Why Do ESG Rating Differences Affect Audit Fees?—Dual Intermediary Path Analysis Based on Operating Risk and Analyst Earnings Forecast Error

Abstract

As environmental, social, and governance (ESG) issues become increasingly important, ESG ratings have become a significant factor influencing audit fees for businesses. However, ESG ratings are typically assessed by multiple agencies or rating firms and, due to differences in evaluation criteria, methodologies, and data sources, the ratings provided by different institutions may vary considerably. Therefore, research on the impact of discrepancies in ESG ratings on audit fees is of great significance. This paper examines this phenomenon by analyzing a sample of Chinese listed companies from 2015 to 2022, yielding 3056 observational values through various methodologies. The study employs two-way fixed effects methods. The findings indicate that discrepancies in ESG ratings significantly elevate enterprises’ audit expenses, with operating risk and analyst earnings forecast errors serving as intermediary factors. Additionally, media attention intensifies these effects by increasing corporate disclosure, intensifying regulatory pressure, and heightening reputational risks for the company, and the positive impact of ESG rating discrepancies on audit fees is more significant when the “Big 4” accounting firms are involved in the audit. The research offers insights for enterprises, auditors, and regulatory bodies, contributing to the enhanced implementation of the ESG concept and fostering sustainable enterprise development.

1. Introduction

The global importance of ESG (environmental, social, and governance) issues is increasingly prominent, encompassing multiple domains such as corporate operations, investment decisions, global policies, and social responsibility. As challenges such as climate change, resource depletion, social inequality, and governance issues become more pressing, governments, businesses, and investors worldwide are actively promoting sustainable development, striving to balance economic growth with environmental protection and social responsibility. In response, the international community has introduced a series of relevant standards and reports, such as the United Nations’ “Who Cares Wins” report and the United Nations Principles for Responsible Investment (PRIs). These documents provide in-depth explanations of the ESG concept and its significance, and emphasize the necessity of incorporating it into investment assessment frameworks. ESG issues not only concern the long-term development of businesses but also relate to the global sustainability of ecosystems, society, and economies, carrying profound global implications.

ESG ratings are playing an increasingly crucial role in investment decisions. These ratings can assist investors in accurately assessing an enterprise’s investment potential, offering an essential reference point for decision-making. However, as ESG rating standards become more diverse and rating agencies diverge, discrepancies in the understanding and application of ESG information are emerging between investors and enterprises. Such disagreements not only influence investment decisions but also have potential implications for companies’ audit costs. The divergence in ESG rating standards means that different rating agencies evaluate companies’ performance in environmental, social, and governance aspects using varying criteria. Investors make different investment decisions based on these diverse ratings, which compels companies to provide tailored reports and explanations according to each rating standard when communicating with different investors. As a result, this increases the disclosure and communication costs for companies. Furthermore, audit firms are increasingly required to consider the disclosure and transparency of ESG factors when evaluating a company’s financial statements, as these factors directly impact the comprehensiveness and accuracy of the company’s financial position. Given that ESG metrics often include non-financial information and cover multiple domains, such as environment, society, and governance, audit firms need to develop more detailed and specialized auditing procedures. These procedures include analyzing the effectiveness of environmental impact assessments, reviewing social responsibility reports, and examining the independence and transparency of corporate governance structures. This is particularly important in a global context with varying regulatory environments, ensuring that companies comply with relevant laws and standards, which further affects the complexity and workload of audits. Variations in ESG ratings lead auditors to require additional procedures and reviews to ensure compliance and authenticity in environmental, social, and governance areas. Consequently, in the context of the rapid growth of global sustainable investment, understanding how ESG rating differences impact audit fees has become a significant concern for enterprises and auditors today.

Recent studies have explored the various impacts of ESG rating discrepancies on businesses, including effects on corporate value impairment [1], tax avoidance [2], and credit availability [3]. However, few studies have focused on the perspective of audit firms regarding ESG rating discrepancies, particularly in the context of Chinese auditing institutions. Therefore, this paper examines the influence of ESG rating divergence on enterprise audit expenses from the perspective of auditing institutions. Utilizing ESG rating data from six major sources—Bloomberg, Wind, Sino-Securities, FTSE Russell, SynTao Green Finance, and SusallWave—we calculate the ESG rating discrepancies. Control variables are gradually incorporated based on the relevant literature. To account for heterogeneity across years and industry characteristics, capture dynamic changes over time, and enhance the explanatory power of the model, a two-way fixed effects linear regression model is employed. The model uses audit fee data from the CSMAR database for the period of 2015–2022 to test the effect of ESG rating discrepancies on audit fees, aiming to provide decision-making insights for policymakers, auditing institutions, and corporate management. Specifically, how ESG rating discrepancies may increase business risk and analysts’ earnings forecast errors in Chinese firms, thereby driving up audit fees, has not been fully addressed in the existing literature. Consequently, this study introduces two mediating variables to conduct empirical analysis, filling this gap and shedding light on the potential impact pathways of ESG rating discrepancies on audit fees. Furthermore, this paper is the first to explore the moderating role of media attention in the relationship between ESG rating discrepancies and audit fees, providing feasible suggestions for reducing audit costs for listed companies in China.

The next section reviews the literature and develops the hypotheses, followed by the research design and methodology. The results and discussion provide insights into the findings, and the paper concludes with practical implications and avenues for future research.

2. Research Hypotheses

2.1. ESG Rating Divergence and Audit Fees

With the introduction of “carbon neutrality” and “carbon peak” goals, sustainable development has assumed a growing significance in corporate governance. Within this framework [4], ESG (environmental, social, and governance) ratings of enterprises have emerged as crucial indicators for investors and decision-makers [5]. A high ESG rating typically signifies enhanced investment sustainability [6], improved investment efficiency [7], increased enterprise value [8], and diminished corporate credit risk [9]. In China, ESG research is gaining increasing attention, with studies in this area becoming more comprehensive. Notable research focuses on aspects such as enterprise green innovation [10], digital transformation [11], and the total factor productivity of family businesses [12].

Chatterji et al. (2016) [5] compared the scores of the same enterprise given by various ESG rating agencies and discovered significant inconsistencies among these ratings. Such discrepancies in ESG ratings can lead to divergent risk assessments for the same company, ultimately affecting investment decisions [13]. The divergence in ESG ratings can have both negative and positive implications. For instance, variation in ESG ratings significantly enhances the stock price synchronization of rated companies [14]. Furthermore, this divergence diminishes the accuracy of analysts’ earnings forecasts [15] while simultaneously encouraging a higher level of voluntary information disclosure by enterprises [16].

Differences in ESG ratings not only significantly influence investor decisions but can also spark a chain reaction in other areas, particularly affecting the audit process and corresponding fees. The ESG performance of companies is a crucial factor auditors consider during financial audits, and variations in ratings can increase the complexity and uncertainty of audit tasks. When different rating agencies assign varying ESG ratings to the same company, auditors might need to allocate more resources to thorough verification, assessing corporate social responsibility and governance structures to ensure financial reporting is transparent and accurate. Consequently, discrepancies in ESG ratings could be a key factor in altering audit fees. This paper will subsequently examine how variations in ESG ratings impact corporate audit fees.

How does the divergence in ESG ratings affect corporate audit fees?

Research indicates that disparities in ESG ratings have significant negative effects on corporate credit rating adjustments [17]. As an essential evaluation of corporate credit status, changes in credit ratings often signal shifts in enterprise credit risk. To effectively address potential changes in credit risks, auditors must carry out more rigorous and detailed audit procedures to ensure the financial report accurately reflects the enterprise’s true financial situation and potential risks. This demand for additional auditing inevitably increases audit costs.

Moreover, ESG rating divergences can significantly inflate the audit risk premium for enterprises [18]. This premium represents the extra compensation auditors require when assessing corporate risk, adding to audit costs. The rise in these costs is not only due to more complex audit procedures and increased audit resources but also stems from the extra efforts auditors make to minimize the risk of audit failures.

Additionally, differences in ESG ratings heighten the incentive for corporate management to engage in earnings management [19]. Such behavior undermines the principles of accuracy and transparency in financial reporting, making it considerably more difficult for auditors to detect and correct financial misstatements, thereby raising the audit risk. To tackle this challenge, auditors must allocate more resources to ensure audit quality, further pushing up audit costs.

Based on the above analysis, this paper makes the following assumption:

Hypothesis H1:

Discrepancies in ESG ratings increase audit fees.

2.2. Mechanism Inspection of Operational Risk

In analyzing the impact of variations in ESG ratings on enterprises’ audit costs, it is crucial to delve into the underlying mechanisms at play. Disparities in ESG ratings often highlight the inherent uncertainties that companies encounter in environmental, social, and governance dimensions, which can significantly translate into operational risks. The accumulation of operational risks directly increases the complexity of the auditing process and subsequently drives up audit costs.

In this context, operational risk acts as an intermediary, linking ESG rating disparities with audit costs. Firstly, the widening of ESG rating discrepancies significantly exacerbates market information asymmetry [20]. When companies encounter significant discrepancies in ESG performance assessments from various rating agencies, investors and stakeholders are unable to clearly assess the company’s social responsibility and governance status [21]. This undermines market confidence in their sustainability and compliance, thereby amplifying investors’ and stakeholders’ doubts [22]. When investor sentiment is depressed, they tend to adopt more cautious investment strategies, leading to reduced capital inflows into companies [23]. This results in declining stock prices, higher financing costs [24], and, subsequently, increases in the operational risks faced by firms, compelling management to respond more vigorously to external pressures. As operational risks rise, auditors must implement more stringent audit procedures for high-risk enterprises to ensure the reliability of financial reporting, often involving comprehensive reviews of internal controls and risk management, especially regarding the verification of ESG-related information. Consequently, operational risk mediates the relationship between ESG rating discrepancies and audit costs.

Based on the above analysis, this paper makes the following assumption:

Hypothesis H2:

Discrepancies in ESG ratings increase audit fees by exacerbating operational risk.

2.3. Mechanism Test of Analyst Earnings Forecast Error

ESG rating divergence can trigger a series of chain reactions in the capital market, exerting a profound and multi-dimensional impact. It not only influences the internal operational strategies of enterprises and their valuation by external markets [1] but also significantly disrupts analysts’ accuracy in the process of information transmission and interpretation. Analysts play a central role in the integration of information and future forecasting in capital markets. Wu Hao (2020) [25] pointed out that the quality of corporate information is a key factor influencing the accuracy of analysts’ predictions. The ambiguous positioning of ESG rating standards across different agencies leads to the transmission of competing ESG information to the market, which in turn deteriorates the quality of market information [26] and increases analysts’ earnings forecast errors.

In the modern capital market structure, the determinants of audit costs are complex, encompassing various dimensions such as company size and audit risk [27]. Among these, the quality of enterprise information and market expectations are pivotal factors affecting audit cost levels. This relationship indicates a link between analysts’ forecast errors and corporate audit expenses. Analysts’ errors in earnings forecasts indicate that there is a lack of consensus in the market regarding the interpretation of information, leading to divergent opinions among market participants [28] and the emergence of cognitive biases. This, in turn, worsens information asymmetry and uncertainty [29].

In this context, to ensure the accuracy and compliance of companies’ financial reports, auditors often need to invest additional time and effort in verification, thereby increasing the complexity and cost of the audit [30]. When companies encounter significant ESG rating differences, analysts face heightened challenges in predicting future financial performance due to increased information asymmetry and uncertainty. This situation significantly raises the cost of information processing for analysts and exacerbates errors in earnings forecasts, which are ultimately reflected in increased enterprise audit costs [15].

Based on the above analysis, this paper makes the following assumption:

Hypothesis H3:

Discrepancies in ESG ratings increase audit fees by exacerbating analyst surplus forecast errors.

2.4. The Interaction Effect of Media Attention and the Divergence in ESG Ratings

The relationship between ESG rating discrepancies and corporate audit fees extends beyond interactions between companies and auditors. The media holds a vital position in shaping public perception through information dissemination. The extent of media focus significantly influences the speed and scope of information spread.

When a company garners significant media attention, this trend can accentuate discrepancies in ESG ratings, notably influencing audit costs. Firstly, heightened media scrutiny results in the public, investors, and other stakeholders closely monitoring corporate behavior and performance. This scrutiny enhances enterprise information disclosure [31]. When discrepancies in ESG ratings arise, particularly concerning unmet market or public expectations in environmental and social responsibilities, the complexity and depth of audits increase. To ensure the accuracy of financial statements and the integrity of corporate disclosures, auditors are compelled to allocate more time and resources to thoroughly reviewing financial information.

Additionally, significant media attention could elevate reputational risks for companies [32]. As a result, companies may proactively seek auditors to perform more stringent audits to assuage investor and public concerns and to safeguard or enhance their public image through high-quality financial reporting.

Moreover, from a market dynamics standpoint, media attention amplifies the focus of investors and regulatory institutions on corporate ESG performance. Increased regulatory pressure compels enterprises to strengthen or rectify their internal control and risk management mechanisms [33]. This requires auditors to undertake more comprehensive testing and evaluation during the audit process, thereby broadening the scope and depth of audit work.

Based on the above analysis, this paper makes the following assumption:

Hypothesis H4:

Discrepancies in ESG ratings significantly increase audit fees when companies are under media attention.

2.5. Interaction Effect of BIG 4 and ESG Rating Divergence

In the realm of global accounting and auditing, the Big 4 international accounting firms—hereafter referred to as the “Big 4”—hold a dominant market position due to their expansive international networks, extensive industry experience, and exceptional service quality [34]. Regarding ESG rating discrepancies, the variance between the “Big 4” and other firms in addressing complex matters and meeting stringent regulatory standards results in a noticeable disparity in audit cost fluctuations.

On the one hand, the “Big 4” accounting firms demonstrate clear advantages in managing high-risk projects that attract significant public attention, thanks to their strong brand presence and solid reputation. Divergent ESG ratings often bring increased audit risk and complexity, particularly in assessing compliance with environmental and social responsibilities. Equipped with a more professional audit team, an advanced technical support system, and extensive ESG-related experience [35], the “Big 4” can deliver thorough and comprehensive services. These professional services typically come with higher audit costs due to complex audit procedures and an elevated level of risk management. Additionally, clients of the “Big 4” are often large multinational or heavily regulated firms that must adhere to stringent ESG standards globally. In instances of divergent ESG ratings, such companies usually implement rigorous audit measures to uphold their corporate image and meet international standards, ensuring the accuracy and transparency of their ESG reporting. Leveraging their global influence and professional expertise [36], the “Big 4” are the preferred audit partners for these companies, contributing to higher audit costs.

In conclusion, the professionalism and complexity with which the “Big 4” firms address ESG rating discrepancies enhance the positive impact of audit costs influenced by these differences. In contrast, the “non-four” firms lack sufficient resources, technology, and global influence, resulting in less pronounced increases in audit costs under similar circumstances [34].

Based on the above analysis, the following assumption is proposed:

Hypothesis H5:

Discrepancies in ESG ratings significantly increase audit fees when the audit firm is a “Big 4”.

3. Data and Methods

3.1. Data and Samples

We examined the impact of ESG rating divergence on corporate audit expenses using a sample of listed companies from 2015 to 2022. Because the ESG rating system gradually matured during this period, relevant policies and regulations were gradually strengthened, and the availability and completeness of data were ensured. In addition, the market’s increased attention to ESG investments has driven a shift in corporate disclosure of ESG information, which further provides an effective timeframe for the study. Therefore, this time period provides a suitable sample period to study the impact of ESG rating divergence on audit fees and its impact mechanism. The sample selection process was as follows: First, we excluded financial and insurance companies, as they differ significantly from other listed companies in terms of their main business activities, company size, and information disclosure. Second, we excluded (*) ST listed companies due to anomalies in financial indicators and information disclosure. Third, we eliminated listed companies with a short history of listing and inadequate historical information. Fourth, we removed samples with missing data for audit charges and control variables. Ultimately, we had 3056 annual company-sample observations. To reduce the impact of extreme values on empirical results, continuous variables were winsorized at the 0.01 and 0.99 levels using winsor2. Specifically, extreme values in the top and bottom 1% of the data were replaced with the corresponding 1st and 99th percentile observations, respectively. In this study, ESG rating divergence affects audit fees by influencing operational risk and analyst surplus forecast errors, which in turn affect audit fees. Failure to treat extreme values can distort the true impact of ESG rating divergence on audit fees by causing these data to dominate the regression model due to the anomalous financial or operational metrics of certain companies. By shrinking the tails, this study is able to more accurately reflect the relationship between the core variables and ensure that the conclusions are not disturbed by a few extreme observations. ESG rating divergence data were sourced from Bloomberg, Wind, Sino-Securities, FTSE Russell, SynTao Green Finance, and the SusallWave database, while other data were obtained from the CSMAR database. Through the collection of ESG rating data from six rating agencies from 2015 to 2022, reference to previous studies with ESG rating data will use stata 17 software to calculate the generation of ESG rating divergence data, and for the rest of the control variables and dependent variables we use Python 3.11 software to read the data in the CSMAR database; excel software to summarize, organize, and import them into the stata software; and a two-way fixed method. The fixed industry and year effects model is designed to control industry and time effects to ensure the accuracy of the model results. The fixed industry effect helps to exclude the impact of inter-industry differences on audit fees, and the fixed year effect reduces the interference of macroeconomic fluctuations and policy changes, thus accurately identifying the impact of ESG rating divergence on audit fees. By collecting panel data and analyzing them in regression, the mediating role of operational risk and surplus forecasting errors is revealed, thus enhancing the credibility of the research findings.

3.2. Formula Design and Variable Definition

This article employs a bidirectional fixed effects model for regression analysis. To assess the impact of ESG rating divergence on companies’ audit expenses (as posited in hypothesis H1), we reference Xiaofang et al. (2021) [37] and propose Formula (1) to conduct an empirical test:

$$\mathrm{F}\mathrm{E}{\mathrm{E}}_{\mathrm{i},\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\beta }}_1\mathrm{E}\mathrm{S}\mathrm{G}\_\mathrm{D}\mathrm{i}{\mathrm{s}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_2\mathrm{C}\mathrm{O}\mathrm{N}\mathrm{T}{\mathrm{R}}_{\mathrm{i},\mathrm{t}}+\sum \mathrm{Y}\mathrm{e}\mathrm{a}\mathrm{r}+\sum \mathrm{I}\mathrm{n}\mathrm{d}+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}$$

(1)

In this paper, the dependent variable, FEE, represents the audit fee for company I during period t. Following the methodology outlined by Baixing Li et al. (2019) [38], we utilize the natural logarithm of the audit costs of listed companies as the measure for audit costs. The primary independent variable, ESG_Dis, is based on Avramov et al. (2022) [39]. Initially, each grader is ranked according to their data provider’s original rating scale. For each company, we calculate the normalized percentile rank (0–1), standardizing the unit of measurement and generating the ranking variable. Subsequently, we compute the standard deviation of scoring rankings between different institutions in pairwise comparisons. Ultimately, this process leads to the calculation of divergence variables associated with the ESG ratings for listed companies. α represents the intercept term, which is the value of FEE when ESG_Dis and all controls are zero. $\beta$ is the regression coefficient, which indicates the extent to which the independent variable ESG_Dis or the control variables affect FEE, and $\epsilon$ is the error term, which represents the change in the dependent variable FEE in the unexplained portion of the regression model that is not accounted for by the independent and control variables. CONTR encompasses all control variables in this study. Drawing on Fang Xiao and Lingxiu Guo et al. [37,40], we plan to control for factors including company size (SIZE), asset–liability ratio (Lev), return on assets (ROA), board size (Board), proportion of independent directors (Indep), largest shareholder’s ownership ratio (Top1), TobinQ (TobinQ), and the affiliation with a “Big 4” accounting firm (BIG 4). Among them, TobinQ (TobinQ) reflects the company’s market value and capital expenditure ratio; a higher TobinQ implies better growth of the company and a higher market expectation, which may affect the company’s performance in the capital market, the demand for external auditing, and, thus, the audit fee. Board size (Board) is usually related to the governance structure and decision-making efficiency of the company. Larger boards imply more complex governance structures and thus require more audit work. Therefore, using the number of directors as a control variable helps to eliminate the effect of differences in corporate governance structure on audit fees. Refer to

Table 1. Variable definitions.

Variable	Name and Calculation Description
FEE	Audit costs (audit costs to take the natural logarithm).
ESG_Dis	ESG ratings differ when calculating the standard deviation of the rating ranking between different institutions.
Size	Company size (the natural logarithm of the annual total assets).
Lev	Asset–liability ratio (the total liabilities at the end of the year divided by the total assets at the end of the year).
ROA	Total assets net profit margin (average balance of net profit/total assets).
Board	The number of directors; the number of those on the board of directors.
Indep	Proportion of independent directors (independent directors divided by the number of directors).
Top1	The proportion of the largest shareholder (the number of the largest shareholder/total number of shares).
TobinQ	TobinQ (market value of outstanding shares + number of non-outstanding shares’ net assets per share + book value of liabilities)/total assets.
Big 4	Where the “Big 4” accounting firms are audited by the Big 4 (PWC, DDT, KPMG, EY), this is 1; otherwise, it is 0.
ORisk	Operating risk (the degree of volatility of the companies’ profits).
Media	Media attention (the total number of current network-media negative news reports of listed companies).
FER	Analyst earnings forecast error (the average error of the analyst earnings forecast).

for the definitions of specific variables.

In order to verify the mechanism of ESG rating divergence on companies’ audit fees, this paper draws on the studies of Lingxiu Guo and Xuedan Wang et al. [40] to propose testing the mechanism of the impact of business risk using Equations (2) and (3), and the mechanism of the impact of analysts’ surplus prediction error using Equations (4) and (5). Drawing on the Ting Jiang mediation effect two-step approach [41], the explanatory variable ESG_Dis is regressed on the explanatory variable FEE, then the explanatory variable ESG_Dis is regressed on the mediator variable ORISK, and finally the effect of the mediator variable on the explanatory variable is analyzed by drawing on the literature studies.

$$ORIS{K}_{i,t}={\alpha }_0+{\beta }_{1}ESG\_Di{s}_{i,t}+{\beta }_{2}CONT{R}_{i,t}+\sum Year+\sum Ind+{\epsilon }_{i,t}$$

(2)

$$FE{E}_{i,t}={\alpha }_0+{\beta }_{1}ESG\_Di{s}_{i,t}+{\beta }_{2}ORIS{K}_{i,t}+{\beta }_{3}CONT{R}_{i,t}+\sum Year+\sum Ind+{\epsilon }_{i,t}$$

(3)

$$FE{R}_{i,t}={\alpha }_0+{\beta }_{1}ESG\_Di{s}_{i,t}+{\beta }_{2}CONT{R}_{i,t}+\sum Year+\sum Ind+{\epsilon }_{i,t}$$

(4)

$$FE{E}_{i,t}={\alpha }_0+{\beta }_{1}ESG\_Di{s}_{i,t}+{\beta }_{2}FE{R}_{i,t}+{\beta }_{2}CONT{R}_{i,t}+\sum Year+\sum Ind+{\epsilon }_{i,t}$$

(5)

In Formula (2), ORISK represents the company’s operating risk. This is based on the work of Xiaohong Dong and Zhenghan Sun (2023) [42], who use the variability of a company’s earnings to assess the magnitude of operating risk. This paper considers the period from year t−1 to t+1 as a cycle to calculate operating risk. In Equation (3), the mediation variable ORISK is incorporated into Equation (1), while the other variables remain unchanged. In Equation (4), FER denotes the error in the analyst’s earnings forecast, following the approach of Yongqiang Ma and Weizhong Chen (2024) [43]. The denominator reflects the average forecast error made by analysts. Equation (5) introduces the mediation variable FER into the framework of Equation (1), with all other variables remaining consistent with those in Equation (1).

In order to verify the interaction effect of media attention and Big4 on the results of this paper, this paper draws on the study of Chunhua Tao and Xin Chen et al. [44] and proposes using Equations (6) and (7) for testing.

$$FE{E}_{i,t}={\alpha }_0+{\beta }_{1}ESG\_Di{s}_{i,t}+{\beta }_{2}ESG\_Di{s}_{i,t}Medi{a}_{i,t}+{\beta }_{2}CONT{R}_{i,t}+{\beta }_{3}Year+{\beta }_{4}Ind+{\epsilon }_{i,t}$$

(6)

$$FE{E}_{i,t}={\alpha }_0+{\beta }_{1}ESG\_Di{s}_{i,t}+{\beta }_{2}ESG\_Di{s}_{i,t}Big{4}_{i,t}+{\beta }_{2}CONT{R}_{i,t}+{\beta }_{3}Year+{\beta }_{4}Ind+{\epsilon }_{i,t}$$

(7)

In Equation (6), “Media” denotes media attention as the interaction effect variable, while the remaining variables are essentially identical to those in Equation (1). The media attention variable is quantified by the total count of negative news reports concerning online media, as documented by Chunhua Tao et al. (2023) [44]. In Equation (7), “Big4” indicates whether the interaction effect variable pertains to the “Big 4” accounting firms, with the other variables essentially mirroring those in Equation (1).

3.3. Descriptive Statistics

Table 2. Descriptive statistics of the variables.

Variable	N	Mean	Std. Dev.	Min	Max
FEE	3056	14.56	0.858	13.06	17.37
ESG_Dis	3056	0.191	0.0997	0.0141	0.462
Size	3056	23.88	1.211	21.56	26.43
Lev	3056	0.469	0.184	0.0897	0.837
ROA	3056	0.0621	0.0553	−0.0705	0.222
Board	3056	2.184	0.206	1.609	2.639
TobinQ	3056	2.020	1.459	0.816	8.545
Big 4	3056	0.180	0.384	0	1
Indep	3056	0.382	0.0605	0.333	0.571
Top1	3056	0.375	0.153	0.0992	0.731

presents the results of the descriptive statistical analysis for the dependent, independent, and control variables in this study. The average ESG rating divergence stood at 0.191, with a standard deviation of 0.0997, indicating a relatively high variance among the companies sampled. The mean audit cost was 14.56, accompanied by a standard deviation of 0.858, which aligns with findings in the existing literature. The average company size was 23.88, with a standard deviation of 1.211, suggesting significant size differences among the sampled companies. The mean asset–liability ratio was 0.469, with a standard deviation of 0.184; the maximum and minimum ratios recorded were 0.837 and 0.0897, respectively, highlighting substantial variation in these ratios among the companies. The average net profit margin relative to total assets was 0.0621, with a standard deviation of 0.0553, indicating minor variability across the sample. The mean number of directors was 2.184, with a standard deviation of 0.206, signaling minimal differences in board size among the companies. Tobin’s Q had a mean value of 2.020 and a standard deviation of 1.459, reflecting significant disparity among the sampled companies. The standard deviation for the proportion of independent directors was 0.0605, pointing to slight variability in their proportion among these companies. Finally, the maximum shareholding ratio of the largest shareholders ranged from 0.731 to a minimum of 0.0992, indicating considerable variation in the shareholding ratios within the sample.

4. Empirical Results Analysis

4.1. Analysis of the Panel Regression Results

The results of the master regression analysis on the impact of ESG rating divergence on enterprise audit costs are presented in

Table 3. Results of the master regression.

Variable	(1)	(2)	(3)
	FEE	FEE	FEE
ESG_Dis	0.1007 **	0.0826 **	0.0966 **
	(0.0248)	(0.0375)	(0.0139)
Size		0.4014 ***	0.3944 ***
		(0.0000)	(0.0000)
Lev		−0.0384	−0.0479
		(0.5109)	(0.4119)
ROA		−0.5354 ***	−0.4996 ***
		(0.0000)	(0.0000)
Board		0.0426	0.0309
		(0.2498)	(0.4746)
Indep			−0.0614
			(0.6163)
Top1			0.2223 ***
			(0.0090)
TobinQ			−0.0094 **
			(0.0484)
Big 4			0.2209 ***
			(0.0000)
Year	control	control	control
Ind	control	control	control
_cons	14.2498 ***	4.6396 ***	4.7636 ***
	(0.0000)	(0.0000)	(0.0000)
N	3056	3056	3056
adj. R2	0.2266	0.3952	0.4103

Note: *** and ** are significant at the 1% and 5%, respectively.

. The divergence in ESG ratings positively and significantly affects enterprise audit costs by increasing information asymmetry, raising audit risks, and complicating audit procedures. In Column (1), the coefficient for ESG rating divergence (ESG_Dis) is 0.1007, which is significant at the 5% level. This preliminary finding suggests that ESG rating divergence notably raises audit costs; as the divergence increases, so do the audit expenses. Columns (2) and (3) incorporate multiple control variables into the analysis introduced in Column (1). In this adjusted analysis, the coefficients for ESG_Dis were 0.0826 and 0.0966, respectively, both maintaining significance at the 5% level. This outcome indicates that the positive effect of ESG rating divergence on audit costs remains unaffected by other control variables, demonstrating high stability and reliability in its impact. These regression results support hypothesis H1.

4.2. Discussion of Influence Mechanism

To examine the mediating influence of operating risk (ORisk) and analyst surplus forecast deviation (FER) on the effect of ESG rating divergence on corporate audit expenses (FEE), a detailed analysis of the results in

Table 4. Mechanism test of operating risk and analyst surplus forecast error.

Variable	(1)	(2)	(3)	(4)
	ORisk	FEE	FER	FEE
ESG_Dis	0.0116 ***	0.0966 **	0.5363 **	0.0966 **
	(0.0034)	(0.0139)	(0.0191)	(0.0139)
Size	−0.0038 **	0.3944 ***	0.1035	0.3944 ***
	(0.0178)	(0.0000)	(0.2692)	(0.0000)
Lev	−0.0086	−0.0479	−1.0337 ***	−0.0479
	(0.1432)	(0.4119)	(0.0024)	(0.4119)
ROA	0.0041	−0.4996 ***	−11.0501 ***	−0.4996 ***
	(0.6872)	(0.0000)	(0.0000)	(0.0000)
Board	−0.0023	0.0309	0.0265	0.0309
	(0.5976)	(0.4746)	(0.9160)	(0.4746)
Indep	0.0060	−0.0614	0.4988	−0.0614
	(0.6291)	(0.6163)	(0.4848)	(0.6163)
Top1	−0.0165 *	0.2223 ***	0.1629	0.2223 ***
	(0.0534)	(0.0090)	(0.7422)	(0.0090)
TobinQ	−0.0008	−0.0094 **	0.0871 ***	−0.0094 **
	(0.1053)	(0.0484)	(0.0017)	(0.0484)
Big4	0.0044	0.2209 ***	−0.0427	0.2209 ***
	(0.1199)	(0.0000)	(0.7951)	(0.0000)
Year	control	control	control	control
Ind	control	control	control	control
_cons	0.1438 ***	4.7636 ***	−3.4315	4.7636 ***
	(0.0006)	(0.0000)	(0.1558)	(0.0000)
N	3056	3056	3056	3056
adj. R2	−0.0905	0.4103	0.0142	0.4103

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively.

was conducted.

In Column (1), the coefficient of ESG_Dis for ORisk is 0.0116, demonstrating a significant positive correlation at the 1% level. This indicates that a divergence in ESG ratings markedly elevates the operational risk of businesses. This is attributed to the fact that ESG rating divergence triggers widespread stakeholder skepticism about a company’s ability to be sustainable [21], intensifying investor doubts, which in turn changes investment decisions in the company, causing volatility in the company’s share price [45] and increasing the uncertainty and risk level of the company’s operations. Column (2) reveals that the coefficient of ESG_Dis for FEE is 0.0966, and also shows a significant positive correlation at the 5% level, thereby confirming the direct and positive impact of ESG rating divergence on audit costs. Increased operational risk induced by divergent ESG ratings may lead to a crisis in business performance [46], which in turn exacerbates the business risk of audit firms [47], which are required to perform more detailed audit procedures in order to issue a correct audit opinion, to ensure audit quality, and to mitigate their own risk [48], which requires audit firms to charge higher audit fees to compensate for the cost [49]. Overall, operational risk serves as a crucial intermediary between ESG rating divergence and audit fees. This finding supports research hypothesis H2.

Based on the findings from Column (3), the coefficient of ESG_Dis for FER is 0.5363, which is significantly positive at the 5% level. This indicates that discrepancies in ESG ratings substantially increase the bias in analysts’ earnings forecasts. The inconsistent assessments of corporate ESG performance by various rating agencies make it challenging for analysts to accurately evaluate the future profitability of enterprises [50]. This inconsistency affects the judgment of capital market participants and results in considerable deviations in their earnings forecasts [51]. In Column (4), the coefficient of ESG_Dis for FEE remains at 0.0966 and is significantly positive, suggesting that the positive and direct impact of ESG rating discrepancies on audit fees persists, even when taking into account the deviations in analyst earnings forecasts. Jiesheng Huang points out that the higher the accuracy of analysts’ surplus forecasts, the higher the quality of financial information they convey to stakeholders [52]. On the contrary, when analysts’ forecast surplus errors, the corresponding poor quality of financial information will convey biased information to investors and ultimately harm their interests [43], investors will generate negative emotions, auditors will avoid audit failures by increasing audit prudence [53], and auditors will invest more time and resources to verify the accuracy of the financial statements, which will push up the audit fee. This will consequently drive up audit costs, thus supporting hypothesis H3.

In conclusion, operating risk and analyst surplus forecast deviation serve as intermediary variables that play a crucial role in how ESG rating divergence influences audit costs. This discovery not only uncovers the intricate mechanism by which ESG rating divergence impacts audit fees but also underscores the importance of assessing audit costs through both direct and indirect means—namely, operating risk and analyst forecast deviation. This study provides important insights for firms, auditors, and regulators to help firms identify and address the risks and costs associated with divergent ESG ratings, to help auditors enhance their professional competence to cope with more complex audit assignments, and to support regulators in improving ESG disclosure standards and strengthening supervision, thereby promoting information transparency and market stability and fostering sustainable corporate development.

4.3. The Interaction Effect of Media Attention and BIG 4

The following is a polished version of the content, further exploring the interaction test results regarding the influence of ESG rating divergence (ESG_Dis) on media attention (Media) and the “Big 4” accounting firms (BIG 4) as regulatory variables. Refer to

Table 5. Interaction effects of media attention and BIG 4.

Variable	(1)	(2)	(3)	(4)
	FEE	FEE	FEE	FEE
ESG_Dis	0.0966 **	0.0779 **	0.0966 **	0.0871 **
	(0.0140)	(0.0499)	(0.0139)	(0.0272)
Media*ESG_Dis		0.0990 ***
		(0.0046)
Big4*ESG_Dis				0.2161 **
				(0.0176)
Media	0.0007	0.0015
	(0.9299)	(0.8492)
Big 4	0.2208 ***	0.2233 ***	0.2209 ***	0.2217 ***
	(0.0000)	(0.0000)	(0.0000)	(0.0000)
Size	0.3942 ***	0.3935 ***	0.3944 ***	0.3944 ***
	(0.0000)	(0.0000)	(0.0000)	(0.0000)
Lev	−0.0481	−0.0452	−0.0479	−0.0498
	(0.4106)	(0.4386)	(0.4119)	(0.3938)
ROA	−0.5002 ***	−0.4980 ***	−0.4996 ***	−0.5011 ***
	(0.0000)	(0.0000)	(0.0000)	(0.0000)
Board	0.0309	0.0266	0.0309	0.0307
	(0.4747)	(0.5368)	(0.4746)	(0.4762)
Indep	−0.0616	−0.0514	−0.0614	−0.0524
	(0.6156)	(0.6749)	(0.6163)	(0.6687)
Top1	0.2225 ***	0.2211 ***	0.2223 ***	0.2270 ***
	(0.0090)	(0.0093)	(0.0090)	(0.0076)
TobinQ	−0.0095 *	−0.0096 **	−0.0094 **	−0.0089 *
	(0.0512)	(0.0496)	(0.0484)	(0.0624)
Year	control	control	control	control
Ind	control	control	control	control
_cons	4.7653 ***	4.7711 ***	4.7636 ***	4.7589 ***
	(0.0000)	(0.0000)	(0.0000)	(0.0000)
N	3056	3056	3056	3056
adj. R2	0.4101	0.4118	0.4103	0.4113

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively.

for detailed findings.

In the regression results presented in Column (2), the coefficient of the interaction term Media * ESG_Dis is 0.0990, which is significant at the 1% level. This indicates that media attention plays a crucial regulatory role in the relationship between ESG rating divergence and audit fees. Capelle’s research points out that information disclosed in the media is more likely to attract the attention of market participants [54] and arouse the interest of investors than corporate announcements [55]. However, the media tends to report negative news about companies [56], which has a significant impact on corporate reputation [57], exacerbating reputational risk and jeopardizing the economic interests of companies [58]. To address the pressure of public opinion, enterprises require auditors to conduct more thorough and comprehensive audit work, ensuring the accuracy of financial statements and ESG compliance. Additionally, auditors need to compensate for harsh litigation risks. Consequently, this leads to higher audit costs. This outcome supports hypothesis H4 of the study.

Based on the results from Column (4), the coefficient of the interaction term Big4 * ESG_Dis is 0.2161, which is significant at the 5% level. This suggests that audits conducted by the Big 4 accounting firms can indeed moderate the relationship between ESG rating discrepancies and audit fees. Fernandez’s research suggests that the “Big Four” have a potential advantage in entering the sustainability assurance market [59]. Moreover, reputation plays a key role in firm branding and is an important indicator of a firm’s competitiveness [60]. The better an intermediary’s reputation is in the capital market, the greater the incentive is to maintain it. In the face of divergent ESG ratings, the “Big 4” will devote more resources to audit work in order to protect their reputation and ensure audit quality while engaging in sustainability assurance [61]. This supports hypothesis H5.

In summary, media attention and the “Big 4” serve as crucial moderating variables in how ESG rating discrepancies impact audit costs. This underscores the significant role of external environmental factors (media attention) and the nature of audit service providers, specifically whether they belong to the “Big 4” in shaping the connection between a company’s ESG practices and its audit expenses. It helps companies, auditors, and regulators understand the impact of the external environment and auditor characteristics on audit costs, develop clearer rating criteria for ESG rating disagreements, reduce the negative impact of disagreements on all parties, and drive the market forward steadily.

5. Conclusions

5.1. Research Conclusion

This paper examines the data from China’s listed companies between 2015 and 2022 to investigate how divergences in ESG (environmental, social, and governance) ratings influence corporate audit expenses. The study reveals that significant disparities in high ESG ratings lead to increased audit costs for companies. The analysis of the impact mechanism indicates that such divergences either elevate operational risks or amplify errors in analysts’ earnings forecasts, thereby affecting audit expenses. Further findings demonstrate that substantial ESG rating differences notably inflate audit fees, with this effect being particularly pronounced when the auditing firm belongs to the “Big 4”.

5.2. Research Enlightenment

First, companies should standardize ESG management and ESG disclosure consistency. They should incorporate ESG concepts into strategies and operations to ensure consistency between environmental, social, and governance policies and practices and to reduce rating disagreements. At the same time, enterprises need to strengthen risk management, enhance communication with analysts, provide accurate information, and stabilize market expectations.

Secondly, audit institutions must enhance their ESG auditing capabilities and professional expertise. Auditors should prioritize the acquisition of pertinent knowledge and skills and comprehend auditing standards and methodologies. Furthermore, it is essential to consider the unique characteristics of media and customer profiles. For enterprises with significant media exposure, auditors should meticulously evaluate ESG risks and allocate additional resources. The “Big 4” accounting firms should capitalize on their professional strengths, while other institutions must bolster their capabilities to meet the growing market demand for ESG audits.

Third, regulatory agencies should standardize ESG rating criteria and norms to promote a framework that reduces the variability in ESG ratings. By minimizing discrepancies in corporate assessments, a fair and transparent market environment can be cultivated, thereby supporting enterprises in fulfilling their ESG responsibilities and offering stakeholders reliable references for decision-making.

Fourth, investors should thoroughly consider ESG factors when making investment decisions. It is essential not only to examine financial indicators but also to focus on variations in corporate ESG performance and rating. By conducting a comprehensive evaluation of ESG performance and analyzing rating disparities, investors can gain a more holistic understanding of an enterprise’s investment value and risks, enabling them to make rational and sustainable investment choices. Additionally, it is vital to remain attentive to media reports and audit quality signals.

5.3. Limitations of the Study and Future Perspectives

This study adopts a more rigorous method of empirical analysis, but the selection of data samples and the timeframe are affected to some extent. These data focus on the Chinese region, where ESG auditing practices are still in the development stage, with problems such as inadequate disclosure, low transparency, and a lack of uniform standards. In addition, the regulatory system is relatively loose, the disclosure quality of companies with ESG reports is low, and rating agencies rate companies based on limited data or inconsistent standards, which leads to increased divergence in ESG ratings. Under such circumstances, auditors need to devote more resources to audit procedures. As a result, firms in emerging markets typically face higher audit fees when ESG ratings are more divergent. However, ESG disclosure and auditing standards are relatively well established in Europe and North America. For example, Europe’s Non-Financial Reporting Directive (NFRD) requires listed companies to disclose ESG-related non-financial information. As the disclosure of ESG information is more standardized and transparent, the degree of rating disagreement is relatively small, and the audit work is relatively simplified; the increase in audit fees is less affected by ESG rating disagreement compared to in emerging markets.

A more in-depth cross-country comparative analysis of ESG audit dynamics can be conducted in the future to understand the differences. Meanwhile, how AI-driven ESG analysis can improve audit efficiency to reduce audit costs can be further explored.