Abstract
The implementation of green financial reform and innovation pilot zones is a pivotal initiative aimed at directing financial resources more effectively towards green transformation and national sustainable development strategy. To this end, this study adopts a dual machine learning model to examine the effect of this pilot policy on energy intensity and the underlying mechanisms, drawing upon data from 254 cities in China spanning from 2006 to 2019. The conclusions obtained confirm that the establishment of these pilot zones has exerted a substantial impact on mitigating energy intensity. This inhibitory effect is particularly evident in cities with lower administrative levels, cities in western regions, smaller and medium-sized cities, and cities dominated by the secondary industry. It should be emphasized that the reduction in energy intensity is achieved through fostering green technology innovation and enhancing green financial development. The results not only provide empirical evidence for the effectiveness of green finance pilot policies in reducing energy intensity, thereby enriching the inclusive impact of financial innovation, but also offer practical insights for strengthening the green financial system and replicating and expanding the pilot zones.
| Original language | English |
|---|---|
| Article number | 122631 |
| Journal | Journal of Environmental Management |
| Volume | 370 |
| DOIs | |
| State | Published - Nov 2024 |
| Externally published | Yes |
Keywords
- Dual machine learning model
- Energy intensity
- Green financial development
- Green technology innovation
- Policy evaluation
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