*4.1. Selection of Data Sources and Variables*

This study evaluates the impact of pollution control in 31 provinces and municipalities of China on China's industrial production efficiency from 2013 to 2017. The publicly quantifiable data are obtained from the statistical yearbook of China's National Bureau of Statistics (National Bureau of Statistics of China: http://www.stats.gov.cn/tjsj/ndsj/, accessed on 1 February 2022) from 2013 to 2017, and the efficiency is analyzed through open and objective data. The relevant contents of the selected variables are as follows:

Labor force: including manufacturing, power, heat, gas and water production and supply, and the number of employed persons in urban units. Employed persons refer to persons aged 16 and above who engage in certain social work and obtain labor remuneration or business income. Unit: 10,000 persons.

Total capital formation: refers to the total value of fixed assets acquired by permanent residents less fixed assets disposed of in a certain period of time. Fixed assets are assets produced through production activities with a service life of more than one year and a unit value of more than the specified standard, excluding natural assets. It can be divided into total tangible fixed capital formation and total intangible fixed capital formation. Unit: 100 million yuan.

Energy consumption: electricity consumption by region. Unit: 100 million kWh.

Industrial water consumption: industrial water consumption by region. Unit: 10,000 tons. Wastewater treatment fund: the completion of wastewater treatment investment generated by industrial pollution. Unit: 10,000 yuan.

Waste gas treatment funds: the completion of waste gas treatment investment generated by industrial pollution. Unit: 10,000 yuan.

Total wastewater discharge: total wastewater discharge by region. Unit: 10,000 tons. Lead in wastewater: the discharge of main pollutants in wastewater. Unit: kg.

SO2: emission of sulfur dioxide in waste gas by region. Unit: 10,000 tons.

Smoke and dust: emission of smoke (powder) dust in waste gas by region. Unit: 10,000 tons.

Industrial output value: regional industrial output value. Unit: 100 million yuan.

## *4.2. Input and Output Variables Statistical Analysis*

As shown in the narrative analysis of various variables from 2013 to 2017 (Table 1), the average part shows a growth trend in labor force, total capital formation, energy consumption, waste treatment funds and industrial output value. The amount of industrial wastewater, wastewater treatment funds, lead, SO2, smoke and dust in wastewater show a downward trend. The total amount of wastewater discharge has little change. In the largest part, labor force, total capital formation, energy consumption, waste gas treatment funds and industrial output value show a growth trend. Lead, SO2, smoke and dust in wastewater show a downward trend, and other variables change little. In the minimum part, total capital formation, energy consumption, total wastewater discharge and industrial output value show a growth trend, the wastewater treatment funds and waste gas treatment funds show a downward trend, and the other variables have little change.


**Table 1.** Input–output variables from 2013 to 2017 statistical analysis.

#### *4.3. Empirical Results*

In this study, 31 provinces and municipalities in China were divided into two groups: the Yellow River Basin and the Non-Yellow River Basin. The DDF method was used to evaluate the difference in industrial production efficiency between the two groups. The common boundary efficiency and group boundary efficiency of the two groups are evaluated by the TGR method to find the technology gap ratio. The results and analysis are as follows.

(1) Industrial production efficiency of DDF in the Yellow River and Non-Yellow River Basins

The empirical results show that (as shown in Figure 4 and Appendix A) the best average value of the total efficiency of the Yellow River and Non-Yellow River basins is 1 in 17 provinces and cities, including Beijing, Tianjin and Hebei, of which only Shandong and Sichuan are located in the Yellow River Basin, and a total of 15 provinces and cities are located in the Non-Yellow River Basin. The average total efficiency of the Non-Yellow River Basin is 0.9793, and the three worst-performing regions are Yunnan (0.7804), Xinjiang (0.9188) and Guizhou (0.9257). The average value of the total efficiency of the Yellow River Basin is 0.9688, which is slightly lower than that of the Non-Yellow River Basin. The three regions with the worst performance of the total efficiency are Gansu (0.8604), Shanxi (0.9417) and Ningxia (0.9592). We further explore the period efficiency of each year in the Non-Yellow River Basin, with the best performance in 2015 and 2016, the efficiency value is 0.982, the worst performance is 0.9741 in 2013, of which Yunnan (0.7197) has the worst efficiency performance. In the part of efficiency in each year of the Yellow River Basin, only 0.9863 performed best in 2013, slightly higher than 0.9741 in the Non-Yellow River Basin. In the next four years, the overall efficiency performance lagged behind the Non-Yellow River Basin. The overall efficiency performance was the worst in 2015 (0.9561), of which Gansu (0.7593) performed the worst in 2015.

**Figure 4.** Efficiency of DDF in the Yellow River and Non-Yellow River Basins from 2013 to 2017.

This study further uses the Wilcoxon rank sum test to make α = 0.05; the confidence interval is 95%, and the result shows that z = −3.517, which indicates that there are regional differences in DDF efficiency between the Yellow River Basin and the Non-Yellow River Basin, and the efficiency value of the Non-Yellow River Basin is better than that of the Yellow River Basin.

(2) Analysis of TGR technology gap ratio between the Yellow River and Non-Yellow River Basins

We use TGR to objectively measure the level of industrial production efficiency. When the TGR value is closer to 1, it means that the industrial production efficiency is relatively high and the efficiency is better. On the contrary, the lower or closer the TGR value is to 0, the more it indicates that there is still room for significant improvement. According to the TGR of 31 provinces and cities in China from 2013 to 2017 (Figure 5 and Appendix B), the TGR values of 22 provinces and cities in the Non-Yellow River Basin are less than 1, indicating that the technical level has not reached the technical level on the common boundary, which can improve the efficiency of industrial production and pollution control. The average value of TGR is 0.5234, and a total of 12 regions are higher than the average value. The better-performing regions are Tibet (0.9876), Hainan (0.8965) and Liaoning (0.8675), the three worst-performing regions are Hubei (0.1413), Guangxi (0.1321) and Hunan (0.1156). The TGR values of nine provinces, cities and administrative regions in the Yellow River Basin are also less than 1. The average TGR value is 0.3825, which is lower than the average TGR value of the Non-Yellow River Basin by 0.5234. In total, the four regions are higher than the average value. The better-performing regions are Ningxia (0.7545), Qinghai (0.5708) and Shandong (0.5411), and the three worst-performing regions are Sichuan (0.1965), Shaanxi (0.1822) and Inner Mongolia (0.1152).

**Figure 5.** TGR analysis of the Yellow River and Non-Yellow River basins from 2013 to 2017.

Based on the combined analysis of DDF efficiency and TGR results of the Yellow River and Non-Yellow River basins from 2003 to 2007 (Figure 6), the overall efficiency performance of the two regions has little change during the study period. Among them, the Yellow River Basin was only slightly better than the Non-Yellow River basin (0.9863) in 2013 (0.9741), but in the TGR part, the performance of the two regions still has room for significant improvement. Among them, the TGR of the Yellow River Basin is significantly behind the Non-Yellow River Basin. Through reasonable human and capital allocation, we can implement the use of pollution prevention and control funds, and improve the technical level of industrial production to improve pollutant emission and increase output value, to improve the overall efficiency performance.

**Figure 6.** Analysis of DDF efficiency and TGR in the Yellow River and Non-Yellow River basins from 2013 to 2017.
