Tourism forecasting using SARIMA models in Chilean regions

In this paper, we search for the best statistical model of time series with seasonal effect (seasonal autoregressive integrated moving average (SARIMA)) for forecasting arrivals in 13 regions of Chile. We use monthly time series of arrivals from January 2004 to March 2009. The forecasting performance is assessed using data for the period October 2008 to March 2009. We use three methods for the specification of the model: the Box?Jenkins method with Akaike criterion, the method of minimising the forecast error and the regARIMA method of the X12-ARIMA package. We compare the performance of the three methods according to their forecast results. Regions have different SARIMA specifications, resembling the underlying differences in tourism infrastructure and capacities available within each region.