Exploring the Impact of Digital Inclusive Finance on Agricultural Carbon Emission Performance in China

Le Sun, Congmou Zhu (), Shaofeng Yuan, Lixia Yang, Shan He and Wuyan Li
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Le Sun: School of Finance, Zhejiang Gongshang University, Hangzhou 310018, China
Congmou Zhu: Department of Land Resources Management, Zhejiang Gongshang University, Hangzhou 310018, China
Shaofeng Yuan: Department of Land Resources Management, Zhejiang Gongshang University, Hangzhou 310018, China
Lixia Yang: School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou 310018, China
Shan He: College of Economics and Management, China Jiliang University, Hangzhou 310018, China
Wuyan Li: The Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, Hangzhou 310018, China

IJERPH, 2022, vol. 19, issue 17, 1-18

Abstract: This paper attempts to reveal the impact and mechanisms of digital inclusive finance (DIF) on agricultural carbon emission performance (ACEP). Specifically, based on the provincial panel data in China from 2011 to 2020, a super slacks-based measure (Super SBM) model is applied to measure ACEP. The panel regression model and spatial regression model are used to empirically analyze the impact of DIF on ACEP and its mechanism. The results show that: (1) during the study period, China’s ACEP exhibited a continuous growth trend, and began to accelerate after 2017. The high-value agglomeration areas of ACEP shifted from the Huang-Huai-Hai plain and the Pearl River Delta to the coastal regions and the Yellow River basin, the provincial differences displayed an increasing trend from 2011 to 2020. (2) DIF was found to have a significant positive impact on ACEP. The main manifestation is that the development of the coverage breadth and depth of use of DIF helps to improve the ACEP. (3) The positive impact of DIF on ACEP had a significant spatial spillover effect, that is, it had a positive effect on the improvement of ACEP in the surrounding provinces. These empirical results can help policymakers better understand the contribution of DIF to low-carbon agriculture, and provide them with valuable information for the formulation of supportive policies.

Keywords: agricultural carbon emission performance; digital inclusive finance; super SBM model; panel regression model; spatial regression model; China (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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