Research Note: A Study of Outliers of International Tourism Statistics

Abstract

As international tourism is an industry that is easily impacted by external shocks, there is always structural mutation of the time series related with it, which causes the existence of outliers. Those outliers will have an impact on analyses based on such data. Using quarterly data from 1994 to 2006, this paper detects outliers in the time series of international tourists to China and finds that the number of international tourists during the second and the third quarters of 2003 are outliers of the time series. To eliminate the impact of outliers, the paper uses the SARIMA model to forecast the values of outliers. By replacing the original value with the forecasted values, the authors conduct a co-integration analysis with the new time series and the corresponding quarterly gross domestic product (GDP) data. The results show that research conducted without considering outliers overestimates the effect of international tourism on economic growth.

Tourism demand and the COVID-19 pandemic: an LSTM approach

“…The outbreak of SARS in 2003 caused increased international anxiety due to its transmissibility and fast spread by air travel (Wenzel & Edmond, 2003) and, at the same time, resulted in severe economic losses for the global tourism industry. As a direct consequence of the SARS outbreak, the number of international tourists during the second and third quarters of 2003 has decreased by 42.83% and 7.24% respectively (Feng-Yuan & Feng-Jie, 2013). Risk events such as SARS may have a devastating impact on the global economy, but there is increased risk in the tourism industry since it is highly sensitive to external shocks (Novelli et al, 2018).…”