首页|浙江省县域绿色金融发展水平变化特征、影响因素与情景预测

浙江省县域绿色金融发展水平变化特征、影响因素与情景预测

扫码查看
文章以浙江省为研究区域,构建县域绿色金融发展水平评价指标体系,揭示了2007-2022年浙江省县域绿色金融发展水平的变化特征;运用空间计量模型探究影响县域绿色金融发展水平变化的关键因素,并利用系统动力学(SD)模型对县域绿色金融发展水平进行了仿真预测.结果表明:①浙江省县域绿色金融发展水平不断上升,县域之间存在显著空间差异.②县域绿色金融发展水平由以低值区为主转变为以高值区为主,方向性特征明显,分布范围整体上呈现收缩趋势.③科技创新水平、存款水平、产业结构升级和环境污染影响方向为正,经济发展水平以及能耗水平则有显著负向影响.④当浙江省保持协同发展型路径时,2030和2035年县域绿色金融发展能力得分最高,分别为75.46及78.80;而在稳定现状型路径下的县域绿色金融发展能力得分最低,分别为74.78及77.04.
Change Characteristics of the Green Finance Development Level and Its Influencing Factors and Scenario Prediction in Counties of Zhejiang Province
Taking Zhejiang Province as the research area,this paper establishes an evaluation index system of the green finance development level at county level,and reveals the evolution characteristics of green finance development from 2007 to 2022.It uses spatial econometric models to identify the key factors influencing the green finance development level in counties of Zhejiang Province,and system dynamics(SD)models for simulation and prediction.It's found that:1)The green finance development level has been consistently rising in counties of Zhejiang Province,with notable spatial disparities among them.2)The green finance development level has shifted from primarily low-value areas to predominantly high-value areas,exhibiting clear directional characteristics and a general trend of shrinking distribution range.3)Factors such as technological innovation,deposit level,industrial structure upgrading and environmental pollution exhibit a positive impact,economic development and energy consumption level have a significant negative effect.4)When Zhejiang Province maintains a collaborative development path,the county-level green finance development capacity achieves the highest scores which are 75.46 in 2030 and 78.80 in 2035,respectively.Conversely,under the stable status quo path,the county-level green finance development capability achieves the lowest scores which are 74.78 in 2030 and 77.04 in 2035,respectively.

ecological civilizationgreen financegreen credit and insurancetechnological innovationscenario predictionSD model

孔凡斌、罗锐峰、徐彩瑶

展开 >

南京林业大学 经济管理学院,中国 江苏 南京 210037

南京林业大学 数字林业与绿色发展研究院,中国 江苏 南京 210037

浙江农林大学 经济管理学院,中国 浙江 杭州 311300

浙江农林大学 浙江省乡村振兴研究院,中国 浙江 杭州 311300

展开 >

生态文明 绿色金融 绿色信贷与保险 科技创新 情景预测 SD模型

2024

经济地理
中国地理学会 湖南省经济地理研究所

经济地理

CSTPCDCSSCICHSSCD北大核心
影响因子:2.575
ISSN:1000-8462
年,卷(期):2024.44(11)