Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 1 results ...

Bassioni, H, Emasry, M I, Ragheb, A M and Youssef, A A (2012) Time series analysis for the prediction of RC material components prices in Egypt . In: Smith, S.D (Ed.), Proceedings 28th Annual ARCOM Conference, 3-5 September 2012, Edinburgh, UK. Association of Researchers in Construction Management, 381–90.

  • Type: Conference Proceedings
  • Keywords: reinforced concrete; time-series analysis; material prices; Egypt
  • ISBN/ISSN: 978-0-9552390-6-9
  • URL: http://www.arcom.ac.uk/-docs/proceedings/ar2012-0381-0390_Bassioni_Elmasry_Ragheb_Youssef.pdf
  • Abstract:
    Reinforced concrete (RC) as a construction material is widely used in the Middle East and particularly Egypt. Prices of the RC material components usually comprise an important portion of construction project costs. Prices of RC materials have witnessed significant changes and fluctuations over the past 15 years in Egypt, leading to severe impacts on the running projects’ costs and to the failure of various projects as well as legal consequences on contracting companies. Factors affecting steel and cement prices (the major cost contributors to RC) have been related in previous literatures to cost of the production process, raw material prices, energy prices, macroeconomic variables, and industry related factors. Time Series Analysis involves the use of historical data to predict the future outcomes and the associated risks. Thus, the objective of this paper is to apply Time Series Analysis to better predict the prices of RC material components in Egypt. Prices of steel, cement, sand and crushed stones were collected for the period from 1997 to 2010. The collected data was divided into two sections based on the economic growth within the studied periods. A computer-based analysis was conducted using ForecastX and SPSS software to apply the Time Series analyses and detect trends, stationarity, and seasonality. Results indicate that the outputs on applying the Time Series models in both programmes were nearly identical. Furthermore, the predictions for the last quarter of 2009 and the first two quarters of 2010 were compared to actual past prices as a way to validate the analyses. A reasonable degree of prediction accuracy was concluded for all materials, and in particular cement, although the global financial crisis in 2008 was found to negatively affect the predictive capability of the model. Time Series Analysis in general, although being a good prediction technique in stable economic and industry conditions, cannot predict sudden macroeconomic or other events, and therefore, future research is required to tie in input variables of material costs based on leading cost indicators and to explore how the effects of sudden events can be realized and hopefully predicted, if possible.