The Impact of ESG Information Disclosure on Corporate Environmental Performance: Evidence from China’s Shanghai and Shenzhen A-Share Listed Companies

Abstract

Drawing on an annual dataset of Chinese Shanghai and Shenzhen A-share listed companies covering the years 2011 to 2023, this study employs multiple regression analysis to investigate the impact of ESG information disclosure on corporate environmental performance and its underlying mechanisms. The results indicate that ESG disclosure significantly enhances environmental performance, a relationship mediated by green innovation, media attention, and executive compensation. Furthermore, heterogeneity analysis reveals that this positive effect is more pronounced in state-owned enterprises, firms with high-quality internal controls, and environmentally sensitive industries. This large-sample study provides a new perspective on how ESG disclosure bolsters corporate green competitiveness and long-term value, offering theoretical support for improving environmental governance and informing policy to promote sustainable economic development in China.

1. Introduction

The world faces severe environmental challenges that are fundamentally changing how companies operate. The importance of businesses taking environmental responsibility is increasingly obvious, making sustainable development a key concern for society.

As one of the largest and fastest-growing economies, China officially announced its “dual carbon” goals at the 75th UN General Assembly: to achieve carbon peak by 2030 and carbon neutrality by 2060. Promoting green and low-carbon transformation and exploring new paths and models for green development are directly related to achieving these dual carbon goals and sustainable development targets.

Businesses play a key role in taking environmental responsibility. Their environmental performance is the foundation for China’s sustainable development strategy and its participation in global environmental governance. It is increasingly agreed that environmental performance is crucial for companies to enhance their green competitiveness.

In this context, corporate environmental performance has become an important topic in academic research. This concept refers to how well a company manages its environmental impacts. In our study, we use the method from Qu [1] to measure environmental performance. We create a detailed index based on information the company provides about its environmental practices. These include whether the company has environmental protection goals, management systems, and certifications like ISO 14001 [2]. Section 3.2 will provide the complete details about how we measure this important variable.

ESG information disclosure refers to the public reporting of a company’s performance in three areas: environment, social responsibility, and corporate governance (Khamisu and Paluri [3]). The goal of disclosing ESG information is communicating the company’s non-financial performance to the public, supplementing the limitations of traditional financial reporting. Companies are usually assessed using ESG indicators developed by third parties to measure their level of ESG information disclosure.

These indicators have become core metrics for evaluating corporate sustainability performance. To advance the development of China’s sustainability disclosure standards, the China Securities Regulatory Commission (CSRC) issued a revised “Administrative Measures for Information Disclosure by Listed Companies” in March 2025. This revision improves the information disclosure system for listed companies. It guides companies to fully implement the new development concept. These measures mark a historic shift in China. ESG disclosure has changed from being voluntary to legally required. This significantly raises the legal status of ESG reporting in China.Against this background, it is crucial to examine how ESG disclosure influences corporate environmental performance.

ESG information disclosure serves as a tool for companies to communicate with external parties and is an important reflection of their ESG performance (Yuan et al. [4]). Previous studies on the economic consequences of ESG disclosure have shown that sufficient disclosure of non-financial information serves as a bridge between companies and the market. It communicates corporate social responsibility concepts to the public, strengthens positive interaction with stakeholders, fosters broader and more stable business partnerships, reduces information asymmetry, lowers agency costs (Wu and Xu [5]), promotes innovation (Fang and Hu [6]), enhances green competitiveness, and supports high-quality corporate development.

However, some scholars hold opposing views. For instance, Eduard and Javier [7] argue that engaging in ESG activities requires significant financial investment, which increases operational costs, reduces financial performance, and may even lead to financial distress. Moreover, companies might take advantage of ESG disclosure to engage in non-standard “greenwashing” practices, misleading the public and stakeholders by obscuring their actual poor ESG performance. This hinders investors from making sound decisions (Yi and Van Luu [8], Huang [9]).

Most of the existing research focuses on the relationship between ESG reporting and corporate operational development. There is still no clear and targeted conclusion on whether ESG information disclosure can effectively drive improvements in corporate environmental performance. Under the “dual-carbon” goals, key questions require exploration: Does ESG disclosure improve corporate environmental performance? If so, what is the underlying mechanism? This study specifically examines the mediating roles of green innovation, media attention, and executive compensation.

This study provides useful insights for promoting the low-carbon transition towards a green economy and society in China, as well as for advancing ecological conservation and high-quality socioeconomic development. Its main contributions are as follows:

1.

While existing literature focuses on ESG’s impact on investment efficiency and financial performance, this research specifically examines its effect on environmental performance, clarifying the theoretical relationship between disclosure quality and environmental outcomes.

2.

The paper examines the mechanisms through three specific channels: green innovation, media attention, and executive compensation, providing empirical evidence on how ESG disclosure enhances environmental performance.

The structure of the paper is as follows: Section 2 develops the theoretical analysis and research hypotheses. Section 3 describes the research design, including the sample selection, variable definitions, and empirical model. Section 4 presents the empirical results and analysis, covering main findings, robustness checks, endogeneity tests, mechanism analyses, and heterogeneity discussions. Section 5 concludes with the main findings, policy implications, and research limitations.

2. Theoretical Analysis and Research Hypotheses

Previous research on ESG disclosure has mainly studied its effect on financial performance and investment efficiency. However, its direct impact on environmental performance is less clear. Some studies find that ESG disclosure helps build trust with stakeholders. Other studies argue that it can be costly and might be used for ’greenwashing’. This mixed evidence shows a need for more research on the direct link. This chapter develops our hypotheses by combining key theories with findings from recent literature.

2.1. The Direct Impact of ESG Information Disclosure on Environmental Performance

Under China’s dual-carbon goals, ESG (Environmental, Social, and Governance) factors have become central to evaluating corporate sustainability (Zhao et al. [10]). It is crucial to distinguish between ESG performance—the actual outcomes of a company’s practices—and ESG disclosure, which is the external communication of those activities. This study focuses specifically on the role of ESG reporting. This study proposes that high-quality disclosure is not merely a reflection of performance but an active mechanism that can drive improvement, particularly in environmental performance.

First, from the perspectives of signaling and stakeholder theories, high-quality ESG disclosure serves as a credible signal of a company’s commitment to environmental responsibility. This signal facilitates trust building and enables companies to secure vital support from key stakeholders (Wang et al. [11]). For regulators, it demonstrates compliance, reducing regulatory risks. For investors and business partners, it showcases long-term sustainability capabilities, facilitating access to green investments and stable cooperation. This enhanced support and reduced risk provide companies with both the resources and the motivation to increase investments in environmental protection and advanced pollution control technologies, thereby directly improving their environmental performance.

Second, ESG disclosure improves environmental performance by reducing information gaps and building a strong green reputation. As Li and Liu [12] notes, it is hard for stakeholders like investors and customers to know a company’s real environmental efforts because of information asymmetry. Here, ESG information disclosure acts as a positive signal. It shows the market that the company manages its environmental risks well and is committed to sustainability. This clear communication narrows the information gap and builds trust (Ge et al. [13]). As Chen [14] suggests, this trust attracts more green investment. This investment provides the money needed to develop better environmental technologies and upgrade equipment.

Furthermore, a strong green reputation brings wider support. Wang et al. [11] points out that a company known for its real commitment to sustainability can attract specialized investors, earn customer loyalty, and build stronger partner trust. This overall support provides more resources, can lower operating costs, and improves investment efficiency. To keep this valuable reputation, companies are motivated to continuously improve their environmental management, which directly leads to better environmental performance.

Finally, strengthening ESG reporting requirements can help alleviate principal-agent conflicts between shareholders and management, leading to significant improvements in environmental performance. Based on principal-agent theory, enhancing environmental performance often requires long-term and sustained resource investments, which increase short-term costs and may create conflicts of interest with management (Xu et al. [15]). Managers might make decisions that deviate from the interests of shareholders and the company as a whole.

ESG information disclosure reduces information asymmetry and improves corporate governance mechanisms, thereby effectively lowering agency costs in management. It enhances the efficiency and quality of communication between executives and shareholders. Moreover, the external market attention generated by such disclosure creates additional pressure, enabling shareholders, governments, and the public to better monitor and restrain management. This helps reduce opportunistic practices such as “greenwashing”, where a company’s actions are inconsistent with its claims, and discourages short-sighted decision-making by management that might compromise environmental investments (Zou et al. [16], Bolognesi et al. [17]). As executors of corporate environmental strategy, executives may proactively increase resource allocation and strategic focus on environmental governance, thereby driving improvements in corporate environmental performance. Thus, we posit that there is a positive correlation between ESG disclosure and corporate environmental performance, forming our first hypothesis:

Hypothesis 1.

There is a positive relationship between the quality of ESG information disclosure and corporate environmental performance.

2.2. The Mediating Mechanisms

Since ESG disclosure covers information across environmental, social, and governance dimensions, each dimension may influence corporate environmental behavior and performance through distinct mechanisms. Therefore, this section will elaborate on the theoretical pathways through which ESG reporting affects environmental performance from three perspectives: green innovation, media attention, and executive compensation, in order to systematically reveal the underlying logical relationships between ESG information disclosure and corporate environmental performance.

Green Innovation. Green innovation allows companies to develop better pollution control technologies, optimize production, and improve resource recycling. These improvements directly cut pollutant releases and lower environmental costs, leading to better environmental performance (Wang and Wang [18], Wang et al. [19]). As Wang et al. [20] states, these actions also build a positive image of a company that cares for the environment, which helps it gain public recognition and further improves its environmental results.

High-quality ESG disclosure supports green innovation in two main ways. First, it reduces information asymmetry by clearly showing a company’s commitment to the environment (Cui et al. [21]). This helps investors and banks better assess the company’s future, attracting those who value sustainability. While this creates some external pressure, it also opens up more financing options. According to Zou et al. [16], this easing of funding constraints makes it easier for firms to get investor money and green loans, providing the necessary financial fuel for green innovation projects.

Second, ESG disclosure highlights a company’s dedication to its social duties and long-term goals. This strengthens employees’ sense of belonging and boosts their motivation to innovate, improving team unity and loyalty. As Sheng et al. [22] notes, this helps attract skilled technical talent. Furthermore, as Shi and Jiang [23] points out, it also helps keep customers who care about the environment, as they are more likely to stay loyal to a responsible brand. Together, these effects make the company stronger against risks, increase stakeholder support for the uncertainties of green innovation, and make the company more willing and able to manage these innovation risks effectively.

Media Attention. Media has become a key part of social oversight in today’s digital world. Media reports can strongly affect a company’s reputation and its relationships with stakeholders (Suo et al. [24]). At the same time, company managers can use media reports to learn what the public expects about environmental governance.

More media attention means more coverage. This creates external pressure that helps monitor how companies behave. Sun et al. [25] explains, when media reports negative ESG news about a company, public scrutiny pushes the firm to protect its image. This encourages more investment in environmental protection and faster development of green technologies. On the other hand, when media highlights good ESG performance, it motivates companies to keep their good reputation. According to Qu [1], this helps companies build stronger stakeholder ties and take more active steps to meet social responsibilities, which boosts their green competitiveness and environmental performance.

When companies provide high-quality ESG reports, the public may question if the information is true and worry about possible greenwashing. Greenwashing creates false impressions that can hurt investor interests. This kind of false information is also more likely to be found and spread by the media. On the contrary, honest ESG reporting meets the capital market’s need for reliable company information. As Liu et al. [26] notes, this gives media a reason to cover these companies more closely. To meet investor demand for good information, journalists are more likely to focus on companies with strong ESG reporting and carefully analyze their disclosures. This creates a powerful system of social supervision through media oversight.

Executive Compensation. High-quality ESG disclosure encourages executives to actively manage environmental issues through better compensation incentives, which improves corporate environmental performance. Good ESG reporting shows greater corporate transparency and a stronger focus on long-term sustainable development. It reduces information gaps between the company and its stakeholders, easing principal-agent problems. This helps stakeholders better judge the company’s ability to handle environmental risks and pursue sustainable growth.As external pressure and public attention increase, boards of directors have stronger reasons to include environmental criteria in executive evaluations and improve pay structures (Chen and Song [27]). This performance-based pay motivates managers to actively improve environmental governance. It aligns the interests of owners and managers, promoting sustainable business models instead of short-term strategies.

Executives are key decision-makers who directly control company resources and play a vital role in environmental management. When environmental targets are included in executive pay, personal financial benefits become linked to corporate environmental goals. This makes sure management prioritizes sustainability in their planning and actions. According to Chang et al. [28], this leads to more investment in environmental protection, better environmental management systems, and improved employee environmental training. These steps make corporate environmental management more efficient. With such incentives, executives become more willing to fund green projects, even if they have higher short-term costs or lower returns.

Executives may also improve ESG disclosure to build their social reputation and show commitment to sustainability. At the same time, to protect both personal and company reputation, they will enforce stricter controls over environmental compliance risks. Feng et al. [29] notes, this reduces the chance of penalties and bad publicity from environmental violations. These leadership choices help achieve the positive effect of ESG reporting on environmental performance.

Hypothesis 2.

ESG information disclosure enhances corporate environmental performance by promoting green innovation, increasing media attention, and strengthening executive compensation incentives.

3. Research Design

3.1. Sample Selection and Data Sources

This study selects Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2011 to 2023 as the initial sample. The following screening procedures were applied: (1) exclusion of financial industry samples; (2) removal of samples under special treatment status such as ST and *ST; (3) elimination of samples with missing values in regression variables. To mitigate the influence of extreme values, all continuous variables included in the regression models were winsorized at the 1st and 99th percentiles. The final sample consists of 31,630 firm-year observations. Statistical analysis was conducted using Stata 18.0. Data on ESG information disclosure and other firm-level variables were obtained from the Wind and CSMAR databases.

3.2. Variable Definitions

3.2.1. Explained Variable

Corporate Environmental Performance (EP). Corporate environmental performance refers to the effectiveness of a company’s management of its environmental impacts during operations. It is a core element reflecting green competitiveness and sustainable development. Following the approach of Qu [1], this study constructs a corporate environmental performance index based on the following nine components: (1) whether the company has an environmental protection philosophy; (2) whether it has set environmental protection goals; (3) whether it has adopted an environmental management system; (4) whether it conducts environmental protection training and education; (5) whether it carries out special environmental actions; (6) whether it has an emergency response mechanism for environmental incidents; (7) whether it implements the “three simultaneities” system; (8) whether it has received honors or awards related to environmental protection; (9) whether it has obtained ISO 14001 certification. Each item is assigned a score of 1 if present and 0 otherwise. The total score across all items serves as a proxy variable for corporate environmental performance.

In the robustness test section, this study follows the approach of Xu and Zhang [30] by using the pollution fee per unit of operating revenue to measure corporate environmental performance (EP1). This indicator is calculated as the ratio of the natural logarithm of the annual pollution fee to the natural logarithm of the annual operating revenue. A higher value of EP1 indicates better corporate environmental performance, as it reflects a greater emphasis on environmental protection relative to economic output.

3.2.2. Explanatory Variable

ESG Information Disclosure (ESG). Drawing on the approach of Sheng et al. [22], this study employs the Hua Zheng ESG rating as a proxy for ESG information disclosure.

The Hua Zheng ESG rating system is built on a comprehensive three-tier analytical framework comprising over 130 underlying indicators that systematically evaluate corporate performance across environmental, social, and governance dimensions. The rating provides a detailed assessment through its nine-level classification system ranging from C to AAA, which we convert into numerical scores from 1 to 9 for analytical purposes, with higher values indicating superior ESG disclosure quality. We select this rating because it offers extensive historical coverage and comprehensive inclusion of Chinese listed companies, while its methodology is particularly adapted to China’s unique institutional environment, making it well-suited for studying the Chinese market context. The rating’s robustness and widespread adoption in academic research on Chinese firms further support its reliability for this study.

3.2.3. Control Variables

Drawing upon previous research related to environmental performance, this study selects the following control variables: firm size (SIZE), firm age (AGE), return on assets (ROA), and asset-liability ratio (LEV), among others. Fixed effects for both industry and year are also controlled. Detailed definitions of all variables are provided in

Table 1. Variable Definitions.

Variable Name	Symbol	Definition
Environmental Performance	EP	For details, refer to variable definition
ESG Information Disclosure	ESG	Hua Zheng ESG Rating
Green Innovation	RD	R&D expenditure/Total assets
Media Attention	Media	Natural logarithm of the total number of online media reports
Executive Compensation	Salary	Natural logarithm of the total compensation of the top three executives
Firm Size	SIZE	Natural logarithm of total assets
Firm Age	AGE	Natural logarithm of (Year of observation − Year of establishment + 1)
Profitability	ROA	Net profit/Total assets
Leverage	LEV	Total liabilities/Total assets
Largest Shareholder Ownership	TOP1	Percentage of shares held by the largest shareholder
CEO Duality	DUAL	Equals 1 if the chairman and general manager are the same person, otherwise 0
Board Size	BOARD	Natural logarithm of (Number of board members + 1)
Proportion of Independent Directors	INDBOARD	Number of independent directors/Total number of board members
Big Four Auditing	AUDIT	Equals 1 if the auditor is one of the Big Four international firms, otherwise 0
Management Shareholding Ratio	MHOLD	Total shares held by directors, supervisors, and senior executives/Total shares outstanding
Industry Fixed Effects	Industry	Industry dummy variables
Year Effects	Year	Year dummy variables

.

3.3. Empirical Model

To test the research hypothesis, this study employs a fixed-effects model to examine the impact of ESG information disclosure on corporate environmental performance. The baseline regression model is constructed as follows:

$$\begin{array}{cc}\hfill {\mathrm{EP}}_{it}& ={\beta }_0+{\beta }_1{\mathrm{ESG}}_{it}+\gamma {\mathbf{X}}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}\hfill \end{array}$$

(1)

where ${\mathbf{X}}_{it}$ is a vector of control variables, ${\mu }_i$ represents firm fixed effects, and ${\lambda }_t$ represents year fixed effects.

4. Empirical Analysis

4.1. Main Results

4.1.1. Descriptive Statistics

The descriptive statistics of the variables are presented in

Table 2. Descriptive Statistics.

Variable	N	Mean	Std. Dev.	Min	Max	Median
EP	31,630	4.121	2.198	0.000	9.000	1.000
EP1	1694	0.658	0.077	0.414	0.669	0.819
ESG	31,630	2.206	0.993	1.000	8.000	4.000
SIZE	31,630	22.177	1.243	20.070	26.152	21.972
LEV	31,630	0.396	0.199	0.051	0.884	0.384
ROA	31,630	0.039	0.061	−0.229	0.201	0.040
TOP1	31,630	33.326	14.441	8.350	72.800	31.070
DUAL	31,630	0.328	0.469	0.000	1.000	0.000
INDBOARD	31,630	0.377	0.052	0.333	0.571	0.364
AGE	31,630	2.947	0.320	2.079	3.611	2.996
MHOLD	31,630	0.165	0.205	0.000	0.693	0.044
BOARD	31,630	2.109	0.194	1.609	2.639	2.197
AUDIT	31,630	0.055	0.228	0.000	1.000	0.000

. As can be observed, the EP variable has a maximum value of 9 and a minimum value of 0, indicating considerable variation in environmental performance across different firms. The mean and standard deviation are 2.121 and 2.198, respectively, suggesting significant disparities in environmental performance among Chinese companies, with an overall relatively low average level. For the alternative environmental performance measure EP1, which is based on pollution fees per unit of operating revenue, the mean value is 0.658 with a standard deviation of 0.077, reflecting a relatively concentrated distribution. From the perspective of corporate ESG disclosure, the mean and median values for the sample companies are 4.206 and 4, respectively, indicating that the majority of firms receive an ESG information disclosure rating around Level B. Detailed results for other control variables can be found in Table 2.

4.1.2. Multivariate Regression Analysis

Table 3. Multiple Regression Results.

	(1)	(2)
	EP Basic	EP Full Model
ESG	0.547 ***	0.445 ***
	(25.987)	(25.848)
SIZE		0.508 ***
		(22.598)
LEV		0.282 **
		(2.360)
ROA		1.039 ***
		(4.194)
TOP1		0.004 ***
		(2.614)
DUAL		−0.129 ***
		(−3.474)
INDBOARD		−0.468
		(−1.112)
AGE		0.130 *
		(1.833)
MHOLD		−0.547 ***
		(−5.351)
BOARD		0.478 ***
		(3.877)
AUDIT		0.466 ***
		(4.714)
Constant	−0.180 **	−12.387 ***
	(−2.133)	(−21.386)
Controls	No	Yes
Industry FEs	No	Yes
Year FEs	No	Yes
Observations	31,630	31,630
R2	0.061	0.382

(t-statistics in parentheses; the same applies hereinafter). * p < 0.1, ** p < 0.05, *** p < 0.01.

reports the regression results examining the impact of ESG disclosure on corporate environmental performance. Column (1) presents the results without control variables, industry fixed effects, or year fixed effects. The coefficient of ESG information disclosure is 0.547 and is statistically significant, indicating a positive correlation with corporate environmental performance.

In Column (2), after incorporating control variables as well as year and firm fixed effects, the regression coefficient of ESG disclosure remains positive at 0.445 and significant at the 1% level. This suggests that, all else being equal, ESG information disclosure has a significant positive effect on corporate environmental performance, supporting research Hypothesis 1 that ESG reporting significantly enhances corporate environmental performance. For corporate managers, this finding confirms that investing in better ESG disclosure is not just a compliance exercise but is associated with substantial, measurable improvements in environmental outcomes. The stability of this relationship across different model specifications, even after accounting for various firm characteristics and time invariant factors, gives us confidence that this is a robust finding with real world implications for corporate environmental strategy.

Furthermore, variance inflation factor (VIF) tests were conducted based on the multivariate regression analysis. The maximum VIF value was 1.92, with a mean value of 1.36, both well below the conventional threshold of 10. This indicates that the regression model does not suffer from severe multicollinearity issues.

4.2. Robustness

4.2.1. Replacing Key Variables

To avoid potential bias resulting from different measurement methods of the variables and to verify the reliability and robustness of the empirical results, this study refers to the approach of Ren and Niu [31] by adopting an alternative measure of ESG disclosure. Specifically, the Bloomberg ESG score (ESG1) is used as a substitute variable for reassessing corporate ESG information disclosure. After re-estimating Model (1), the regression results presented in Column (1) of

Table 4. Robustness Test Results.

	(1)	(2)	(3)	(4)
	EP	EP1	EP	EP
	EP Alternative ESG Measure	Alternative EP Measure	Excluding Pandemic Years	Firm & Year FEs
ESG1	0.129 ***
	(23.178)
ESG		0.007 **	0.476 ***	0.167 ***
		(2.264)	(25.189)	(12.296)
Constant	−7.184 ***	0.573 ***	−12.580 ***	−7.056 ***
	(−6.114)	(5.927)	(−20.918)	(−5.823)
Controls	Yes	Yes	Yes	Yes
Industry FEs	Yes	Yes	Yes	No
Year FEs	Yes	Yes	Yes	Yes
Firm FEs	No	No	No	Yes
Observations	9391	1694	24,920	31,630
R2	0.412	0.276	0.394	0.702

** p < 0.05, *** p < 0.01. Notes: The variations in the number of observations across columns are due to the different data requirements and sample restrictions of each test: Column (1) uses the Bloomberg ESG score, which is not available for all firms; Column (2) uses the pollution fee measure (EP1), which has limited data availability; Column (3) excludes the extraordinary years of 2020–2021; Column (4) includes firm fixed effects in addition to year fixed effects but maintains the full sample.

show that the coefficient of ESG1 is significantly positive at the 1% level, confirming the robustness of the findings.

Furthermore, Draw on the research methods of Xu and Zhang [30], this study replaces the explained variable with pollution fees per unit of operating revenue (EP1), which is measured as the ratio of the natural logarithm of annual pollution fees to the natural logarithm of annual operating revenue, reflecting the extent of corporate emphasis on environmental protection. After re-running the estimation of Model (1) using this alternative measure, the results in Column (2) of Table 4 indicate that the coefficient of ESG remains significantly positive at the 5% level, although the magnitude is smaller than in the baseline results. This difference can be attributed to the distinct nature of the two environmental performance measures: while EP captures comprehensive managerial efforts in environmental governance systems, EP1 reflects actual emission outcomes that are more directly influenced by external regulatory enforcement and may exhibit a longer time lag in responding to corporate ESG initiatives. Despite the attenuated effect size, the persistent positive and statistically significant relationship corroborates the baseline finding that ESG disclosure enhances environmental performance, thereby supporting the robustness of our conclusions from a different methodological perspective.

4.2.2. Excluding Extraordinary Years

To enhance the generalizability of the research findings, this study draws on the approach of Wang et al. [32] by excluding data from exceptional periods (the years 2020–2021, which were affected by the pandemic) and re-estimating Model (1). The regression results, presented in Column (3) of Table 4, show that the significance and direction of the core explanatory variable’s coefficient remain consistent with the baseline regression. This further confirms the robustness of the study’s conclusions.

4.2.3. Firm Fixed Effects

In the baseline regression, this study has already controlled for industry fixed effects and time fixed effects. To further account for the impact of firms’ individual characteristics on environmental performance and improve the accuracy of the estimation, this study refers to the approach of Liu et al. [33] and incorporates firm fixed effects in addition to time fixed effects. The results in Column (4) of Table 4 show that even after controlling for firm-level heterogeneity, ESG information disclosure continues to have a significant positive effect on corporate environmental performance, confirming the robustness of the baseline findings.

4.2.4. Placebo Test

To rule out the potential influence of data structure and other unobservable factors, this study refers to the method of Zhang et al. [34] and conducts a placebo test by randomly assigning the ESG variable to listed companies 500 times. This process generated 500 p-values for the regression coefficients of the simulated explanatory variable. The results, shown in Figure 1, indicate that the kernel density plot of the p-values reveals that the majority of the randomly generated regression coefficients have p-values greater than 0.1, with only a very few below 0.1, suggesting no significant correlation. This helps eliminate the influence of time-varying factors and other unobserved random disturbances to a certain extent, thereby further supporting the robustness of the research findings.

4.2.5. Endogeneity Tests

1. Propensity Score Matching (PSM) Method. To mitigate potential self-selection bias in the sample, this study follows the approach of Zhang et al. [35] by re-estimating Model (1) using a sample constructed through propensity score matching. First, a dummy variable (treat_ESG) was created based on whether a firm’s ESG disclosure score was above (assigned 1) or below (assigned 0) the sample average. Firms with higher ESG information disclosure levels were designated as the treatment group, while the others formed the control group.

Next, the control variables included in Model (1) were used as covariates to perform 1:1 nearest neighbor matching. Finally, the matched sample was used to rerun the regression. The results, presented in

Table 5. Endogeneity Test Results.

	(1)	(2)	(3)	(4)	(5)
	EP	ESG	EP	ESG	EP
	PSM Sample	First Stage	Second Stage	First Stage	Second Stage
ESG	0.466 ***		0.156 ***		0.668 ***
	(22.025)		(3.058)		(21.49)
IVESG		0.969 ***
		(36.736)
IVESG1				0.572 ***
				(99.88)
Constant	−12.360 ***	−5.837 ***		−1.347 ***
	(−17.304)	(−19.522)		(−8.93)
Kleibergen-Paap rk Wald F		1349.511		9976.496
		[16.38]		[16.38]
Kleibergen-Paap rk LM		625.462 ***		1199.855 ***
Controls	Yes	Yes	Yes	Yes	Yes
Industry FEs	Yes	Yes	Yes	Yes	Yes
Year FEs	Yes	Yes	Yes	Yes	Yes
Observations	15,173	31,630	31,630	26,388	26,388
R2	0.381	0.221	0.192	0.456	0.204

*** p < 0.01. Notes: The variations in the number of observations across columns are due to the different sample requirements: the PSM procedure reduces the sample to matched pairs; the use of the lagged ESG variable in Columns (4) and (5) results in the loss of one year of data due to the lag structure, thus further reducing the sample size compared to the full sample used in Columns (2) and (3).

, show that the estimated coefficient of ESG remains significantly positive at the 1% level, consistent with the baseline regression results. This indicates that the main findings hold even after accounting for self-selection bias.

2. Instrumental Variable (IV) Approach. To address potential endogeneity concerns in the relationship between ESG disclosure and environmental performance, this study employs an instrumental variable (IV) approach with two alternative instruments. Following Lei and Lin [36] and Yuan et al. [4], we use both the current industry-year average ESG score (IVESG) and its one-period lagged value (IVESG1). These instruments are selected because they effectively capture industry-wide trends and common shocks in ESG practices, while satisfying the exclusion restriction.

Firms within the same industry are subject to similar regulatory pressures, technological pathways, and market expectations, leading to correlated ESG disclosure patterns across peers. At the same time, industry-level ESG averages are unlikely to directly affect an individual firm’s environmental performance after controlling for firm-level characteristics and fixed effects. The lagged instrument (IVESG1) further helps mitigate reverse causality concerns, as past industry ESG levels may influence current firm disclosure but are not affected by the firm’s current environmental performance.

Table 5 presents the empirical results. Columns (2) and (3) report estimates using the current industry average instrument (IVESG). The first-stage F-statistic is 1349.511, well above conventional thresholds, and the second-stage results show a statistically positive effect of ESG disclosure on environmental performance. Columns (4) and (5) present results using the lagged instrument (IVESG1), which yields an even stronger first-stage F-statistic of 9976.496. For both instruments, the Kleibergen-Paap rk LM test yields a p-value of 0.000, indicating no under-identification problem. Moreover, the results from the IV approach are consistent with the baseline regression estimates, further supporting the robustness of our findings.

In summary, the consistent results across both instrument specifications, supported by strong first-stage statistics and identification tests, suggest that endogeneity is not driving the core findings. This reinforces the conclusion that ESG disclosure has a causal positive effect on environmental performance.

4.3. Mechanism Test

Previous findings have confirmed that corporate ESG reporting significantly promotes environmental performance. Based on the theoretical analysis of Hypothesis 1 proposed earlier, this paper argues that green innovation, media attention, and executive compensation are three important pathways through which corporate ESG information disclosure exerts its effects. With reference to the mediation effect test method by Wen and Ye [37], and in combination with Model (1), the following models are established to verify these mechanisms:

$${\mathrm{RD}/\mathrm{Media}/\mathrm{Salary}}_{it}={\beta }_0+{\beta }_1{\mathrm{ESG}}_{it}+\gamma {\mathbf{X}}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(2)

$${\mathrm{EP}}_{it}={\beta }_0+{\beta }_1{\mathrm{ESG}}_{it}+{\beta }_2{\mathrm{RD}/\mathrm{Media}/\mathrm{Salary}}_{it}+\gamma {\mathbf{X}}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(3)

4.3.1. Mediation Effect Test Based on Green Innovation

By conducting high-quality ESG disclosure, companies reduce information asymmetry and convey a strong commitment to environmental protection. This helps attract more sustainability-oriented investors, thereby securing long-term financial support for green innovation activities. As a result, firms can enhance their green innovation capabilities, which in turn leads to environmental benefits through cost reduction and the development of environmental technologies, ultimately improving corporate environmental performance.

In light of this, the current study incorporates green innovation as a mediating mechanism. Drawing on the research of Zhou et al. [38], it is posited that total R&D expenditure reflects a firm’s green innovation motivation. Accordingly, R&D intensity (R&D expenditure divided by total assets) is used to measure the level of corporate green innovation.

Table 6. Mechanism Test Results.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	EP	RD	EP	Media	EP	Salary	EP
ESG	0.445 ***	0.001 ***	0.441 ***	0.014 *	0.444 ***	0.033 ***	0.440 ***
	(25.848)	(7.833)	(25.628)	(1.888)	(25.796)	(5.799)	(25.680)
RD			2.629 ***
			(2.719)
Media					0.101 ***
					(4.609)
Salary							0.146 ***
							(4.319)
Constant	−12.387 ***	0.056 ***	−12.533 ***	−2.591 ***	−12.125 ***	9.215 ***	−13.729 ***
	(−21.386)	(8.495)	(−21.608)	(−9.267)	(−21.018)	(44.319)	(−20.786)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Industry FEs	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FEs	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	31,630	31,630	31,630	31,630	31,630	31,630	31,630
R2	0.385	0.376	0.386	0.423	0.386	0.439	0.386

* p < 0.1, *** p < 0.01. Notes: This table presents the results of the mediation effect tests. Columns (1), (3), (5), and (7) are regressions where the dependent variable is Environmental Performance (EP). Columns (2), (4), and (6) are the first-stage regressions for the mediators: Green Innovation (RD), Media Attention (Media), and Executive Compensation (Salary), respectively. Robust t-statistics are in parentheses.

presents the regression results of the mechanism test. From columns (2) and (3) of Table 6, it can be seen that the coefficients of corporate ESG disclosure on corporate green innovation are positive and significant at the 1% level. This indicates that corporate ESG disclosure can improve the level of corporate green innovation. This finding reveals a key pathway through which ESG disclosure affects environmental performance. Although previous research by Fang and Hu [6] suggested that ESG promotes overall corporate innovation, this study further clarifies that its impact has a “green-oriented” specificity. When green innovation (RD) is added to the main regression, the significance of the environmental performance coefficient decreases. This suggests that green innovation is one of the potential mechanisms through which ESG disclosure influences corporate environmental performance. The results of this study provide new perspectives and empirical evidence for understanding how ESG can shape and guide corporate innovation strategies to improve environmental performance.

4.3.2. Mediation Effect Test Based on Media Attention

ESG disclosure refers to the public release of information by companies regarding their environmental, social, and corporate governance practices. Its main goal is to make up for the limitations of traditional financial statement disclosures by providing non-financial information.By increasing the transparency and accessibility of a company’s environmental information, it becomes easier for the public to supervise the company. To meet the public’s demand for this information, media outlets tend to report more on companies with high-quality ESG disclosures. This draws media attention to the company’s environmental actions, creating a broad social supervision effect.

According to signal theory, high-quality ESG information sends a positive signal to the market about a company’s commitment to environmental responsibility. This attracts widespread attention from the media, which is an important information intermediary. With increased media attention, companies face ongoing external pressure from public opinion. This pressure encourages them to more actively take on social and environmental responsibilities. They work to protect their brand reputation and market acceptance, which ultimately leads to improved corporate environmental performance.

This study draws on the research of Yu et al. [39] and uses the natural logarithm of the number of online media reports (Media) as a measurement indicator.A higher value indicates greater media attention on the company in that year.The test results are presented in columns (4) and (5) of Table 6. The coefficients of corporate ESG disclosure on media attention are positive and significant at the 10% and 1% levels, respectively. This shows that corporate ESG disclosure can increase media attention. When media attention (Media) is added to the main regression, the significance of the environmental performance coefficient decreases. This indicates that media attention is one of the potential mechanisms through which ESG disclosure influences corporate environmental performance.

This finding reveals the mechanism of ESG disclosure from the perspective of signal theory. ESG disclosure not only directly communicates information about a company’s environmental responsibility but also, by attracting media attention as an amplifying channel, strengthens market supervision over the company’s environmental behavior. This, in turn, motivates the company to improve its environmental performance. This mechanism clarifies the pathway through which ESG disclosure improves environmental performance by attracting media attention, thereby refining the media supervision theory proposed by Qu [1]. Furthermore, unlike the study by Sun et al. [25], which primarily focused on media supervision triggered by negative events, this research shows that a company’s proactive, high-quality ESG disclosure can also become a focus of media attention.

4.3.3. Mediation Effect Test Based on Executive Compensation

Higher-quality ESG reporting indicates greater corporate transparency, enabling companies to convey more internal information to external stakeholders. This helps mitigate principal–agent problems, allowing shareholders to more accurately evaluate management efforts and enhancing the effectiveness of incentive mechanisms. It ensures that management focuses on sustainability and social responsibility when formulating and implementing strategies, which not only improves executive compensation but also motivates senior management to closely align with corporate interests, social responsibility, and environmental protection practices. As a result, executives devote more effort to improving the company’s environmental performance.

To minimize the influence of scale and magnitude, this study draws on the approach of Zhang et al. [40] and uses the natural logarithm of the total compensation of the top three executives (Salary) as a proxy for executive compensation. The test results in columns (6) and (7) of Table 6 show that executive compensation plays a partial mediating role between ESG disclosure and corporate environmental performance. This means that ESG disclosure can promote the improvement of corporate environmental performance through the channel of increasing executive compensation.

This finding not only confirms the key role of compensation incentives in the transmission mechanism of ESG disclosure but also provides empirical support for the theoretical proposal by Chen and Song [27] to “incorporate environmental performance into executive compensation contracts”. It further clarifies the governance function of improving compensation incentive mechanisms in promoting corporate green transformation.

4.3.4. Bootstrap Robustness Test

To further verify the reliability of our mediation results, we conduct bootstrap tests with 5000 replications. This method does not rely on normal distribution assumptions and provides more robust confidence intervals. The results in

Table 7. Bootstrap Mediation Test Results.

	Green Innovation	Media Attention	Executive Compensation
bs_1	0.0037 ***	0.0014 **	0.0049 ***
	[0.0022, 0.0053]	[0.0004, 0.0024]	[0.0033, 0.0064]
bs_2	0.4412 ***	0.4435 ***	0.4401 ***
	[0.4200, 0.4624]	[0.4228, 0.4643]	[0.4184, 0.4617]
bs_3	0.4449 ***	0.4449 ***	0.4449 ***
	[0.4238, 0.4661]	[0.4241, 0.4658]	[0.4233, 0.4666]
Observations	31,630

95% confidence intervals in brackets. Note: Bootstrap with 5000 replications. Models include control variables and year/industry fixed effects. ** p < 0.01, *** p < 0.001.

show that the indirect effects through all three mechanisms remain statistically significant. The 95% confidence intervals for green innovation [0.0022, 0.0053], media attention [0.0004, 0.0024], and executive compensation [0.0033, 0.0064] do not include zero. These findings confirm that our mediation results are robust and not sensitive to distributional assumptions. The bootstrap analysis thus provides strong additional support for our proposed mechanisms.

4.4. Further Analysis

4.4.1. Heterogeneity Test Based on Ownership Nature

Ownership structure plays a critical role in shaping corporate environmental performance. The impact of ESG information disclosure on environmental performance varies significantly between enterprises of different ownership types.

On the one hand, under the broader goal of sustainable development, state-owned enterprises (SOEs)—as key pillars of the national economy—face stricter government supervision and greater public scrutiny. They are subject to stronger political pressure and public expectations, making ESG disclosure an important tool for fulfilling their political and social responsibilities. SOEs are often required to not only meet sustainability targets but also undertake broader social obligations and respond more vigorously to environmental initiatives. In contrast, non-state-owned enterprises (non-SOEs) primarily face pressure from stakeholders and exhibit a clear market-oriented approach. Their disclosures tend to focus more on their own operational development.

On the other hand, SOEs generally encounter fewer financial constraints in environmental governance. Typically larger and with more established organizational structures, SOEs have stronger financing capabilities and are more willing to invest in green innovation and environmental facility upgrades. Non-SOEs, whose main objective is profit maximization, often prioritize economic outcomes and adhere strictly to cost-benefit principles. The sunk costs associated with green innovation may hinder voluntary initiatives, leading non-SOEs to overlook environmental issues or even sacrifice environmental quality for short-term gains.

Based on the nature of the actual controller, firms are categorized into SOEs and non-SOEs. As shown in columns (1) and (2) of

Table 8. Heterogeneity Test Results.

	Ownership		Internal Control		Industry Env. Sensitivity		Time
	(1) EP SOEs	(2) EP Non-SOEs	(3) EP High	(4) EP Low	(5) EP High	(6) EP Low	(7) EP 2018–2023	(8) EP 2011–2017
ESG	0.535 ***	0.400 ***	0.539 ***	0.402 ***	0.513 ***	0.414 ***	0.467 ***	0.419 ***
	(16.27)	(20.34)	(23.19)	(19.21)	(14.51)	(21.84)	(24.34)	(16.18)
Constant	−11.164 ***	−11.448 ***	−13.162 ***	−11.319 ***	−11.435 ***	−12.701 ***	13.014 ***	11.128 ***
	(−9.81)	(−17.19)	(−18.76)	(−15.76)	(−9.34)	(−19.77)	(−20.24)	(−13.54)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Industry FEs	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year FEs	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Group diff. p-value	0.000		0.000		0.000		0.024
Observations	8918	22,712	14,717	14,718	9420	22,210	19,885	11,745
R2	0.420	0.349	0.419	0.349	0.336	0.364	0.371	0.323

*** p < 0.01; t-statistics in parentheses. The p-values for between-group differences are based on the bootstrap-based Fisher permutation test with 1000 replications.

, the regression coefficients of ESG are significantly positive for both groups. However, the coefficient is notably larger for SOEs than for non-SOEs. An empirical p-value of 0.000, obtained through bootstrap sampling with 1000 replications, confirms that the difference in ESG coefficients between SOEs and non-SOEs is statistically significant. Thus, compared with non-SOEs, ESG reporting has a more substantial effect on improving environmental performance in SOEs.

4.4.2. Heterogeneity Test Based on Internal Control Quality

Internal control is a crucial internal governance mechanism within enterprises, led by management and involving all employees through established policies and procedural standards. Effective internal control standardizes management processes and continuously optimizes the internal governance system, thereby fostering a corporate culture attentive to environmental protection and social responsibility. This, in turn, enhances the transparency and credibility of ESG information disclosures.

Under a high-quality internal control system, companies can more efficiently translate ESG disclosures into actionable environmental management initiatives, strengthening the fulfillment of environmental responsibilities and reducing the risk of major environmental incidents caused by short-sighted managerial decisions. Furthermore, a robust internal control framework helps curb opportunistic behavior, lowers agency costs, and ensures that resources allocated to environmental protection are properly managed and effectively utilized.

Following the approach of Chen et al. [41], this study uses the logarithm of the Dibo Internal Control Index plus 1 to measure internal control quality. Firms are divided into “high internal control quality” and “low internal control quality” groups based on the median value, and groupwise regression is performed. The results, shown in columns (3) and (4) of Table 8, indicate that the coefficients of ESG are significantly positive in both groups but larger in the high internal control quality group. A between-group difference test confirms that this disparity is statistically significant. These findings suggest that higher internal control quality strengthens the positive effect of ESG information disclosure on corporate environmental performance.

4.4.3. Heterogeneity Test Based on Industry Environmental Sensitivity

On one hand, in industries with high environmental sensitivity, improvements in the quality of ESG disclosure signal to the market that the company emphasizes environmental management, while also revealing any existing environmental issues. If a company has environmental problems, it will attract the attention of nearby residents, leading to broader public scrutiny and supervision. Under both policy pressure and public oversight, companies in high environmental sensitivity industries are more proactive in enhancing their environmental performance to improve their corporate image and fulfill social responsibilities.

On the other hand, against the backdrop of increasing awareness of sustainable development and the implementation of green credit policies, companies in high environmental sensitivity industries face intensified financing constraints. Moreover, once environmental violations are detected, the resulting costs are significantly higher than those for industries with low environmental sensitivity. To reduce the high costs associated with environmental pollution and improve their financing capacity, companies in environmentally sensitive industries place greater emphasis on ESG information disclosure to secure more long-term financial support. This enables them to increase investment in environmental technology, thereby more substantially improving their environmental performance.

Drawing on the grouping method of Li et al. [42], this study divides the sample companies into high and low environmental sensitivity industries based on whether they belong to heavily polluting industries. Columns (5) and (6) of Table 8 present the estimated results of the impact of ESG information disclosure on the environmental performance of companies in industries with different levels of environmental sensitivity. The results show that the coefficients of ESG information disclosure on environmental performance are 0.513 and 0.414 for high and low environmental sensitivity industries, respectively, both significant at the 1% level. A Fisher’s permutation test yields a p-value of 0.000, indicating that the impact of ESG information disclosure on environmental performance is significantly stronger in high environmental sensitivity industries compared to low environmental sensitivity industries.

4.4.4. Heterogeneity Test Based on Time

We further examine whether the positive impact of ESG disclosure on environmental performance has changed over time, particularly considering the evolving regulatory landscape in China. The sample is split into two periods: 2011–2017 and 2018–2023. The results in columns (7) and (8) of Table 8 show that the coefficient for ESG disclosure is positive and statistically significant at the 1% level in both periods. However, the magnitude of the coefficient is notably larger in the more recent period (2018–2023, coefficient = 0.467) than in the earlier period (2011–2017, coefficient = 0.419).

A bootstrap-based Fisher permutation test confirms that this difference between the two periods is statistically significant, with a p-value of 0.024. This indicates that the effect of ESG information disclosure on improving corporate environmental performance became stronger after 2018.

This finding aligns with key regulatory developments in China. The year 2018 marked a turning point, as the China Securities Regulatory Commission (CSRC) revised the Code of Corporate Governance for Listed Companies, formally establishing a foundational framework for ESG disclosure. This regulatory enhancement likely increased the credibility and importance of ESG information. As a result, corporate ESG disclosures after 2018 became more substantive and were met with greater scrutiny from investors and the public. This heightened attention and the more formalized reporting environment appear to have amplified the role of ESG disclosure in driving tangible improvements in environmental performance.

4.5. The Moderating Role of Financial Constraints

To examine whether financial constraints affect the strength of the mediating pathways, we introduce financial constraints as a moderating variable. We measure financial constraints using the FC index, which is a comprehensive measure that captures a firm’s external financing difficulties (KONG and LIU [43]). To mitigate multicollinearity and facilitate interpretation, we use the mean-centered value of the FC index (denoted as FC_c) in our analysis. We estimate the following moderated mediation models following the approach of WEN and YE [44]:

$${\mathrm{RD}/\mathrm{Media}/\mathrm{Salary}}_{it}={\beta }_0+{\beta }_1{\mathrm{ESG}}_{it}+{\beta }_2\mathrm{FC}\_{\mathrm{c}}_{it}+{\beta }_3({\mathrm{ESG}}_{it} \times \mathrm{FC}\_{\mathrm{c}}_{it})+\gamma {\mathbf{X}}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(4)

$${\mathrm{EP}}_{it}={\beta }_0+{\beta }_1{\mathrm{ESG}}_{it}+{\beta }_2{\mathrm{RD}/\mathrm{Media}/\mathrm{Salary}}_{it}+\gamma {\mathbf{X}}_{it}+{\mu }_i+{\lambda }_t+{\epsilon }_{it}$$

(5)

In the first equation, we test whether financial constraints moderate the effect of ESG disclosure on the three mediators. The interaction term $ESG\times FC\_c$ captures this moderating effect. The second equation examines how each mediator influences environmental performance.

The results in

Table 9. Moderated Mediation Test Results: Financial Constraints.

	(1)	(2)	(3)	(4)	(5)	(6)
	RD	Media	Salary	EP	EP	EP
ESG	0.001 ***	0.013 *	0.033 ***	0.443 ***	0.445 ***	0.442 ***
	(7.47)	(1.92)	(5.82)	(25.62)	(25.78)	(25.67)
FC_c	0.002	−0.181	−0.097
	(0.57)	(−1.62)	(−1.13)
ESG × FC	−0.002 ***	−0.114 ***	−0.055 ***
	(−3.99)	(−4.72)	(−3.12)
RD				2.692 ***
				(2.78)
Media					0.102 ***
					(4.63)
Salary						0.144 ***
						(4.28)
Constant	0.089 ***	0.107	10.576 ***	−12.566 ***	−12.150 ***	−13.748 ***
	(10.39)	(0.29)	(38.11)	(−21.64)	(−21.03)	(−20.81)
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Industry FEs	Yes	Yes	Yes	Yes	Yes	Yes
Year FEs	Yes	Yes	Yes	Yes	Yes	Yes
Observations	31,242	31,242	31,242	31,242	31,242	31,242
R2	0.374	0.428	0.436	0.382	0.383	0.383

* p < 0.1, *** p < 0.01. Notes: This table presents the results of the moderated mediation effect tests with financial constraints as the moderator. Columns (1)–(3) are the first-stage regressions for the mediators: Green Innovation (RD), Media Attention (Media), and Executive Compensation (Salary), respectively. Columns (4)–(6) are the second-stage regressions where the dependent variable is Environmental Performance (EP). The interaction terms (ESG × FC) represent the moderating effect of financial constraints. Robust t-statistics are in parentheses.

show that financial constraints significantly weaken all three mediating pathways. The negative and significant coefficients for the interaction terms indicate that the positive effect of ESG disclosure on green innovation, media attention, and executive compensation becomes weaker when companies face higher financial constraints. This is likely because firms with limited financial resources have less capacity to fund green innovation projects, may receive less media coverage due to their weaker overall market position, and could have fewer funds available to link executive compensation to environmental performance targets.

These findings suggest that strong financial health supports companies in turning their ESG commitments into real environmental improvements. Even with high quality ESG disclosure, limited financial resources can reduce a company’s capacity to invest in green technology, attract positive media attention, or create effective executive incentives for better environmental performance.

5. Conclusions

5.1. Research Conclusions and Policy Implications

This study utilizes data from Shanghai and Shenzhen A-share listed companies spanning the period from 2011 to 2023. Focusing on environmental performance as the key outcome, it employs a two-way fixed effects model and a mediation effect model to investigate the impact of ESG information disclosure on corporate environmental performance and its underlying mechanisms. The empirical results demonstrate that: (1) high-quality ESG information disclosure significantly enhances corporate environmental performance, a conclusion that remains robust after a series of rigorous tests; (2) mechanism analyses indicate that ESG information disclosure improves environmental performance primarily by promoting green innovation, increasing media attention, and strengthening executive compensation incentives; (3) further analysis reveals that the positive effect of ESG information disclosure on environmental performance is more pronounced in state-owned enterprises, firms with high-quality internal control systems, and companies operating in industries with high environmental sensitivity.

These findings provide important empirical evidence for understanding the economic consequences of ESG information disclosure and offer valuable insights for reconciling conflicting conclusions in existing literature. While previous studies such as Eduard and Javier [7] emphasize the cost burdens associated with ESG activities, our results demonstrate that under China’s “dual-carbon” policy context, the environmental benefits of ESG disclosure through the three main channels of green innovation, media monitoring, and executive compensation incentives substantially outweigh its potential costs. This conclusion not only supports the positive ESG effects identified by scholars like Fang and Hu [6] and Wu and Xu [5], but also extends the research perspective to the crucial dimension of environmental performance. The heterogeneity analysis further clarifies the boundary conditions for ESG effectiveness, collectively advancing our understanding of ESG’s governance role.

Based on these findings, this study offers the following policy implications:

First, improve the incentive mechanisms for ESG information disclosure to promote corporate sustainable development. Based on our findings that show stronger effects in state-owned enterprises, the government should provide concrete incentives like tax benefits and green credit preferences to companies with high-quality ESG reports. Financial institutions should offer special financing options for green innovation projects, particularly in environmentally sensitive industries where our results show greater impact. This combined approach will help companies overcome cost barriers and encourage more investment in environmental improvement.

Second, give full play to the role of media supervision and strengthen external oversight of ESG information disclosure. Our research confirms that media attention significantly affects corporate environmental behavior. Therefore, we recommend creating a legal framework that protects media independence in ESG reporting. An information sharing platform should connect regulators, investors and media to improve oversight efficiency. Additionally, training programs for journalists will enhance their ability to identify and report ESG issues accurately, strengthening the overall monitoring system.

Third, improve the standards and regulatory system for ESG information disclosure and encourage companies to integrate ESG concepts into strategic management. Given the current voluntary nature of ESG reporting in China, we recommend developing unified national standards with clear measurement guidelines. This will reduce selective disclosure and improve data comparability. Furthermore, companies should link executive compensation to environmental performance indicators, as our results show this effectively motivates managers to prioritize sustainability goals in their decision-making.

5.2. Limitations and Future Research Directions

Despite its contributions, this study has several limitations that should be acknowledged. First, while we employ both a self-constructed environmental performance index and an alternative measure based on pollution fees, these proxies may not fully capture all dimensions of corporate environmental impacts. The index approach, though comprehensive, relies on disclosed environmental initiatives rather than actual environmental outcomes.  Second, regarding our key explanatory variable, the Hua Zheng ESG rating, while widely used in Chinese market research, shares common limitations with other ESG metrics. These include potential measurement errors arising from its reliance on corporate disclosures and the inherent subjectivity in weighting different ESG components.  Third, our sample is limited to Chinese Shanghai and Shenzhen A-share listed companies. While this provides valuable insights into an important emerging market, the findings may not be readily generalizable to other institutional contexts, emerging markets with different regulatory environments, or private firms that face different disclosure pressures and governance structures. 

These limitations suggest promising directions for future research. Subsequent studies could incorporate more objective and dynamic environmental data, such as real-time emission monitoring statistics. Researchers could also develop more refined ESG measurement approaches that better account for industry-specific environmental impacts.