Open Access

ARTICLE

Correlation Analysis between Economic Growth and Environmental Quality

Baiqing Zhou¹, Na Li^1,*, Duan Lu¹, Jinyue Xia²

1 Huzhou Vocational & Technical College, Huzhou, 313000, China
2 International Business Machines Corporation (IBM), New York, NY, USA

* Corresponding Author: Na Li. Email:

Computer Systems Science and Engineering 2022, 41(1), 127-140. https://doi.org/10.32604/csse.2022.017750

Received 09 February 2021; Accepted 10 May 2021; Issue published 08 October 2021

Abstract

With the rapid development of the economy, China’s environment has been damaged severely, which has attracted much attention from scholars and the local government. The concept of green development has been an underlying trend since 2012, and it is of great significance to explore the relationship between economic growth and environmental quality. Huzhou is a prefecture-level city under the jurisdiction of Zhejiang Province, and it is one of the 27 cities in the central area of the Yangtze River Delta. In recent years, this city develops well not only in economic development but also in maintaining a green environment. In the paper, the back propagation neural network is used to evaluate the local environmental quality. Meanwhile, the panel model is exploited to analyze the relationship between economic growth and environmental quality. All the data presented in the paper range from the year 2008 to 2018. Theoretical analysis indicates that the evaluation value of environmental quality, the emissions of industrial SO₂, and waste water exhibit an inverted U-shaped relationship with economic growth. As for the regression results, the inflection point of income in the environmental Kuznets curve of the model which takes the evaluation value of the environmental quality as a dependent variable is higher than that of the model which takes the SO₂ emission as an independent variable. The research result would help the local government to take appropriate countermeasures to improve the environment and economy.

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Citations