Abstract
As climate is not only a valuable tourism resource but also a factor influencing travel experience, estimating climate volatility has implications for sustainable development of the tourism industry. This study develops the Climate Volatility Index (CVI) using a Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model and estimates the relationship between CVI and Japanese tourism demand in Korea, using a tourism demand model based on monthly data from January 2000 to December 2013. Possible time lags and multicollinearity among variables are considered for the model specification. The results show that an increase in climate volatility leads to a decrease in tourism demand.
Highlights
It is essential to respond properly to climate change for achieving sustainability of the tourism industry [1] because climate is a critical tourism resource as well as a determinant of tourist satisfaction, which affects tourism demand [2]
This study introduced a tourism demand model in order to verify the relationship between climate volatility and tourism demand as shown in the Equation (2). lnTAt refers to tourism demand and it is measured by a log transformation of the number of Japanese tourists visiting Korea at month t. lnINCOMEt refers to Japanese tourists’ income and it is measured by a log transformation of the income of Japanese tourists at time t. lnRECOSTt refers to the relative travel cost in Japan compared to that in Korea and it is measured by a log transformation of the relative travel cost at time t
According to the results of this test, we applied time lags for tourism demand ranging from t − 1 to t − 3 to minimize the value of Akaike Information Criterion (AIC)
Summary
It is essential to respond properly to climate change for achieving sustainability of the tourism industry [1] because climate is a critical tourism resource as well as a determinant of tourist satisfaction, which affects tourism demand [2]. Other studies have tried to explain the impact of climate change on tourism demand by using an index comprised of multiple indicators [8,9,10]. By taking both changing weather events and the degree of climate change, i.e., volatility, into consideration, the estimation of climatic impact can be more efficient and further improved. We tried to consider climate volatility explicitly in order to better explain the impact of climate change on tourism demand, aside from the average or the extreme of climate indicators.
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