[I]

Martin Meschede, H. Murawski, W. Meyer
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引用次数: 0

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 datasets 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 standardised moments of the bids and a posthoc rationalisation of the empirical outcome of the analysis.
[我]
表示出价值的统计分布构成了许多拍卖模型的重要组成部分,并涉及广泛的假设,包括均匀、正态、对数正态和威布尔密度。从建模的角度来看,它的好坏是由它能在多大程度上估计出一个特定出价值的概率来定义的——过去的出价用于事后分析,未来的出价用于事前(预测)分析。然而,迄今为止,对于什么是最合适的形式还没有达成一致意见,而且经验工作也很少。本文分析了来自四大洲不同时期的12个现有建筑数据集,假设投标人的同质性(ID未知),以确定它们是否适合各种候选统计分布。结果表明,没有一个单一的拟合分布,但3p对数正态分布、fr /2p对数正态分布、正态分布、Gamma分布和Gumbel分布通常是事后最好的,2p对数正态分布、Normal分布、Gamma分布和Gumbel分布是事后最好的,其中事前拟合比事后差三到四倍。最后的评论集中在与投标的第三和第四个标准化时刻有关的结果以及分析的实证结果的事后合理化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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