Price adjustment clauses: Enhanced price volatility forecasting for construction materials

Price adjustment clauses (PACs) are used by state departments of transportation (DOTs) to share the risk of material price fluctuations. Existing models that depict the price fluctuations of materials forecast a mean within a horizon while relying on the assumption of a constant volatility throughout that horizon. However, none of them examine whether the prices of construction material exhibit similar volatility following a sudden price surge or a price drop. The prospect of PACs and their associated trigger values is hindered in the absence of empirical assessments of their capacity to capture the volatilities in material prices. This paper fills this knowledge gap by adopting a methodology that comprised (1) data collection of the prices of materials; (2) forecasting their trends using autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM); and (3) augmenting the price forecasts with quantification of their asymmetric conditional volatilities using Glosten-Jagannathan-Runkle generalized autoregressive conditional heteroscedasticity (GJR-GARCH). The developed approach was demonstrated using the prices of asphalt, steel, cement, and fuel in Ohio; it can be applied to any other similar data set. Results indicate the existence of significant conditional volatility in the prices of asphalt, steel, and fuel. Further findings suggest that the prices of asphalt and steel are more volatile following a sudden price drop rather than following a price surge. Integration of ARIMA and GJR-GARCH models generates volatility ranges that accurately forecast the fluctuations of material prices in the 12-month forecasting horizon. Out-of-sample forecasts indicated that the GJR-GARCH range constitutes a viable alternative to confidence intervals of competing models. Examining asymmetric conditional volatility in material prices can alleviate the bias in assessing the PACs trigger values following an unstable period. The presented framework aids state DOTs and contractors in their risk sharing strategies in the context of PACs.