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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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    1. Jeffrey P. Cohen & Cletus C. Coughlin & Jeffrey Zabel, 2020. "Time-Geographically Weighted Regressions and Residential Property Value Assessment," The Journal of Real Estate Finance and Economics, Springer, vol. 60(1), pages 134-154, February.
    2. David Brasington & Donald R. Haurin, 2006. "Educational Outcomes and House Values: A Test of the value added Approach," Journal of Regional Science, Wiley Blackwell, vol. 46(2), pages 245-268, May.
    3. Gao, Yuan & Tian, Li & Cao, Yandong & Zhou, Lin & Li, Zhibin & Hou, Deyi, 2019. "Supplying social infrastructure land for satisfying public needs or leasing residential land? A study of local government choices in China," Land Use Policy, Elsevier, vol. 87(C).
    4. Kang, Hsin-Hong & Liu, Shu-Bing, 2014. "The impact of the 2008 financial crisis on housing prices in China and Taiwan: A quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 356-362.
    5. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    6. repec:dau:papers:123456789/14350 is not listed on IDEAS
    7. Daams, Michiel N. & Sijtsma, Frans J. & Veneri, Paolo, 2019. "Mixed monetary and non-monetary valuation of attractive urban green space: A case study using Amsterdam house prices," Ecological Economics, Elsevier, vol. 166(C), pages 1-1.
    8. Yuan, Feng & Wu, Jiawei & Wei, Yehua Dennis & Wang, Lei, 2018. "Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China," Land Use Policy, Elsevier, vol. 75(C), pages 225-236.
    9. Efthymiou, D. & Antoniou, C., 2013. "How do transport infrastructure and policies affect house prices and rents? Evidence from Athens, Greece," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 1-22.
    10. Jorge Chica-Olmo, 2007. "Prediction of Housing Location Price by a Multivariate Spatial Method: Cokriging," Journal of Real Estate Research, American Real Estate Society, vol. 29(1), pages 95-114.
    11. 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.
    12. Grislain-Letrémy, Céline & Katossky, Arthur, 2014. "The impact of hazardous industrial facilities on housing prices: A comparison of parametric and semiparametric hedonic price models," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 93-107.
    13. Cordera, Ruben & Chiarazzo, Vincenza & Ottomanelli, Michele & dell’Olio, Luigi & Ibeas, Angel, 2019. "The impact of undesirable externalities on residential property values: spatial regressive models and an empirical study," Transport Policy, Elsevier, vol. 80(C), pages 177-187.
    14. Franco, Sofia F. & Macdonald, Jacob L., 2018. "The effects of cultural heritage on residential property values: Evidence from Lisbon, Portugal," Regional Science and Urban Economics, Elsevier, vol. 70(C), pages 35-56.
    15. Liang, Wenquan & Lu, Ming & Zhang, Hang, 2016. "Housing prices raise wages: Estimating the unexpected effects of land supply regulation in China," Journal of Housing Economics, Elsevier, vol. 33(C), pages 70-81.
    16. Matías Martínez & José Lorenzo & Noela Rubio, 2000. "Kriging methodology for regional economic analysis: Estimating the housing price in Albacete," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 6(3), pages 438-450, August.
    17. Yan Kestens & Marius Thériault & François Des Rosiers, 2006. "Heterogeneity in hedonic modelling of house prices: looking at buyers’ household profiles," Journal of Geographical Systems, Springer, vol. 8(1), pages 61-96, March.
    18. Yee Leung & Chang-Lin Mei & Wen-Xiu Zhang, 2000. "Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model," Environment and Planning A, , vol. 32(1), pages 9-32, January.
    19. Cui, Yin & Sun, Yu, 2019. "Social benefit of urban infrastructure: An empirical analysis of four Chinese autonomous municipalities," Utilities Policy, Elsevier, vol. 58(C), pages 16-26.
    20. Votsis, Athanasios, 2017. "Planning for green infrastructure: The spatial effects of parks, forests, and fields on Helsinki's apartment prices," Ecological Economics, Elsevier, vol. 132(C), pages 279-289.
    21. Liu, Tian & Hu, Weiyan & Song, Yan & Zhang, Anlu, 2020. "Exploring spillover effects of ecological lands: A spatial multilevel hedonic price model of the housing market in Wuhan, China," Ecological Economics, Elsevier, vol. 170(C).
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    2. 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.
    3. 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.
    4. 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).
    5. 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).
    6. 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.
    7. 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.

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