An emission trading system (ETS) is a powerful emission reduction tool for achieving low-carbon economic development in the world. Focusing on the industrial subsectors, this paper comprehensively analyzes the environmental and economic effects of the pilot ETS in China from the perspectives of economic development, technological optimization, and innovation-driven development by using the propensity score matching–difference in differences (PSM-DID) model based on 2005–2017 provincial panel data. This paper compensates for the limitations of existing studies on the effects of ETS on different subsectors; furthermore, the triple difference model (DDD) model is used to discuss the impacts of differences in environmental responsibility and economic potential among subsectors on policy effects. The empirical results show that: (1) The pilot ETS produces a 14.5% carbon reduction effect on the covered subsectors while reducing GDP by 4.8% without achieving a low-carbon economy. Thus, production decline is the main reason for carbon emission reductions. (2) Economic development factors have significant positive impacts on carbon emissions, while technological optimization and innovation-driven development are key factors for achieving reductions in carbon emissions. (3) The pilot ETS produces a 60.1% carbon emission inhibition effect and 23.2% GDP inhibition effect on the subsectors with greater environmental responsibility. Therefore, the Chinese government should fully simulate the impact of technological innovation and utilize resource endowment differences in the environmental and economic aspects of different sectors to achieve low-carbon economic development.

A carbon emission trading system (ETS) is an effective market mechanism for promoting the reduction of global greenhouse gas emissions and achieving sustainable development between the economy and the environment. To analyze the emissions reduction effect and economic effect of China’s ETS and further discuss the mechanisms of economic development differences and industrial development differences on the final effect of the policy, this study adopts the propensity score matching-difference in differences method and triple difference method. The empirical results show the following: (1) The ETS can simultaneously achieve both the emissions reduction effect and economic effect when key control variables are included. (2) The population, carbon emissions intensity and per capita GDP have significant positive impacts on carbon emissions; the environmental pollution control intensity, research structure, and research intensity have negative impacts on carbon emissions; and the capita stock, employment, and energy consumption have significant positive economic effects. (3) The ETS has a stronger inhibitory effect on the provinces with higher levels of economic and service development compared to the provinces with lower levels of economic and service development. In contrast, the policy has a weaker inhibitory effect on provinces with higher levels of industrial and construction development compared with the lower level provinces.

Air pollution, particularly SO₂ emission, has become a global problem, seriously threatening the sustainable development and health of mankind. Based on the panel data of 248 prefecture-level cities in China during 2003–2018, this study used the Propensity Score Matching-Difference in Difference (PSM-DID) method within the counterfactual framework to evaluate the treatment effect of the policy made by the National Resource-Based Economic Transformation Comprehensive Supporting Reform Pilot Zone (CRZ) on sulfur dioxide (SO₂) emissions. The results show the following. (1) The benchmark regression results demonstrate that the CRZ policy has significantly decreased per capita SO₂ emissions (PCSO₂) and SO₂ emissions per unit of GDP (PGSO₂) in the pilot zone, and the placebo test indicates that the evaluation of the policy effect is robust. (2) The dynamic effect test indicates that there is a lag in the effect of the CRZ policy on reducing SO₂ emissions. The policy effect of the CRZ policy on PCSO₂ and PGSO₂ was not obvious in the first stage (2011–2015), the CRZ policy significantly reduced the PCSO₂ and PGSO₂ in the second stage of policy implementation (2016 and beyond), and the reduction effect of CRZ policy on SO₂ emissions is increasing over time. (3) The mechanism analysis shows that optimizing industrial structure, increasing human capital, strengthening technological innovation, and expanding opening to the outside world are the main ways for the CRZ policy to reduce SO₂ emissions. The study will help promote SO₂ emissions reduction in Shanxi Province, providing a reference for the transformation and development of other resource-based cities in China and the world and contributing to accelerating the achievement of regional emission reduction targets and sustainable development.

Based on panel data on 248 prefecture-level cities in China from 2003 to 2018, this study first estimates the treatment effect of the Shanxi Comprehensive Reform Area policy on PM_2.5 concentrations using a PSM-DID method within the counterfactual framework. The average treatment effect shows that contrary to the naive before-after analysis, on average, the Shanxi Comprehensive Reform Area policy significantly increased the PM_2.5 concentrations of prefecture-level cities in Shanxi Province by 0.211% annually, and the place-based placebo test shows that the treatment effect obtained above is robust. Second, the dynamic treatment effects show a continuous decrease in incremental effects during 2011–2018, gradually decreasing from a significant positive increment during 2011–2015 to a zero or even a negative increment during 2016–2018, indicating that the Shanxi Comprehensive Reform Area policy gradually increased in environmental friendliness. Third, the mediating effects estimated by the causal steps procedure show that the Shanxi Comprehensive Reform Area policy influenced PM_2.5 concentrations by increasing the intensity of resource exploitation and decreasing the intensity of environmental regulations, but the capacity of scientific and technological innovations had no mediating effect on the relationship between the policy and PM_2.5 concentrations. Therefore, the government should further reduce the intensity of resource exploitation, strengthen the intensity of environmental regulations, and promote environmentally focused scientific and technological innovations to reduce PM_2.5 concentrations in Shanxi Province.

Based on panel data on 248 prefecture-level cities in China from 2003 to 2018, this study first estimates the treatment effect of the Shanxi Comprehensive Reform Area policy on PM _2.5 concentrations using a PSM-DID method. The empirical results show that, on average, the Shanxi Comprehensive Reform Area policy significantly increased the PM _2.5 concentrations of prefecture-level cities in Shanxi Province by 0.211% annually, and the place-based placebo test shows that the treatment effect obtained above is robust. Second, the dynamic effects show a continuous decrease in incremental effects during 2011–2018, gradually decreasing from a significant positive increment during 2011–2015 to a zero or even a negative increment during 2016–2018, indicating that the Shanxi Comprehensive Reform Area policy gradually increased in environmental friendliness. Third, the influencing mechanisms show that the Shanxi Comprehensive Reform Area policy influenced PM _2.5 concentrations by increasing the intensity of resource exploitation and decreasing the intensity of environmental regulations, but the capacity of scientific and technological innovations had no mediating effect on the relationship between the policy and PM _2.5 concentrations. Therefore, the government should further reduce the intensity of resource exploitation, strengthen the intensity of environmental regulations, and promote environmentally focused scientific and technological innovations to reduce PM _2.5 concentrations in Shanxi Province.