Template-type: ReDIF-Paper 1.0
Author-Name: Chia-Lin Chang
Author-Workplace-Name: Department of Applied economics, Department of Finance National Chung Hsing University, Taiwan.

Author-Name: Shu-Han Hsu
Author-Workplace-Name:
 Department of Applied economics National Chung Hsing University, Taiwan.
Author-Name:
 Michael McAleer
Author-Workplace-Name:
 Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of 
	Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of 
	Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.
Title: An event study of chinese tourists to Taiwan
Abstract: The number of Chinese tourists visiting Taiwan has been closely related to the political relationship across the Taiwan Strait. The occurrence of 
	political events and disasters or accidents have had, and will continue to have, a huge impact on the Taiwan tourism market. To date, there has been 
	relatively little empirical research conducted on this issue. In this paper, tourists are characterized as being involved in one of three types of 
	tourism: group tourism (group-type), individual tourism (individualtype), and medical cosmetology (medical-type). We use McAleer’s (2015) fundamental 
	equation in tourism finance to examine the correlation that exists between the rate of change in the number of tourists and the rate of return on 
	tourism. Second, we use the event study method to observe whether the numbers of tourists have changed abnormally before and after the occurrence of 
	major events on both sides of the Strait. Three different types of conditional variance models, namely, GARCH (1,1), GJR (1,1) and EGARCH (1,1), are 
	used to estimate the abnormal rate of change in the number of tourists. The empirical results concerning the major events affecting the changes in the 
	numbers of tourists from China to Taiwan are economically significant, and confirm which types of tourists are most likely to be affected by such major 
	events.
Classification-JEL: G14, C22, C52, C58.
Keywords: Event study, Abnormal rate of change, Chinese tourists, OLS, GARCH, GJR, EGARCH, Tourism finance.
Length: 98 pages 
Creation-Date: 2018-01
Number: 2018-01
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1801.txt
File-URL: https://eprints.ucm.es/id/eprint/46073/1/1801.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1801