An econometric model for forecasting private construction investment in Hong Kong
AbstractAcknowledging the importance of the private construction market and a close linkage between private construction investment, public sector output and general economic conditions, there is a strong motivation to develop reliable models to forecast private construction investment. Based on the Hong Kong scenario, two modelling approaches, namely the vector error correction (VEC) and the multiple regression models are developed and compared for their modelling accuracy and ability to handle non-stationary time series data. The result suggests that private construction investment in Hong Kong can be predicted by reference to public investment in construction, gross domestic product (GDP) and unemployment rate. All in all, the VEC model is considered more accurate and robust in handling non-stationary data. Through the VEC model, it is possible to confirm that the crowding-in effect of public work programmes, though minimal, is discernible in private construction investment in Hong Kong. Yet private construction investment is more sensitive to general economic conditions, as represented by GDP and unemployment rate. The GDP could represent the ability of investors to pay for construction items, while the unemployment rate is used as a proxy for the willingness of end-users to purchase the construction items. The models proposed should help policy and decision makers formulate suitable policies and strategies to sustain the construction industry in the medium to long run.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Construction Management and Economics.
Volume (Year): 29 (2011)
Issue (Month): 5 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RCME20
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.