Modeling and Forecasting Monthly Domestic Tourism Expenditure through the SARIMAX Approach

Abstract

Forecasting domestic tourism expenditure supports budgeting, financial planning, and encourages responsible spending, fostering economic stability. The Consumer Price Index (CPI) is crucial for domestic tourism expenditure as it reflects inflation, guiding budget decisions and expenditure planning. However, there is limited research that focuses on predicting monthly domestic tourism expenditure. This paper proposes a forecasting framework that employs a seasonal autoregressive integrated moving average model with exogenous variables (Consumer Price Index (CPI)) to forecast domestic tourism expenditure. The dataset of this study contains monthly observations from the Korea Tourism Knowledge & Information System and a set of exogenous variables such as monthly Consumer Price Index (CPI) data for Transportation, Recreation and Culture, and Restaurants and Hotels. Experimental results indicated that SARIMAX model shows a predictive accuracy.