IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Housing attributes and Hong Kong real estate prices: a quantile regression analysis

  • Lennon H.T. Choy
  • Winky K.O. Ho
  • Stephen W.K. Mak
Registered author(s):

    By nature, people’s tastes and preferences are unique and diverse so that a constant coefficient of each housing attribute produced by ordinary least squares (OLS) is not able to fully describe the behaviour of homebuyers of different classes. To complement the least squares, quantile regression is used to identify how real estate prices respond differently to a change in one unit of housing attribute at different quantiles. Theoretically, quantile regression can be utilized to estimate the implicit price for each housing attribute across the distribution of real estate prices, allowing specific percentiles of prices to be more influenced by certain housing attributes when compared to other percentiles. Empirical results demonstrate that most housing attributes, such as apartment size, age and floor level, command different prices at different quantiles. With the use of this approach, the efficiency of the mortgage markets is enhanced by offering more accurate prediction of real estate prices at the lower and upper price distribution.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://hdl.handle.net/10.1080/01446193.2012.677542
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Taylor & Francis Journals in its journal Construction Management and Economics.

    Volume (Year): 30 (2012)
    Issue (Month): 5 (March)
    Pages: 359-366

    as
    in new window

    Handle: RePEc:taf:conmgt:v:30:y:2012:i:5:p:359-366
    Contact details of provider: Web page: http://www.tandfonline.com/RCME20

    Order Information: Web: http://www.tandfonline.com/pricing/journal/RCME20

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:taf:conmgt:v:30:y:2012:i:5:p:359-366. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.