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

机译：预测施工需求：带有虚拟变量的矢量误差校正模型

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摘要

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.
机译：对建筑需求水平进行建模对于政策制定和实施至关重要，因为建筑业在一个国家的经济发展过程中发挥着重要作用。在建筑经济学中，对建筑需求建模和预测的研究工作多种多样，但是很少有研究人员考虑全球经济事件对建筑需求建模的影响。先进的多元建模技术，即带有虚拟变量的矢量误差校正（VEC）模型，被用来预测澳大利亚建筑市场的需求。预测精度测试的结果表明，一般的VEC模型和带有虚拟变量的VEC模型都可以用于预测建筑经济指标。但是，考虑到外部影响的VEC模型比常规VEC模型具有更高的预测精度。该模型估计表明，在解释建筑需求变化时，人口增长，国民收入变化，利率波动和家庭支出变化都起着重要作用。带有扰动的VEC模型可以用作使用先进的计量经济学方法的实验，该方法可以用于分析特定事件或因素对建筑市场增长的影响。

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