School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.
Beijing Laboratory of National Economic Security Early-Warning Engineering, Beijing Jiaotong University, Beijing 100044, China.
Int J Environ Res Public Health. 2023 Mar 6;20(5):4658. doi: 10.3390/ijerph20054658.
Green credit is a vital instrument for promoting low-carbon transition. However, designing a reasonable development pattern and efficiently allocating limited resources has become a challenge for developing countries. The Yellow River Basin, a critical component of the low-carbon transition in China, is still in the early stages of green credit development. Most cities in this region lack green credit development plans that suit their economic conditions. This study examined the impact of green credit on carbon emission intensity and utilized a k-means clustering algorithm to categorize the green credit development patterns of 98 prefecture-level cities in the Yellow River Basin based on four static indicators and four dynamic indicators. Regression results based on city-level panel data from 2006 to 2020 demonstrated that the development of green credit in the Yellow River Basin can effectively reduce local carbon emission intensity and promote low-carbon transition. We classified the development patterns of green credit in the Yellow River Basin into five types: mechanism construction, product innovation, consumer business expansion, rapid growth, and stable growth. Moreover, we have put forward specific policy suggestions for cities with different development patterns. The design process of this green credit development patterns is characterized by its ability to achieve meaningful outcomes while relying on fewer numbers of indicators. Furthermore, this approach boasts a significant degree of explanatory power, which may assist policy makers in comprehending the underlying mechanisms of regional low-carbon governance. Our findings provide a new perspective for the study of sustainable finance.
绿色信贷是推动低碳转型的重要工具。然而，为发展中国家设计合理的发展模式和有效配置有限的资源已成为一项挑战。黄河流域作为中国低碳转型的关键组成部分，其绿色信贷发展仍处于初级阶段。该地区大多数城市缺乏适合其经济条件的绿色信贷发展规划。本研究考察了绿色信贷对碳排放强度的影响，并利用 k-均值聚类算法，根据四个静态指标和四个动态指标，对黄河流域 98 个地级市的绿色信贷发展模式进行了分类。基于 2006 年至 2020 年的城市层面面板数据的回归结果表明，黄河流域绿色信贷的发展可以有效降低当地的碳排放强度，促进低碳转型。我们将黄河流域的绿色信贷发展模式分为五种类型：机制建设、产品创新、消费业务扩张、快速增长和稳定增长。此外，我们还针对不同发展模式的城市提出了具体的政策建议。这种绿色信贷发展模式的设计过程具有以下特点：在依赖较少指标的情况下，实现有意义的结果；同时具有很强的解释能力，这可能有助于政策制定者理解区域低碳治理的内在机制。我们的研究结果为可持续金融的研究提供了一个新的视角。
