Seasonal ARIMA forecasting of inbound air travel arrivals to Taiwan

This article uses the Holt–Winters method, the seasonal ARIMA (SARIMA) model, and the GM(1,1) grey forecasting model to replicate monthly inbound air travel arrivals to Taiwan and to compare the models’ forecasting performance. It uses the mean absolute percent error (MAPE) for the measurement of forecast accuracy and implements turning point analysis (TPA) to compare the model performance between the direct and indirect forecast methods. Based on the out-of-sample forecasts, all fitted models have good forecasting performance in terms of the MAPE criterion, and the SARIMA model is the best one for forecasting inbound air travel arrivals to Taiwan. According to the TPA results, this article supports the out-performance of the indirect forecast method.