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On the distribution of bids for construction contract auctions

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  • Pablo Ballesteros-Pérez
  • Martin Skitmore

Abstract

The statistical distribution representing bid values constitutes an essential part of many auction models and has involved a wide range of assumptions, including the Uniform, Normal, Lognormal and Weibull densities. From a modelling point of view, its goodness is defined by how well it enables the probability of a particular bid value to be estimated – a past bid for ex-post analysis and a future bid for ex-ante (forecasting) analysis. However, there is no agreement to date of what is the most appropriate form and empirical work is sparse. Twelve extant construction data-sets from four continents over different time periods are analysed in this paper for their fit to a variety of candidate statistical distributions assuming homogeneity of bidders (ID not known). The results show there is no one single fit-all distribution, but that the 3p Log-Normal, Fréchet/2p Log-Normal, Normal, Gamma and Gumbel generally rank the best ex-post and the 2p Log-Normal, Normal, Gamma and Gumbel the best ex-ante – with ex-ante having around three to four times worse fit than ex-post. Final comments focus on the results relating to the third and fourth standardized moments of the bids and a post hoc rationalization of the empirical outcome of the analysis.

Suggested Citation

  • Pablo Ballesteros-Pérez & Martin Skitmore, 2017. "On the distribution of bids for construction contract auctions," Construction Management and Economics, Taylor & Francis Journals, vol. 35(3), pages 106-121, March.
    • Handle: RePEc:taf:conmgt:v:35:y:2017:i:3:p:106-121
    DOI: 10.1080/01446193.2016.1247972
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    Cited by:

    1. Michael Warlters, 2023. "Stamp Duty Reform and Home Ownership," The Economic Record, The Economic Society of Australia, vol. 99(327), pages 492-511, December.
    2. Qiao, Yu & Labi, Samuel & Fricker, Jon D., 2021. "Does highway project bundling policy affect bidding competition? Insights from a mixed ordinal logistic model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 228-242.
    3. Tomáš Hanák & Ivan Marović & Nikša Jajac, 2020. "Challenges of Electronic Reverse Auctions in Construction Industry—A Review," Economies, MDPI, vol. 8(1), pages 1-14, February.
    4. Haitian Xie, 2020. "Finite-Sample Average Bid Auction," Papers 2008.10217, arXiv.org, revised Feb 2022.

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