It shows that a disappearance of significant impacts from SD and MP in other Chinese cities, and variable ME is omitted because of multicolliearity – mega events were only held in Beijing and Shanghai. It might be explained by less public attention and less tourism prosperity of those cities, thus international tourists would not be disturbed by air quality. While FDI and PP are still significant, they play dominant effect on international tourism demand in the non-hotspot cities. Another reason caused this insignificance of SD and MP might be that other factors among those cities are not caught into this analysis, but since this research is not in depth of statistics, further researches are needed to detect those variables. East vs. West Unequal distribution of wealth was an important reason resulting difference of international tourism between eastern and western China. The border of east and west is drawn according to Figure 2, the cities in white area are included in the regression of eastern China, and the cities in grey area are included in the regression of western China. As a result, in eastern regions, there are 156 observations used for regression, while western are 76. Comparable results of regression models are presented in Table 14. Table 14: Results of eastern and western China Model Model 4 Model 4 Model 4 Variable With all observations With eastern China With western China .067037*** .051921*** .095114*** FDI (.000) (.010) (.000) -.001498 -.6535992* -1.092886** Hotel (0.996) (.093) (0.004) .026640** .0198166 ME (.027) (.134) Omitted .008021*** -.0048531** .006419 PP (.000) (.012) (.117) -.000125*** -.0002766*** -.000052 SD (.005) (.000) (.231) -.001089*** -.0009122** -.001571 MP (.001) (.012) (.175) Source: own elaboration Note: * Significant at 10% level, ** Significant at 5% level, *** Significant at 1% level
It shows that a disappearance of significant impacts from SD and MP in other Chinese cities, and variable ME is omitted because of multicolliearity – mega events were only held in Beijing and Shanghai. It might be explained by less public attention and less tourism prosperity of those cities, thus international tourists would not be disturbed by air quality. While FDI and PP are still significant, they play dominant effect on international tourism demand in the non-hotspot cities. Another reason caused this insignificance of SD and MP might be that other factors among those cities are not caught into this analysis, but since this research is not in depth of statistics, further researches are needed to detect those variables. East vs. West Unequal distribution of wealth was an important reason resulting difference of international tourism between eastern and western China. The border of east and west is drawn according to Figure 2, the cities in white area are included in the regression of eastern China, and the cities in grey area are included in the regression of western China. As a result, in eastern regions, there are 156 observations used for regression, while western are 76. Comparable results of regression models are presented in Table 14. Table 14: Results of eastern and western China Model Variable Model 4 With all observations Model 4 With eastern China Model 4 With western China FDI .067037*** (.000) .051921*** (.010) .095114*** (.000) Hotel -.001498 (0.996) -.6535992* (.093) -1.092886** (0.004) ME .026640** (.027) .0198166 (.134) Omitted PP .008021*** (.000) -.0048531** (.012) .006419 (.117) SD -.000125*** (.005) -.0002766*** (.000) -.000052 (.231) MP -.001089*** (.001) -.0009122** (.012) -.001571 (.175) Source: own elaboration Note: * Significant at 10% level, ** Significant at 5% level, *** Significant at 1% level