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Spatial-Temporal Variation in the Impacts of Urban Infrastructure on Housing Prices in Wuhan, China

Author

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  • Fan Liu

    (College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China)

  • Min Min

    (College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China)

  • Ke Zhao

    (College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China)

  • Weiyan Hu

    (College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China)

Abstract

This study aims to investigate the spatial and temporal dynamics of housing prices associated with the urban infrastructure in Wuhan, China. The relationship between urban infrastructure and housing prices during rapid urbanization has drawn popular concerns. This article takes 619 residential communities during the period 2010 to 2018 in Wuhan’s main urban area as research units, and uses the geographically and temporally weighted regression (GTWR) model to study the spatial-temporal differentiation in the effects of urban infrastructure on housing prices. The results show that: 1) From 2010 to 2018, housing prices in Wuhan’s main urban area were generally on the rise, but the increment speed has shown an obvious periodic characteristic, the spatial distribution of housing prices has shown an obvious core and periphery distribution and the peak value area shifted from Hankou to Wuchang. 2) The influential factors of housing prices have significant spatiotemporal non-stationarity, while the impact, direction and intensity of the influential factors varies in time and space. Spatially, the influence factors show different differentiation rules for spatial distribution, and the influencing direction and strength of the urban infrastructure on housing prices are closely related to the spatial location, distribution density and the type of urban infrastructure. Temporally, the influencing strength of various urban facilities varies. This research will benefit both urban planners for optimizing urban facilities and policy-makers for formulating more specific housing policies, which ultimately contributes to urban sustainability.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:1281-:d:318915
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    2. Kang, Yuhao & Zhang, Fan & Peng, Wenzhe & Gao, Song & Rao, Jinmeng & Duarte, Fabio & Ratti, Carlo, 2021. "Understanding house price appreciation using multi-source big geo-data and machine learning," Land Use Policy, Elsevier, vol. 111(C).
    3. Hanli Chen & Yu Zhang & Ningxin Zhang & Man Zhou & Heping Ding, 2022. "Analysis on the Spatial Effect of Infrastructure Development on the Real Estate Price in the Yangtze River Delta," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    4. Qing Yao & Yingen Hu, 2023. "Spatial–Temporal Variation and Influencing Factors on Housing Prices of Resource-Based City: A Case Study of Xuzhou, China," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    5. Lan, Hao & Moreira, Fernando & Zhao, Sheng, 2023. "Can a house resale restriction policy curb speculation? Evidence from a quasi-natural experiment in China," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 841-859.
    6. Xiao Tian & Jin Liu & Yong Liu, 2022. "How Does the Quality of Junior High Schools Affect Housing Prices? A Quasi-Natural Experiment Based on the Admission Reform in Chengdu, China," Land, MDPI, vol. 11(9), pages 1-18, September.
    7. Yang, Ziqi & Li, Xinghua & Guo, Yuntao & Qian, Xinwu, 2023. "Understanding active transportation accessibility's impacts on polycentric and monocentric cities' housing price," Research in Transportation Economics, Elsevier, vol. 98(C).

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