Forecasting International Tourist Arrivals from Major Countries to Thailand

Tourism industry is one of the most important industries for Thai economy. This paper proposes and compares forecasting models for international tourism arrivals to Thailand. Since country-specific forecasting models can reflect the uniqueness of each country of origin, major countries for Thai tourism, namely China, Malaysia, Korea, Japan, and Russia are explored. The data used in this research is the number of international tourist arrivals from those countries recorded monthly from Jan 2013 to Sep 2018. The performance of the Seasonal Autoregressive Integrated Moving Average model (SARIMA) and the multiple regression model are evaluated in terms of Mean Absolute Percentage Error (MAPE). Several important economic factors such as income, price, exchange rate, and qualitative factors, represented by dummy variables of seasonal effect are explored to understand their effects on international tourism demand. The results show that the SARIMA is preferred to forecast international tourism arrivals from Malaysia, while multiple regression provides lowest errors for other interested countries.