Dynamic Copula-Based GARCH Model Analysis China Outbound Tourism Demand - Innovative Management in Information and Production - page 125

Thailand and Singapore
(DT12)

Thailand and South Korea
(DT13)

1.0 1.2

0.9 0.8

0.8 0.4

0.7 0.0

0.6 -0.4

0.5 -0.8

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

Thailand and Japan
(DT14)

Singapore and South Korea
(DT23)

.8 1.0

.6

0.8

.4

0.6

.2

0.4

.0

-.2 0.2

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

Singapore and Japan
(DT24)

South Korea and Japan
(DT34)

.8 1.2

1.0

.6

0.8

.4

0.6

0.4

.2

0.2

.0

0.0

-.2 -0.2

97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 9798 99 00 01 02 03 04 05 06 07 08 09 10 11

Fig. 4 Four conditional dependence estimates between four destinations based on Student-t
copula-GARCH

between Thailand and Singapore, Thailand and Japan, and between Singapore and
South Korea exhibits better explanatory ability than other dependence structure; the
Gumbel dependence structure between Thailand and South Korea and Singapore
and Japan exhibits better explanatory ability than other dependence structure, while
the Clayton dependence structure between Japan and South Korea exhibits better
explanatory ability than other dependence structures. These results imply that
introducing the tail dependence between the four destinations adds much to the
explanatory ability of the model.