## 2 Literature Review
It is generally believed that policies can hinder carbon emissions and carbon intensity, but there are different viewpoints on the economic effects of an ETS, and some verify the \"Porter hypothesis\" from different perspectives [30; 31]. The difference in differences (DID) method is often used to evaluate a policy's effect because it can avoid the endogeneity problems of utilizing a policy as an explanatory variable. [PERSON] et al. studied the impact of the carbon intensity constraint policy (CICP) that was proposed by China in 2009 on industry and found that the industrial green production performance (denoted as GPP) in China decreased after a short increase, and the increase of industrial output was the key driving factor for improving the GPP [32]. [PERSON] and [PERSON] studied whether the SO2 trading system pilot could stimulate the \"Porter effect\" in China by controlling regional environmental regulations and other explanatory variables and found that the emissions reduction effect is not sufficient to achieve the \"Porter effect\" [33]. The DDD method adds a dummy variable on the basis of the DID model, which can solve the situation that the common trend hypothesis is not established for the DID; therefore, it is commonly used to solve the related heterogeneity problems. [PERSON] and [PERSON] analyzed the impact of an ETS on the research and development (R&D) innovation of A-share listed companies on the micro level, and found that an ETS policy can improve the R&D investment intensity of the treatment group enterprises; however, it has a significant positive effect only on the innovation investment of large-scale enterprises, and it has no significant effect on the R&D innovation of small-scale enterprises [34]. [PERSON] et al. adopted the panel data of provinces and cities in China to study the effect of an SO2 trading system pilot policy on the total factor productivity (TFP) of enterprises in 2017, and they found that the policy mainly affects TFP by promoting enterprises' technological innovation and optimizing resource allocation efficiency [7]. Furthermore, with respect to the type of enterprise ownership, non-state-owned enterprises were more sensitive to the policy than state-owned enterprises. In addition, from the perspective of environmental enforcement, the higher the environmental enforcement is, the greater the role that enforcement plays in promoting TFP [7]. The above-mentioned literature on the DID model mainly focuses on the overall implementation effect of a certain policy, but it seldom involves issues related to industry differences and enterprise differences. The literature on the DDD model mainly focuses on the heterogeneity of enterprises. It is generally believed that state-owned enterprises and large-scale enterprises have greater advantages than non-state-owned enterprises and small-scale enterprises. However, there is insufficient research on the specific economic differences and industrial differences. On the basis of previous studies, this study systematically analyzes the \"Porter effect\" of China's ETS pilot projects and further discusses the mechanism of the effects of economic development differences and industrial development differences on the current regional ETS.