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The Impact of the Digital Economy on Agricultural Carbon Emissions: A Study Employing the Panel Data Model and Machine Learning Algorithm Based on 31 Provinces in China

Year: 2025

Type: conference-paper

Abstract: This study analyzes the spatial and temporal differences between digital economy development and agricultural carbon emissions in 31 provinces in China from 2012 to 2022. And it utilizes two-way fixed-effects models and machine learning algorithms. The study finds that the level of digital economy development in Chinese provinces has gradually increased, and agricultural carbon emissions have decreased in some provinces. The digital economy significantly reduces agricultural carbon emissions mainly by increasing agricultural green total factor productivity and rural labor productivity, especially in the eastern region and the main grain marketing areas. There is a nonlinear negative correlation between the digital economy and agricultural carbon emissions. The study suggests strengthening the construction of digital infrastructure, promoting the digitization of agriculture, establishing a carbon emission reduction market trading mechanism, and promoting the synergistic development of agricultural carbon emission reduction and digital agriculture.

Source: Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI)

DOI: 10.1145/3745238.3745343

Authors: Xiaowei Yao, Yuxian Gu, Ziyan Cai, Pao-Min Tu

Institution: Dongguan University of Technology

Language: English

Topic: Digitalization and Economic Development in Agriculture

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Climate action, Decent work and economic growth, Industry, innovation and infrastructure, Zero hunger

Open Access status: hybrid

Funder: Dongguan University of Technology