Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Structural breaks, tourism development, and economic growth: Evidence from Taiwan
Mathematics and Computers in Simulation
Forecasting tourism demand using a multifactor support vector machine model
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
International Journal of Fuzzy System Applications
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This paper investigates the long-run relationship between the demand for international travel to Australia from Malaysia and a group of leading macroeconomic variables, including Malaysian income, tourism prices in Australia, transportation costs between Malaysia and Australia, and the exchange rate between the two countries. The Augmented Dickey-Fuller (ADF) procedure is used to test for unit roots, while Johansen's maximum likelihood procedure is used to test for cointegration and to estimate the number of cointegrating vectors. A single cointegrating relationship is found among the set of non-stationary macroeconomic variables, and is compared with the ordinary least squares estimates. It is found that lagged changes in real airfares, and the extent to which the system is out of equilibrium, are statistically significant. Surprisingly, real income does not seem to have a significant effect on tourism demand from Malaysia to Australia when the cointegration technique is used. However, real income (as measured by the logarithm of real private consumption expenditures per capita) is significant when ordinary least squares estimation is used.