数字农业碳减排效应的机理与实证检验

Mechanisms and empirical tests of carbon emission reduction effects in digital agriculture

  • 摘要: 农业碳减排是实现碳中和的重要路径。本研究旨在探讨数字农业对农业碳排放的影响机制, 为低碳农业发展提供理论支撑。本研究选取2011—2020年中国30个省(自治区、直辖市, 不包括中国香港、澳门、台湾和西藏)的面板数据, 利用双向固定效应、中介效应以及门槛效应模型, 探索数字农业对农业碳排放的影响及其路径机制。数字农业在降低农业碳排放方面具有显著的“减碳效应”, 且在多种稳健性检验下依然成立。在机制路径方面, 数字农业通过农地流转实现对农业碳排放的“减碳效应”。门槛模型检验发现, 当劳动力外流超过单一门槛未超过双重门槛时, 数字农业对农业碳排放的抑制作用更显著; 当农业规模化经营超过单一门槛值时, 数字农业对农业碳排放的抑制作用更显著; 当产业合理化超过单一门槛值时, 数字农业对农业碳排放的抑制作用更显著。在加快“双碳”目标实现的进程中, 促进农业碳减排应注重发挥数字农业的“数字红利”, 因地制宜发展数字农业, 探索数字农业发展新模式。

     

    Abstract: Under China’s “dual-carbon” policy framework (carbon peak and carbon neutrality), agricultural emission reduction has become a crucial pathway for achieving sustainable development and environmental sustainability. This study systematically investigated the impact mechanism of digital agriculture on agricultural carbon emissions to provide comprehensive theoretical support and policy implications for the development of low-carbon agriculture. Based on a provincial-level panel dataset encompassing 30 Chinese provinces (autonomous regions and municipalities, excluding Hong Kong, Macao, Taiwan, and Xizang of China) from 2011 to 2020, this study used an integrated analytical framework incorporating two-way fixed effect, mediation effect, and threshold effect models to rigorously examine the complex relationship between digital agriculture development and agricultural carbon emissions. The empirical results robustly demonstrated that digital agriculture exhibited a significant and substantial “carbon reduction effect”. This conclusion remained statistically significant and economically meaningful after conducting a series of robustness tests, including replacing the core explanatory variable, data winsorization, and sample exclusion. Further mechanistic analysis revealed that farmland transfer was a critical mediating pathway through which digital agriculture achieved carbon reduction benefits, facilitating large-scale agricultural operations and technological adoption. The threshold model test revealed that when labor outflow was between the single and double thresholds, the inhibitory effect of digital agriculture on agricultural carbon emissions was more significant. When the scale of agricultural operations exceeded a single threshold value, the inhibitory effect of digital agriculture on carbon emissions became more significant. When industrial rationalization exceeded a single threshold value, the inhibitory effect of digital agriculture on carbon emissions became more significant. These findings have important policy implications for the low-carbon agricultural transition in China. During the critical acceleration phase toward achieving China’s dual carbon goals, policymakers should prioritize fully leveraging the “digital dividend” of agricultural digital transformation. Implementation strategies should focus on creating tailored region-specific models for digital agriculture promotion that align with local resource availability and developmental stages. Concurrently, innovative approaches must be actively investigated to enhance the synergy between digital technology adoption and emission reduction initiatives. This study advances sustainable agricultural research by offering empirical evidence and analytical frameworks to assess the carbon mitigation potential of digital agriculture in developing economies, and provides practical insights for coordinating agricultural digitization with environmental sustainability under China’s “dual-carbon” policy framework.

     

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