The Impact of Green Credit on Agricultural Carbon Emissions: Spatial Spillover Effects and Channels in China
Reducing agricultural carbon emissions is an important component of China’s efforts to achieve its carbon peaking and carbon neutrality goals. As an important policy oriented financial instrument, green credit can facilitate lower agricultural carbon intensity by directing resources more efficiently across regions and encouraging low carbon transformation in agriculture. Using panel data for 30 Chinese provinces from 2005 to 2022, this study measures agricultural carbon emission intensity (ACEI) from six sources. It then examines the spatial spillover effects, transmission channels, and nonlinear characteristics associated with green credit by using a spatial Durbin framework, mediation analysis, and panel threshold model. The results indicate that: (1) green credit development is significantly associated with lower ACEI; (2) green credit exhibits significant spatial spillover effect, being associated with lower ACEI both within a province and in neighboring provinces; (3) green credit exhibits marked regional heterogeneity in its impact on ACEI: it shows both direct and spillover effects in the eastern region, only spillover effects in the central region, and only direct effects without effective diffusion in the western region; (4) green credit is associated with lower ACEI through industrial structure upgrading and lowering agricultural energy consumption intensity; (5) green credit has a single threshold effect on ACEI based on its own development level. After crossing the threshold, the emission intensity reduction effect weakens but remains significant. These results offer empirical evidence for refining green credit arrangements and advancing coordinated agricultural emission reduction across regions.
Institutions
- South China Agricultural University (CN)
Publication Details
- Journal
- Sustainability
- Published
- 2026-05-18
- DOI
- https://doi.org/10.3390/su18105069
- Primary Topic
- Energy, Environment, Economic Growth
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Social Science Fund of China