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Predicting the probability of winning sealed bid auctions: a comparison of models

Author

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  • M Skitmore

    (Queensland University of Technology)

Abstract

This paper is concerned with predicting the probability of tendering the lowest bid in sealed bid auctions. Four of the leading models from the bidding literature are shown to be subsumed within a generalised model. These models are then tested relative to the equal probability model by an empirical analysis of a large sample of real construction contract bidding data via all-in, one-out and one-on sample frames. A binomial test is used to measure the ability to predict the identity of the lowest bidders and the average logscore is used to measure the ability to predict the probability of each bidder being the lowest. Optimal cut-off criterion values are determined for defining the minimum size of dataset needed for disaggregating bidders. The work also highlights the importance of (1) the treatment of new entrants and general shortage of data on individual bidders, and (2) the treatment of predicted ties.

Suggested Citation

  • M Skitmore, 2002. "Predicting the probability of winning sealed bid auctions: a comparison of models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(1), pages 47-56, January.
    • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:1:d:10.1057_palgrave.jors.2601236
    DOI: 10.1057/palgrave.jors.2601236
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    Citations

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    Cited by:

    1. David Cattell & Paul Bowen & Ammar Kaka, 2004. "A model to distribute mark-up amongst quotation component item," Econometrics 0408009, University Library of Munich, Germany.
    2. Marcos Singer, 2002. "Una Introduccion A La Teoria Y La Practica De Las Subastas," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 5(1), pages 3-29.
    3. João Adelino Ribeiro & Paulo Jorge Pereira & Elísio Brandão, 2012. "Reaching an Optimal Mark-Up Bid through the Valuation of the Option to Sign the Contract by the Successful Bidder," CEF.UP Working Papers 1201, Universidade do Porto, Faculdade de Economia do Porto.
    4. João Adelino Ribeiro & Paulo Jorge Pereira & Elísio Brandão, 2013. "Volume Uncertainty in Construction Projects: a Real Options Approach," CEF.UP Working Papers 1309, Universidade do Porto, Faculdade de Economia do Porto.
    5. Dutta, Goutam & Natesan, Sumeetha R., 2016. "Optimization of Customized Pricing with Multiple Overlapping Competing Bids," IIMA Working Papers WP2016-11-02, Indian Institute of Management Ahmedabad, Research and Publication Department.

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