Exploring the effect and mechanism of data elements on agricultural green total factor productivity in China, has great significance for fully releasing the significant potential of data elements and promoting green agricultural development. Based on the panel data of China’s 30 provinces from 2010 to 2022, this paper explored the fixed effects model to analyze the functional response of data elements on the agricultural green total factor productivity (AGTFP). The research finding shows that the data elements have significant promoting effects on the AGTFP, after a series of robustness and endogeneity tests. The mechanism analysis shows that the data elements can influence AGTFP via promoting labors’ non-agricultural transfer, enhancing the optimum scale management, and driving agricultural technological innovation. The heterogeneity analysis revealed that the impact of data elements on AGTFP is more pronounced in China’s western regions. The data elements are only significant on the southeast side of the ‘Hu-Huanyong Line’. Based on the research findings, this paper proposes to expedite the interconnectivity and interoperability of data infrastructure, foster the development of advanced agricultural productivity, and facilitate green and sustainable agricultural growth through location-specific policies in years to come.
Human survival and development have faced major threats since the 21 st century due to continuous climate warming, inadequate food supplies, and declining agricultural production conditions. To effectively prevent and address these issues, countries worldwide have explored advanced agricultural production models, using agricultural economic growth and agricultural pollution control as key indicators for assessing agricultural development performance. Agricultural green total factor productivity, which simultaneously encompasses agricultural economic and environmental aspects, has become an important indicator for the scientific community to assess agricultural development outcomes. Among the numerous factors influencing AGTFP, the data element is a core and crucial factors. This is because it not only stimulates agricultural technological innovation and enables large-scale operationsthereby increasing the value of agricultural products and reducing pollution. Meanwhile, it can promote the integration of digital technologies into agriculture, which helps to reduce labor costs and accelerate the shift of agricultural labor to other sectors. This transition, in turn, leads to improvements in AGTFP, as digital technologies optimize resource allocation and enhance overall efficiency.
In fact, driven by the new round of technological and industrial revolutions, the digital economy, 5G technology and big data applications have become the key drivers of a new wave of the green and sustainable agricultural practives. In 2023, the U.S. Department of Agriculture (USDA) unveiled its ‘Data Strategy 2024-2026’, highlighting the importance of leveraging data capabilities in key areas including fund management and data-driven decision-making to enhance support for American farmers, producers, and agricultural stakeholders. Australia and Japan have implemented diverse practices in digital agriculture by integrating advance digital technologies, i.e., drones, remote sensors, the Internet of Things, artificial intelligence (AI), and blockchain into agricultural production system. These efforts aim to facilitate the transition of agriculture toward greater intelligence and sustainability. China has also introduced a series of policies and measures to promote the development of the digital economy, and strengthen the role of data elements in order to drive agricultural green and sustainable development. In 2015, the State Council issued the ‘Action Outline for Promoting the Development of Big Data’, emphasizing the need to seize advance opportunities presented by data development and expedite the application of big data in agriculture and rural areas.
In 2019, the Fourth Plenary Session of the 19th Central Committee of the Communist Party, China explicitly listed data as a factor of production. In 2023, the National Data Administration released the “Three-Year Action Plan for ‘Data Element ×’ (2024-2026).” The plan calls for the implementation of the ‘Data Element × Modern Agriculture’ initiative, which aims to leverage digitalization to facilitate the transformation and betterment of agriculture, foster the deep integration and development of data elements with modern agriculture, and actively cultivate advance high-quality agricultural productivity. This raises a critical question: Do data elements enhance AGTFP? If so, what are the underlying mechanisms? As China transitions from a major agricultural producer to an agricultural powerhouse and accelerates its shift from a data-rich nation to a leader in data utilization, understanding the role of data elements in boosting AGTFP and the mechanisms behind this effect holds significant practical importance for driving sustainable agricultural transformation.
Scientific research groups have discussed the impact of agricultural mechanization, environmental regulations, agricultural production agglomeration, green credit, rural population aging, agricultural production servicesand fiscal support on the AGTFP. However, the existing literature has yet to adequately explored the influence of the digital economy on AGTFP. A limited number of scholars have assessed this influence from perspectives, such as the rural digital economy, digital inclusive financeand digital rural construction. Fu et al. demonstrated a nonlinear U-shaped relationship between the digital economy and AGTFP. Digitalization has a spatial spillover effect on agricultural green development. Liu et al. found that the digital inclusive finance (DIF) can significantly contribute to the AGTFP growth, and it can enhance AGTFP by facilitating information channels and promoting the innovation of green technologies. Guo et al. found that digital rural construction can reduce agricultural carbon emissions and increase grain production, thereby promoting green agricultural development. As the core component of the digital economy, data elements are direct impact on agricultural total factor productivity. Existing research on the impact of data elements on total factor productivity (TFP) primarily focuses on the industrial and manufacturing sectorsleaving a gap in the empirical verification of this relationship within the agricultural sector.
This research paper investigates the relationship between data elements and AGTFP, using a fixed effects model and provincial panel data from 2010 to 2022. The main contribution is constructing a theoretical framework to analyze how data elements influence AGTFP. This framework aims to deepen the understanding of how data can be leveraged to promote green agricultural development. The panel data model is employed to empirically investigate the impact and underlying mechanisms of data elements on AGTFP, thereby enriching the existing literature and providing a solid foundation for future research. The mediation effect model is used to analyze the functions that labors’ non-agricultural transfer, optimum scale management and agricultural technological innovation exert in the influence of data elements on AGTFP, with an attempt to unveil the black box of their relationship.
