[01] Cuihong Cao, College of Science, Guilin University of Technology, Guilin, China. [02] Yuanying Jiang, College of Science, Guilin University of Technology, Guilin, China.

The tourism industry, as a representative of the third industry, has driven its sustainable development, which is conducive to the adjustment of industrial restructuring and economic development in China. Based on Chinese tourism income data from 1994 to 2015, this paper establishes a multiple linear regression model and analyses the factors affecting Chinese tourism income. The empirical study shows that the Lasso regression, compared with the ordinary least square estimation method, can not only eliminate the multicollinearity influence, but also select the main factors affecting Chinese tourism income. Moreover, it has contributed to reducing the fitting error of the model. According to the models results, Chinese tourism income is positively correlated with the number of tourists, the number of private cars and Internet dial-up users. However, it is negatively related to the road mileage variable.

Chinese Tourism Income, Multicollinearity, Lasso Regression

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