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绿色金融与绿色创新效率耦合协调度的时空分异研究——以中国为例。

Spatial-temporal differentiation of coupling coordination degree for green finance and green innovation efficiency: a case study in China.

机构信息

Business School, Hohai University, Nanjing, 210098, China.

Low Carbon Economy Research Institute, Hohai University, Nanjing, 210098, China.

出版信息

Environ Sci Pollut Res Int. 2023 Jun;30(27):70621-70635. doi: 10.1007/s11356-023-27333-2. Epub 2023 May 8.

Abstract

Continued investment in finance and innovation is beneficial to economic development, and the joining of green system can accelerate the process of economic recovery from environmental distress. To better enhance the relationship of green finance and green innovation, it is vital to demonstrate the synergy between the two thoroughly. Thirty provinces in China are selected to examine the coupling coordination relationship between the two, specifically testing the spatial aggregation and evolutionary differences in the coupling coordination by adopting the coupling coordination degree (CCD) model, spatial autocorrelation, and kernel density estimation. Conclusions of the paper show that green finance is calculated by the EW-TOPSIS method, and the overall score of provinces is low. Using super-SBM model to evaluate green innovation, the uneven distribution of efficiency is obvious, although it is gradually increasing. The CCD in most provinces is in low-level or basic coordination, with significant regional heterogeneity. The global Moran's index becomes gradually evident with time. The local Moran scatter diagram presents a downward trend from east to west, but with more L-L aggregation provinces emerging in 2020. The center of the national kernel density curve gradually shifts to the right, indicating that the national overall synergy level is improving. Deepening the understanding of the empirical results facilitates the formulation of reasonable policies that fit the four major regions.

摘要

持续的金融和创新投资有利于经济发展,绿色系统的加入可以加速经济从环境困境中复苏的进程。为了更好地加强绿色金融和绿色创新之间的关系,彻底展示两者之间的协同作用至关重要。本研究选取了中国的 30 个省份,通过采用耦合协调度(CCD)模型、空间自相关和核密度估计来检验两者之间的耦合协调关系的空间集聚和演化差异。研究结果表明,绿色金融是通过 EW-TOPSIS 方法计算的,各省的总体得分较低。采用超 SBM 模型评估绿色创新,效率的分布不均明显,尽管呈逐渐增加的趋势。大多数省份的 CCD 处于低水平或基本协调状态,具有明显的区域异质性。全局 Moran's 指数随着时间的推移变得越来越明显。局部 Moran 散点图呈从东向西下降的趋势,但 2020 年出现了更多的 L-L 集聚省份。国家核密度曲线的中心逐渐向右移动,表明全国整体协同水平在提高。深化对实证结果的理解有助于制定适合四大区域的合理政策。

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