The role of sectoral coverage in emission abatement costs: evidence from marginal cost savings

Abstract

Abstract Sectoral coverage that plays a critical role in operationalizing the emission trading scheme (ETS), has gained substantive attention. Despite the insightful views on sectoral coverage from the emission reduction potential or carbon leakage, previous studies overlook the cost-effectiveness of ETS in the sense that the varying marginal contributions of each sector to reducing emission abatement costs (EACs) (which is defined as marginal cost savings, MCSs) remain underexplored. To fill this gap, this paper proposes a costs-oriented approach for sectoral coverage (COASCO), which ranks the sectors by estimating and comparing their MCSs. Taking China’s climate targets by 2030 as an example, we conduct an empirical study that implements the COASCO method to explore the impacts of sectoral coverage on China’s EACs. Our analysis demonstrates that, while coverage extension generally reduces China’s EACs, a small sectoral coverage can already lead to a substantial decline in the national EACs. The results underpin the Pareto principle that covering six sectors (i.e. Electricity production, Metallurgy, Transport and storage, Petroleum and gas, Nonmetal mining) out of 29 can reduce China’s EACs by over 80% compared to covering Electricity production only. Although coverage extension may reduce the differences in EACs between sectors and improve market activation, extending the sectoral coverage probably gives rise to the number of big carbon traders, which thenincreases the risks of market manipulation. As a result, covering those six sectors can reach a balance between ETS market activation and risks. By providing a generalized and systematic framework for determining the sectoral coverage, this study makes it possible to minimize the total EACs associated with any sectoral coverages, thus assisting policymakers in fulfilling China’s latest ambitious goals of reaching carbon peaking by 2030 and carbon neutrality by 2060 in a cost-effective manner.