IDEAS home Printed from https://ideas.repec.org/a/kap/jrefec/v2y1989i1p61-70.html
   My bibliography  Save this article

Efficiency of the Office Properties Market

Author

Listed:
  • McIntosh, Willard
  • Henderson, Glenn V, Jr

Abstract

No abstract is available for this item.

Suggested Citation

  • McIntosh, Willard & Henderson, Glenn V, Jr, 1989. "Efficiency of the Office Properties Market," The Journal of Real Estate Finance and Economics, Springer, vol. 2(1), pages 61-70, February.
    • Handle: RePEc:kap:jrefec:v:2:y:1989:i:1:p:61-70
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Maier, Gunther & Herath, Shanaka, 2009. "Real Estate Market Efficiency. A Survey of Literature," SRE-Discussion Papers 2009/07, WU Vienna University of Economics and Business.
    2. Das, Prashant & Füss, Roland & Hanle, Benjamin & Russ, Isabel Nina, 2020. "The cross-over effect of irrational sentiments in housing, commercial property, and stock markets," Journal of Banking & Finance, Elsevier, vol. 114(C).
    3. Raymond Tse & C. W. Ho & S. Ganesan, 1999. "Matching housing supply and demand: an empirical study of Hong Kong's market," Construction Management and Economics, Taylor & Francis Journals, vol. 17(5), pages 625-633.
    4. Geoffrey Keogh & Eamonn D'Arcy, 1999. "Property Market Efficiency: An Institutional Economics Perspective," Urban Studies, Urban Studies Journal Limited, vol. 36(13), pages 2401-2414, December.
    5. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    6. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
    7. William L. Attebery & Ronald C. Rutherford & Mark E. Eakin, 1993. "Industrial Real Estate Prices and Market Efficiency," Journal of Real Estate Research, American Real Estate Society, vol. 8(3), pages 377-386.

    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:kap:jrefec:v:2:y:1989:i:1:p:61-70. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.