Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/46431
Title: Forecasting construction industry demand, price and productivity in Singapore: The Box-Jenkins approach
Authors: Hua, G.B. 
Pin, T.H.O. 
Keywords: Accuracy
Box-Jenkins approach
Construction demand
Forecasting
Productivity
Tender price
Issue Date: 2000
Source: Hua, G.B.,Pin, T.H.O. (2000). Forecasting construction industry demand, price and productivity in Singapore: The Box-Jenkins approach. Construction Management and Economics 18 (5) : 607-618. ScholarBank@NUS Repository.
Abstract: In academic research, the traditional Box-Jenkins approach is widely acknowledged as a benchmark technique for univariate methods because of its structured modelling basis and acceptable forecasting performance. This study examines the versatility of this approach by applying it to analyse and forecast three distinct variables of the construction industry, namely, tender price, construction demand and productivity, based on case studies of Singapore. In order to assess the adequacy of the Box-Jenkins approach to construction industry forecasting, the models derived are evaluated on their predictive accuracy based on out-of-sample forecasts. Two measures of accuracy are adopted, the root mean-square-error (RMSE) and the mean absolute percentage error (MAPE). The conclusive findings of the study include: (1) the prediction RMSE of all three models is consistently smaller than the model's standard error, implying the models' good predictive performance; (2) the prediction MAPE of all three models consistently falls within the general acceptable limit of 10%; and (3) among the three models, the most accurate is the demand model which has the lowest MAPE, followed by the price model and the productivity model.
Source Title: Construction Management and Economics
URI: http://scholarbank.nus.edu.sg/handle/10635/46431
ISSN: 01446193
Appears in Collections:Staff Publications

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