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A Framework to Forecast Highway Construction Materials Prices

Faghih, Amir Mohsen | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46655 (09)
  4. University: Sharif University Technology
  5. Department: Civil Engineering
  6. Advisor(s): Kashani, Hamed
  7. Abstract:
  8. Due¬ to the volatile nature of material prices, projecting highway construction costs are proven to be very difficult, leading to many challenges in cost estimation process. Bid preparations as well as project planning and control processes are also negatively affected by the concerns about the inaccuracy of cost projections. There is a growing body of evidence that suggests the use of inaccurate cost estimate can result in bid loss or profit loss for contractors and hidden price contingencies, delayed or cancelled projects, inconsistency in budgets and unsteady flow of projects for owner organizations. Analysis of historical data indicates that a relationship between construction materials costs and variables such as energy prices may exist. Scientific efforts to statistically characterize such relationships are very rarely documented in the construction engineering and management academic literature. The objective of this research is to create an appropriate framework to forecast the future prices of highway construction materials by characterizing the relationship between construction materials costs and energy prices. This study focuses on asphalt and concrete, which are the most commonly used materials in highway construction projects. Using cointegration analysis, this study shows that there is long-term equilibrium relationship between the prices of these materials and energy prices. Based on an estimated error correction model, this research shows that asphalt and cement prices are influenced by energy prices variations on both the short and the long run. The existence of a unique equilibrium model may have important implications for forecasting and managing the risk of materials price fluctuations. This model can be expanded so that it can characterize the relationships between the price of other construction inputs such as labor and equipment and macro and microeconomic factors
  9. Keywords:
  10. Forecasting ; Geometric Brownian Motion ; Cost Estimation ; Construction Materials ; Energy Price ; Risk Management ; Construction Road ; Costruction Materials

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