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題名：重大事件、經濟因素與波動性對旅遊需求的影響
作者：陳盈志
作者(外文)：Ying-ChihChen
校院名稱：國立成功大學
系所名稱：企業管理學系碩博士班
指導教授：康信鴻
楊澤泉
學位類別：博士
出版日期：2009
主題關鍵詞：旅遊需求預測；季節ARIMA；波動性；GARCH；EGARCH；GJR GARCH；SARS；tourism demand forecast；seasonal ARIMA；volatility；GARCH；EGARCH；GJR GARCH；SARS
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本論文的研究目的為探討影響旅遊需求之因素，包括重大事件、經濟因素與波動性，並建立旅遊需求預測模型。過去關於旅遊需求預測的研究，絕大部分均假設波動為一固定常數，因而忽略了波動性對旅遊需求的影響。事實上，大部分的經濟數據都有波動性叢聚的現象，因此旅遊需求的波動性是否也有自我相關條件異質變異的現象(ARCH effects)很值得研究。然而好、壞消息對波動性的影響是否有不對稱的情形？且壞消息對波動性的影響是否大於好消息，即槓桿效果?這也值得進一步探討。此外，本研究亦要探討經濟因素與重大事件對旅遊需求的影響。
本論文的研究對象為中國的入境旅遊與台灣人民出境至中國旅遊。首先，建立四個入境中國的旅遊需求預測模型，並比較其預測能力。本論文以季節ARIMA來估計條件期望值，以GARCH、EGARCH 與GJR GARCH 來估計條件變異數，發現中國的旅遊需求存在著季節性、ARCH、波動不對稱性與槓桿效果。此外，並以虛擬變數來估計重大事件對旅遊需求的影響，僅有SARS與四川大地震有顯著的負面影響。結果顯示四種模型的樣本內與樣本外的預測能力，皆以GARCH 加上虛擬變數的模型最佳。另外，以迴歸模型來估計經濟變數與重大事件對台灣人民至中國旅遊的影響。研究結果顯示在經濟變數中，所得、價格與前期的旅遊人數為顯著；而在重大事件中僅有SARS有顯著的負面影響，政治事件與921大地震並不會影響台灣人民至中國旅遊的意願。
This thesis aims to find out the impacts of mega events, economic factors, and volatility on tourism demand. Most of the past studies assumed variance of errors to be a constant, but in practice, time series of economic data have often exhibited the volatility clustering phenomenon. Hence, it is worth examining whether tourism demand volatility has ARCH (Autoregressive Conditional Hetetroskedasticity) effects. Further, asymmetric effects, meaning that good and bad news differently affect volatility, and the leverage effect, meaning bad news influences volatility more than good news, ought to be studied as well. The impacts of economic factors and mega events on tourism demand are also what is examined in this thesis.
The subjects are the tourism demand in China and Taiwan’s outbound tourism to China. To study the tourism demand in China, four models are built and compared to find an appropriate forecasting model of the tourism demand in China. Seasonality, ARCH effects, asymmetric effects, and leverage effects are found in estimating the conditional mean by seasonal ARIMA and in estimating the conditional variance of tourist arrivals by GARCH, EGARCH, and GJR GARCH. Meanwhile, whether mega events have impacts on tourism demand is examined by intervention analysis. In all the events studied, only SARS and the Great Sichuan Earthquake had significant effects. Judging by the in-sample and out-of-sample forecasting performance, GARCH with intervention analysis is found to be the best in the four models. Secondly, an econometric model is built to estimate how economic factors and mega events influence Taiwan’s outbound tourism to China. Income, price, and the tourist number of the previous period are found to be significant independent variables. On the other hand, empirical results show that political events did not remarkably reduce Taiwanese people’s intention to travel to China while the SARS outbreak had a greater impact.
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