Issues in Forecasting International Tourist Travel

Document Type

Article

Publication Date

2013

Publication Title

Academy of Information and Management Sciences Journal

ISSN

1524-7252

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.

Comments

This article is available in the Academy of Information and Management Sciences Journal volume 16, number 2 on pages 15-30.

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