The Bidirectional Relationship Between Audit Fees and Corporate Reputation: Panel Evidence from South African Listed Firms

Abstract

As corporate accountability, credibility, transparency, and stakeholders’ trust continue to attract global attention, this study examines how corporate reputation influences audit fees and whether audit fees, in turn, shape reputation. Hence, this study examines the bidirectional relationship between audit fees and corporate reputation in South African listed firms. This study reviewed three theories, such as capital reputation, stakeholder, and agency theories. Exploring panel data from sixteen listed firms over a period of ten years (2015–2024), this study employs panel regression analysis and two-step system generalised method of moments (System GMM) estimates in accounting for endogeneity, heterogeneity, and dynamic relationships. Data was sourced from the annual reports and accounts of selected firms. The results from the fixed effects model indicate that corporate reputation exerts a statistically significant and positive influence on audit fees. Conversely, findings from the random effects model reveal that audit fees positively influence corporate reputation. The two-step GMM result confirms a bidirectional causal relationship as lagged corporate reputation significantly influences subsequent audit fees, while lagged audit fees also significantly influence future corporate reputation. This study recommends that the board of directors should view audit not as an expense but as a strategic investment in sustaining stakeholder trust and reputation. Among other things, policymakers and regulators should also strengthen audit market transparency in ensuring that audit pricing reflects genuine reputational consideration and audit quality.

1. Introduction

In recent years, the interplay between audit fees and corporate reputation has attracted growing professional and scholarly concern, especially in developing countries where transparency and governance practices are evolving. Audit fees are a significant expense for firms and remain a central issue in auditing, influenced by factors such as the firm’s reputation and characteristics, among other factors. It is also a vital component of corporate governance and auditing that reflects the resource and risk assessment required by the external auditors in providing assurance on the financial statements of an entity. In the present-day business environment, the relevance of corporate reputation has gained unprecedented attention, especially in the context of auditing and financial reporting. The trust capital that a company has built up over the course of its long-term operations is at the heart of the notion of corporate reputation, which was initially defined as the stakeholders’ thorough assessment of the firms’ previous actions and future possibilities (Maaloul et al., 2023). One important intangible asset for preserving and boosting a company’s competitiveness in the globalised economy is its reputation. Reputation acts as a shield during economic downturns, protecting the firm’s value and maintaining investor trust (Pfister & Schwaiger, 2016). As companies attempt to enhance their reputation, they often seek to engage in practices that reflect high standards of transparency and governance. One of such practices is an audit fee, which is important for ensuring the reliability of financial statements and also for enhancing investors’ confidence (Malek & Saidin, 2013). Elswah et al. (2024) affirmed that profitable firms most times incur higher audit fees as a result of the risk attributed to their financial statements. Likewise, companies with large foreign operations and extensive market capitalisation have the tendency to pay higher audit fees, reflecting the complexity of their audits (Joshi et al., 2017).

An intangible asset, such as corporate reputation, is vital for creating and sustaining competitive advantages and reflects the stakeholders’ perception of a firm’s credibility and ethical stance, thereby enhancing the stakeholders’ trust, the market competitiveness, and the firm’s operation (Herlambang & Nasih, 2019; Perez-Cornejo et al., 2019). Corporate reputation is also the perception stakeholders have about an entity (Kaur & Singh, 2018a). There are numerous advantages to having a solid corporate image. A well-known company has easier access to the financial markets (Eberl & Schwaiger, 2005) and is considered less risky (Srivastava et al., 1997). Corporate reputation, which encompasses the perceived quality of a firm and its characteristics, may play a critical role in determining audit pricing. Understanding the factors attributed to the audit fees and vice versa has been vital for both corporate management and auditors to ensure fair pricing and to maintain high standards of financial reporting and corporate governance. Among these factors, the interrelationship between firm characteristics, audit fees, and corporate reputation has garnered major attention in recent years, as they play a pivotal role in shaping stakeholder perception and influencing the overall audit process. Studies have also shown that firm characteristics play a substantial role in influencing corporate reputation and audit fees (Blajer-Gołębiewska & Kozłowski, 2016; Malele et al., 2021).

Audit fees are mostly seen as a reflection of the quality and extent of the audit service provided. Higher audit fees may point to more extensive and thorough auditing, which could enhance a firm’s reputation for financial transparency and reliability (Jizi & Nehme, 2018; Ivanova & Prencipe, 2023). On the other hand, excessive audit fees might be perceived negatively, suggesting a higher risk profile or inefficiencies (Silva et al., 2019). An organisation’s reputation, especially in terms of financial integrity and governance, might affect the complexity of the audit engagement and perceived risk. Organisations with strong reputations may incur lower audit fees due to reduced perceived risk, while those with tarnished reputations may face higher fees as auditors demand more compensation for increased risk (Boo & Sharma, 2008). Internal auditing functions as an integral part of a firm’s assurance and governance framework, providing continuous monitoring, risk assessment, and control evaluation. Nzama-Sithole (2023) affirmed that an internal audit offers unbiased confirmation and information regarding the efficiency of internal controls, governance, and risk management procedures.

In the South African context, the factors influencing an audit are predominantly relevant given the nation’s corporate governance landscape that is shaped by the King IV Code, increasing high-profile corporate scandals and regulatory scrutiny that have raised concerns about the independence and quality of an audit (Smith, 2021). Auditors may perceive firms with a strong reputation as less risky, charge lower audit fees, or, conversely, may devote additional audit effort to safeguard their own reputation. Also, firm characteristics continue to play a vital role in shaping audit fees and corporate reputation in emerging economies like South Africa, where the institutional framework differs from other developed countries. This study contributes to the audit fee literature by introducing corporate reputation as an innovative determinant and vice versa, while providing practical insights for policymakers, regulators, and corporate organisations on the factors influencing audit pricing and corporate reputation in emerging markets. This creates a gap in creating insight as to whether reputation serves as a cost-reducing signal of lowering the audit risk, or conversely, as a cost-increasing factor due to heightened auditor caution in safeguarding the auditor’s reputation.

In many African countries, including South Africa, where corporate fraud and scandals have eroded public trust, the audit market operates under heightened scrutiny. A review of the existing literature has revealed no prior studies examining the dynamic relationship between audit fees and corporate reputation, particularly in the South African context. Understanding the bidirectional relationships between audit fees and corporate reputation is pivotal for stakeholders, such as regulators, auditors, and corporate managers. It can inform the strategies for managing audit costs and enhancing corporate reputation through effective governance practices. Also, it can provide insights into how audit fees can be optimised to reflect the true risk and quality of audit engagements, thereby fostering greater trust and transparency in financial reporting.

2. Literature Review

2.1. Theoretical Framework

This paper employed capital reputational, stakeholder, and agency theories. The capital reputational theory posits that firms request higher audit quality to guard their reputation (Zain et al., 2010). The theory is primarily associated with Robert E. Hoskisson and his colleagues and posits that reputation functions as a form of capital that can significantly influence performance and corporate behaviour. It suggests that an organisations’ reputation is an intangible asset that could be leveraged on to create social and economic value and meet the interests of the stakeholders (Dumitraşcu et al., 2013; Vito, 2025). The theory suggests that the reputation of these firms influences their decisions with respect to the quality of the audits they seek and the audit fee. The theory further explains that companies with high reputation capital are stirred to demand an audit of high quality, resulting in a higher audit fee. Ciupitu and Niţă (2018) affirmed that goodwill is a central concept in reputational capital, which represents the intangible value derived from a positive reputation. Also, factors such as participation in sociocultural and educational events, information transparency, and adherence to corporate and ethical principles significantly enhances business reputation, which in turn attracts investments (Yakimova, 2021).

This study is also anchored in stakeholder theory, which posits that firms should endeavour to manage their relationship with several stakeholders to achieve long-term success and to maintain positive corporate reputation. R. Edward Freeman is mostly recognised as the proponent of stakeholder theory. His work, “Strategic Management: A Stakeholder Approach”, published in 1984, laid the foundation for this theory (Melé, 2009; Lock & Seele, 2017). Effective management of stakeholders could reduce client risks, leading to lower audit fees. This is because well-managed stakeholder relationships could mitigate agency problems, which are typically associated with audit fees (Pourheidari & Golmohammadi, 2023). Finally, agency theory highlights the conflicts of interest between the management of an entity and its shareholders. The key proponents of the theory are Michael Jensen and William Meckling (Dobbin & Jung, 2010). Higher audit fees may be justified as a means to mitigate agency problems by making sure that the financial statements are reported accurately, thus enhancing corporate reputation.

2.2. Empirical Review

Studies have examined the interplay between audit fees and corporate reputation, revealing diverse findings across contexts. Huang and Kang (2018, 2022) provided evidence that firms with higher reputation scores have the tendency to engage industry-specialist auditors and to pay higher non-audit service (NAS) fees. Their results suggest that companies with high reputation demand superior audit quality to signal integrity and to sustain stakeholder trust. In the same way, Dumitraşcu et al. (2013) conceptualised corporate reputation as the cumulative outcome of a firm’s social engagement and economic viability, linking to broader sustainability and governance outcomes that may influence audit pricing.

Studies have focused on the factors influencing audit fees, providing insights into how auditor and firm characteristics shape audit pricing. Naser and Nuseibeh (2008) discovered that, in Jordan, the auditors’ status, complexity, firm size, and risk are the main factors influencing the audit fee. Consistent results have been found in other emerging economies, including Kenya and Vietnam (Kimeli, 2013, Pham et al., 2017; Kanakriyah, 2020), where audit fees are positively related to company size, auditor reputation, and risk. Hallak and Silva (2012) further revealed that the Big Four firms and governance quality affect audit fees, which suggests that governance and reputation drive the demand for audit quality. Evidence also reveals that reputation dynamics could influence auditor behaviour and fee structures. Asthana and Kalelkar (2014) found that, when clients gain a reputation, auditors initially offered discounted fees but subsequently charged higher fees, leveraging the reputation association to attract and charge other clients more. Pham et al. (2017), however, reported a negative relationships between audit fees and audit quality among non-Big Four firms, which implies that higher fees do not always translate into better audit outcomes.

2.3. Conceptual Review and Hypothesis Development

2.3.1. Corporate Reputation

Rindova et al. (2005) considered corporate reputation as the stakeholders’ perceptions about an organisation’s ability to create value relative to competitors. Corporate reputation is a multifaceted and intangible asset that substantially influences several facets of an organisation’s performance and stakeholder relationships. It is widely recognised as an intangible asset that can enhance loyalty, customer satisfaction, and investor awareness, while attracting and retaining employees (Pfister & Schwaiger, 2016). Reputation is managed internally but assessed externally by different stakeholders, making it a hybrid asset (Brown & Whysall, 2013). A positive corporate reputation creates a competitive advantage, enhancing financial performance and influencing customer behaviour. Corporate reputation is closely tied to the perception of an investor, which is oftentimes reflected in the organisations’ market capitalisation. The Investors’ confidence in a company’s financial health and future prospects can drive up its market value, thereby enhancing reputation (Pfister & Schwaiger, 2016). Antunovich and Laster (1998) discovered that firms portraying high market capitalisation earn better reputation ratings on Fortune’s “Most Admired Companies” list, and hence large-cap firms exhibit superior corporate reputation (Shefrin & Statman, 1995; Antunovich & Laster, 1998).

2.3.2. Audit Fees

Audit fees also include payments made to auditors for their services in examining and verifying a company’s financial statement. Audit fees refer to the charges levied by auditors for the audit services they provide to a company. These fees are influenced by several factors, basically related to firm characteristics, corporate governance, and external conditions. It is what the public accountants charge their clients. The service includes audits, assurance, and reviews of financial statements (Nwosu et al., 2026). The audit fees charged differ depending on several factors, including the degree of competence required, the complexity of the service, the assignment risk, the firm’s cost structure, and additional professional considerations and terms and conditions (Nwosu et al., 2026). Studies have shown that uncertainty with economic policy and the regulatory environment are external condition that could influence audit fees (Ha, 2024; Sun et al., 2025). Companies that are sensitive to policy changes often face higher audit fees as a result of the increased risk of financial misstatements and the need for a more thorough audit (Ha, 2024).

2.3.3. Hypothesis Development

Drawing on the capital reputational, stakeholder, and agency theories, this study proposes a bidirectional relationship between audit fees and corporate reputation. Firms with a stronger corporate reputation have the tendency to demand a higher audit quality in a bid to safeguard their reputational capital, leading to higher audit fees. Likewise, a higher audit fee, which is most times associated with increased audit efforts, enhanced assurance quality, and engagement of reputable auditors, can strengthen corporate reputation. This study therefore hypothesises that corporate reputation and audit fees mutually influence each other. Explicitly, audit fees are also expected to significantly affect corporate reputation, while corporate reputation is expected to have a significant effect on audit fees. The null hypothesis for this study is stated as follows:

H₀. 

There is no significant bidirectional relationship between audit fees and corporate reputation.

3. Methodology

This study utilised secondary data obtained from the annual reports and accounts of selected listed firms in South Africa. This study explored ex post facto and longitudinal research designs. Since the selected firms’ annual reports and accounts already have the data on pertinent issues, an ex post facto study design is crucial. Thus, the data collected are panel in nature and include 16 cross-sectional units from 2015 to 2024. This study also employed a longitudinal research approach. It is appropriate since it makes it possible to collect a large amount of data, which improves the accuracy of the estimations that are produced.

This study is primarily focused on manufacturing firms listed on the Johannesburg Stock Exchange (JSE). Sixteen manufacturing firms whose stocks were traded on the stock market within the sample period were chosen for this study, exploring a purposive sampling technique due to the availability of data. Appropriate data were readily available. Data spanning from 2015 to 2024 (10 years) were obtained from the audited annual reports and accounts of the selected firms. The data analysis technique employed in this study includes panel regression and dynamic panel-data estimation using the two-step system generalised method of moments (System GMM) approach, complemented by other descriptive and inferential statistical methods.

3.1. Model Specification

By investigating into how audit fee shapes corporate reputations, and vice versa, this study first explored multiple regression analysis in establishing the relationships. The model specification draws on prior frameworks developed by Naser and Nuseibeh (2008), Ezenwoke et al. (2014), and Malele et al. (2021), which were adapted to suit the variables and context of the present study. Accordingly, the functional relationship is expressed as follows: Audit Fees = f(Corporate Reputation, Control Variables)

$${AUF}_{it}={MCP}_{it}{+DPS}_{it}+{FSZ}_{it}+{CAS}_{it}{+ROA}_{it} {+{FAG}_{it}+{LEV}_{it}+\epsilon }_{it }$$

(1)

Corporate Reputation = f (Audit fees, Control Variables)

$${MCP}_{it}={AUF}_{it}{+DPS}_{it}+{FSZ}_{it}+{CAS}_{it}{+ROA}_{it} {+{FAG}_{it}+{LEV}_{it}+\epsilon }_{it }$$

(2)

This study further applied the System GMM estimate technique because it addresses the dynamic and bidirectional relationship between variables while controlling for potential endogeneity and unobserved heterogeneity inherent in panel data. Given that the current level of audit fees may depend on their past values and the corporate reputation may also evolve dynamically over time, the inclusion of the lagged dependent variables makes estimators like random or fixed effects biased and inconsistent. System GMM, by combining equations in both levels and first difference, uses internal instruments derived from the lagged values of the variables to produce efficient and consistent estimates.

This study uses a dynamic panel data technique by exploring the two-step System GMM estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998) in order to analyse the reciprocal relationship between audit fees and corporate reputation. This approach is suitable for controlling potential endogeneity, unobserved firm-specific heterogeneity, and dynamic persistence inherent in the variables. The model in Equation (3), investigates whether corporate reputation affects audit fees.

$${AUF}_{it}={\alpha }_0+{\alpha }_1{AUF}_{it-1}+{\alpha }_2{MCP}_{it-1}+{\alpha }_3{CAS}_{it}+{\alpha }_4{DPS}_{it}+{\alpha }_5{FAG}_{it}+{\alpha }_6{FSZ}_{it}+{\alpha }_7{LEV}_{it}+{\alpha }_8{ROA}_{it}+{\mu }_i+{\mathit{\varepsilon }}_{it}$$

(3)

In this model, the lagged dependent variable (${AUF}_{t-1})$ captures persistence in audit fees, while ${(MCP}_{t-1})$ represents the lagged effect of reputation on subsequent audit fees, while ${\mu }_i$ represents unobserved firm-specific effects and ${\mathit{\varepsilon }}_{it}$ connotes an idiosyncratic error term.

The second model in Equation (4) examines the reverse causality, whether audit fees influence corporate reputation (being proxied by market capitalisation). It captures how prior audit fees influence corporate reputation.

$${MCP}_{it}={\alpha }_0+{\alpha }_1{MCP}_{it-1}+{\alpha }_2{AUF}_{it-1}+{\alpha }_3{CAS}_{it}+{\alpha }_4{DPS}_{it}+{\alpha }_5{FAG}_{it}+{\alpha }_6{FSZ}_{it}+{\alpha }_7{LEV}_{it}+{\alpha }_8{ROA}_{it}+{\mu }_i+{\mathit{\varepsilon }}_{it}$$

(4)

3.2. Measurement of Variables

This study employed several variables to investigate the bidirectional relationship between audit fees and corporate reputation among the listed firms in South Africa. Audit fees (AUF) is proxied as the natural logarithm of total audit fees, with an a priori expectation of either positive or negative association, given the potential bidirectional nature of the relationship. Market capitalisation (MCP) is used to measure corporate reputation following similar studies, such as Kaur and Singh (2018a), Kaur et al. (2024), and Arora et al. (2021), which have also used the same proxy. High market capitalisation or market value is associated with a good reputation (Kaur & Singh, 2018b). Black et al. (2000) discovered that market reputation creates value for the firm by improving its market value. Market capitalisation is computed as the number of shares outstanding multiplied by the market price of the share. Market capitalisation differs from other proxies as it mirrors the aggregate valuation placed on a firm by the investors, derived from the share price and the shares outstanding. Unlike a perception-based reputation (such as brand indices, ESG scores, corporate reputation rankings), it is continuously updated and market-driven, making it highly responsive to expectations, new information, and macroeconomic conditions. It is also expected to exhibit a bidirectional relationship with audit fee. In enhancing the robustness of the model, several control variables are included. Return on assets (ROA), proxied as the ratio of the earnings before interest and tax to the total assets, is expected to have either a positive or negative influence on both audit fee and corporate reputation. Dividend per share (DPS) represents the ratio of total dividends declared to the number of outstanding shares. Firm size (FSZ) is measured by the natural logarithm of the firms. Firm age (FAG) is proxied as the number of years since the company’s incorporation. Cash and near cash (CAS) is proxied by the total cash and near cash reported in the financial statement, while leverage (LEV) is proxied as the ratio of debt-to-equity ratio.

4. Discussion

The descriptive results as shown in

Table 1. Descriptive statistics.

	Mean	Median	Minimum	Maximum	Std. Dev.	Skewness	Kurtosis	Jarque-Bera	Prob.
AUF	19,493.26	11,687.00	0.00	100,000	22,692.34	1.69	5.55	119.35	0.00
MCP	13,779.24	6547.20	178.10	141,138.80	24,219.75	3.41	15.24	1193.37	0.00
CAS	1,734,015	764,871	437.00	14,110,668	2,834,713	2.52	8.68	384.11	0.00
DPS	−2.34	2.39	−100.00	139.62	51.19	−0.06	3.57	1.52	0.47
FAG	65.50	62.00	2.00	175.00	44.41	0.75	3.03	14.88	0.00
FSZ	6.89	6.93	5.87	8.14	0.54	0.26	2.40	4.14	0.13
LEV	1.00	0.71	0.10	9.34	1.20	4.03	24.28	3450.05	0.00
ROA	9.93	8.19	−30.41	72.29	10.67	1.60	13.04	740.64	0.00

Source: Authors’ computations.

reveal significant variations across the sample of listed firms. Audit fees (AUF) show an average value of ZAR 19,493, with a standard deviation of ZAR 22,692. This depicts that, while some companies pay moderate fees, others incur huge higher costs, consistent with differences in the complexity of firms. The distribution is leptokurtic (Kurtosis 5.55) and positively skewed (1.69), which connotes that a few firms pay disproportionately higher audit fees. Dividend per share (DPS) has an unusual negative mean value (−2.34), which implies cases of dividend losses or cuts. Firm size (FSZ) is relatively stable, with a mean value and standard deviation of 6.89 and 0.54, respectively, with low skewness (0.26) reflecting consistency across the selected firms. By contrast, market capitalisation (MCP) and cash and cash equivalents (CAS) exhibit extreme dispersion, with standard deviations of 24.219 and 2.83, respectively. Return on assets (ROA) reveals considerable variations (mean value = 9.93, standard deviation = 10.67). For firm age (FAG), the mean value is 65.5 years, which implies that most firms are well established.

4.1. Correlation Analysis and Variance Inflation Factor

As a preliminary test, a correlation analysis was used to ascertain the degree of association and strength of relationships that exist among the variables. A quick overview of the strength and direction of a linear relationship between two variables is given by the Pearson product-moment correlation, also known as the correlation coefficient. The correlation values between variables during a ten-year period are shown in the asymmetrical matrix in

Table 2. Correlation Analysis.

Correlation
Probability	MCP	CAS	FAG	FSZ	LEV	ROA	DPS	AUF
MCP	1.000
	-----
CAS	0.487	1.000
	(0.000)	-----
FAG	0.564	0.393	1.000
	(0.000)	(0.000)	-----
FSZ	0.520	0.782	0.490	1.000
	(0.000)	(0.000)	(0.000)	-----
LEV	0.019	0.162	−0.042	0.170	1.000
	(0.809)	(0.041)	(0.601)	(0.032)	-----
ROA	0.170	0.029	0.208	−0.128	−0.128	1.000
	(0.032)	(0.718)	(0.008)	(0.107)	(0.106)	-----
DPS	0.162	0.303	0.418	0.138	−0.160	0.342	1.000
	(0.040)	(0.000)	(0.000)	(0.082)	(0.043)	(0.000)	-----
AUF	0.314	0.545	0.384	0.533	0.222	0.086	0.253	1.000
	(0.000)	(0.000)	(0.000)	(0.000)	(0.005)	(0.279)	(0.001)	-----

The p-values are in parentheses; correlation coefficients are in the upper section. Source: Authors’ computations.

. Each value in the table is below the 0.80 threshold (Judge et al., 1988; Bryman & Cramer, 2004). The variance inflation factor (VIF) in the

Table 3. Variance inflation factors.

Variable	VIF	1/VIF	Variable	VIF	1/VIF
MCP	1.79	0.501	AUF	4.27	0.234
CAS	3.09	0.324	CAS	2.99	0.334
DPS	1.53	0.652	DPS	1.65	0.607
FAG	2	0.5	FAG	1.7	0.589
FSZ	3.47	0.288	FSZ	5.84	0.171
LEV	1.09	0.916	LEV	1.17	0.856
ROA	1.29	0.778	ROA	1.25	0.799
Mean VIF	2.04		Mean VIF	2.7

Source: Authors’ computations.

results show that the mean VIF of 2.04 and 2.70, respectively, is well below the conventional threshold of 10, which indicates that multicollinearity is not a serious concern in the model. Also, the centred VIFs for all the explanatory variables range between 1.09 (LEV) and 5.84 (FSZ), suggesting a moderate correlation among some variables but still within the acceptable limits. Multicollinearity is not a serious concern when interpreting the results obtained from the regression if the VIF score is less than 10 (Neter et al., 1983). A lower mean VIF indicates minimal multicollinearity in the model.

4.2. Lagrange Multiplier Tests and Hausman Test

As shown in

Table 4. Breusch–Pagan and related tests.

Test	Cross-Section	Time	Both
Breusch–Pagan	136.926	1.197	138.122
p-value	(0.000)	(−0.274)	(0.000)
King–Wu	11.702	−1.094	6.825
p-value	(0.000)		(0.000)
Honda	11.702	−1.094	7.501
p-value	(0.000)		(0.000)

Source: Authors’ computations.

, the Breusch–Pagan Lagrange Multiplier (LM) test strongly rejects the null hypothesis of no random effects at the cross-sectional level (p = 0.000), while the time effect is insignificant (p = −0.274). This implies that cross-sectional random effects are present and drive the model more than time effects. Both the Honda and King–Wu tests similarly confirm significant cross-sectional and joint effects (p = 0.000), reinforcing the appropriateness of panel estimators over pooled OLS. These results provide strong justification for the adoption of a random effects model as a more appropriate specification compared to the pooled OLS. However, the Hausman test, as indicated in

Table 5. Correlated random effects—Hausman test.

Test Summary	Chi-Sq. Statistic	Chi-Sq. df	Prob.
Cross-Section Random	35.333	7	0

Source: Authors’ computations.

, was employed to select between the fixed effects and random effects models. The result from the Hausman test reveals a chi-squared statistic of 35.333 (df = 7) with a p-value of 0.000, which is significant. This leads to the rejection of the null hypothesis that the random effect is consistent. Because it takes into consideration the possible correlation between the regressors and the individual and specific effects, the fixed effects model is therefore the most suitable specification for the data.

4.3. Regression Analysis

The R-squared value of 0.979 suggests that about 97.9% of the variation in audit fees (AUF) is explained by the explanatory variables, which suggests that the model has a very strong explanatory power. The standard error of regression (0.078) is relatively small, which implies that the residuals (errors) are minimal, which further supports the precision of the estimate. The result reveals that the F-statistics of 163.26 with a p-value of 0.000 confirms that the overall model is statistically significant, which indicates that the explanatory variables jointly influence the audit fees. In conclusion, the fixed effects model demonstrates a very good fit and statistical significance, making it the preferred specification for investigating the factors influencing audit fees with particular focus on the firm characteristics and the corporate reputation of the listed firms. The outcome is shown in

Table 6. Regression analysis. Dependent Variable: AUF.

	RANDOM EFFECTS			FIXED EFFECTS			POOLED OLS
Variable	Coef.	t-Stat.	Prob.	Coef.	t-Stat.	Prob.	Coef.	t-Stat	Prob.
C	−1.905	−3.365	0.806	−1.387	−1.998	0.050	−3.186	−6.718	0.000
MCP	0.000	2.492	0.002	0.000	4.010	0.000	0.005	2.472	0.016
CAS	0.000	−0.801	0.896	0.000	−0.465	0.644	0.001	0.892	0.375
DPS	0.000	−0.246	0.000	0.000	−0.329	0.743	0.000	−1.134	0.260
FAG	0.002	1.133	0.001	0.025	5.695	0.000	0.076	4.007	0.000
FSZ	0.833	10.029	0.426	0.492	4.144	0.000	1.029	15.251	0.000
LEV	0.044	3.249	0.261	0.039	2.729	0.008	0.000	−1.845	0.069
ROA	0.000	0.131	0.015	0.000	0.117	0.907	0.000	0.102	0.919
R-Squared	0.666			0.979			0.868
Adjusted R-Squared	0.637			0.973			0.856
S.E. of Regression	0.092			0.078			0.181
F-Statistic	22.538			163.263			73.971
Prob. (F-Statistic)	0.000			0.000			0.000
Durbin–Watson Stat	1.100			1.294			0.416

Source: Authors’ computations.

, which is the output of a fixed effects model from the regression analysis.

In the fixed effects model, as presented in Table 6, corporate reputation, being proxied by market capitalisation (MCP), has a positive and statistically significant effect on the audit fees (AUF). The result shows a coefficient of 0.000 and a p-value of 0.000. The implication of the result is that market capitalisation is an important driver that influences audit fees in the South African context. This means that firms with a higher market standing and market capitalisation have the tendency to pay higher audit fees. Basically, as the reputation of the firm in the capital market grows, it is associated with greater stakeholder scrutiny, more extensive operations, and higher expectations of transparency. This results in auditors charging higher fees as a result of reputational risk management and increased audit efforts. The result aligns with studies such as Ezenwoke et al. (2014), Joshi et al. (2017), and Malele et al. (2021). In order to preserve their reputations and credibility, reputable companies are likely to require greater audit quality, which raises audit fees. According to Zain et al. (2010), this is consistent with the capital reputational theory, where independent audit committees demand audits of higher quality to guard and sustain their reputation.

Equally, the coefficient of firm size (FSZ) is positive and significant (coef 0.492, p = 0.000), confirming that larger firms incur higher audit costs. Bigger firms have more complex operations, diversified activities, and extensive transactions that demand more audit procedures and expose auditors to greater litigation and reputational risks, thereby justifying higher audit fees. Studies have shown a significant and positive relationship between firm size and AUF (Ezenwoke et al., 2014; Ningtyas & Dewantoro, 2020; Malele et al., 2021). The results also revealed that leverage (LEV), being proxied by debt to equity, exhibits a significant and positive relationship with audit fees (AUF), having a coefficient of 0.039 (p = 0.008). This suggests that, as companies expand their reliance on debt financing, audit fees increase. The rationale is that firms that are highly leveraged carry higher financial risk, which includes strict monitoring by the creditors and more complex financial reporting as a result of debt covenants. As a result of this, the auditors charged higher fees to compensate for risk exposure and the additional audit effort associated with verifying the integrity and accuracy of the financial statements of the firm. The result aligns with the studies by Nikkinen and Sahlström (2005) and Barua et al. (2019). Finally, the result also shows that firm age (FAG) had a positive and significant influence on AUF, having a coefficient of 0.025 with a t-statistic of 5.695 and a p-value of 0.000. The positive relationship suggests that mature and older firms have the tendency to attract higher audit fees due to their more extensive financial histories, complex financial structure, and larger operational scale, which require greater audit effort and professional judgement. The associated risks and complexities could lead to a higher AUF (Ezenwoke et al., 2014; Ferdous et al., 2024; Ogundele et al., 2024). It also reflects that auditors may perceive older firms as having more rigorous compliance or higher audit risk exposure, justifying the higher audit fees.

4.4. Lagrange Multiplier Tests and Hausman Test

The results of the Breusch–Pagan Lagrange Multiplier (LM) test and Hausman test in

Table 7. Breusch–Pagan and related tests.

	Cross-Section	Time	Both
Breusch–Pagan	55.845	0.001	55.846
	0.000	−0.971	0.000
Honda	7.473	0.036	5.309
	0.000	−0.486	0.000
King–Wu	7.473	0.036	4.605
	0.000	−0.486	0.000

Source: Authors’ computations.

and

Table 8. Hausman test.

Test Summary	Chi-Sq. Statistic	Chi-Sq. df	Prob.
Cross-Section Random	35.333	7	0.375

Source: Authors’ computations.

, respectively, provide evidence with respect to the appropriate panel data model specification. The Breusch–Pagan LM test indicates that the variance components for the cross-sectional effects are statistically significant (p-value = 0.000), which suggests the presence of significant differences across firms. This indicates that a random effects model is preferable to a simple pooled OLS regression, as the data exhibits cross-sectional heterogeneity. Nevertheless, the Hausman test yields a chi-squared statistic of 35.333 with a p-value of 0.375 and seven degrees of freedom, which fail to reject the null hypothesis that the random effects estimator is consistent. Therefore, the random effects model is more suitable for this study, which implies that the individual effects are uncorrelated with the explanatory variables, and the model provides efficient and unbiased estimates.

4.5. Regression Analysis

The R-squared value of 0.163 depicts that about 16.3% of the variation in corporate reputation is explained by the variables under the random effects specification. The results reveal that the F-statistics of 4.223 with a p-value of 0.000 confirm that the overall model is statistically significant, meaning that the explanatory variables jointly influence market capitalisation being a proxy for corporate reputation. The Hausman test yielded a chi-squared statistic of 7.575 with seven degrees of freedom and a p-value of 0.3715. Since the p-value is greater than 0.005, we fail to reject the null hypothesis that the random effects model is appropriate. In conclusion, the random effects model demonstrates a very good fit and statistical significance, making it the preferred specification. The outcome, shown in

Table 9. Dependent Variable: MCP.

	RANDOM EFFECTS			FIXED EFFECTS			POOLED OLS
Variable	Coef	t-Stat	Prob.	Coef	t-Stat	Prob.	Coef	t-Stat	Prob.
AUF	0.271	1.893	0.060	0.212	1.328	0.186	0.556	4.169	0.000
DPS	−16.967	−1.060	0.291	−4.288	−0.248	0.804	−51.655	−3.580	0.001
CAS	5428.775	1.511	0.133	5705.058	1.405	0.162	6860.068	2.340	0.021
FAG	209.779	2.356	0.020	−345.397	−0.694	0.489	223.072	5.184	0.000
FSZ	−2318.144	−0.282	0.778	−4086.951	−0.385	0.701	−9177.704	−1.394	0.165
LEV	284.043	0.201	0.841	1010.586	0.672	0.503	−2275.905	−1.721	0.087
ROA	403.400	2.416	0.017	345.154	1.891	0.061	406.392	2.645	0.009
C	−22,227.01	−0.472	0.638	24,560.910	0.381	0.704	16,214.370	0.444	0.658
R-squared	0.163			0.706			0.499
Adjusted R-squared	0.124			0.659			0.476
F-statistic	4.223			14.978			21.660
Prob. (F-statistic)	0.000			0.000			0.000
Durbin–Watson stat	1.071			1.172			0.787

Source: Authors’ computations.

, is the random effects model’s output from the regression analysis.

In the random effects model, as displayed in Table 9, audit fees (AUF) have a positive and statistically significant effects on market capitalisation (MCP), which is a proxy for corporate reputation. Under the model, the coefficient is 0.271, with a t-statistic of 1.893 and a p-value of 0.060. This connotes that audit fees (AUF) have a positive and marginally significant effect on corporate reputation, significant at the 10% level (p < 0.06). The positive coefficient suggests that, as audit fees rise, a firm’s market capitalisation (proxy for corporate reputation) also tends to increase. Higher audit fees indicate more complex audit engagements, engagement of top-tier audit firms, and greater commitment to compliance and accountability, among other things. These features have the potential to enhance investor confidence, thereby enhancing the firm’s market value and corporate reputation. Higher audit fees most times reflect the efforts of the auditor to mitigate the risks associated with financial misstatement and opacity (Danielsen et al., 2007; Li & Ma, 2020). Consequently, firms that invest in higher audit fees are most times perceived to be more trustworthy and reliable, enhancing their corporate reputation in the market and among stakeholders (Zain et al., 2010; Jizi & Nehme, 2018).

Table 9 also shows that firm age (FAG) has a significant and positive influence on corporate reputation (coef 209.78, t-stat 2.356, and p-value 0.020). This suggests that older firms have a higher corporate reputation, as reflected in the greater market value. The possible explanation is that long-established firms are more likely to have built operational experience, brand loyalty, and investor and stakeholder trust over time, all of which contribute to a higher corporate reputation. The evidence suggests that firm age influences corporate reputation, especially through the resilience and stability that older firms can maintain (Pollock et al., 2015). Also, Kataria and Deep (2020) affirmed that older firms have more experience and stability, which can enhance the investors’ confidence and lead to higher market valuation and, hence, corporate reputation. The results also reveal that return on assets (ROA) positively and statistically significantly influences market capitalisation (coef 403.40, p-value 0.017). The findings imply that financial performance (ROA) enhances corporate reputation. Return on assets is a vital indicator of financial health and managerial competence, thereby strengthening the firm’s reputation and standing in the market. Agyemang-Mintah (2015) and Xu et al. (2025) affirmed that a higher ROA indicates better financial health and operational efficiency and, hence, enhances corporate reputation. Companies with strong ROA are perceived to be well-managed and financially stable, which boosts their reputation among stakeholders (Pfister & Schwaiger, 2016).

4.6. Robustness Check to Account for Endogeneity

4.6.1. Does Corporate Reputation Shape Audit Fees?

This study further employed the two-step System GMM dynamic panel-data estimation to explore the causal relationship between audit fees (AUF) and corporate reputation (MCP), as shown in

Table 10. Dynamic panel-data estimation, two-step System GMM.

L. Auf	Coefficient	Corrected Std. Err.	Z	P>|Z|	[95% Conf. Interval]
MCP L1	0.284	0.070	4.040	0.000	0.146	0.422
CAS	−5060.278	8204.290	−0.620	0.537	−21,140.390	11,019.830
DPS	41.596	13.987	2.970	0.003	14.183	69.009
FAG	9.368	134.546	0.070	0.944	−254.338	273.074
FSZ	29,755.480	13,455.530	2.210	0.027	3383.127	56,127.830
LEV	1491.005	2043.688	0.730	0.466	−2514.550	5496.560
ROA	−195.953	150.551	−1.300	0.193	−491.027	99.121
Constant	−166,254.200	54,341.040	−3.060	0.002	−272,760.700	−59,747.75
AR (2) p-value	−1.53, p = 0.126
Hansen Test χ2	8.78, p = 1.000
Diff-in-Hansen	p = 1.000
Wald Test χ2	1206.80, p = 0.00

Source: Authors’ computations.

. The Wald chi-squared and p-value (Wald chi² (7) = 1206.80, p < 0.01) indicate that, overall, the model is statistically significant. Using a lagged dependent variable (L.AUF) confirms that audit fees are persistent over time, which justifies the dynamic specification. The AR (2) test p-value (p = 0.126) indicates no evidence of second-order autocorrelation, while the Hansen test (p = 1.000) confirms the validity of the instruments. These results confirm that the dynamic panel model is well specified and that the System GMM is appropriate for the analysis. This is consistent with Eriqat et al. (2024).

The result in Table 10 shows that lagged market capitalisation (which is a proxy for corporate reputation) has a significant positive effect on audit fees (coef 0.284, p < 0.01). The result is in tandem with the fixed effects model, which indicates robustness in the estimated relationship. This alignment implies that the observed relationship is not driven by unobserved firm effects or endogeneity, thus validating the reliability of the result. The result implies that firms with a higher reputation tend to pay higher audit fees in the subsequent period. This suggests that reputable firms have the tendency to demand higher quality assurance, engage top-tier auditors, or have complex operations that require more audit efforts, which leads to higher audit pricing. Huang and Kang (2018) also affirmed that firms with higher market capitalisation usually have a better reputation, stating that these companies are most likely to demand a higher quality to sustain their reputation, which in turn leads to higher audit fees. Also, higher market capitalisation (proxy for corporate reputation) can imply higher risk and greater complexity in financial reporting, which necessitates a more extensive audit procedure. Auditors usually charge higher fees to compensate for greater risk and increased efforts in auditing these firms (Habib et al., 2013; Habib et al., 2020). Khoo et al. (2020) likewise affirmed that a good corporate reputation is associated with timelier earnings announcements and audits, which can require more intensive audit work and thus higher fees.

The dynamic panel findings that firms with a higher corporate reputation have the tendency to pay higher audit fees are theoretically underpinned to the stakeholder theory’s focus on transparency and accountability, while the capital reputational theory’s emphasis on reputation preservation and the agency theory’s proposition that audits serve as monitoring tools tend to curb agency conflict. Altogether, these theories explain why reputable companies invest more heavily in high-quality audits to sustain legitimacy, trust, and long-term firm value.

4.6.2. Do Audit Fees Shape Corporate Reputation?

The diagnostic tests indicate that the System GMM estimator is appropriate for analysing the dynamic effects relationship between audit fees and corporate reputation, as the model satisfies the assumption of instrument validity and second-order serial correlations. The results from the two-step System GMM estimation reveal the dynamic relationship between corporate reputation (proxied by market capitalisation) and audit fees, as displayed in

Table 11. Dynamic panel-data estimation, two-step System GMM.

L. MCP	Coefficient	Corrected Std. Err.	Z	P>|Z|	[95% Conf. Interval]
AUFL1	0.662	0.255	2.600	0.009	0.163	1.160
CAS	5315.071	7966.607	0.670	0.505	−10,299.19	20,929.330
DPS	−39.548	17.051	−2.320	0.020	−72.968	−6.128
FAG	195.099	101.798	1.920	0.055	−4.422	394.620
FSZ	−9826.395	9201.149	−1.070	0.286	−27,860.32	8207.526
LEV	−1313.947	1396.460	−0.940	0.347	−4050.958	1423.064
ROA	419.236	115.353	3.630	0.000	193.149	645.323
Constant	27,643.170	45,010.650	0.610	0.539	−60,576.08	115,862.400
AR (2) p-value	0.24, p = 0.809
Hansen Test χ2	8.31, p = 1.000
Diff-In-Hansen	p = 1.000
Wald Test χ2	43.02, p = 0.000

Source: Authors’ computations.

. The lagged value of audit fees (AUFL1) is positive and statistically significant (β = 0.662, p = 0.009), which indicates that past audit fees (AUFL1) are associated with corporate reputation in the current period. This suggests that firms that invest more in audit quality tend to enhance their reputation and credibility over time. The significance of the lagged audit fee variable implies that the benefits of investing in audit quality do not occur immediately but accumulate and manifest in subsequent periods. This is consistent with the notion that corporate reputation is a long-term intangible asset that builds gradually through consistent signals of reliability and integrity sent to stakeholders. Higher audit fees might indicate more extensive and thorough auditing, which could enhance corporate reputation for financial reliability and transparency (Ivanova & Prencipe, 2023). Higher audit fees may indicate more thorough and extensive auditing, which could enhance a firm’s reputation for financial transparency and reliability.

The significant positive effects of lagged audit fees on corporate reputation underscore that audit investments serve not only as a compliance mechanism but as a strategic tool for building and sustaining reputational capital. The result is theoretically grounded in the complementary insights of capital reputational, agency, and stakeholder theories, each of which reinforces the view that audit quality has the tendency to enhance market image and long-term credibility.

5. Conclusions

This study examined the directional relationship between corporate reputation being proxied by market capitalisation and audit fees among South African listed firms using dynamic System GMM estimation techniques. The findings reveal a significant two-way relationship between the two constructs. The results display that corporate reputation exerts a significant and positive influence on audit fees, which suggests that firms with a strong reputation have the tendency to engage a higher quality auditor, call for better audit assurance, and thus pay higher audit fees. The results also show that audit fees influence corporate reputation over time, which indicates that investment in audit quality contributes to improved market value and stakeholders’ trust. The results align with the theories explored (capital reputational, agency, and stakeholder theories), which emphasised that corporate reputation, audit fees, and audit quality are mutually reinforcing mechanisms that promote accountability, transparency, and sustainable corporate governance.

6. Recommendations

Based on the findings in examining the bidirectional relationship between audit fees and corporate reputation among listed South African firms, this study proposes the following recommendations:

i.

Companies should view audit fees as a strategic investment in enhancing corporate reputation and stakeholder confidence and not compliance expense.

ii.

Board of directors should prioritise robust governance frameworks that promote transparency in audit fee determination. This is to ensure that audit engagements are not influenced by managerial discretion, thereby improving both financial reporting quality and reputational outcomes.

iii.

Regulatory authorities should encourage disclosures regarding audit fees and reputation-related initiatives. Such transparency will enhance investor confidence and comparability in corporate reporting.

iv.

Professional bodies and regulators should strengthen capacity development and audit quality reviews to ensure that higher audit fees correspond to the reliability of financial statements.

v.

Management should embed reputation risk management into the business strategy and ethical leadership should be prioritised to sustain a positive corporate image.

vi.

Finally, the regulatory authority and policymakers should engage in periodic review of the audit fee structure. This could help to prevent excessive pricing while maintaining audit quality standards.

7. Suggestion for Further Studies

Further studies could expand on this study by incorporating a cross-country or sector comparative analysis across emerging markets to explore how institutional quality and audit market dynamics moderate the relationship between audit fees and corporate reputation. This will provide insight into how the governance environment shapes the nexus between audit fees and corporate reputation. Further studies could also explore a mixed-methods approach by combining quantitative panel data analysis with qualitative data. This would allow for a more holistic insight of how audit fee, audit quality, and corporate reputation are perceived and managed within firms. Studies could enhance external validity by conducting cross-country comparative analyses across emerging and developed economies, or by further extending the sample to multiple jurisdictions with differing regulatory and governance frameworks to investigate whether the audit fee–corporate reputation relationship holds beyond the South African context. Finally, further studies could employ other alternatives or composite measures of corporate reputation, such as stakeholder surveys, ESG reputation metrics, media sentiment analysis, and reputation rankings, among other factors.