Dynamic Copula-Based GARCH Model Analysis China Outbound Tourism Demand - Innovative Management in Information and Production - page 118

4 Empirical Result

4.1 Descriptive Data

In order to estimate the dynamic dependence structure of tourism demand in the
top destination, this research designated the proxy variable the number of China's
tourist arrivals to the following four destinations: Thailand, Singapore, South Korea,
and Japan. China monthly tourist arrival data from Jan 1997 to Oct 2011 were used
for this study, yielding a total of 178 observations. The data are obtained from Bank
of Thailand, Singapore Tourism Board, Japan National Tourist Organization, and
Korea Tourism Organization, respectively. China's monthly tourist arrival series are
plotted in Fig. 1 , which rises over time and along clear cyclical seasonal patterns,
although tourist arrivals fell sharply around the time of SARS (2003) and the global
financial crisis (2008 and 2009).
In building a model, most of the economic time series data are processed with the
use of the logarithmic transformation. Hence, the monthly tourist arrival return r i , t is
computed a continuous compounding basis as y i , t =

,where Y t and Y t − 1
are current and one-period lagged monthly tourist arrivals. y i , t is y thai , t ,

Ln ( Y t / Y t − 1 )

y korea , t ,
and y jap , t as incremental rate of Chinese tourist arrivals in Thailand, Singapore,
South Korea, and Japan, respectively. The tourist arrival incremental rates are
plotted in Fig. 2 , which show the GARCH model is appropriate for modeling the

y sing , t ,

THAILAND SINGAPORE

200,000 200,000

160,000 160,000

120,000 120,000

80,000 80,000

40,000 40,000

0

0

1998 2000 2002 2004 2006 2008 2010 1998 2000 2002 2004 2006 2008 2010

SOUTHKOREA JAPAN

280,000 200,000

240,000

160,000

200,000

120,000

160,000

120,000

80,000

80,000

40,000

40,000

0 0

1998 2000 2002 2004 2006 2008 2010

1998 2000 2002 2004 2006 2008 2010

Fig. 1 Chinese tourist arrivals to each destination