Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model

Abstract

Firstly, we introduce the "Zero Sum Gains" game theory into the SBM (Slacks-based Measure) model, and establish the ZSG-SBM model. Then, set up 4 development scenarios for the China's economic system in "13·5" (The Chinese government formulates a Five-Year Planning for national economic and social development every five years, "13·5" means 2016 to 2020.) period through two dimensions as economic growth and energy consumption structure, and make the efficient allocation in provincial level of carbon reduction target by using the above ZSG-SBM model based on the China's overall carbon reduction constraint (18%) which is set in "13·5" planning. Finally, we analyze the provincial development path of low-carbon economy by comparing the economic development status with the allocated result of carbon reduction target. Results show that: After the ZSG-SBM model being applied to the efficiency allocation of carbon emission, the input and output indicators of the 30 provinces realize the effective allocation, and the carbon emission efficiency reaches the efficiency frontier. The equity-oriented administrative allocation scheme of government will bring about efficiency loss in a certain degree, and the efficiency allocation scheme, based on the ZSG-SBM model, fits better with the long-term development requirement of low-carbon economy. On the basis of carbon intensity constraint, the re-constraint of energy intensity will force the provinces to optimize their energy consumption structure, thereby enhancing the overall carbon emission efficiency of China. Sixteen provinces' allocation results of carbon reduction target are above China's average (18%) in "13·5" period, all the provinces should select appropriate development path of low-carbon economy according to the status of their resource endowment, economic level, industrial structure and energy consumption structure.

Enlarging Regional Disparities in Energy Intensity within China

“…According to the 13th FYP (2016–2020), carbon emission control for different provinces will still be categorized, which may lead to the gaps in energy intensity. The intention of categorized constraint is to promote economic growth and optimize resource allocation efficiency (Guo et al, 2017). However, as our study shows, this may also result in a rigescent energy consumption structure and heavy industry agglomeration in regions with less advanced green technologies, thus leading to disparity and polarization in energy intensity and resulting in an overall obstructive effect on energy saving.…”

The co-benefit of emission reduction efficiency of energy, CO2, and atmospheric pollutants in China under the carbon neutrality target

“…Researches on carbon emissions and carbon emission reduction in China are mainly based on national and provincial administrative regions. For example, Guo et al, (2017), Fang et al, (2019), Cheng et al, (2020), and Chen et al, (2020) conducted empirical studies on carbon emission reduction efficiency and its influencing factors in 30 provincial administrative regions in China. Wanshui Wu et al, (2013), Shijin Wang et al, (2018), and Yang et al, (2020) presented comparative studies in a particular province or city or between provinces in China.…”

The contemporary value, basic framework and realization mechanism of the rule of law in rural revitalization

“…DEA is the abbreviation of Data Envelopment Analysis (DEA), which can calculate the comprehensive analysis results of each decision-making unit without converting each input and output indicator into the same unit [26]. In view of the applicability of the DEA method to the evaluation of environmental governance efficiency, this paper also chooses this method as the basic method of this study.…”