| Title |
Does green credit affect the green innovation performance of high-polluting and energy-intensive enterprises? Evidence from a quasi-natural experiment |
| ID_Doc |
35572 |
| Authors |
Liu, S; Xu, RX; Chen, XY |
| Title |
Does green credit affect the green innovation performance of high-polluting and energy-intensive enterprises? Evidence from a quasi-natural experiment |
| Year |
2021 |
| Published |
Environmental Science And Pollution Research, 28, 46 |
| DOI |
10.1007/s11356-021-15217-2 |
| Abstract |
Taking the green credit policy in 2012 as a quasi-natural experiment, this paper applies the methods of propensity score matching and Difference-in-Difference (PSM-DID) to investigate the relationship between green credit policy and enterprises' green technology innovation performance based on Chinese industrial enterprises database and green patent database. The results show that the implementation of "green credit guidelines" policy has significantly improved the green innovation performance of high-polluting and high-energy consuming enterprises, which indicates that the incentive effect of green credit policy on enterprises exceeds the constraint effect and leads to "Porter effect." Moreover, the green credit policy has significantly increased the number of non-invention patents rather than invention patents. In addition, the green credit policy has a more significant effect on the green innovation performance of high-polluting and energy-intensive enterprises that are state-owned and have weak market power. Mechanism test shows that green credit policy can change the credit financing constraints and R&D investment allocation to affect the green innovation performance of high-polluting and energy-intensive enterprises. |
| Author Keywords |
Green credit; Green innovation; Difference-in-Difference; Propensity score matching |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000670173900022 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
https://www.researchsquare.com/article/rs-205842/latest.pdf
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