## 5 Conclusions and Policy Implications  
Starting from 2013 to 2014, China formally launched an ETS pilot project in the seven provinces and cities of Beijing, Tianjin, Shanghai, Chongqing, Guangdong, Hubei, and Shenzhen, and it planned to gradually expand the pilot to a national ETS in 2017, which would replace the EU ETS as the largest ETS in the world. Therefore, studying the policy effects of the ETS pilot will provide important enlightenment on the establishment of the national ETS [15]. This study selected 30 provincial panel data from 2005 to 2017 and used the PSM-DID model to analyze the policy effect of the ETS pilot. Then, the DDD model was introduced to further study the impact of the heterogeneity of the economic and industrial differences on the policy. The empirical conclusions can be summarized as follows:  
1. China's ETS pilot policy has achieved the \"Porter effect,\" but due to the incomplete mechanism and short establishment time, it is necessary to add key control variables to improve the robustness of the results. The study finds that the policy increases GDP by 6.4% while reducing carbon emissions by 10.0%, and it can be found from the dynamic effect table that the carbon reduction effect and economic effect remain stable over a certain range. 2. The analysis of the mechanism of the effect of a single control variable shows that the population, carbon intensity, and per capita GDP have major positive effects on carbon emissions. However, the environmental pollution control intensity, research structure and research intensity have negative effects. Finally, the capital stock, employment and energy consumption have significant positive economic effects. 3. After adding dummy variables for the economic and industrial differences, the coefficient of the interaction term in the DID model is found to be significant, which indicates that it is necessary to introduce the DDD model to further analyze the impact of heterogeneity on the final effect of the policy. Empirical analysis shows that compared with the provinces with lower levels of economic development, the ETS pilot policy has a stronger inhibitory effect on the carbon emissions in the provinces with higher levels of economic development. Compared with the provinces with lower levels of industrial and construction development, the pilot policy has a weaker inhibitory effect on the carbon emissions in the provinces with higher levels of industrial and construction development. Finally, compared with the provinces with lower levels of service development, the pilot policy has a stronger inhibitory effect on the carbon emissions in provinces with higher levels of service development. The levels of economic and industrial development have no significant impacts on the economic effect of the policy. 4. In recent years, the reductions of the industrialization rate, carbon intensity, and energy structure and the increases of the environmental regulation intensity, research structure, and research intensity in the pilot provinces have generated emissions reduction effects. The economic effect comes from the increased capital, employment, and energy consumption. Compared with the provinces with lower levels of economic and industrial development, the population, carbon intensity and per capita GDP of the provinces with high levels of development have positive effects on carbon emissions, while the environmental pollution control intensity, research structure and research intensity have negative effects on carbon emissions. The level of economic and industrial development has no significant impacts on the economic effect of the policy. As a policy tool to control greenhouse gas emissions, according to the total quota setting and allocation scheme, the baseline method and the historical intensity method can be used as the standards to reduce carbon emissions by forcing enterprises to save energy and enhance efficiency, thereby improving the output value of their products and achieving energy conservation and emission reduction.