Predicting the probability of winning sealed bid auctions: the effects of outliers on bidding models

Martin Skitmore

Construction Management and Economics, 2004, vol. 22, issue 1, 101-109

Abstract: This paper is concerned with the effect of outliers on predictions of the probability of tendering the lowest bid in sealed bid auctions. Four of the leading models are tested relative to the equal probability model by an empirical analysis of three large samples of real construction contract bidding data via all-in (in-sample), one-out and one-on (out-of-sample) frames. Outliers are removed in a sequence of cut-off values proportional to the standard deviation of bids for each auction. A form of logscore is used to measure the ability to predict the probability of each bidder being the lowest. The results show that, although statistically significant in some conditions, all the models produce rather poor predictions in both one-out and one-on mode, with the effects of outliers being generally small.

Keywords: Bidding models; bidding theory; construction contracts; empirical tests; predicted probability; probability of lowest bid; sealed bid auctions; tendering theory; logscore test; outliers (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0144619042000186103 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:conmgt:v:22:y:2004:i:1:p:101-109

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCME20

DOI: 10.1080/0144619042000186103

Access Statistics for this article

Construction Management and Economics is currently edited by Will Hughes

More articles in Construction Management and Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().