| By: |
George Athanasopoulos;
Roman A. Ahmed;
Rob J. Hyndman |
| 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 for
different geographical regions and for different 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 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 for the Australian domestic tourism market. |
| Keywords: |
Australia, exponential smoothing, hierarchical forecasting, innovations state space models, optimal combination forecasts, top-down method, tourism demand. |
| JEL: |
C13 C22 C53 |
| Date: |
2007–08 |
| URL: |
http://d.repec.org/n?u=RePEc:msh:ebswps:2007-12&r=tur |