China has experienced a massive growth in international tourism over the past two decades. To date, there have been few attempts to analyse this massive increase in the demand for international tourism to China.
This study, therefore, employs modern econometric techniques to identify the important determinants of tourism demand to China and thus determine the best forecasting models of tourism demand applied to China. This thesis has set three objectives for itself. First, it aims to undertake the first application of modern time-series econometric techniques to modelling international tourism flows to China. Second, it provides the first application of the Vector Autoregression (VAR) approach to modelling the demand for tourism. Third, this thesis compares relative forecasting performance of the two econometric techniques — the time-series approach and the VAR approach, in order to provide 'best possible' forecasts of international tourism flows to China. The thesis
models demand from three of China's most important markets for international travelers: Australia, the USA and Japan.