Significant changes in highway construction cost are problematic for cost estimation, bid preparation, and investment planning of highway construction projects in the United States. Analysis of the temporal relationships between highway construction cost, macroeconomic, and construction and energy market indicators helps to have a better understanding about highway construction cost changes within the U.S. macroeconomic, and construction and energy market context. This temporal analysis helps to identify leading indicators of highway construction costs. Leading indicators of highway construction costs are indicators, which past values contain information that is useful for forecasting the future values of highway construction costs. The research objective is to analyze the temporal relationship between highway construction costs and macroeconomic, and construction and energy market indicators using multivariate time-series tests. The data set under study includes National Highway Construction cost index (NHCCI) provided by Federal Highway Administration (FHWA) and indicators representing macroeconomic condition (producer price index, gross domestic product (GDP), GDP implicit price deflator, Dow Jones industrial average, money supply, prime loan rate, unemployment rate, federal funds rate, and consumer price index), construction market condition (number of housing starts, number of building permits, construction spending, average hourly earnings, average weekly hours, and employment rate in construction), and energy market condition (crude oil price). Research results show that crude oil price and average hourly earnings are the leading indicators of NHCCI. The research findings contribute to the body of knowledge by filling the gap in knowledge about the leading indicators of highway construction costs. The research findings contribute to the state of practice by helping cost estimators, budget planners, and construction market analysts explain highway construction cost variations and forecast the future trends to improve the accuracy of their budgets, estimates, and bids.
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Mohsen Shahandashti (2014) studied this question.