Determining the Probability of Project Cost Overruns
Publication: Journal of Construction Engineering and Management
Volume 139, Issue 3
Abstract
The statistical characteristics of cost overruns experienced from contract award in 276 Australian construction and engineering projects were analyzed. The skewness and kurtosis values of the cost overruns are computed to determine if the empirical distribution of the data follows a normal distribution. The Kolmogorov-Smirnov, Anderson-Darling, and chi-squared nonparametric tests are used to determine the goodness of fit of the selected probability distributions. A three-parameter Frechet probability function is found to describe the behavior of cost overruns and provide the best overall distribution fit. The Frechet distribution is then used to calculate the probability of a cost overrun being experienced. The statistical characteristics of contract size and cost overruns were also analyzed. The Cauchy (), Wakeby (A$1 to 10 million, ) and four-parameter Burr (A$11 to 50 million) tests were found to provide the best distribution fits and used to calculate cost overrun probabilities by contract size. Ascertaining the best fit probability distribution from an empirical distribution at contract award can produce realistic probabilities of cost overruns, which should then be incorporated into a construction cost contingency.
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 139 • Issue 3 • March 2013
Pages: 321 - 330
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Aug 11, 2011
Accepted: Jan 31, 2012
Published online: Apr 28, 2012
Published in print: Mar 1, 2013
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