ORIGINAL RESEARCH
Research on the Correlation between Environmental Performance and Financial Performance in China’s Heavy Pollution Industries Based on RAGA-PP Model
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1
Department of Economics and Management, North China Electric Power University, Baoding, Hebei, 071003, China
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School of Business, Hebei University of Economics and Business, Shijiazhuang, Hebei, 050061, China
CORRESPONDING AUTHOR
Yongzhen Sun   

School of Business, Hebei University of Economics and Business, China
Submission date: 2021-10-05
Final revision date: 2022-02-09
Acceptance date: 2022-02-09
Online publication date: 2022-05-16
Publication date: 2022-06-20
 
Pol. J. Environ. Stud. 2022;31(4):3195–3205
 
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ABSTRACT
With the rapid development of economy, environmental pollution is becoming more and more serious. Whether the environment and economy can achieve a win-win situation has always been a controversial issue. This paper conducts an empirical study on the correlation between environmental performance and financial performance of 16 heavy polluting industries in China. The evaluation index system is constructed by closely following the characteristics of high energy consumption and high pollution in heavy pollution industry, and the projection pursuit model based on RAGA is applied to measure the environmental performance and financial performance of enterprises, which can overcome the interference and limitation of artificial assignment of data structure by traditional methods and has the characteristics of strong anti-interference and high accuracy. On this basis, the relationship between the two is investigated by establishing a multiple regression equation, and the results show that the environmental performance of listed companies in China’s heavy pollution industry has a negative relationship with financial performance, and the improvement of environmental performance does not bring about an overall improvement in financial performance. Finally, this paper makes an in-depth analysis of the causes of this result and puts forward some corresponding suggestions.
eISSN:2083-5906
ISSN:1230-1485