Hierarchical forecasts for Australian domestic tourism
George Athanasopoulos (),
Roman A. Ahmed () and
Rob Hyndman ()
No 12/07, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics
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. (search for similar items in EconPapers)
JEL-codes: C13 C22 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for and nep-tur
Date: 2007-08, Revised 2007-11
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http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2007/wp12-07.pdf Revised version, November 2007 (application/pdf)
Journal Article: Hierarchical forecasts for Australian domestic tourism (2009)
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