Abstract

China has the highest carbon dioxide emissions worldwide. Exploring the mechanism of fiscal decentralisation on agricultural carbon intensity can help China reach its carbon peak and become carbon neutral. This study used panel data for 30 provinces in Mainland China from 2000 to 2019 and constructed a spatial Durbin model to investigate the spatial-temporal patterns and internal relationships among fiscal decentralisation, environmental regulation, and agricultural carbon intensity. The results indicated that (1) from 2000 to 2019, the agricultural carbon intensity showed a downward trend and showed a spatial pattern of 'high in the north and low in the south'. The degree of fiscal decentralisation has gradually increased, and the spatial pattern of 'high in the north and low in the south' has also emerged. The intensity of environmental regulation continues to increase, and the intensity of environmental regulation in inland areas is higher than that in coastal areas. (2) From 2000 to 2019, the global Moran index of agricultural carbon intensity showed a development trend of first rising and then falling, and the spatial correlation changed from strong to weak. Agricultural carbon intensity tends to develop from polarisation to balanced development. (3) Both fiscal decentralisation and environmental regulation can reduce agricultural carbon intensity, and environmental regulation has a negative spatial spillover effect. (4) Under the influence of fiscal decentralisation, environmental regulation is not conducive to reducing agricultural carbon intensity due to the characteristics of 'race to the bottom', causing the 'green paradox' effect. (5) Environmental regulation and fiscal decentralisation in main grain producing areas have less impact on agricultural carbon intensity than in non-main grain producing areas. Therefore, the central government should focus on optimising the fiscal decentralisation system, formulating a differentiated agricultural carbon emission control system, regulating competition among local governments, and optimising a political performance evaluation system.

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