| Title |
Can Green Credit Improve the Innovation of Enterprise Green Technology: Evidence from 271 Cities in China |
| ID_Doc |
30228 |
| Authors |
Mi, KA; Cui, ZT; Zhu, XY; Zhuang, RL |
| Title |
Can Green Credit Improve the Innovation of Enterprise Green Technology: Evidence from 271 Cities in China |
| Year |
2024 |
| Published |
Systems, 12, 2 |
| DOI |
10.3390/systems12020063 |
| Abstract |
With the promotion of the "carbon neutrality" and "carbon peak" initiatives, green credit plays an important role in helping enterprises to change their high-pollution, high-energy-consumption production methods and establishing a sound green, low-carbon, and circular economic system. This study used spatial correlation analysis and a fixed effects SDM model to examine the spatiotemporal and causal relationship between green credit levels and enterprise green technology innovation in 271 prefecture level cities in China from 2013 to 2021. It found that (1) green credit and green technology innovation levels are both highest in the eastern region, followed by the central region, and exhibit spatial correlation characteristics. The main types of agglomeration are high-high and low-low agglomeration. (2) Green credit has a significant enhancing effect on green technology innovation in enterprises, and this conclusion still holds after robustness and endogeneity tests. (3) There is significant regional heterogeneity in the impact of green credit on green technology innovation, mainly concentrated in the central and western regions. (4) Green credit can significantly increase enterprise R&D investment and enhance the level of green technology innovation through this channel. Finally, some policy implications are provided to the decision-making departments that can be used for reference. |
| Author Keywords |
green credit; enterprise green technology innovation; spatial correlation; double fixed SDM model; China |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:001172217500001 |
| WoS Category |
Social Sciences, Interdisciplinary |
| Research Area |
Social Sciences - Other Topics |
| PDF |
https://www.mdpi.com/2079-8954/12/2/63/pdf?version=1708334745
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