IDEAS home Printed from https://ideas.repec.org/a/taf/jpropr/v33y2016i4p293-308.html
   My bibliography  Save this article

A robust house price index using sparse and frugal data

Author

Listed:
  • Phil Maguire
  • Robert Miller
  • Philippe Moser
  • Rebecca Maguire

Abstract

In this article, we describe a house price index algorithm which requires only sparse and frugal data, namely house location, date of sale and sale price, as input data. We aim to show that our algorithm is as effective for predicting price changes as more complex models which require detailed or extensive data. Although various methods are employed for determining house price indexes, such as hedonic regression, mix-adjusted median or repeat sales, there is no consensus on how to determine the robustness of an index, and hence no agreement on which method is the best to use. We formalise an objective criterion for what a house price index should achieve, namely consistency between time periods. Using this criterion, we investigate whether it is possible to achieve strong robustness using frugal data covering only 66 months of transactions on the Irish property market. We develop a simple multi-stage algorithm and show that it is more robust than the complex hedonic regression model currently employed by the Irish Central Statistics Office.

Suggested Citation

  • Phil Maguire & Robert Miller & Philippe Moser & Rebecca Maguire, 2016. "A robust house price index using sparse and frugal data," Journal of Property Research, Taylor & Francis Journals, vol. 33(4), pages 293-308, October.
  • Handle: RePEc:taf:jpropr:v:33:y:2016:i:4:p:293-308
    DOI: 10.1080/09599916.2016.1258718
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/09599916.2016.1258718
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/09599916.2016.1258718?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.

    References listed on IDEAS

    as
    1. Chris McDonald & Mark Smith, 2009. "Developing stratified housing price measures for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/07, Reserve Bank of New Zealand.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Aoife K. Hurley & James Sweeney, 2024. "Irish Property Price Estimation Using A Flexible Geo-spatial Smoothing Approach: What is the Impact of an Address?," The Journal of Real Estate Finance and Economics, Springer, vol. 68(3), pages 355-393, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Grant M. Scobie & Katherine Henderson, 2009. "Saving Rates of New Zealanders: A Net Wealth Approach," Treasury Working Paper Series 09/04, New Zealand Treasury.
    2. Asli Kaya & Ayça Topaloglu Bozkurt & Emine Meltem Bastan & Özgül Atilgan Ayanoglu, 2013. "Constructing a house price index for Turkey," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 153-171, Bank for International Settlements.
    3. Jed Armstrong & Ashley Dunstan & Tobias Irrcher, 2017. "Evaluating alternative monthly house price measures for New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2017/02, Reserve Bank of New Zealand.
    4. Sarah Drought & Chris McDonald, 2011. "Forecasting house price inflation: a model combination approach," Reserve Bank of New Zealand Discussion Paper Series DP2011/07, Reserve Bank of New Zealand.

    More about this item

    Statistics

    Access and download statistics

    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:jpropr:v:33:y:2016:i:4:p:293-308. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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/RJPR20 .

    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.