Mechanisms Through Which the Digital Economy Influences Agricultural Carbon Emissions

Impact of digital economy development on agricultural carbon emissions: evidence from scale and efficiency effects

Agricultural digitalization is increasingly viewed as a key pathway to modernizing agriculture and advancing low-carbon transformation. Using provincial panel data from China spanning 2011–2022, this study examines how agricultural digitalization affects agricultural carbon emissions and carbon emission efficiency from the perspectives of scale effect and efficiency effect. A two-way fixed-effects model is employed as the main analytical approach. The results show that agricultural digitalization significantly improves agricultural carbon performance. Specifically, a 1% increase in the level of agricultural digitalization leads to a 15.72% reduction in total agricultural carbon emissions and a 3.97% improvement in carbon emission efficiency, indicating that both scale and efficiency effects are operative. Mechanism evidence suggests that, at the current stage, the mitigation effect primarily works through incremental innovation rather than breakthrough innovation. The carbon-reduction effect is stronger in southern China and in provinces with more advanced digital development, and digitalization also exhibits spatial spillover effects. These findings suggest that accelerating agricultural digitalization, while strengthening region-specific support and innovation incentives, can contribute to the transition toward low-carbon agriculture.

From traditional production to low-carbon transformation: the impact of the digital economy on agricultural carbon emissions

The rapid development of the digital economy is reshaping traditional agricultural production models, providing new opportunities for low-carbon agricultural transformation. However, the mechanisms through which the digital economy affects agricultural carbon emissions remain underexplored. Based on panel data from 30 Chinese provinces during 2011–2021, this study employs a fixed-effects model, the SYS-GMM model, and a Spatial Durbin Model (SDM) to systematically examine the impact of DE on agricultural carbon emissions (ACE) from both local mitigation and spatial spillover perspectives. DE significantly reduces ACE within the region, with agricultural technological innovation and improvements in agricultural total factor productivity serving as important transmission mechanisms through which the emission reduction is achieved. Furthermore, the development of DE also exerts a significant inhibitory effect on carbon emissions in neighboring regions, thereby promoting coordinated regional emission reduction. Moreover, the carbon reduction effect exhibits significant regional heterogeneity, with stronger total effects observed in eastern and central regions as well as in areas with higher levels of large-scale agricultural operation. This study reveals the dual role of DE in facilitating local emission reduction and regional low-carbon coordination, thereby extending the research perspective on the relationship between DE and agricultural lowcarbon transformation. The findings also provide important policy implications for promoting green and low-carbon agricultural development and strengthening regional collaborative governance.

[Impact and Mechanism of Rural Digital Economy Development on Agricultural Low-carbon Transformation].

Can the Digital Economy Enhance the Export Competitiveness of Agricultural Products?—An Empirical Analysis Based on Panel Data from 30 Chinese Provinces

As a new engine of economic development, the digital economy is profoundly reshaping the governance structure and production models of modern agriculture and has increasingly become a significant force driving the high-quality development of agricultural export trade. Based on provincial panel data from 30 Chinese provinces spanning from 2014 to 2023, this paper employs a two-way fixed effects model to systematically examine the statistical association between the digital economy and agricultural export competitiveness. Furthermore, a mediation effects model is adopted to explore the underlying transmission pathways, and a threshold effects model is applied to reveal the nonlinear characteristics of this association, thereby providing a multidimensional analysis of the underlying mechanisms. The empirical results indicate that: (1) there is a significant positive statistical association between the digital economy and agricultural export competitiveness, and this finding remains robust across a series of robustness checks; (2) upgrading of agricultural industrial structure, agricultural technological innovation, and agricultural labor transfer serve as three important transmission pathways through which the digital economy is associated with enhanced export competitiveness; (3) this positive association exhibits regional heterogeneity, with stronger effects observed in central regions and major grain-producing areas; and (4) there is a nonlinear relationship between the digital economy and agricultural export competitiveness. Finally, based on these empirical findings, several policy implications are proposed, including strengthening digital infrastructure construction, enhancing trade openness, cultivating agricultural digital talents, optimizing factor allocation structures, and improving the digital economy governance system, so as to fully unlock the potential space of the positive association between the digital economy and agricultural export competitiveness.

The Impact Mechanism of New Quality Productive Forces in Agriculture on Agricultural Carbon Emissions

Agricultural carbon emissions are a key issue in global climate governance. New quality productive forces in agriculture, an advanced productivity form driven by scientific and technological innovation, significantly directly inhibit agricultural carbon emissions by promoting the green and low-carbon transformation of agricultural production methods. Employing panel data spanning from 2010 to 2023 across 31 provincial - level administrative units in China (including autonomous regions and municipalities directly under the central government), this research paper systematically assesses the influence, transmission processes, and spatial attributes of the new - quality productive forces in the agricultural sector on agricultural carbon emissions. It achieves this by utilizing two - way fixed - effects models, mediation - effects models, and spatial Durbin models. The conclusions are as follows: (1) The emergence of novel, high - quality productive forces in the agricultural sector exerts a substantial direct suppressive impact on agricultural carbon emissions. This effect remains stable even after addressing endogeneity issues and conducting multiple robustness verifications. (2) The enhancement of agricultural total factor productivity and the optimization of agricultural industrial agglomeration are two parallel mediating transmission pathways; (3) The carbon reduction effect of new quality productive forces in agriculture has significant regional heterogeneity, with a stronger inhibitory effect in northern China than in southern China; (4) It has a significant spatial spillover effect, which can not only suppress local carbon emissions, but also play a radiating driving role in adjacent regions. This paper provides systematic theoretical framework and empirical evidence for understanding the carbon reduction effect of new quality productive forces in agriculture.

Digitalization to lower crop production carbon emissions -- a quasi-natural experiment in 745 counties.

The agricultural sector is a major contributor to global carbon emissions, and reducing emissions from crop production is critical for mitigating greenhouse gases and combating climate change. Digitalization has emerged as a promising strategy for agricultural decarbonization, yet most existing studies focus on the whole agriculture, with limited attention to crop production separately. Moreover, analyses often rely on provincial-level data, overlooking higher-resolution datasets. Using panel data from 745 counties in China, this study employs the 'Broadband China' policy as a quasi-natural experiment and applies a staggered difference-in-differences approach to examine the impact of digital infrastructure development on crop production carbon emissions. The findings hold up under several robustness checks. Further analysis indicates that industrial structure, rural household income, and educational attainment are important channels associated with this effect. The decarbonization effects of digitalization vary across economic regions and grain-production zones. These findings suggest that digital infrastructure development can support greener crop production, although its effects differ across regional contexts. Accordingly, greater investment in digital infrastructure is recommended for less developed regions and major grain-producing areas, whereas more developed regions and grain-consuming areas may require complementary non-digital measures to achieve further emission reductions. Greater investment in digital infrastructure is recommended for less developed regions and major grain-producing areas, whereas more developed regions and grain-consuming areas may require complementary non-digital approaches to achieve emission reductions.