ORIGINAL RESEARCH
Digital Rural Construction and Carbon Emission Intensity of Animal Husbandry: Evidence from China
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1
College of Economics and Management, Guangxi Normal University, Guilin 541004, China
 
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School of Economics, Guizhou University, Guiyang 550025, China
 
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Institute of Agricultural Economics and Development, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
 
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College of Finance, Nanjing Agricultural University, Nanjing 210095, China
 
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College of Business, Huaiyin Institute of Technology, Huaian 223001, China
 
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College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
 
 
Submission date: 2024-04-02
 
 
Final revision date: 2024-06-13
 
 
Acceptance date: 2024-08-15
 
 
Online publication date: 2024-12-18
 
 
Corresponding author
Yanjun Jiang   

Institute of Agricultural Economics and Development, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
 
 
 
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ABSTRACT
The booming digital economy is a new engine for sustainable agricultural development. However, there are few studies on the impact of digital rural construction on carbon emissions from animal husbandry, and this study utilized China’s provincial panel data from 2011 to 2020 and employed fixed effect models and instrumental variable methods to investigate such effects. Results indicate that digital rural construction significantly inhibits carbon emission intensity in animal husbandry. Further, regional and livestock species heterogeneity exists in terms of how digital rural construction affects local animal husbandry’s carbon emission intensity reduction process; beef cattle, live pigs, and animal husbandry in central regions are more likely to benefit from it. Lastly, promoting technological progress and optimizing agricultural structure are the key paths for digital rural construction to achieve carbon reduction. Therefore, the government needs to emphasize the role of digital rural construction in the green development of agriculture while developing the rural areas according to local conditions.
eISSN:2083-5906
ISSN:1230-1485
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