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Forecasting construction demand: a vector error correction model with dummy variables

Listed author(s):
  • Heng Jiang
  • Chunlu Liu
Registered author(s):

    Modelling the level of demand for construction is vital in policy formulation and implementation as the construction industry plays an important role in a country’s economic development process. In construction economics, research efforts on construction demand modelling and forecasting are various, but few researchers have considered the impact of global economy events in construction demand modelling. An advanced multivariate modelling technique, namely the vector error correction (VEC) model with dummy variables, was adopted to predict demand in the Australian construction market. The results of prediction accuracy tests suggest that the general VEC model and the VEC model with dummy variables are both acceptable for forecasting construction economic indicators. However, the VEC model that considers external impacts achieves higher prediction accuracy than the general VEC model. The model estimates indicate that the growth in population, changes in national income, fluctuations in interest rates and changes in householder expenditure all play significant roles when explaining variations in construction demand. The VEC model with disturbances developed can serve as an experimentation using an advanced econometrical method which can be used to analyse the effect of specific events or factors on the construction market growth.

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    Article provided by Taylor & Francis Journals in its journal Construction Management and Economics.

    Volume (Year): 29 (2011)
    Issue (Month): 9 (August)
    Pages: 969-979

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    Handle: RePEc:taf:conmgt:v:29:y:2011:i:9:p:969-979
    DOI: 10.1080/01446193.2011.611522
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