IDEAS home Printed from https://ideas.repec.org/a/taf/jocebs/v6y2008i3p291-302.html
   My bibliography  Save this article

The impacts of distance to CBD on housing prices in Shanghai: a hedonic analysis

Author

Listed:
  • Jie Chen
  • Qianjin Hao

Abstract

It is widely recognized that location is the primary determining factor of housing price. But to what extent the variation of housing price in Shanghai can be explained by the locational factor has not been empirically examined. In this paper, we examine the power of applying the hedonic method to the spatial-statistical analysis of housing prices in Shanghai. The data we use covers all new commercial residential housings sold in Shanghai during July 2004 and June 2006. The main focus in this paper is to examine the effect of geographical distance to city centre on the selling price of residential housings in Shanghai. We also discuss how the price gradient varies at different directions in Shanghai. Finally, we demonstrate the importance of applying quality control on the development of a housing price index. The statistical methodology and empirical results obtained in this paper carry interesting implications for other cities in China as well.

Suggested Citation

  • Jie Chen & Qianjin Hao, 2008. "The impacts of distance to CBD on housing prices in Shanghai: a hedonic analysis," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 6(3), pages 291-302.
    • Handle: RePEc:taf:jocebs:v:6:y:2008:i:3:p:291-302
    DOI: 10.1080/14765280802283584
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/14765280802283584
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14765280802283584?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ming Li & Guojun Zhang & Yunliang Chen & Chunshan Zhou, 2019. "Evaluation of Residential Housing Prices on the Internet: Data Pitfalls," Complexity, Hindawi, vol. 2019, pages 1-15, February.
    2. Dani Broitman, 2023. "“Passive” Ecological Gentrification Triggered by the Covid-19 Pandemic," Urban Planning, Cogitatio Press, vol. 8(1), pages 312-321.
    3. Potrawa, Tomasz & Tetereva, Anastasija, 2022. "How much is the view from the window worth? Machine learning-driven hedonic pricing model of the real estate market," Journal of Business Research, Elsevier, vol. 144(C), pages 50-65.
    4. Liao, Wen-Chi & Wang, Xizhu, 2012. "Hedonic house prices and spatial quantile regression," Journal of Housing Economics, Elsevier, vol. 21(1), pages 16-27.
    5. T. Thanh-Binh Nguyen & Kuan-Min Wang, 2010. "Causality between housing returns, inflation and economic growth with endogenous breaks," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 8(1), pages 95-115.
    6. Erez Buda & Dani Broitman & Daniel Czamanski, 2021. "Urban Structure in Troubled Times: The Evolution of Principal and Secondary Core/Periphery Gaps through the Prism of Residential Land Values," Sustainability, MDPI, vol. 13(10), pages 1-12, May.
    7. Walsh, Patrick & Griffiths, Charles & Guignet, Dennis & Klemick, Heather, 2017. "Modeling the Property Price Impact of Water Quality in 14 Chesapeake Bay Counties," Ecological Economics, Elsevier, vol. 135(C), pages 103-113.
    8. Jie Chen & Qianjin Hao, 2010. "Submarket, Heterogeneity and Hedonic Prediction Accuracy of Real Estate Prices: Evidence from Shanghai," International Real Estate Review, Global Social Science Institute, vol. 13(2), pages 190-217.
    9. Zhu, Jin & Pawson, Hal & Han, Hoon & Li, Bingqin, 2022. "How can spatial planning influence housing market dynamics in a pro-growth planning regime? A case study of Shanghai," Land Use Policy, Elsevier, vol. 116(C).
    10. Forouhar, Amir, 2022. "Rail transit station and neighbourhood change: A mixed-method analysis with respect to neighbourhood context," Journal of Transport Geography, Elsevier, vol. 102(C).
    11. Hao Huang & Jianyi Li, 2021. "The spatial variation of moderating effects of density and natural amenities on housing prices in Wuhan, China," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(6), pages 1778-1804, December.
    12. Gianni Guastella & Stefano Pareglio, 2017. "Spatial Analysis Of Urbanization Patterns: The Case Of Land Use And Population Density In The Milan Metropolitan Area," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 29(2), pages 89-102, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jocebs:v:6:y:2008:i:3:p:291-302. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RCEA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.