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

Le Sun; Congmou Zhu; Shaofeng Yuan; Lixia Yang; Shan He; Wuyan Li

doi:10.3390/ijerph191710922

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

Int J Environ Res Public Health. 2022 Sep 1;19(17):10922. doi: 10.3390/ijerph191710922.

Authors

Le Sun^{1

2}, Congmou Zhu³, Shaofeng Yuan³, Lixia Yang⁴, Shan He⁵, Wuyan Li⁶

Affiliations

¹ School of Finance, Zhejiang Gongshang University, Hangzhou 310018, China.
² School of Humanities and Art Design, Zhejiang Gongshang University Hangzhou College of Commerce, Hangzhou 310018, China.
³ Department of Land Resources Management, Zhejiang Gongshang University, Hangzhou 310018, China.
⁴ School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou 310018, China.
⁵ College of Economics and Management, China Jiliang University, Hangzhou 310018, China.
⁶ The Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, Hangzhou 310018, China.

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: China; agricultural carbon emission performance; digital inclusive finance; panel regression model; spatial regression model; super SBM model.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Agriculture
Carbon Dioxide / analysis
Carbon* / analysis
China
Economic Development
Rivers*

Substances

Carbon Dioxide
Carbon

Grants and funding

This research was funded by Zhejiang Provincial Social Science Federation Research Project, grant number 2022N111; National Natural Science Foundation of China, grant number 42001201; Zhejiang Province Philosophy and Social Science Planning Project, grant number 22NDQN287YB and 21NDJC097YB.