碳排放预测及其对我国金融政策的影响

Predicting Chinas Carbon Emissions and Its Impact on the Financial Policy Based on PCA⁃GRNN

碳排放与金融关系是当下中国面临的重要问题之一,基于《能源统计年鉴》及国家统计局数据,建立PCA模型,采用广义回归神经网络方法,实现我国未来几年碳排放量的预测。研究发现:我国将持续减排,煤炭能源结构占比逐渐减少;2024—2028年碳排放持续上升,2028年增速“由正变负”;2030年碳达峰目标提前完成,清洁能源取代煤炭。面对此现象,我国应该追踪“双碳”目标,建立绿色金融体系,进一步开发清洁能源,调整产业结构,定向绿色融资,坚持“节能减排”。同时,国家金融政策需要持续创新,推动全社会能源结构调整:(1)继续完善绿色金融顶层设计,建立切实可行的激励机制。(2)扩大碳交易市场,加强对碳金融市场的监管。(3)构建绿色供应链金融生态系统。

The relationship between carbon emissions and finance is one of the important issues facing China at present.This article adopts the principle of generalized regression neural network(GRNN)to establish a principal component analysis(PCA)model to achieve future prediction of Chinas carbon emissions based on the Energy Statistical Yearbook and the data from the National Bureau of Statistics.It is discovered:in the future,China will continue to reduce carbon emissions,and the propor⁃tion of coal energy structure will gradually decrease;carbon emissions continue to rise from year 2024 to 2028,and the growth rate in 2028 will change from positive to negative;the carbon peak target will be achieved ahead of 2030,and the clean energy will replace coal.In the face of this phenomenon,our country should track the“double carbon”goal and establish a green fi⁃nance system,support the development and utilization of clean energy and further adjust the industrial structure,innovate finan⁃cial institutions and policy,vector green financing to assist“energy conservation and emission reduction”.To promote the adjust⁃ment of the energy structure of the entire society,Chinas finance should take the following approaches:firstly,continue to im⁃prove the top-level design of green finance and establish a practical incentive mechanism;secondly,expand the carbon trading market and strengthen regulation of the carbon finance market;thirdly,build a green supply chain financial ecosystem.