Forecast of International Tourist Arrivals Based on ARIMA Model

As the world's fastest-growing economic industry, the forecast of changes in the number of inbound tourists can promote the growth of local investment, economy and trade, foreign exchange and labor employment. In this paper, we want to study the impact of the epidemic on the number of international tourists arrivals in China. By observing the information displayed in ACF, PACF, EACF and other images, we build a suitable ARIMA model by using seasonal difference method on the data before the epidemic, and predict the number of international tourists arrivals if the epidemic does not occur. Finally, based on our forecasts, we observe that our projected trends differ significantly from actual visitor trends, suggesting that the impact of the coronavirus pandemic on international visitor arrivals is huge and difficult to recover. This model is no longer suitable for measuring post-pandemic international arrivals when a pandemic occurs.