為了改善中國旅客來台旅遊人數減少之問題，我國政府推出「新南向政策」藉以強化我國與南亞、東南亞地區國家、紐西蘭及澳洲之合作，並持續促進我國經濟發展。隨著政策發展，新南向國家旅客對台灣觀光產業之重要性與日俱增。因此，本研究主要探討新南向國家旅客至台灣旅遊人次變動率的短期與長期持續衝擊及旅遊需求風險特性(不對稱效果和槓桿效果)，並期望研究結果能對公、私部門制訂旅遊相關政策與行銷企劃時有所參考價值。研究結果發現，除了馬來西亞與印度，其他新南向國家來台旅遊人次變動率對衝擊具有長期與短期持續性影響，其中，馬來西亞旅客之來台旅遊需求僅具有短期衝擊效果，而印度旅客僅反映長期衝擊效果。此外，除了印度旅客，其他新南向政策國旅客來台旅遊人次變動率的波動具有不對稱效果，表示這些國家之來台旅遊需求受負面事件影響大於正面事件影響。另外，本研究亦在新加坡、菲律賓、泰國、紐西蘭的旅客來台旅遊人次變動率的波動中捕捉到槓桿效果，顯示這些國家的旅客對於小事件衝擊的反應較為敏感。

 To mitigate the loss of inbound Chinese tourists, Taiwan government has launched the ‘New Southbound Policy’ and promoted a series of programs to intensify the collaboration with the New Southbound countries, including countries in southeastern Asia, as well as New Zealand and Australia, in hopes of boosting the economic development of Taiwan. As a result of the policy, the New Southbound countries have gradually become the main source of inbound international tourists for Taiwan, and the importance of the New Southbound countries is on the rise. Hence, the paper aims at investigating the tourism demand of these countries and further analyze the characteristics (symmetric, asymmetric and leverage effect) for the volatility. Also, the paper detects the persistence of shocks on the volatility of the change rate of daily international inbound tourists from the New Southbound countries. The paper adopts the daily data from 1 January 2014 to 17 March 2020 with three econometric models, which are GARCH(1,1), GJR(1,1), and EGARCH(1,1) models for empirical analysis. The findings show that for most New Southbound countries, the impact of shocks on tourism demand would persist in both long- and short-run. For Malaysia, impact of shocks only last for a short period of time, while for India, the impact on the tourism demand caused by shocks would only be shown in the long run. In addition, asymmetric effects are captured in the volatility of international inbound tourists from all studied countries, except for India. It means that tourists, Indian tourists excluded, from the New Southbound countries are more sensitive to negative shocks as the volatility of the international inbound tourists would react greatly to negative events comparing to the positive ones. Furthermore, the leverage effects are captured in half of the studied countries, including Singapore, Vietnam, Philippines, Thailand, and New Zealand, which means that small-scale incidents rather than big ones are more likely to bring volatility to their tourism demand. Overall, to constantly increase the number of international inbound tourists from the new Southbound countries, it is suggested that the Taiwan authority and the private tourism agencies reduce the negative events that would damage the image of Taiwan to the least possible level, as well as stimulate the tourism demand by launching programs which entail ongoing preferential policy and short-term promotions. 

Table of Contents
Chapter 1	Introduction	1
Chapter 2	Literature Review	9
Chapter 3	Methodology	14
3.1	Fundamental Tourism Finance Equation	14
3.2.	Univariate Conditional Volatility Models	15
3.2.1.	GARCH model	15
3.2.2.	GJR model	17
3.2.3.	EGARCH model	18
3.3.	Data and Variables	20
Chapter 4	Empirical Results	27
4.1.	Malaysia	27
4.2.	Singapore	30
4.3.	Indonesia	32
4.4.	Vietnam	34
4.5.	Philippines	36
4.6.	Thailand	38
4.7.	India	40
4.8.	Australia	42
4.9.	New Zealand	44
4.10.	Potential markets	46
Chapter 5	Discussion	48
5.1.	Key source markets—Malaysia, Singapore, Vietnam and Thailand	49
5.2.	Growing markets – Indonesia, Philippines, and India	50
5.3.	Australia and New Zealand	51
5.4.	Potential markets (Myanmar, Cambodia, Laos, Bhutan, Brunei, and Sri Lanka)	51
Chapter 6	Conclusion	53
References	55

List of Figures
Figure 1. The total number of inbound visits and the visitor expenditures (foreign exchange earnings from tourism industry) (Taiwan Tourism Bureau, 2022).	2
Figure 2. The annual total number of international inbound tourists from New Southbound countries (by region) (Taiwan Tourism Bureau, 2022).	4
Figure 3. Changes in the number of international inbound tourists from New Southbound countries (by residence) (Taiwan Tourism Bureau, 2022).	5
Figure 4. The total number of tourists from China and New Southbound countries (Taiwan Tourism Bureau, 2022).	6
Figure 5. The total number of Daily International Inbound Tourists from 1 January 2014 to 17 March 2020.	22
Figure 6. The Change Rate of Daily International Inbound Tourists from 1 January 2014 to 17 March 2020.	23
 
List of Tables
Table 1. Descriptive Statistics	26
Table 2. Estimation Results for International Inbound tourists from Malaysia.	29
Table 3. Estimation Results for International Inbound tourists from Singapore	31
Table 4. Estimation Results for International Inbound tourists from Indonesia	33
Table 5. Estimation Results for International Inbound tourists from Vietnam	35
Table 6. Estimation Results for International Inbound tourists from Philippines	37
Table 7. Estimation Results for International Inbound tourists from Thailand	39
Table 8. Estimation Results for International Inbound tourists from India	41
Table 9. Estimation Results for International Inbound tourists from Australia	43
Table 10. Estimation Results for International Inbound tourists from New Zealand	45
Table 11. Estimation Results for International Inbound tourists from Potential Markets	47
Table 12. Summary of the risk volatility attributes to the change rate of daily inbound tourists from New Southbound countries	48

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