Journal
INTERNATIONAL JOURNAL OF FORECASTING
Volume 25, Issue 1, Pages 146-166Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijforecast.2008.07.004
Keywords
Australia; Exponential smoothing; Hierarchical forecasting; Innovations state space models; Optimal combination forecasts; Top-down method; Tourism demand
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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. (C) 2008 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
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