Forecasting Monthly Tourist Departures from Australia

This paper builds time series forecasting models for monthly international tourist departures from Australia, categorized by the major destinations and by the main purposes of travel. Descriptive and statistical analyses reveal that strong trend and seasonality are the major features of all time series considered. The seasonal ARIMA model is used as a forecasting tool and its trend and seasonal components are specified based on inferential outcomes of the HEGY test for seasonal unit roots. Other alternative forecasting methods used include Holt-Winters' exponential smoothing method and the regression models that involve deterministic trend or seasonal dummy variables. It is found that forecasts generated from seasonal ARIMA models are more accurate than other alternative forecasts in most cases.