Title
Issues in Forecasting International Tourist Travel
Document Type
Presentation
Publication Date
4-2012
Abstract
In this paper two popular time series methods for modeling seasonality in tourism forecasts are compared. The first uses a decomposition methodology to estimate seasonal variation. In this method seasonal variation is estimated with a ratio-to-centered moving average approach. Three different approaches in calculating the seasonal indices are analyzed. The deseasonalized series are then forecast using an ARIMA model. The second methodology uses a multiplicative seasonal ARIMA (SARIMA) approach to simultaneously model trend and seasonal variations. The two methodologies are compared and the accuracy and managerial advantages of each are discussed.
Sponsorship/Conference/Institution
Allied Academies International Conference
Location
New Orleans, LA
Recommended Citation
Moss, Steven E., Jun Liu, Janet Moss.
2012.
"Issues in Forecasting International Tourist Travel."
Logistics & Supply Chain Management Faculty Presentations.
Presentation 54.
https://digitalcommons.georgiasouthern.edu/logistics-supply-facpres/54