Standard Deviation of Bids for Construction Contract Auctions
[EN] Previous research has confirmed that the distribution of bids for construction auctions can be reasonably modeled with Lognormal distribution. The location parameter of this distribution (the mean mu) has been found to have a good linear correlation with the bidders' cost estimates. Ho...
| Authors: | , , , , , |
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| Format: | article |
| Publication Date: | 2021 |
| Country: | España |
| Institution: | Universitat Politècnica de València (UPV) |
| Repository: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Language: | English |
| OAI Identifier: | oai:riunet.upv.es:10251/180324 |
| Online Access: | https://riunet.upv.es/handle/10251/180324 |
| Access Level: | Open access |
| Keyword: | Construction contracts Auctions Bids Tendering Dispersion Bid modelling Bid forecasting PROYECTOS DE INGENIERIA 10.- Reducir las desigualdades entre países y dentro de ellos |
| Summary: | [EN] Previous research has confirmed that the distribution of bids for construction auctions can be reasonably modeled with Lognormal distribution. The location parameter of this distribution (the mean mu) has been found to have a good linear correlation with the bidders' cost estimates. However, the scale parameter (standard deviation of the bids, sigma) remains noticeably difficult to anticipate. By analyzing 13 construction auction datasets, hard evidence is provided that the high variability of sigma observed in construction auctions is mostly due to sample size (number of bids per auction). Moreover, we show that the coefficient of variation (sigma/mu) of log-transformed bids follows the same chi(2) distribution in uncapped auctions. This means the sigma's population value in similar auctions is nearly proportional to mu provided the bid price is not upper limited. Other findings are that more frequent bidders do not tend to bid lower, but their dispersion is narrower than sporadic bidders. These findings allow the introduction of important simplifications in construction bidding models, especially when access to historical data is limited. |
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