Gan Chang, Voda Mihai
College of Tourism, Hunan Normal University, Changsha, China.
Geography Department, Dimitrie Cantemir University, Targu Mures, Romania.
Environ Sci Pollut Res Int. 2023 Jan;30(1):640-653. doi: 10.1007/s11356-022-22176-9. Epub 2022 Jul 29.
Against the background of carbon emission reduction, green finance (GF) has become a crucial financial instrument that promotes industrial transformation and low-carbon development. Although some scholars have explored the driving factors affecting the carbon emission intensity (CEI), there is a dearth of literature on the mediation and threshold effects of GF on CEI. Based on the panel data of 30 provinces in China during the period of 2004~2019, this study examined the direct, indirect, and threshold effects of GF on CEI by adopting the panel ordinary least squares, mediation effect, and threshold regression models, respectively. This study draws the following conclusions: GF can directly reduce the CEI. In addition, the scale economics effect and green technology innovation caused by GF have an inhibiting effect on the CEI. However, GF can promote the CEI through structural transformation. What's more, this study interestingly found that the effect of GF reducing CEI is dynamic and nonlinear. These findings can provide references for policy-makers who hope to accelerate carbon emission reduction and achieve low-carbon development.
在碳排放减少的背景下，绿色金融已成为推动产业转型和低碳发展的关键金融工具。尽管一些学者探讨了影响碳排放强度的驱动因素，但关于绿色金融对碳排放强度的中介效应和门槛效应的文献却很匮乏。基于2004年至2019年中国30个省份的面板数据，本研究分别采用面板普通最小二乘法、中介效应模型和门槛回归模型，考察了绿色金融对碳排放强度的直接、间接和门槛效应。本研究得出以下结论：绿色金融能够直接降低碳排放强度。此外，绿色金融所带来的规模经济效应和绿色技术创新对碳排放强度具有抑制作用。然而，绿色金融也会通过结构转型促进碳排放强度上升。更有趣的是，本研究发现绿色金融降低碳排放强度的效应是动态且非线性的。这些研究结果可为希望加速碳排放减少并实现低碳发展的政策制定者提供参考。
