Carbon dioxide emission reduction quota allocation study on Chinese provinces based on two-stage Shapley information entropy model

Chinese central government made a commitment to achieve a 40–45% reduction in carbon dioxide (CO2) per unit of GDP by 2020 compared with 2005. This targeted reduction was allocated averagely among all the provinces rather than individually according to different situations of each province. Though some research has been done regarding this rough allocation, two shortcomings in previous studies exist: Firstly, CO2 marginal abatement cost (MAC) has been ignored as one of the CO2 emission reduction allocation indexes. Secondly, either subjective or objective method has been used rather than comprehensively of both subjective and objective method to calculate the weight of each index in the previous studies. In order to fill the gaps, this paper builds a two-stage Shapley information entropy model to allocate CO2 emission reduction quota among the Chinese provinces based on the equity and efficiency principles. Afterward, three CO2 emission reduction quota allocation scenarios have been proposed. The results show that the CO2 MAC is an indispensable index in CO2 emission reduction quota allocation, because its value of CO2 Shapley information entropy is the highest among five indexes. CO2 emission reduction quota of lower-MAC provinces should be allocated larger, while the quota of higher-MAC provinces should be allocated smaller. Therefore, two suggested policies have been proposed: First, differential CO2 emission reduction quota allocation should be proposed. Second, synergetic development should be promoted.