Residential construction demand forecasting using economic indicators: a comparative study of artificial neural networks and multiple regression

Abstract

In recent years, demand for residential construction has been growing rapidly in Singapore. This paper proposes the use of economic indicators to predict demand for residential construction in Singapore. At the same time, two forecasting techniques are applied, namely, Artificial Neural Networks (ANN) and Multiple Regression (MR), the former being a state-of-the-art technique while the latter a conventional one. A comparative study is carried out to determine whether the use of economic indicators with the application of the ANN technique can produce better predictions than with the MR method. A total of 12 economic indicators are identified as significantly related to demand for residential construction. Quarterly data from these 12 indicators are used to develop the ANN model. In order to assess the forecasting performance of this state-of-the-art technique, the same set of data is used to develop a conventional MR model. A comparison is made between the two models, in terms of their forecasting accurac...