## 5 Empirical Analysis
### Analysis of the Results
The total amount of carbon quotas to be allocated is higher than the total amount of carbon emissions in 2019, which is the main reason for the increases in carbon quotas for industries in the majority of regions in Figure 3. Among them, the carbon before and after the allocation of the three major industries in Jiangsu, Hainan, and Shaanxi do not change; the ratio \((R_{j}^{rp}/R_{j}^{p})\) of the three major industries in Zhejiang and Gansu is greater than 1 after allocation. Put differently, they have obtained more carbon quotas and occupy a favorable position in the carbon trading market. The post-allocation ratios \((R_{j}^{rp}/R_{j}^{p})\) of the remaining regions show a great variation. For example, the primary industries in Hubei and Yunnan need to reduce carbon emissions, and the secondary and tertiary industries need to increase carbon emissions to reach their optimal GDP potentials. This implies that the differences among industries have an effect on the outcome of the allocation process, which is anticipated. It is worth noting that regional industrial carbon quota changes can be expressed in absolute and relative terms. When the initial carbon emissions quantity is large, even a small relative change to the proportion of carbon emissions can lead to a larger absolute change in quantity. In that case, it is a great challenge to implement emission reductions for regional industries. To address this issue, regional industries that are to receive fewer carbon quotas can first consider coordinating industries to better use quotas within the region; if their carbon quotas have dropped significantly from the pre-allocation level, and they fail to meet the emission reduction targets through internal coordination, they may obtain more carbon quotas through carbon trading mechanisms. For example, the increase in carbon quotas for the secondary industry in Shanxi is much smaller than the reductions in the primary and tertiary industries, and the reductions in carbon quotas for the secondary industry in Chongqing is smaller than the increase for the tertiary industry. The provinces with sufficient carbon emission quotas, such as Hubei, Sichuan, and Yunnan, can profit from carbon trading. Since regional differences are prominent in China, many policies need to be specified at the regional level. The Development Research Center of the State Council divided China into eight comprehensive economic zones based on resources, regional development, and other factors (as shown in Table A2[23]). Below we analyze the regional carbon quota allocation results based on this classification. The specific quota results are shown in Table 5 and Figure 4. From Table 5, it can be found that the regions with the largest total carbon quotas before and after allocation are both northern coastal regions, and the smallest total carbon quotas are both northwestern regions. In addition, the allocation of industrial carbon quotas has the feature that the primary industry and the secondary industry are respectively allocated the lowest amount of quotas and the highest amounts of quotas in all regions. Among the primary and secondary industries, the northern coastal region obtains the highest amount of carbon quotas. This is because the Northern coastal has two large industrial provinces, Shandong and Hebei. Finally, based on the breakdown of the tertiary industry quotas, it can be seen that the eastern coastal region gets the highest amount of carbon quotas, which is due to the rapid commercial and financial development of Shanghai, Jiangsu, and Zhejiang, which have a large share of the national GDP. Figure 5 visualizes the changes in the proportion of each regional industry before and after the allocation. From the perspective of the nation, the carbon quotas of the southern coastal, eastern coastal, Middle Yangtze River, northwestern, and southwestern regions have significantly increased, while the carbon quotas of the northern coastal, Middle Yellow River, and northeastern regions have decreased.