Forecasting construction industry demand, price and productivity in Singapore: the BoxJenkins approach
- 1 July 2000
- journal article
- research article
- Published by Taylor & Francis Ltd in Construction Management and Economics
- Vol. 18 (5), 607-618
- https://doi.org/10.1080/014461900407419
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.Keywords
This publication has 17 references indexed in Scilit:
- An evaluation of the accuracy of the multiple regression approach in forecasting sectoral construction demand in SingaporeConstruction Management and Economics, 1999
- Forecasting residential construction demand in Singapore: a comparative study of the accuracy of time series, regression and artificial neural network techniquesEngineering, Construction and Architectural Management, 1998
- Model for forecasting construction cost indices in TaiwanConstruction Management and Economics, 1998
- Construction cost prediction for public school buildings in JordanConstruction Management and Economics, 1996
- Dynamic Modelling of the Building Cycle: 2. Empirical ResultsEnvironment and Planning A: Economy and Space, 1987
- Building price-level forecasting: an examination of techniques and applicationsConstruction Management and Economics, 1987
- Dynamic Modelling of the Building Cycle: 1. Theoretical FrameworkEnvironment and Planning A: Economy and Space, 1987
- The accuracy of extrapolation (time series) methods: Results of a forecasting competitionJournal of Forecasting, 1982
- Accuracy of Forecasting: An Empirical InvestigationJournal of the Royal Statistical Society. Series A (General), 1979
- Forecasting with Econometric Methods: Folklore Versus FactThe Journal of Business, 1978