Modelling seasonality in Australian building approvals

Abstract

The paper examines the impact of seasonal influences on Australian housing approvals, represented by the State of Victoria building approvals for new houses (BANHs). The prime objective of BANHs is to provide timely estimates of future residential building work. Due to the relevance of the residential property sector to the property sector as whole, BANHs are viewed by economic analysts and commentators as a leading indicator of property sector investment and as such the general level of economic activity and employment. The generic objective of the study is to enhance the practice of modelling housing variables. In particular, the study seeks to cast some additional light on modelling the seasonal behaviour of BANHs by: (i) establishing the presence, or otherwise, of seasonality in Victorian BANHs; (ii) if present, ascertaining is it deterministic or stochastic; and (iii) determining out of sample forecasting capabilities of the considered modelling specifications. To do so the study utilises a structural time series model of Harvey (1989). The modelling results confirm that the modelling specification allowing for stochastic trend and deterministic seasonality performs best in terms of diagnostic tests and goodness of fit measures. This is corroborated with the analysis of out of sample forecasting capabilities of the considered modelling specifications, which showed that the models with deterministic seasonal specification exhibit superior forecasting capabilities. The paper also demonstrates that if time series are characterized by either stochastic trend or seasonality, the conventional modelling approach (a modelling approach based on the assumption of deterministic trend and deterministic seasonality) is bound to be mis-specified i.e. would not be able to identify statistically significant seasonality in time series. According to the selected modeling specification, factors corresponding to June, April, December and November are found to be significant at five per cent level.