# Dynamic Evaluation and Internal Driving Factors of Water Resources Green Efficiency in China
## 4 Result and Discussion
### Decomposition of Driving Factors for Water Resources Green Efficiency
#### 4.2.2 Spatial Differentiation Characteristics of Water Resources Green Efficiency Decomposition  
(1) Spatial difference analysis of efficiency decomposition at national level  
The standard deviation and coefficient of variation of the efficiency decomposition index were calculated for each province from 2000 to 2016, as shown from Figures 7-10. The mean variance indicates the absolute difference between provinces, and the coefficient of variation reflects the relative difference between provinces. It can be seen from the figures that the trends of absolute and relative differences in the water resources green efficiency between provinces since 2000 were the same or similar. From the trend of the difference curve between provinces, the trend line of the difference in PEC between provinces fluctuated first before increasing and then decreasing (Figure 7). The difference in SEC between provinces was small (Figure 8), and the difference in STC was increasing (Figure 10). The difference in PTC fluctuated first and then decreasing steadily (Figure 9). All four indicators showed that the ability of Chinese provinces to master frontier technology gradually decreased, and the scale effect in different provinces was quite different. Therefore, at the national level, it is necessary to further improve the efficiency and scale effect of technological change to realize coordinated development among provinces and the spatial balance of water requirements. Figure 6: Changes in the components of water resources green efficiency in the western region of China during the study period 2000–2016 (PEC = pure technical efficiency change, SEC = scale efficiency change, PTC = pure technology change and STC = scale technology change). Figure 8: Changes in average variance and coefficient of variation of SEC. Figure 7: Changes in average variance and coefficient of variation of PEC. (2) Spatial difference analysis of efficiency decomposition at provincial level  
As can be seen from Table 5, only Tianjin, Qinghai, Gansu and Guizhou among the 30 provinces in the country have not improved in PTC. The proportions of provinces in which PEC, SEC, and STC indices improved were 40%, 46.67%, and 60%, respectively. This conclusion is consistent with the characteristics of the time change of each index. Figure 10: Changes in average variance and the coefficient of variation of STC. Figure 9: Changes in average variance and the coefficient of variation of PTC. By further analysis of Figure 11, it is found that the five provinces with the largest increase and decrease in PEC in the study period were mainly located in central and western provinces, while the central and eastern coastal provinces where PEC remained unchanged account for 57.14%. The five provinces with the largest increase and decrease in SEC were also mainly located in the central and western provinces. Specifically, it mainly includes Sichuan and Yunnan in the west, Hubei, Anhui, and Jilin in the central, and Jiangsu in the east. While the scale effect of technological changes improved in most of China. These results may be due to the fact that the eastern coastal provinces early paid attention to the innovation of environmental protection technologies and equipment. However, there is still a certain gap between the technical efficiency of the developed eastern provinces and that of the western developed countries, leading to low-level repetitive investment and a decline in the scale effect of technological efficiency, which leads to low-level repeated investment. This is also an urgent problem to be solved in the process of realizing the green development of social economy in the future. Most of the central provinces are home to (mainly) heavy industries, which are slow to respond to the innovation of pure technical efficiency, which has led to a decline in the PEC. However, some central provinces have seized the policy dividend of \"the rise of central China\" to optimize and upgrade their industrial structure and improve pure technical efficiency.