Dynamic Copula-Based GARCH Model Analysis China Outbound Tourism Demand - Innovative Management in Information and Production - page 120

Tabl e 2 Tests of hypotheses of unit-root

ADF PP

Log of first
difference

Log of first
difference Variables Level Level

Thailand − 5 . 10972 ∗∗ − 12 . 04982 ∗∗ − 4 . 98858 ∗∗ − 28 . 3882 ∗∗

30905 ∗∗

Singapore − 0 . − 7 . 43598 ∗∗ − 3 . 77929 ∗∗ − 40 . 76052 ∗∗

71588 ∗∗ 09804 ∗∗ South Korea 2 . − 5 . 55876 ∗∗ − 0 . − 33 . 4513 ∗∗

Japan − 0 . 8423 ∗∗ − 4 . 5195 ∗∗ − 4 . 4855 ∗∗ − 32 . 9507 ∗∗

− .

Note: The critical values for the rejection of the null hypothesis of a unit-root are 3 451, and

− .

870 for 1% and 5%, respectively. The symbol ** and * denote rejection of the null hypothesis
at the 1% and 5% significance levels, respectively

2

Tabl e 3 Result for GARCH model

GARCH
Thailand Singapore South Korea Japan

C 0 − 0 . 0413 ∗∗∗ − 0 . 0352 ∗∗∗ − 0 . 0151 ∗∗ − 0 . 0211 ∗∗∗

( 0 . 0134 ) ( 0 . 0110 ) ( 0 . 0061 ) ( 0 . 0037 )

C 1 − 0 . 5842 ∗∗∗∗ − 0 . 5626 ∗∗∗ − 0 . 3403 ∗∗∗ 0 . 0626

( 0 . 0579 ) ( 0 . 0583 ) ( 0 . 1096 ) ( 0 . 0868 )

C 2 0 . 7070 ∗∗∗ 0 . 6214 ∗∗∗ 0 . 2545 ∗ − 0 . 8697 ∗∗∗

( 0 . 0759 ) ( 0 . 0814 ) ( 0 . 1449 ) ( 0 . 0441 )

. ∗∗∗ . ∗∗∗ . ∗∗∗ . ∗∗∗

D 1 0 1648 0 1382 0 0955 0 1352

( . ) ( . ) ( . ) ( . )

0 0260 0 0203 0 0165 0 0220

D 2 0 . 1406 ∗∗∗ 0 . 1786 ∗∗∗ 0 . 0996 ∗∗∗ 0 . 0815 ∗∗∗

( 0 . 0223 ) ( 0 . 0213 ) ( 0 . 0140 ) ( 0 . 0150 )

ω i 0 . 0028 ∗ 0 . 0040 ∗∗∗ 0 . 0004 0 . 0011

( 0 . 0017 ) ( 0 . 0014 ) ( 0 . 004 ) ( 0 . 0008 )

α i 0 . 1916 ∗∗ 0 . 2331 ∗∗ 0 . 0456 0 . 3266

( 0 . 0941 ) ( 0 . 1041 ) ( 0 . 0452 ) ( 0 . 3488 )

β i 0 . 6111 ∗∗∗ 0 . 3390 ∗ 0 . 8571 ∗∗∗ 0 . 6360 ∗

( 0 . 1556 ) ( 0 . 1975 ) ( 0 . 1001 ) ( 0 . 3332 )

η i 5 . 4558 ∗∗∗ 12 . 3850 ∗∗∗ 6 . 0185 ∗∗∗ 3 . 7896 ∗∗

( 1 . 6542 ) ( 3 . 5203 ) ( 2 . 2835 ) ( 1 . 5674 )

λ − 0 . 3668 ∗∗∗ − 0 . 3223 ∗∗∗ − 0 . 0233 − 0 . 2963 ∗∗ i

)
Note that ***, **, and * denote rejection of the null hypothesis at the 1%, 5%, and 10%
significance levels, respectively

( 0 . 1100 ) ( 0 . 1140 ) ( 0 . 1180 ) ( 0 . 1236

4.2 Estimation Results

The estimated result of the GARCH model is reported in Table 3 , using a maximum
likelihood estimation method. The ARCH coefficient

α i is significant in Thailand
and Japan. These results imply that a shock to the tourist arrival series has short
run persistence in Thailand and Japan. All autoregressive coefficients β i are highly

significant. These results imply that a shock to the tourist arrival has long-run