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The impact of income gap on regional green economic growth – evidence from 283 prefecture-level cities in China

Shiying Hou (Business School, University of Shanghai for Science and Technology, Shanghai, China)
Liangrong Song (Business School, University of Shanghai for Science and Technology, Shanghai, China)
Wanrui Dai (Business School, University of Shanghai for Science and Technology, Shanghai, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 17 June 2022

Issue publication date: 1 November 2023

124

Abstract

Purpose

This paper aims to research the relationship between income gap (IG) and green economic growth based on the perspective of economic inequality.

Design/methodology/approach

Based on the panel data of 283 prefecture-level cities in China from 2011 to 2020, this paper uses the super slack based model (Super-SBM) to measure the efficiency of regional green economic growth, and constructs a regression model of the IG and regional green economic growth.

Findings

Firstly, the IG has an inhibitory effect on the growth of regional green economy (GE). Secondly, the relationship between the IG and regional green economic growth will be affected by the threshold value of income level. Thirdly, environmental regulation and government competition will increase the inhibitory effect of the IG.

Originality/value

According to the characteristics of China's regional economy, the researchers construct an empirical model of the IG and green economic growth to study their relationship, the threshold effect of income level and the moderating effect of environmental regulation and local government competition. The research content, methods and conclusions of this paper provide new evidence for the sustainable growth of China's regional GE.

Keywords

Acknowledgements

The authors acknowledge the funding support by the National Natural Science Foundation of China under award number 71871144.

Citation

Hou, S., Song, L. and Dai, W. (2023), "The impact of income gap on regional green economic growth – evidence from 283 prefecture-level cities in China", Kybernetes, Vol. 52 No. 10, pp. 4812-4828. https://doi.org/10.1108/K-04-2022-0635

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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