Agricultural carbon financial innovation and carbon emission reduction effect: an empirical study based on system GMM

In recent years, the green economy has been developing rapidly, and the environmentalization of industries has been widely popularized in various industries.This paper carries out an in-depth study on the relationship between agricultural carbon finance and carbon emission reduction, and after understanding the theory related to carbon finance and carbon emission, it adopts the method of system GMM estimation to construct a dynamic panel model for the study of agricultural carbon finance and carbon emission, and selects research variables.The development of agricultural carbon financial innovation and carbon emission in 30 provincial-level administrative regions in China from 2014 to 2024 is studied, and regression analysis is carried out using system GMM so as to obtain the relationship between the impact of agricultural carbon financial innovation on carbon emission reduction, and the robustness test is carried out.The maximum values of agricultural carbon financial scale, carbon financial efficiency, carbon financial structure, and per capita carbon emission are 16.942, 7.052, 1.926, and 128.945 respectively, while the minimum values are 0.965, 0.048, 0.079, and 0.145 respectively, and the maximum values are 17.56, 146.92, 100.33, and 889.28 times of the minimum values.There are large differences in the development of agricultural carbon financial innovation and carbon emission reduction effects among different provinces.Per capita carbon emissions are reduced by 22.5%, 20.5% and 24.5% for each unit increase in carbon financial scale, carbon financial efficiency and carbon financial structure, respectively.The parameter estimates of carbon financial scale, carbon financial efficiency, and carbon financial structure are significant at the levels of 10%, 1%, and 5%, respectively.It indicates that the innovative development of agricultural carbon finance can effectively promote carbon emission reduction.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-16
DOI
https://doi.org/10.61091/jcmcc127a-291
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
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article

Agricultural carbon financial innovation and carbon emission reduction effect: an empirical study based on system GMM

Journal of Combinatorial Mathematics and Combinatorial Computing
Impact of AI and Big Data on Business and Society
article

Agricultural carbon financial innovation and carbon emission reduction effect: an empirical study based on system GMM

article en

Abstract

In recent years, the green economy has been developing rapidly, and the environmentalization of industries has been widely popularized in various industries.This paper carries out an in-depth study on the relationship between agricultural carbon finance and carbon emission reduction, and after understanding the theory related to carbon finance and carbon emission, it adopts the method of system GMM estimation to construct a dynamic panel model for the study of agricultural carbon finance and carbon emission, and selects research variables.The development of agricultural carbon financial innovation and carbon emission in 30 provincial-level administrative regions in China from 2014 to 2024 is studied, and regression analysis is carried out using system GMM so as to obtain the relationship between the impact of agricultural carbon financial innovation on carbon emission reduction, and the robustness test is carried out.The maximum values of agricultural carbon financial scale, carbon financial efficiency, carbon financial structure, and per capita carbon emission are 16.942, 7.052, 1.926, and 128.945 respectively, while the minimum values are 0.965, 0.048, 0.079, and 0.145 respectively, and the maximum values are 17.56, 146.92, 100.33, and 889.28 times of the minimum values.There are large differences in the development of agricultural carbon financial innovation and carbon emission reduction effects among different provinces.Per capita carbon emissions are reduced by 22.5%, 20.5% and 24.5% for each unit increase in carbon financial scale, carbon financial efficiency and carbon financial structure, respectively.The parameter estimates of carbon financial scale, carbon financial efficiency, and carbon financial structure are significant at the levels of 10%, 1%, and 5%, respectively.It indicates that the innovative development of agricultural carbon finance can effectively promote carbon emission reduction.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Openalex Percentile: Top 90%
Impact of AI and Big Data on Business and Society
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