Corporate ESG disclosure and regulatory inquiry: Evidence from comment letters on annual reports

IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE North American Journal of Economics and Finance Pub Date : 2025-02-06 DOI:10.1016/j.najef.2025.102388
Xin Li , Yan Tong , Guoquan Xu
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引用次数: 0

Abstract

Using a sample of Chinese A-share listed firms from 2015 to 2021, this paper finds that corporate ESG disclosure reduces the likelihood of regulatory inquiries. Channel analysis demonstrates that corporate ESG disclosure lowers regulatory inquiry risk by reducing agency costs and business risks. This relationship is more pronounced in firms that have less disagreement in ESG ratings, have higher levels of digital transformation, operate in highly polluting industries, or are situated in more favorable institutional environments. Further analysis indicates that corporate ESG disclosure is associated with a lower probability of delayed responses by firms, the need for verification opinions from intermediary institutions by stock exchanges, and inquiries regarding risk information from stock exchanges. The study expands the literature on the determinants of regulatory inquiries. It also sheds light on corporations’ improvement of information disclosure.
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来源期刊
CiteScore
7.30
自引率
8.30%
发文量
168
期刊介绍: The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.
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