In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

1. 서 론
2. 시계열 모형
    2.1 ARIMA모형과 SARIMA모형
    2.2 외생변수를 갖는 SARIMA모형
3. 실증 분석
    3.1 시계열 변환
    3.2 모형 식별
    3.3 모형 추정
    3.4 외생변수 설정
    3.5 예측
    3.6 비교 실험
4. 결 론
References

• Geun-Cheol Lee(건국대학교 경영대학) | 이근철
• Seong-Hoon Choi(상명대학교 경영공학과) | 최성훈 Corresponding Author