Predicting final cost for competitively bid construction projects using regression models

This paper studies the relationship between the low bid and completed cost for competitively bid highway projects. Data are analyzed from several agencies managing highway and dredging projects. A natural log transformation of the low bid and final cost was found to produce regression models for each agency that had high R and R² values. These models can predict completed project cost using only the project low bid as input. A separate regression model was determined for each agency. Based on the form of the calculated models it appears that highway agencies construct projects where the final cost increases as an increasing percentage of the low bid price as the project magnitude increases. The dredging projects appear to follow different mechanisms of cost increase than the highway projects and were not predicted as well by the regression models. The regression models can also be used for budgeting purposes by submitting the sum of the low bids for a group of projects as input. The regression models output a prediction of the cost of the group of projects that was found to be highly accurate.