Analysis of driving factors and allocation of carbon emission allowance in China

Abstract China's “13th Five-Year Plan” proposes that carbon emissions per unit of GDP be reduced by 18% from their 2015 levels. In this context, the present study uses grey relational analysis to explore the correlation degree between carbon emissions and economic, energy and population effects. This study also quantitatively analyzes the contribution rate of each driving factor by using logarithmic mean Divisia index. Results show that per capita GDP and energy consumption per unit of GDP are the key factors that lead to changes in carbon emissions. Then, the input-oriented BCC model in data envelopment analysis (DEA) is used to evaluate the efficiency of the primary carbon emission allowance allocation scheme in the “13th Five-Year Plan”. The results show that the average score of technical efficiencies is only 0.7409. Finally, the zero-sum-gains DEA model is used to adjust and optimize the scheme under the premise of constant total carbon emissions. Thereafter, a scientific carbon-emission allowance allocation scheme is proposed. We verified that the optimal scheme can ensure the compatibility of the carbon emission allowances of provincial-level administrative regions with their economy, energy, and population from the perspective of efficiency.