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Influence of data elements on China's agricultural green total factor productivity
Guoqun Ma1,2, Ruimin Qin1, Shuangcheng Lei3
1School of Economics and Management, Guangxi Normal University, Guilin, 541006, China.
Data elements significantly boost agricultural green total factor productivity (AGTFP) in China. This promotes labor transfer, optimal scale management, and technological innovation, especially in western regions.
Area of Science:
- Agricultural Economics
- Environmental Science
- Data Science
Background:
- Agricultural green total factor productivity (AGTFP) is crucial for sustainable development.
- Data elements offer untapped potential for enhancing agricultural efficiency and sustainability.
- Understanding the impact of data elements is vital for policy formulation in China's agriculture sector.
Purpose of the Study:
- To investigate the effect of data elements on AGTFP in China.
- To analyze the underlying mechanisms through which data elements influence AGTFP.
- To examine the regional heterogeneity of data elements' impact on AGTFP.
Main Methods:
- Panel data analysis of 30 Chinese provinces from 2010-2022.
- Application of a fixed effects model to assess the relationship.
- Robustness and endogeneity tests to validate findings.
- Heterogeneity analysis, including the 'Hu-Huanyong Line' demarcation.
Main Results:
- Data elements demonstrate a significant positive effect on AGTFP.
- Mechanisms include promoting labor's non-agricultural transfer, enhancing optimal scale management, and driving agricultural technological innovation.
- The impact is more pronounced in western regions and on the southeast side of the 'Hu-Huanyong Line'.
Conclusions:
- Data elements are key drivers for improving China's AGTFP.
- Policy recommendations focus on data infrastructure, advanced agricultural productivity, and tailored regional strategies.
- Facilitating data element utilization is essential for green and sustainable agricultural growth.
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