An integrated regression analysis and time series model for construction tender price index forecasting

S. Thomas Ng, Sai On Cheung, Martin Skitmore and Toby Wong

Construction Management and Economics, 2004, vol. 22, issue 5, 483-493

Abstract: Clients need to be informed in advance of their likely future financial commitments and cost implications as the design evolves. This requires the estimation of building cost based on historic cost data that is updated by a forecasted Tender Price Index (TPI), with the reliability of the estimates depending significantly on accurate projections being obtained of the TPI for the forthcoming quarters. In practice, the prediction of construction tender price index movement entails a judgemental projection of future market conditions, including inflation. Statistical techniques such as Regression Analysis (RA) and Time Series (TS) modelling provide a powerful means of improving predictive accuracy when used individually. An integrated RA-TS model is developed and its predictive power compared with the individual RA or TS models. The accuracy of the RA-TS model is shown to outperform the individual RA and TS models in both one and two-period forecasts, with the integrated RA-TS model accurately predicting (95% confidence level) one-quarter forecasts for all the 34 holdout periods involved, with only one period not meeting the confidence limit for two-quarter forecasts.

Keywords: Cost estimate; integrated forecasting model; tender price index forecast; time series modelling; regression analysis (search for similar items in EconPapers)
Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0144619042000202799 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:conmgt:v:22:y:2004:i:5:p:483-493

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCME20

DOI: 10.1080/0144619042000202799

Access Statistics for this article

Construction Management and Economics is currently edited by Will Hughes

More articles in Construction Management and Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().