Abstract
Central bank green communication is one of the key measures for achieving the Sustainable Development Goals (SDGs). Exploring its impact on the carbon emissions of high-energy-consuming firms holds significant practical implications for achieving SDGs. We collected 5066 green finance-related texts from the official website of China's central bank to construct a “Central Bank Green Communication Index.”, using a ChatGPT-based text analysis method. We employ a panel model to examine its impact on the carbon emissions of high-energy-consuming firms. The results show that central bank green communication can significantly reduce carbon emissions in these firms, with a more pronounced effect in provinces with a higher frequency of communication and among large firms. Mechanism analysis further indicates that promoting technological innovation, enhancing external supervision, and alleviating financial constraints are the three main channels. Regarding policy recommendations, this study suggests that the central bank should increase both the frequency and depth of its green communication. In addition, the central bank should integrate green communication into its regulatory framework and incorporate it into its monetary policy framework.
| Original language | English |
|---|---|
| Article number | 125088 |
| Journal | Journal of Environmental Management |
| Volume | 380 |
| DOIs | |
| Publication status | Published - Apr 2025 |
Keywords
- Central bank
- ChatGPT
- Firm carbon emissions
- Green communication
ASJC Scopus subject areas
- Environmental Engineering
- Waste Management and Disposal
- Management, Monitoring, Policy and Law