IDEAS home Printed from
   My bibliography  Save this article

Bidding models: testing the stationarity assumption


  • Martin Skitmore
  • Goran Runeson


With notably few exceptions, bidding models contain probability distributions with parameters that are assumed to be fixed, or stationary, over time. Some methods of testing the tenability of this assumption are examined and applied to eight datasets. Of particular interest is the statistical significance of two types of periodicity: (1) that bidders gradually reduce their bids prior to winning a contract; and (2) that bidders have periods in which they are more competitive and periods in which they are less competitive. To test (1), McCaffer and Pettitt's (1976) cusum method is used and shown to have a limited interpretation in this context. McCaffer's 'deficit' statistic is then used in conjunction with a one-way analysis of variance (ANOVA) and shows (1) to be untenable for the samples involved. To test (2), the deficit statistic is again used with an ANOVA to examine all possible sub-series of bids.

Suggested Citation

  • Martin Skitmore & Goran Runeson, 2006. "Bidding models: testing the stationarity assumption," Construction Management and Economics, Taylor & Francis Journals, vol. 24(8), pages 791-803.
  • Handle: RePEc:taf:conmgt:v:24:y:2006:i:8:p:791-803
    DOI: 10.1080/01446190600680432

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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


    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:conmgt:v:24:y:2006:i:8:p:791-803. 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: (Chris Longhurst). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.