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• W3081036766 abstract "China's economy is currently moving from a stage of high-speed growth to a stage of high-quality development. Agricultural green total factor productivity is of great significance for promoting the high-quality development of the economy. Based on the panel data of China's provincial agriculture, this paper uses the Super-SBM model to calculate China's agricultural green total factor productivity based on carbon emissions. On this basis, this paper uses the nuclear density estimation method to investigate its dynamic evolution trend and the panel data model to empirically study the influencing factors of China's agricultural green total factor productivity. The results show that China's agricultural carbon emissions show an inverted-“U” trend, but the overall growth rate shows a gradual declining trend. The main concentration areas are transferred from the eastern region to the central region, and agricultural fertilizer is the main source of such emissions. China's agricultural green total factor productivity overall shows a fluctuating growth trend, and the differences between provinces show an increasing trend. Agricultural factor endowments and regional characteristics affect China's agricultural green total factor productivity, and there are regional differences in these effects. An important way to improve China's agricultural green total factor productivity and promote the coordinated development of agricultural regions and the high-quality development of the economy is by promoting clean agricultural production, strengthening the research and development of agricultural science and technology, expanding the agricultural opening-up level, and promoting the deep integration of industrialization and agricultural modernization." @default.
• W3081036766 created "2020-09-01" @default.
• W3081036766 creator A5030143780 @default.
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• W3081036766 date "2021-01-01" @default.
• W3081036766 modified "2023-10-14" @default.
• W3081036766 title "China's agricultural green total factor productivity based on carbon emission: An analysis of evolution trend and influencing factors" @default.
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• W3081036766 doi "https://doi.org/10.1016/j.jclepro.2020.123692" @default.
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