A Study on ESG Management and Financial Characteristics of Chinese Companies

Purpose: The purpose of this study is to analyze the impact of ESG management of Chinese companies on the financial characteristics of companies with severe pollution and those without severe pollution. Research design, data, and methodology: A n empirical a nalysis w as c onducted o n A stock companies listed on the Shanghai Stock Exchange and Shenzhen Stock Exchange in China from 2011 to 2022. CSMAR (China Stock Market & Accounting Research Database) was used to analyze the financial characteristics of Chinese companies, and the ESG index and nominal tax rate were analyzed using the Shanghai and WIND databases, respectively. Results: As a result of empirical analysis, first, tax avoidance according to the financial characteristics of companies whose ESG management of Chinese companies is highly polluted shows a significant negative (-) effect. Second, it was found that tax avoidance according to the financial characteristics of companies whose ESG management of Chinese companies is not severely polluted had a negative (-) significant effect. Conclusions: ESG management was found to have the effect of suppressing tax avoidance behavior, regardless of whether it was heavily contaminated or not, and companies that were not heavily contaminated were more significant than those that were heavily contaminated. In other words, it shows that companies that are not heavily contaminated have better indicators in ESG management than those that are heavily contaminated and help increase the deterrent effect against tax avoidance. Industrial characteristics affecting ESG management efficiency were analyzed by classifying companies into highly polluted and non-contaminated industries, which provided new insights for industry classification research.

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Publication Details

Journal
Korean Academy Of International Commerce
Published
2024-12-30
DOI
https://doi.org/10.18104/kalc.2024.39.4.215
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
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article

A Study on ESG Management and Financial Characteristics of Chinese Companies

Wancai Yang, Jung Ho Kim
Korean Academy Of International Commerce
Impact of AI and Big Data on Business and Society
article

A Study on ESG Management and Financial Characteristics of Chinese Companies

Wancai Yang, Jung Ho Kim
article en

Abstract

Purpose: The purpose of this study is to analyze the impact of ESG management of Chinese companies on the financial characteristics of companies with severe pollution and those without severe pollution. Research design, data, and methodology: A n empirical a nalysis w as c onducted o n A stock companies listed on the Shanghai Stock Exchange and Shenzhen Stock Exchange in China from 2011 to 2022. CSMAR (China Stock Market & Accounting Research Database) was used to analyze the financial characteristics of Chinese companies, and the ESG index and nominal tax rate were analyzed using the Shanghai and WIND databases, respectively. Results: As a result of empirical analysis, first, tax avoidance according to the financial characteristics of companies whose ESG management of Chinese companies is highly polluted shows a significant negative (-) effect. Second, it was found that tax avoidance according to the financial characteristics of companies whose ESG management of Chinese companies is not severely polluted had a negative (-) significant effect. Conclusions: ESG management was found to have the effect of suppressing tax avoidance behavior, regardless of whether it was heavily contaminated or not, and companies that were not heavily contaminated were more significant than those that were heavily contaminated. In other words, it shows that companies that are not heavily contaminated have better indicators in ESG management than those that are heavily contaminated and help increase the deterrent effect against tax avoidance. Industrial characteristics affecting ESG management efficiency were analyzed by classifying companies into highly polluted and non-contaminated industries, which provided new insights for industry classification research.

Korean Academy Of International CommerceVol. 39(4)
Openalex Percentile: Top 64%
Impact of AI and Big Data on Business and Society
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