| Since 1978, Chinese inbound tourism has kept a steadily fast development trend and has made enormous contribution to the foreign exchange revenue and the balance of payments of our country. However, inbound tourism is an extremely sensitive trade, and it may be greatly affected by political and economic turbulence or various kinds of accidents in the world. This thesis is trying to apply quantitative analysis to study the demand of Chinese inbound travel market and its variation tendency, and to create metrics models to predict the number of inbound visitors of China.This thesis introduces the development course of Chinese inbound travel market and its enormous contribution to Chinese national economy, and detailedly analyzes the factors which influence the inbound tourism and various kinds of accidents which have greatly affected Chinese inbound travel business since 1978. These are regarded as the base of the model. And then three econometrics models are structured in order to predict the variation tendency of the number of the inbound travelers of China. The first model is a multi-variable linear regression model. The explanatory variables are Chinese consumer price index, foreign comprehensive weighting exchange rate, foreign comprehensive weighting real GDP and a dummy variable. The second model is a time series model. It adopts the ARIMA(p,d,q)(P,D,Q)_s model which was put forward byBox&Jenkins in 1976. The third model combines the variables and parameters of the first and the second model to create a linear mixture regression model. At last, having compared the predicting ability of the three models, the third model, which combines the regression model and the time series model, is regarded as the optimum model. The thesis suggests the government or relevant enterprises to apply the linear mixture regression model in the forecasting of the number of travelers. It should be more accurate than the simple time series model or the simple linear regression model. |
PDF Full Text Request