Ng, S T; Cheung, S O; Skitmore, M and Wong, T C Y (2004) An integrated regression analysis and time series model for construction tender price index forecasting. Construction Management and Economics, 22(5), pp. 483-493. ISSN 01446193
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | cost estimate; integrated forecasting model; regression analysis; tender price index forecast; time series modelling |
| Index terms: | inflation, tender price index, movement, time series, accuracy, market condition, commitment, regression analysis, cost estimate, cost data, estimate, modelling, forecasting, estimation |
| Subjects: | quantity surveying, accounting and finance, professional development, statistical analysis, economic and policy analysis, health behaviours and lifestyles, psychology, data science, financial and cost management, analytical methods, economic analysis, prediction and forecasting |
| Topics: | Information Management, Engineering Principles, Research Practice, Cost Management, Business Strategy, Procurement, Organizational Design |
| Descriptive scope: | 4 PCTA |
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