### Accounting for Correlations Price Adjustments in Unit-Cost Construction Contracts

Abstract

Macroeconomic conditions, such as commodity prices, affect the cost of construction projects. In
a volatile market environment, contractors respond by adding premiums in bid prices when highway
agencies pass such risk on to contractors by using fixed-price contracts. How much of the commodity
cost risk should highway agencies pass on to contractors? More specifically, this study aims to investigate
the impact of correlation among commodity prices on optimal risk-hedging decisions. A weighted least-squares
regression model is used to estimate the risk premium; both univariate time series and vector time series
models are estimated and applied to simulate changes in commodity prices over time, including the effect of
correlation. A genetic algorithm is used as a solution approach to a multiobjective optimization problem
(cost versus future risk exposure). In a case study, project cost risks are shown to be significantly underestimated
if correlations are not accounted for.