Abstract
Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision. The use of construction tender price index provides a realistic estimate at the early stage of the project. Tender price index (TPI) is influenced by various economic factors, hence there are several statistical techniques that have been employed in forecasting. Some of these include regression, time series, vector error correction among others. However, in recent times the integrated modelling approach is gaining popularity due to its ability to give powerful predictive accuracy. Thus, in line with this assumption, the aim of this study is to apply autoregressive integrated moving average with exogenous variables (ARIMAX) in modelling TPI. The results showed that ARIMAX model has a better predictive ability than the use of the single approach. The study further confirms the earlier position of previous research of the need to use the integrated model technique in forecasting TPI. This model will assist practitioners to forecast the future values of tender price index. Although the study focuses on the Ghanaian economy, the findings can be broadly applicable to other developing countries which share similar economic characteristics.
Highlights
Tender price indices are comparable to output price indices
Forecasting the movement of the Tender price index (TPI) is never a straightforward process, as it could be influenced by a series of socio-economic factors such as interest rate, gross domestic product (GDP), unemployment rate and the varying challenges in tender appraisals rising from current trend of complex designs (Fitzgerald and Akintoye, 1995; Ng, et al, 2000; Wong and Ng, 2010)
These confirm that the residuals from the fitted model autoregressive integrated moving average with exogenous variables (ARIMAX) (0, 2, 1) – TPI are independent and normally distributed
Summary
Tender price indices are comparable to output price indices It is an output index demarcating the average building prices within a specific period, i.e. the agreed price to be paid by the clients/owners. It reflects the common market conditions (Ng, et al, 2000). Wong, Bai and Chu (2010) posited that the rate at which one can precisely forecast the tender price of a construction project has been a subject of research a few decades ago, as tender prices could influence the ideas of clients, contractors, property investors, financial institutions, etc. Tender Price Indices (TPI) is, employed to track the historical inclinations in the movement of tender price levels of construction contracts throughout the respective stages
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