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JACIII Vol.28 No.4 pp. 845-853
doi: 10.20965/jaciii.2024.p0845
(2024)

Research Paper:

Digital Economy, Green Innovation and Urban-Rural Income Gap—Analysis Based on Prefecture-Level City Panel Data of China

Chengkun Liu, Mengyu Yan, and Minghong Zhang

School of Statistics and Data Science, Jiangxi University of Finance and Economics
No.168 East Shuanggang Road, Nanchang, Jiangxi Province 330013, China

Corresponding author

Received:
January 15, 2024
Accepted:
March 1, 2024
Published:
July 20, 2024
Keywords:
digital economy, green innovation, urban-rural income gap, panel vector error correction model
Abstract

Coordinating the relationship between the digital economy, green innovation, and the urban-rural income gap is conducive to promoting common prosperity in high-quality development. This study aims to show that, in the short term, the development of the digital economy will promote the level of green innovation, which, in turn, will promote the development of the digital economy, but will also widen the urban-rural income gap. The study uses panel data of 273 prefecture-level cities from 2011 to 2019, and adopts the panel vector error correction model for quantitative analysis, combined with the theoretical analysis of the long- and short-term causal relationship among the digital economy, green innovation, and urban-rural income gap. The results reveal that, in the long term, the digital economy, green innovation, and urban-rural income gap demonstrate a double-circular causality that is positively promoting each other. The robustness test validates the conclusions. Therefore, while promoting the development of the digital economy and green innovation, the government should control the urban-rural income gap within a reasonable range, to provide theoretical and practical support for promoting the sustainable development of China’s economy and realizing the goal of common prosperity.

Cite this article as:
C. Liu, M. Yan, and M. Zhang, “Digital Economy, Green Innovation and Urban-Rural Income Gap—Analysis Based on Prefecture-Level City Panel Data of China,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.4, pp. 845-853, 2024.
Data files:
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Last updated on Dec. 06, 2024