Hierarchical forecasts for Australian deomstic tourism
International Journal of Forecasting (2009), 25, pp. 146-166.
George Athanasopoulos, Roman A. Ahmed and Rob J. Hyndman
Department of Econometrics and Business Statistics, Monash University, VIC 3800, Australia.
Abstract
In this paper we explore the hierarchical nature of tourism demand time series and produce short-term forecasts for Australian domestic tourism. The data and forecasts are organized in a hierarchy based on disaggregating the data according to geographical regions and purposes of travel. We consider five approaches to hierarchical forecasting: two variations of the top-down approach, the bottom-up method, a newly proposed top-down approach where top-level forecasts are disaggregated according to the forecasted proportions of lower level series, and a recently proposed optimal combination approach. Our forecast performance evaluation shows that the top-down approach based on forecast proportions and the optimal combination method perform best for the tourism hierarchies we consider. By applying these methods, we produce detailed forecasts of the Australian domestic tourism market.
Keywords:Australia; Exponential smoothing; Hierarchical forecasting; Innovations state space models; Optimal combination forecasts; Topdown
method; Tourism demand.