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

Author

Listed:
  • S. Thomas Ng
  • Sai On Cheung
  • Martin Skitmore
  • Toby Wong

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.

Suggested Citation

  • S. Thomas Ng & Sai On Cheung & Martin Skitmore & Toby Wong, 2004. "An integrated regression analysis and time series model for construction tender price index forecasting," Construction Management and Economics, Taylor & Francis Journals, vol. 22(5), pages 483-493.
    • Handle: RePEc:taf:conmgt:v:22:y:2004:i:5:p:483-493
    DOI: 10.1080/0144619042000202799
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    Cited by:

    1. Juntao Li & Tianxu Cui & Kaiwen Yang & Ruiping Yuan & Liyan He & Mengtao Li, 2021. "Demand Forecasting of E-Commerce Enterprises Based on Horizontal Federated Learning from the Perspective of Sustainable Development," Sustainability, MDPI, vol. 13(23), pages 1-29, November.
    2. Ma, Le & Liu, Henry J. & Edwards, David J. & Sing, Michael C.P., 2021. "Housing price dynamics on residential construction: A case study of the Australian property sector," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 525-532.
    3. Linlin Zhao & Zhansheng Liu & Jasper Mbachu, 2019. "Energy Management through Cost Forecasting for Residential Buildings in New Zealand," Energies, MDPI, vol. 12(15), pages 1-24, July.
    4. Chien-Chung Nieh & Hwey-Yun Yau & Ken Hung & Hong-Kou Ou & Shine Hung, 2013. "Cointegration and causal relationships among steel prices of Mainland China, Taiwan, and USA in the presence of multiple structural changes," Empirical Economics, Springer, vol. 44(2), pages 545-561, April.

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