طرح های معاملاتی انتشار آزمایشی
Abstract
1. Introduction
2. Research design and methodology
3. Data
4. Results and discussions
5. Conclusions
Declarations of interest
Acknowledgements
Appendix A. Industrial sub-sectors covered by the pilot ETSs
Appendix B. Test of covariate balancing of PSM-DID
Appendix C. Trends for outcome variables
References
Abstract
Scholars and policy makers put great emphasis on analyzing the mitigation effect of an emissions trading scheme (ETS), while empirical researches on the mitigation effects of China’s pilot ETSs are both thin and with significant limitations. This paper tries to analyze this issue from the perspective of industrial subsectors at the provincial level. We first calculate the carbon emissions of 37 individual industrial subsectors in each of China’s 26 provinces from 2005 to 2015, covering both direct and indirect emissions. Cautiously identifying the industrial sub-sectors covered by China’s pilot ETSs, we explore the causal impact of China’s pilot ETSs on reducing carbon emissions at the initial stage (2013e2015) and analyze the paths of achieved emission reductions, applying a difference-in-difference (DID) model and a combination of DID estimator and propensity score matching technique. Our results yield robust evidence that China’s pilot ETSs have significantly promoted carbon emission reductions of the covered industrial sub-sectors, and this impact has presented an overall enhanced trend according to year-byyear analysis. The results also show that the pilot ETSs have failed to enable covered industrial subsectors to effectively cut carbon intensity and the impact on carbon intensity is not obvious in any of the first three years, and the carbon emission reductions have mainly been achieved through the decreased outputs of industrial sub-sectors. China’s policy makers should tighten the free allowance allocation approaches in order to facilitate low-carbon technology innovations and reduce carbon intensity of industrial sectors.
Introduction
Global climate change, which is caused by excessive anthropogenic greenhouse gas (GHG) emissions, has become a major environmental threat facing humanity. Aiming at curbing GHG emissions and facilitating a transition to low-carbon economy, emissions trading scheme (ETS) has found increasingly wider attention and application globally (ICAP, 2018; Wang et al., 2018a,b). By setting an emissions cap, an ETS encourages cleaner production of enterprises and facilitates emission reductions in a cost-effective way (Wang and Wang, 2015; Singh and Weninger, 2017). A thorough understanding of the emission reduction effect of an ETS serves as the premise for improving the system design. China has become the world’s largest GHG emitter and one of the priority spots for global emission mitigation (Wu, 2010; Liu et al., 2016a; Mi et al., 2017). In 2011, China announced to start its pilot ETSs in two provinces, i.e. Hubei and Guangdong, and five municipalities, i.e. Beijing, Shanghai, Tianjin, Chongqing and Shenzhen. Whether the pilot systems have promoted carbon emission reductions has been of great interest to policy makers and scholars. By definition, a cap-and-trade system will produce emission reductions as long as the cap is set tight enough and regulated emitters are not in gross violation of the scheme (Martin et al., 2016). But even in the case of decreasing emissions cap, the observed decline in emissions cannot be automatically attributed to the ETS, because there could be many other policies or context factors that can promote emission reductions, e.g. mandatory energy efficiency improvement policy. This is especially true for China where many policies that may have carbon mitigation impacts are implemented in parallel (Nam et al., 2014; Duan et al., 2017; Yi et al., 2019).