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The Determinants of Audit Fees: The Context of Cameroon

Samuel Tanjeh Mukah, Michael Forzeh Fossung*, Kueda Wamba Berthelo, Samka Marion Nyuykighan

Department of Accounting, Faculty of Social and Management Sciences, University of Buea, Cameroon

Abstract: This study is crystallised on examining the determinants of the amount of audit fees paid in the context of Cameroon using a causal research design. Data was collected through a structured questionnaire administered to companies subject to statutory audit in Cameroon's three regions: Littoral, North-West, and Centre. The model is tested by running a multilinear regression of the audit fees on the auditor characteristics, the auditee characteristics and auditor/Auditee relationship characteristics by using a sample of 171 companies. The size of the auditee, the auditor's expertise, the corporate complexity, the duration of the mandate, the reporting time lag, and the auditor's experience were found to be the most critical drivers of audit fees. While the analysis shows that industry is not a key factor of audit fees, it also indicates that audit fees are not affected by auditor rotation. The current study strongly reinforces that most prior studies are also appropriate to the Cameroonian audit market. This research is unique since it's the first to empirically determine factors affecting the level of audit fee paid by auditee in the context of Cameroon.

Keywords: audit fees, auditor, auditee, Cameroon

Received January 03, 2022; Revised February 05, 2022; Accepted February 11, 2022

Citation: Samuel Tanjeh Mukah, Michael Forzeh Fossung, Kueda Wamba Berthelo, Samka Marion Nyuykighan, The Determinants of Audit Fees: The Context of Cameroon. Journal of Finance and Accounting, 10 (1). 7-14. January 2022. doi:10.12691/jfa-10-1-2

1. Introduction

The external audit fees paid by companies to their auditors are of interest to the auditees and the auditors. Companies wish that an effective audit be conducted by audit firms at the lowest price possible, while audit firms want to provide audit services at the highest price possible. Furthermore, the level of audit fees and how they are determined are significant matters to both national and international professional bodies to indicate the basis on which audit fees should be determined [1].

Simunic [2] was the first to empirically investigate the determinants of audit fees in the private sector using publicly quoted companies [3]. Simunic [2] pointed out that audit fees depend, among other things, on the size of the auditee, the complexity of the 'auditees' operations, and auditing problems associated with financial statements. The proper management of companies in general and financial institutions in particular is exceptionally complex and problematic in Cameroon and the world. Enron, an energy company that traded extensively in energy derivatives markets, caused one of the major scandals which shook the auditing profession and the world. In 2000, Anderson earned 25 million USD in audit fees and 27 million USD in consulting fees. This amount accounted for roughly 27% of audit fees of public clients for the Andersons Houston office. Yet, Anderson did not fulfil its professional responsibilities in connection with auditing Enron's financial statement. The accounting scandal of Enron in 2001 puts to question the independence of certified public accountants serving as auditors. In 2002 Arthur Anderson was also implicated in the collapse of WorldCom, one of the biggest telecommunications companies in the United States. Arthur Andersen, as auditor, was found to have failed in taking proper steps to detect accounting irregularities.

In 2018 there was a spectacular collapse of GETBACK S.A in Poland. Moreover, in its reports for 2018, its legal successor showed a loss of PLN 1.56 billion, negative capital of PLN 2.2 billion and a position that was particularly surprising because revenues were negative and amounted to PLN 730 billion. When examining the financial statements for 2017, the auditor finally issued a disclaimer opinion, and the entire issue became extremely popular in the media due to the many irregularities. The largest companies paid millions of Zlotysfor an audit (WSE–listed polish companies, 2019) and millions of Zlotysfor an audit (WSE –listed polish companies, 2019), but this does not protect investors from losses. GETBACK S.A paid PLN 6.9 million to its auditors in 2018, where more than PLN 5 million was remuneration for assistance at the initial public offering.

In Africa, we have the case of the Nigerian banking crisis in 2009. Francis [4] mentioned that contrary to auditors' claims to protect the public interest, accountants are partly responsible for cases of distress and the collapse of banks in Nigeria. They failed to qualify their reports when there were indications of financial difficulties in the banks. The Nigerian banking crisis indicated conflicts of interest which arose when PwC received 112 million (in 2007) and 208 million (in 2008) in audit fees from Intercontinental bank plc (annual report 2008).

Regarding the accounting scandals in Cameroon, we have the case of SODECOTON, CAMAIR Co, CONFINEST and recently (in 2016), the BICEC case. We understand that the quality of accounting information produced and disseminated attracted the attention of multiple users. Indeed, it was discovered that despite the controls of COBAC and external auditors at these banks, an amount of fifty (50) billion FCFA was swindled from BICEC, [5]. Regarding the case of SODECOTON, attendance fees of one million per auditor at each meeting seemed to have compromised their independence and objectivity. They could no longer identify or report the irregular keeping of accounts. Undoubtedly, this act affected audit quality within the organisation and auditors also provided non-audit services, which affected audit fees [6]. The multiple challenges of auditors' work by « la Chambre des Comptes » constitute the basis of the failure of the role of auditors in auditing public enterprises in Cameroon. The case of private companies is not different.

This study aims to find out the determinants of audit fees in the context of Cameroon, highlighting the relationship between audit firm characteristics, auditee characteristics and the relationship between auditor and auditee characteristics and audit fees. Specific objectives were to: 1. determine the extent to which the size of an auditee influences audit fees; 2. Determine if audit firm’s experience influence audit fees; 3. determine the impact of audit report lag on audit fees; 4. Determine if the duration of audit mandate influences audit fees; 5. Determine the impact of industry type on audit fees; 6. Determine if the rotation of auditors influence audit fees; and 7. Determine if the client’s complexity influence audit fees.

2. Literature Review

The agency theory was considered a fundamental theory in this study. It states that a company consists of a nexus of a contract between the owners of economic resources (the principal) and managers (the agents) who are charged with using and controlling these resources [7]. According to this theory, "top management does not always act to maximise shareholders' return on investment in a public corporation". Consequently, it becomes the central problem concerning shareholders' interests. Corporate executive agency costs are incurred following the divergence between management interest and shareholders interest [7]. The essence of the agency theory deals with the relationship between business principals and their agents, where agents can carry out activities that are not in line with the principal's interests [7]. Agency theory helps to explain the development of audit quality and audit fees [8]. Agency theory guided the research in understanding how audit quality and audit fees came about. Independent audits ensure that that the relationship between the principal and agents is cordial.

Another theory considered was the audit pricing theory. This theory was provided by Simunic [2]. He asserted that an external audit fee is simply a pair of market-clearing quantity (q) and price (p). The quantity represents labour hours, and the price represents an average hourly billing. Simunic [2] developed a positive model of the process by which audit fees are determined. An audit fee is the product of unit price and the number of audit services demanded by the management of the audited company (auditee). Cross-sectional differences in fees can represent either the effect of quantity differences or price differences. In this regard, the service is viewed as an economic good to the auditee, with substitutes and complements in consumption. Thus, the quantity of auditing demanded by an auditee will result from a conventional equalisation of marginal private benefits and costs. Audit fee = Q x P. Interesting, although both Simunic [2] and Francis [9] provided great discussions of the predictor variable in their models. Audit fees are observable, but neither P nor Q is observable without access to proprietary internal firm data. However, the current audit fee theory has not developed sufficiently to allow P and Q to be separately modelled, so existing audit fee models jointly estimate an unobservable price and quantity.

Empirical studies to establish the relationship between audit fees and client size abound. Simunic [2], Simon & Taylor [10], Alhassan [11], Karol & Piotr [12] found a positive relationship between audit fees and client size, while Fleming & Romanus [13], Walid [14], found a negative relationship between client size and audit fees. Simunic [2], Hay [15], Alhassan [11] found a positive relationship between client profitability and audit fees. However, Hossain & Sobhan [16], Elkana [17] found no association between audit fees and client profitability. In contrast, Edosa & Chinwuba [18] found a negative relationship between audit fees and client profitability. Yousef [19], Elkana [17] discovered client size is positively related to audit fees. Karol & Piotr [12] found a negative relationship between audit fees and client complexity. Taylor [10], Alhassan [11] found a positive relationship between client risk and audit fees, while Elkana [17] found no association between audit fees and client risk. Hassan & Naser [1] found a negative relationship between client risk and audit fees. Elkana [17] found no association between reporting season and audit fees. Edosa & Chinwuba [18] asserted that industry type has a positive relationship with audit fees, while Yousef [19] argued that industry type has a negative relationship with audit fees.

Previous research has also been carried out relating to auditor attributes. The status of audit firms has a positive relationship with audit fees [20]. In contrast, Yousef [19] argued that audit fee has a significant negative relationship with the status of the audit firm.

Lastly, studies have also shown a relationship between audit fees, the auditor, and the auditee. Bedard & Johnstone [21] found a strong relationship between audit tenure and audit fees. Chan et al. [22] discovered a positive relationship between audit fees and audit reports, while Dao & Pham [23] argued that audit fees negatively correlated with audit reports.

From the above empirical literature review, the following research hypotheses are formulated:

Auditor characteristics and audit fees

H₁: Experience of the audit firm has a significant positive influence on audit fees.

H₂: Audit report lag has a significant positive influence on audit fees.

Auditee characteristics and audit fees

H₃: Industry type has a significant positive influence on audit fees.

H₄: Auditee size has a significant positive influence on audit fees.

H₅: Client complexity has a significant positive influence on audit fees.

Auditor/Auditee characteristics and audit fees

H₆: Rotation of audit team has a significant positive influence on audit fees

H₇: Duration of the mandate has a significant positive influence on audit fees.

Figure 1. Conceptual Model (Source: Authors)

Table 1. Previous research on determinants on audit fees from 2020-1980

Table 1 summarises the empirical literature reviewed above related to the determinants of audit fees considering authors from 1980 to 2020.

From Table 1, it is revealed that:

From the year 2015 to 2020, most of the variables that were used by authors who carried out studies on the determinants of audit fees were client size, client complexity, Big four, client profitability, leverage, auditor size, auditor experience, auditor reputation, rotation of audit team, client risk, reporting time lag, industry type, and the status of audit firms. Variables such as duration of the mandate, client size, rotation of audit team and financial risk were not actually used.

Also, from the Year 1980 to 2014, the variables that were used mainly by authors were client size, client complexity, Big four, client profitability, audit tenure, financial risk, auditor size, auditor experience, auditor reputation, reporting time lag, rotation of audit team members, client risk, reporting season, industry type and status of the audit firm, while variables such as duration of mandate and leverage were not actually used.

Despite a fair amount of literature on the subject determinants of audit fees, little has been mentioned concerning the duration of the mandate, rotation of audit team members, client size, client complexity, industry type, the experience of the audit firm, and audit report lag. Therefore, this study covers the gap lacking in existing literature regarding the variables mentioned above. Also, a project of this nature has not yet been carried out in the context of Cameroon. So this will enable readers, audit firms and client firms in Cameroon to be more informed on the determinants of audit fees.

3. Methodology

This study makes use of the causal research design. The instrument used for data collection is a structured questionnaire administered to 249 companies. These companies were made up of companies having an obligation to make their accounts certified by an auditor and operating in three regions of Cameroon, namely: Littoral, North-West, and Centre. These regions were chosen because they host the majority of audit firms and client firms in Cameroon. According to the national institute of statistics (2016), Littoral has 37% of companies in Cameroon, Centre 27.1%, and North-West 6.3%. On the 249 questionnaires administered, 185 were collected with more than 14 poorly filled, making a final sample of 171 companies for this study.

Table 2. Measurements of Variables

3.1. Model Specification

Multiple linear regression has been used to highlight the determinants of audit fees in the context of Cameroon.

Audit fees = ʄ(Auditor characteristics, Auditee characteristics, Auditor and Auditee relationship characteristics)

Based on the model above, the models are presented as follows:

Model 1: Predicting audit fees using auditor characteristics

[picture] | (1)

Model 2: Predicting audit fees using auditee characteristics

[picture] | (2)

Model 3: Predicting audit fees using auditor/auditee relationship characteristics

[picture] | (3)

Where: AUD_FEE represents audit fees; EXP_AUF represents the experience of audit firm; AUD_SIZ represents auditee size; CLT_COM represents client complexity; IND_TYP represents industry type; ROT_AUT represents the rotation of audit team; DUR_MAN represents the duration of mandate; ARL_AUD represents audit report lag; MO represents managerial ownership; CO represents the concentration of ownership; IO institutional ownership; ID represents indebtedness; α₁-α₇ represent the correlation coefficients of the independent variables, and ε represents the error term of the model.

4. Results and Discussion

The size of the enterprise was measured, taking into consideration the number of employees within the organisation. The analysis shows that 22.22% of the enterprises are big firms with employees between 100 and 500. Medium-sized firms made up 69.42%, with employees between 21 and 100. There were 20 big enterprises, constituting 9.36%. The employees were more than 500. Looking at the number of regions of operations, 9.36% of companies are operating in one region, 58.48% between 2 to 4 regions. However, 18.13% operated between 5 to 7 regions, and lastly, 14.04% of organisations operated in more than 7 regions. As far as the enterprises' number of activities are concerned, 81.87% of the companies carried out only one activity, while 15.79% carried out 2 to 4 activities. However, 2.34% carry out more than 6 activities. The data shows that 9.94% of companies are family businesses while 90.06% are non-family businesses. Considering indebtedness, 23.98% of companies have a low debt level, while 54.97% have a high debt level. Lastly, 21.05% have medium level of debt.

Correlation Analysis

From Table 3, we can generally observe that most of the correlation coefficient is below 0.5 which means there is a weak association between the variables to be included in the model.

Looking at the levels of significance, it was observed that the associations were significant at 1%, 5%, and 10%. Specifically, the correlation coefficient between industry type and audit fee was 0.218. This indicated that there was a positive but weak association between the two variables at 1%. However, the correlations between the experience of the audit firm and client complexity 1 indicated a coefficient of -0.147. This was a negative and weak association at 5% significance. The correlation coefficient between capital concentration and auditee size indicates a correlation coefficient of 0.312. This states that there is a positive but weak correlation between the variables at a 1% level of significance. The coefficient between the concentration of ownership and client complexity1, audit report lag, management ownership and institutional ownership indicates positive values. This means that there was a positive but weak association between these variables at the level of 1%. The above correlation analysis also suggested that there may not be any multicollinearity problem. But to confirm this, VIF test was run.

Table 3. Correlation Analysis

Verification of Multicollinearity

To confirm the absence of multicollinearity predicted by the previous correlation analysis, a Variable Inflation Factor (VIF) calculation was done and results given in Table 4.

Table 4. MultiCollinearity Statistics

Table 4 shows typically that Variance Inflation Factor (VIF) is less than 10, implying all the variables are correlated with low-level multicollinearity. Specifically, the experience of audit firms with VIF =1.88 greater than 1, stated that it is associated with low-level multicollinearity. And following Hair et al. [39], the VIF value less than 10 indicates that multicollinearity is not a severe concern in interpreting the findings. Hence all the variables can be included in the model.

The multilinear regression was carried out concerning each model. Model one was the effect of audit firm characteristics on audit fees in the context of Cameroon.

Table 5. Audit firm characteristics and audit fees

From Table 5, it is observed that the experience of the audit firm and indebtedness has positive but insignificant association with audit fees. Also, it is noticed that there is a positive but weak association at a significance level of 1% between audit report lag, management ownership, concentration ownership and audit fees. Moreover, one could conclude that this model is significant with F-statistics 0.0236 and the p-value of 0.010. The R squared coefficient is 0.0842, which means that we have an 8.42% variance in audit fees explained by the model.

In model two: The effect of auditee characteristics on audit fees in the context of Cameroon was given in Table 6.

Table 6. Multilinear regression on auditee characteristics and audit fees

From Table 6, we understand that auditee size and management ownership has a negative and insignificant effect on audit fees. Institutional ownership has a negative and significant impact on audit fees at the level of 5%. Client complexity1 and client complexity2 have a positive and significant effect at the level 5% on audit fees. There is a strong positive and significant relationship between industry type and audit fees at the level of 10%. Moreover, one could conclude that this model is significant with F-statistics 0.0029 and a p-value of 0.082. The R squared coefficient is 0.1330, which means that the model explains 13.3% of the variance in audit fees.

Model three states the effect of the relationship between auditor and auditee characteristics on audit fees in the context of Cameroon had the results presented in Table 7.

Table 7. Auditee/auditor characteristics and audit fees

Table 7 indicates that audit team members' rotation and management ownership negatively and significantly associated with audit fees. Also, we noticed that there was, between institutional investors and audit fees, a negative and significant relationship at 1%. Concentration ownership has a positive and weak association at a significance level of 1% with audit fees. The duration of the mandate has a positive and significant impact on audit fees at the level of 10%. Moreover, we could conclude that this model is significant with F-statistics 0.0026 and the p-value of 0.000, suggesting that the hypothesis could be partially valid. The R squared coefficient is 0.1550, meaning that the model explains 15.5% of the variance in audit fees explains 15.5% of the variance in audit fees.

4.1. Discussion of Findings

Model one: The effect of audit firm characteristics on audit fees in the context of Cameroon

The first hypothesis speculated a positive relationship between the experience of the audit firm and audit fees. The regression analysis confirms this hypothesis. This could be explained by the fact that an increase in the experience of audit firms will lead to an increase in audit fees. The firm achieves experience by training and probably sponsorship of its members, in and out of the country. The extra cost incurred by the firm due to accrued experience is transferred to the company in terms of an increase in audit fees. Also, since perfection comes with a high price, charging more is necessary. This result goes in line with the study conducted by Read [24], Siheng [26], Addullah [27], Doa & Pham [23]. However, this result contradicts that of Alhassan [11], which held that the experience of audit firms has a negative influence on audit fees.

The results also confirmed the second hypothesis, which stated a positive relationship between audit report lag and audit fees. This could be explained by the fact that auditing companies tend to be very busy during this period leading to more audit fees. This showed that the longer the period between the audit report and the preparation of the financial statements the higher the audit fee. This corroborates the findings of Read [24], Merve & Rafet [25] and Alhassan [11], which indicated that audit report lag (i.e. the length of days required by the auditor to complete the audit process of the company's financial statements after the closing date of the company's books) has a positive relationship with audit fees.

Model two: The effect of auditee characteristics on audit fees in the context of Cameroon

The third hypothesis expected a positive relationship between the industry type of client and audit fees. Our finding confirms such a relationship. Manufacturing companies that are characterised by high technology need extra effort to complete the auditing process due to its complexity leading to higher audit fees than non-manufacturing companies. Prior literature consistently agreed that manufacturing companies must disclose more compulsory or voluntary information than others [16]. Therefore, the involved complexity in the control of financial statements for manufacturing companies requires higher audit fees. This result goes in line with research carried out by Siheng [26], Addullah [27] and Edosa & Chinwuba [18] and Simunic [2]. Thus it can be argued that industry type is considered as an important dominant determinant of audit fees. However, Elkana [17] did not detect this significance.

The fourth hypothesis expected a positive relationship between auditee size and audit fees. Our finding did not confirm such a relationship. This finding is based on the assertion that medium-sized companies do not have more transactions and records to be examined. The auditors will require less time, less staff, and less effort to carry out the audit. Less effort and time are what translated to a low charge as audit fees. Also, these companies faced financial issues and thus, affected the amount of audit fees to be paid. This finding supports the finding of Gonthier-Besacier & Schatt [40], which asserted that the smaller the client size, the lower the audit fees. This result also agrees with those of the research carried out by Xu [29]. However, it contradicts some previous studies, such as Read [24] and Merve & Rafet [25], asserting that firm size is a major determinant of audit fees.

The study points out that client complexity1 (measured by the number of regions in which the firm is operating) is positively and significantly associated with audit fees. This indicates that the more regions a company is operating, the higher the external audit fee. Also, the paper points out that client complexity2 (measured by the number of activities the firm carries out) is positively and significantly associated with audit fees. This means that the more activities the firm has, the higher the audit fee. Therefore, the client complexity is considered as an important dominant determinant of audit fees. This result is in consonance with that of Elkana [17], Ivam [28], Yousef [19], Owu et al. [30], and Simunic [2]. However, the results do not agree with those of Read [24], Merve & Rafet [25], and Xu [29], which indicate a negative relationship with audit fees.

Model three: The effect of the relationship between auditor and auditee characteristics on audit fees in the context of Cameroon

In relation to the rotation of audit team members, the findings showed a negative relationship with audit fees. This indicates that in Cameroon, the rotation of audit team members is not a determinant of audit fees. This result is in line with earlier research carried out by Daniel [31], Yousef [19], Elkana [17], and Alhassan [11], in which they found that rotation of audit team member has a negative relationship with audit fees. Furthermore, the findings indicate that the duration of the mandate has a positive relationship with audit fees in Cameroon. It is understood that the longer the auditor works in the organisation, the more he gains knowledge, which leads to higher audit fees.

5. Conclusion

The main objective of this study was to investigate the determinants of audit fees in the context of Cameroon. Through a causal research design, data were gathered by a questionnaire administered to firms qualified and authorised to carry out external audits. The main findings revealed that audit fees in Cameroon are determined by the audit firm's experience, audit report lag, client complexity, duration of the mandate, and industry type. Most companies did not disclose both the audit and non-audit fees in their financial reports. Therefore, it was recommended that OHADA law provide mandatory disclosure of such amounts and provide criteria defining audit and non-audit fees. This will enable interested parties in the published reports to determine how much they can rely on the reports.

This study contributes insights into the international audit fee literature by empirically investigating the pricing of fees in Cameroon. Audit scholars can benefit from the findings of this study in the development of future research about the audit market in Cameroon. However, the effect of macroeconomic factors such as inflation was overlooked in the study. Further research could be carried out on this topic, considering the various sectors (primary, secondary and tertiary sectors); other variables such as client profitability, financial risk, differentiate family from non-family companies, and even private from public companies.

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