A Method for Allocation of Carbon Emission Quotas to Provincial-Level Industries in China Based on DEA

Abstract

At present, China implements a quota-based trading mechanism to achieve carbon emission reduction, in which the allocation of carbon emission quotas among different provinces is short of considering the influence of unbalanced provincial development. Heterogeneity among the provincial-level three major industries, namely, agriculture, manufacturing and mining, and service industries, is a case in point. To address this insufficiency, this paper proposes a novel parallel data envelopment analysis (DEA) based method for carbon emission quota allocation. The method models each province as a decision-making unit (DMU) and the provincial-level three major industries as parallel sub-decision-making units (SDMUs). A distinguished feature of the method is that it makes explicit tradeoffs between efficiency and equality considerations for policymakers in allocating the carbon quotas among three heterogeneous provincial-level major industries. The empirical results show that the proposed method effectively improves the overall provincial gross domestic product (GDP) potentials through the reallocation of carbon quotas among industries while the equality level is not worse off. This work is helpful for policymakers to achieve a long-term emission reduction target and provides suggestions for improving the initial allocation mechanism of a national carbon trading market.