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      Green Finance, Chemical Fertilizer Use and Carbon Emissions from Agricultural Production

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      Agriculture
      MDPI AG

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          Abstract

          This study aimed to understand green finance’s impact on fertilizer use and agricultural carbon emissions. We selected the macro panel data of 30 provinces (cities) in China from 2000 to 2019. The main research methods are standardized test framework (cross-sectional dependence, unit root and cointegration test), the latest causal test, impulse response, and variance decomposition analysis. Examined the long-term equilibrium relationship between green finance, fertilizer use, and agricultural carbon emissions. The results show: fertilizer consumption and agricultural carbon emissions have a positive correlation. However, green finance can significantly reduce agricultural carbon emissions. The causal test confirmed the bidirectional causal relationship between agricultural carbon emissions and fertilizer use. At the same time, verified one-way causality from green finance to both of them. Interpret the results of impulse response and variance decomposition analysis: among the changes in agricultural carbon emissions, chemical fertilizers contributed 2.45%, green finance contributed 4.34%. In addition, the contribution rate of green finance to chemical fertilizer changes reached 11.37%. Green finance will make a huge contribution to reducing fertilizer use and agricultural carbon emissions within a decade. The research conclusions provide an important scientific basis for China’s provinces (cities) to formulate carbon emission reduction policies. China has initially formed a policy system and market environment to support the development of green finance, in 2020, the “dual carbon” goal was formally proposed. In 2021, the national “14th Five-Year Plan” and the 2035 Vision Goals emphasized the importance of green finance. It plays an important supporting role in carbon emission reduction goals, and green finance has become an important pillar of national strategic goals.

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          Most cited references54

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          Investigating Causal Relations by Econometric Models and Cross-spectral Methods

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            Testing for a unit root in time series regression

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              Unit root tests in panel data: asymptotic and finite-sample properties

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                Author and article information

                Contributors
                Journal
                ABSGFK
                Agriculture
                Agriculture
                MDPI AG
                2077-0472
                March 2022
                February 22 2022
                : 12
                : 3
                : 313
                Article
                10.3390/agriculture12030313
                e72c2070-15c3-42eb-82ce-b1569f4a2d8c
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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