Prediction of total cost of construction project with dependent cost items

Construction projects are typically carried out in highly uncertain environments with the risk of cost and time overruns, and subsequent disputes between stakeholders. One of common risk factors is that most cost items of a project are dependent random variables. Thus, correlations between basic cost items need to be considered in predicting the total cost of the project. This paper intends to propose a generic copula-based Monte Carlo simulation method for prediction of construction projects' total costs with dependent cost items. An algorithm to generate the joint probability distribution function of correlated cost items is developed and two examples are presented to demonstrate the applicability of copulas in modeling construction costs as random variables. A merit of the proposed method is that it not only can incorporate all different types of distributions in one framework, but it also captures the best dependence structure between variables. This paper finds that different dependence structures can lead to different probability distributions of total cost. It also finds that the existing goodness of fit tests can be employed in choosing the best performing copula. The paper concludes that the copula-based Monte Carlo simulation method can predict total cost of construction projects with reasonable accuracy.