File(s) under permanent embargo

Construction price prediction using vector error correction models

journal contribution
posted on 2013-11-01, 00:00 authored by Jason Jiang, Y Xu, Chunlu LiuChunlu Liu
Reliable prediction of construction prices is essential for the construction industry because price variation can affect the decisions of construction contractors, property investors, and related financial institutions. Various modeling and prediction techniques for construction prices have been studied, but few researchers have considered the impact of global economic events and the seasonality of construction prices. In this study, global economic events and construction price seasonality as intervention dummies, together with a group of macroeconomic variables, are considered in a vector error correction (VEC) model to accurately predict the movement of construction prices. The proposed prediction model is verified against a series of diagnostic statistical criteria and compared with conventional VEC, multiregression, and Box-Jenkins approaches. Results indicate that the VEC model with dummy variables is more effective and reliable for forecasting construction prices. The VEC model with dummy variables can also assist construction economists to analyze the effect of special events and factors on the construction industry. © 2013 American Society of Civil Engineers.



Journal of Construction Engineering and Management






American Society of Civil Engineers



Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2013, American Society of Civil Engineers