MODELLING HONG KONG RESIDENTIAL CONSTRUCTION DEMAND: EXPERIENCES GAINED AND THEIR IMPLICATIONS

  • Ryan Y.C. Fan (Department of Civil Engineering, The University of Hong Kong) ;
  • S. Thomas Ng (Department of Civil Engineering, The University of Hong Kong) ;
  • James M.W. Wong (Department of Civil Engineering, The University of Hong Kong)
  • Published : 2009.05.27

Abstract

The construction industry has been a main pillar and serves as a regulator of the Hong Kong economy. Subsequently, the fluctuations in the level of construction output can induce significant rippling effects to the economy. The Asian Financial Crisis started in 1997 and the SARS outbreak in 2003 both introduced major challenges and impacts to the Hong Kong economy and consequently the construction sector. Such decline in the importance of construction has suggested a possible structural change in the sector. It is worth investigating the driving forces behind the construction demand and see if they have changed after the heavy impacts in the past decade. The above considerations have, therefore, been the motivation of the present study to model the Hong Kong residential construction demand through multiple regression technique which can identify the significant influencing factors to the residential demand. The residential construction is studied as it constitutes a significant portion of the total construction volume. The residential sector has great influence to the general economy of Hong Kong. It is found that the underlying market structure and the driving factors for Hong Kong residential demand before and after the Asian Economic Crisis and SARS outbreak are different, suggesting that the residential construction sector or even the larger construction industry may have undergone a major structural change as Hong Kong's economy approaches maturity. It is also observed that the past literatures on construction demand are mostly focusing on predicting demand under a stable economic environment. Hence, it is worth examining if it is possible to model during economic hardship when the residential sector fluctuate dramatically under different external impacts, such as the recent global financial tsunami.

Keywords

Acknowledgement

The authors would like to thank the financial support of the Research Grants Council through the General Research Fund (grant no: 7152/07E).