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Chinese Journal of Management Science ›› 2024, Vol. 32 ›› Issue (3): 70-81.doi: 10.16381/j.cnki.issn1003-207x.2021.2405

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The Club Convergence and Its Dynamic Evolution of Urban Pollutant Emissions in China

Qiaoru Wang1,2,Dayu Liu1,3,Tingyu Liu1,2()   

  1. 1.School of Economics and Management, Nanchang University, Nanchang 330031, China
    2.Research Center of Central China Economic and Social Development, Nanchang University, Nanchang 330031, China
    3.Center for Quantitative Economics, Jilin University, Changchun 130012, China
  • Received:2021-11-18 Revised:2022-02-18 Online:2024-03-25 Published:2024-03-25
  • Contact: Tingyu Liu E-mail:liutingyu@ncu.edu.cn

Abstract:

A theoretical analysis and empirical examination of the convergence of pollution emissions in China is conducted under the modified spatial green Solow model framework. The following key conclusions are primarily drawn: Firstly, theoretical analysis suggests that when the growth rate of emission reduction technologies exceeds the overall output growth rate, the economy will surpass the turning point of the environmental Kuznets curve, providing theoretical support for the existence of pollution emission convergence. Subsequently, the results of the spatial panel model estimation indicate that urban pollution emissions in China currently exhibit convergent characteristics, with “club convergence” being the first to materialize. Finally, the results of the grouped estimation reveal that there are three categories of urban clusters in China, namely, low-pollution, moderate-pollution, and high-pollution. Among them, the low-pollution city cluster has entered a virtuous development model for pollution control. The moderate-pollution club has experienced pollution transfer phenomena, reflecting a certain degree of “pollution haven” effect. In contrast, the high-pollution club exhibits a typical pollution-positive feedback loop mechanism, indicating the continued risk of worsening pollution.

Key words: urban pollutant emission, club convergence, spatial green solow model, spatial diagnosis

CLC Number: