Data Elements and Agricultural Green Total Factor Productivity: Evidence from a Quasi-Natural Experiment Based on Public Data Openness in China
Jiazhen Ren, Min Wang, Xiaojing Li, Xiaoyu Ding
Yantai University
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The digital economy’s development has been significantly influenced by data, which have emerged as a new propelling force for the promotion of high-quality and environmentally friendly agricultural development. This paper employs panel data from 30 provinces in China, spanning from 2000 to 2022. We construct a multi-period difference-in-differences model to investigate the impact of data elements on agricultural green total factor productivity (AGTFP) by utilizing the launch of public data open platforms as a quasi-natural experiment. AGTFP is substantially improved by public data openness, as indicated by the findings. Cross-sectoral labor transfer and green technological innovation are critical pathways through which public data openness enhances AGTFP, according to the mechanism analysis. Furthermore, heterogeneity analysis indicates that the beneficial impact of public data openness on AGTFP is more pronounced in regions with high levels of environmental regulation and non-major grain-producing regions. The results of this study have significant policy implications for the evaluation of the economic impacts of data elements and the promotion of sustainable and environmentally friendly agricultural development.
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Economic and Environmental Valuation · Fiscal Policy and Economic Growth
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