song & Hongxun Li, 2020. "The Heterogenous Demand for Urban Parks between Home Buyers and Renters: Evidence from Beijing," Sustainability, MDPI, vol. 12(21), pages 1-16, October.
    3. Beimer, Waldemar & Maennig, Wolfgang, 2020. "On the price gap between single family houses and apartments," Journal of Housing Economics, Elsevier, vol. 49(C).
    4. Takaaki Ohnishi & Takayuki Mizuno & Tsutomu Watanabe, 2019. "House Price Dispersion in Boom-Bust Cycles: Evidence from Tokyo," Working Papers on Central Bank Communication 008, University of Tokyo, Graduate School of Economics.
    5. Fan Liu & Min Min & Ke Zhao & Weiyan Hu, 2020. "Spatial-Temporal Variation in the Impacts of Urban Infrastructure on Housing Prices in Wuhan, China," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    6. Takaaki Ohnishi & Takayuki Mizuno & Tsutomu Watanabe, 2020. "House price dispersion in boom–bust cycles: evidence from Tokyo," The Japanese Economic Review, Springer, vol. 71(4), pages 511-539, October.
    7. Takaaki Ohnishi & Takayuki Mizuno & Tsutomu Watanabe, 2019. "House Price Dispersion in Boom-Bust Cycles: Evidence from Tokyo," CARF F-Series CARF-F-461, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    8. Wenhao Xue & Xinyao Li & Zhe Yang & Jing Wei, 2022. "Are House Prices Affected by PM 2.5 Pollution? Evidence from Beijing, China," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
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    More about this item

    Keywords

    Quantile decomposition; House price; China;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis

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