摘要
“双碳”目标是中国对国际社会做出的庄严承诺,党的二十大为推进“双碳”目标的实现进行了全面部署。基于中国加快发展方式绿色转型的事实,从金融的集聚特征出发,采用2000—2022年全国30个省份的面板数据,通过构建空间杜宾模型,研究金融集聚和碳排放强度之间的关系。结果表明,中国金融集聚与本省和邻省的碳排放强度均存在显著的“倒N型”曲线关系,金融集聚能够通过技术创新和绿色金融发展水平两种机制对碳排放产生影响,这一影响会因资源禀赋不同而产生差异。因此,甘肃、重庆等省市需相应调整金融集聚程度,充分利用金融集聚特性促进碳减排,还要利用好碳排放权交易市场,更好地发挥两大机制的作用,同时警惕“资源诅咒”现象。
The“dual carbon”goal is a solemn commitment made by China to the international community,and the 20th National Congress of the Communist Party of China has made comprehensive arrangements to promote the achievement of this goal.Based on the fact that China is accelerating the green transformation of its development model,this paper starts from the characteristics of financial agglomeration and uses panel data from 30 provinces across the country from 2000 to 2022.By constructing a spatial Durbin model,it studies the relationship between financial agglomeration and carbon emission intensity.The results show that there is a significant“inverted N-shaped”curve relationship between financial agglomeration and carbon emission intensity in both the province itself and neighboring provinces.Financial agglomeration can affect carbon emissions through two mechanisms:technological innovation and the level of green finance development,with variations due to differences in resource endowments.Therefore,to fully leverage the agglomeration characteristics of finance to promote carbon reduction,provinces such as Gansu and Chongqing need to adjust their level of financial agglomeration accordingly,avoiding a situation where the level of financial agglomeration lies between the two inflection points.They should effectively utilize the carbon emission trading market and better harness the roles of the two mechanisms while being vigilant against the“resource curse”phenomenon.
作者
张国庆
吴婧湉
Zhang Guoqing;Wu Jingtian(School of Economics,Lanzhou University,Lanzhou Gansu 730000,China)
出处
《天水师范学院学报》
2024年第4期101-114,共14页
Journal of Tianshui Normal University
关键词
金融集聚
碳减排
空间杜宾模型
空间溢出
financial agglomeration
carbon reduction
spatial durbin model
spatial spillover