Work

Marginal potential for agricultural R&D innovation to improve agricultural carbon efficiency declines under low-carbon constraints

Year: 2025

Type: article

Abstract: Chinese agriculture is experiencing a crucial transition towards intelligent and green low-carbon agriculture, and the development of high-quality agricultural productivity is particularly important. Translating agricultural R&D innovation into actual output and transformation efficiency has become the focus of scholars and governments worldwide. Calculating agricultural carbon efficiency and analyzing its key influencing factors can help achieve agricultural carbon reduction. This study considered agricultural R&D innovation as an input factor in agricultural production using the GB-US-SBM model to calculate the carbon emission abatement of China's 31 provinces between 2000 and 2022, and calculated agricultural carbon efficiency based on the abatement amount compared with actual values. Subsequently, we employed a spatial durbin model to explore the spatial spillover effects of R&D innovation on agricultural carbon efficiency under low-carbon constraints. Results showed that (1) the average agricultural carbon efficiency in China was 0.7072, with an average annual growth rate of 0.87 % from 2000 to 2022. (2) Agricultural carbon efficiency has a significant ‘siphon’ effect on surrounding areas and is characterized by a strong negative externality. (3) Agricultural R&D innovation in a province has notable spatial spillover effects on agricultural carbon efficiency in neighboring regions. (4) There may be a marginal decline in the spatial impact of R&D innovation on agricultural carbon efficiency. This study not only contributes to promoting the green transformation and development of agriculture in China but also has important implications for the sustainable development of agriculture in other emerging economies.

Source: Sustainable Futures

DOI: 10.1016/j.sftr.2025.100549

Authors: Hui Liu, Qiang Gao, Silu Pang, Jieqiong Li, Qun Li

Institutions: Nanjing Forestry University, Nanjing Normal University, Chinese Academy of Social Sciences

Language: English

Topic: Efficiency Analysis Using DEA

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Climate action, Zero hunger, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,340