The problem of the proper supervision of listed companies is extremely complex and a current one in Poland. In 2018, there was a spectacular collapse of GetBack S.A. (currently Getback S.A. in restructuring), which debuted a few months earlier on the Warsaw Stock Exchange (WSE). Moreover, in its report for 2018, its legal successor shows a loss of PLN 1.56 billion, negative capital of PLN 2.2 billion and a position which may be particularly surprising because revenues are also negative and amount to PLN -730 million. When examining the financial statements for 2017, the auditor finally issued a disclaimer of opinion, and the entire issue became extremely popular in the media due to the many irregularities (e.g. the mode of the sale of bonds of GetBack S.A., the transactions of the company with related entities, the work of the auditor), which are currently the subject of prosecution proceedings.
The subject of fees for statutory auditors in Poland appears in the context of this still unfinished case. The largest companies pay many millions of zlotys for an audit, and yet this does not protect investors from losses. The above-mentioned GetBack S.A. paid PLN 6.9 million to its auditor in 2018 where more than PLN 5 million was remuneration for assistance at the initial public offering (IPO). This article aimed to understand the determinants of audit fees based on data from WSE-listed Polish companies, compared to factors identified in world literature.
This article explores the issue of audit fees for a mandatory audit of the financial statements of companies listed on the WIG20, mWIG40 and sWIG80 indices of the WSE for 2018.
To explain what influences audit fees, several theories that have appeared many times in studies concerning this issue should be considered. The first of these is the agency theory developed in the 1960s and 1970s. The essence of the agency theory is the relationship between business principals and their agents, where the agents can carry out activities that are not in line with the principals’ interests (Jensen & Meckling, 1976, p. 313). From the perspective of this theory, the entire company is perceived as a network of contracts, whereas stakeholders (suppliers, bankers, customers, employees and so on) contribute to the company at a certain price. In this kind of relationship, managers act as agents who seek to obtain input from their stakeholders (bankers, shareholders, employees and so on) (Watts & Zimmermann, 1978, 1986). The involvement of an independent auditor who is appointed to represent the interests of both stakeholders and managers is one of the supervisory mechanisms that could solve the agents’ problem (Jensen & Meckling, 1976, p. 308). Another theory derived from the agency theory is the stakeholder theory proposed by Freeman (1984). This model includes not only the external environment, broadly understood as shareholders, employees, customers and suppliers, but also new stakeholders, that is, those entities that have any interest in the activities of a given company (the media, local authorities, government agencies and so on) (Freeman, Wicks, & Parmar, 2004). In turn, in the stakeholder theory, which evolved from the agency theory, there is a conflict of interest between managers and stakeholders. However, the basic feature that differentiates both theories is that in the stakeholder theory, managers must consider the goals of all stakeholders, whereas in the agency theory, agents should first take care of the interests of the owners of capital. Here, too, the solution to the conflict of interest is to introduce an independent auditor who would provide an independent audit of financial matters and issue an opinion. It should be remembered that owners have a high demand for information, and so auditors are expected to perform their work at a very professional level (Freeman, 1984; Jones & Wicks, 1999; Donaldson & Preston, 1995; Jones, 1995). The aforementioned conflicts of interest between agents and principals or stakeholders lead to the phenomenon of information asymmetry, which results in a moral hazard. The phenomenon of moral hazard has been studied in detail in the context of research on the insurance market and refers to the situation in which the existence of an insurance contract may significantly affect actions taken by the insured (they may take more risky actions than they would if they bore the full costs of that risk) (Rowell & Connelly, 2012). In the context of financial reporting, this phenomenon may occur when companies present false reports for publication, knowing that users of financial statements are unable to prove fraud in reports without access to information from within the organisations. This problem can be partially resolved at additional costs (Spence, 1973). These costs in relation to financial reporting can include the audit costs that are incurred by a company to ensure the highest quality of financial statements.
The subject of audit fees has been repeatedly discussed in the literature, mainly due to the study conducted by Simunic (1980). He was the first to formulate a model examining the determinants of audit fees (Simunic, 1980). He provided the theoretical foundations for many future empirical studies in subsequent years. In his work, he pointed out that audit fees depend, among others, on business complexity, the size of the assets of the audited company and the asset-liability ratio. Based on the Simunic model, in subsequent years, other researchers used variables and the structure of the model itself to find out what and to what extent determines audit fees. Simunic also claimed that internal control and external auditing can substitute for each other if the former is well performed.
Existing research regarding audit fees has been used to formulate research hypotheses and select a set of variables that will be subject to further analysis. Most often, the variables used in research on audit fees are divided into two perspectives: the client's perspective (the audited) and the perspective of the auditing firm (the auditor). From the point of view of the audited company, regardless of whether we consider research on the European, American, Asian or African markets, the following variables can be listed:
the company size—many researchers have indicated a significant relationship between the company size and audit fees. It results directly from the fact that the larger the audited company, the more procedures must be performed to obtain a sufficient level of assurance that a financial statement is free from material misstatements. Following this, the auditor needs more resources (more employees involved in the audit) which results in a audit fee increase. Researchers usually determine the company size based on the total assets (Wallace & Naser, 1996; Inchausti, 1997; Ali, Ahmed & Henry, 2004; Galani, Alexandridis, & Stavropoulos, 2011; Ali & Aulia, 2015; Demirkan & Zhou, 2016; Liu, 2017), sales volume (Inchausti, 1997; Depoers, 2000; Prencipe, 2004; Rouf, 2011) or market capitalisation (Naser, Al.-Kwari, & Nuseibeh, 2006; Chatterjee & Mir, 2008). The company size is also determined based on various combinations of data from the balance sheet of the company, such as the volume of inventories, debt, liabilities or receivables (Simunic, 1980; Taylor & Simon, 1999; Hay, Knechel, & Wong, 2006; Hassan & Naser, 2013). In this article, the variables that determine sales volume, total assets and revenue growth are used as variables in the model.
Hence, hypothesis H1 is as follows: factors related to the company size, such as the total assets, sales volume and the increase in revenues, positively affect the amount of audit fees.
profitability—the literature on the subject also indicates a possible correlation between audit fees and the profitability of the audited company (Joshi & Al-Bastaki, 2000; Dekeyser, Gaeremynck, & Willekens, 2019). It can be argued that this is because high-profit companies also disclose more information and brag about their achievements (Watts & Zimmermann, 1986). High-profit companies also pay their managers’ high salaries, and so the management boards of these companies may strive to confirm their competence and justify their high remuneration (Inchausti, 1997). Researchers used various combinations of profitability ratios: net profit, net profit to sales ratio, return on assets (ROA) ratio and return on equity (ROE) ratio. In their research, they have proved that audit fees depend on the company's profitability and that this correlation is significant (Simunic, 1980; Francis and Simon, 1987; Hay, Knechel, & Ling, 2008; Nam, 2018). Most often, this variable was used as a discrete variable describing either profit or loss, and its size was irrelevant.
Therefore, hypothesis H2 has been formulated: factors related to the company's profitability, such as net profit and ROA have a positive impact on audit fees.
complexity—other interesting variables used by researchers are undoubtedly various combinations of business complexity. Researchers have indicated a positive relationship between the number of subsidiaries (the size of a corporate group) and audit fees (Simunic, 1980; Cameran, 2005; Joshi & Al-Bastaki, 2000; Clatworthy & Peel, 2006; Thinggaard & Kiertzner, 2008; Ellis & Booker, 2011; Verbruggen, Christiaens, Reheul, & Van Caneghem, 2011). The main reason for this is that the more entities form a corporate group, the more time the auditor needs to express an appropriate opinion (Sandra & Patrick, 1996). It should also be noted that the more foreign entities there are in a corporate group, the more difficult a task it is for the parent company to create a consolidated financial statement because subsidiaries operating in other markets do not necessarily apply the international accounting standards (IAS)/the international financial reporting standards (IFRS) in their accounting. Therefore, when creating consolidated financial statements, the parent company must also adjust the data reported by subsidiaries according to the applicable IAS requirements for the consolidated financial statements of WSE-listed corporate groups. Moreover, the study (Clatworthy & Peel, 2006) indicates that the more companies in a corporate group, the greater the auditor's exposure to claims than that of the smaller entities. Researchers have also described the complexity of operations, that is, operating segments (Langendijk, 1997; Joshi & Al-Bastaki., 2000; Tee, Gul, Foo, & Teh, 2017) and the structure of total assets (Peel & Clatworthy, 2001; Simunic, 1980; Francis & Stokes, 1986; Francis & Simon, 1987; Joshi & Al-Bastaki, 2000; Carson, Fargher, Simon, & Taylor, 2004; Gonthier & Schatt, 2007; Thinggaard & Kiertzner, 2008). In the literature, complexity factors are also described as the number of operational entities in a corporate group, the number of countries in which they operate, and the number of separate opinions that an auditor must issue during the audit of the corporate group. Moreover, in the research, there are also indicators related in other ways to the company size, that is, the cash flow to total assets ratio. For this work, various ratios regarding the structure of a corporate group, inventories, receivables, debts and cash flows are used.
Therefore, hypothesis H3 takes the form of the specification: complexity factors, that is, the percentage of foreign companies, the operating cash flow to total assets ratio, ratios regarding inventories, receivables, debt, the number of operating segments, if there has been a merger/acquisition and prior year adjustments have a positive effect on audit fees.
In turn, from the auditors’ point of view, the size of the audited firm is primarily considered. Although initially the research from the 1980s (Simunic, 1980) did not indicate a significant impact of the company size on audit fees, as the years went by a high premium for being a large auditing company began to be noticeable. For example, Craswell set the amount of premium at 34% in his research on audit fees, based on the data of companies listed on the Australian Stock Exchange (Craswell, Francis, & Taylor, 1995).
Researchers also emphasise that large auditing firms can afford higher earnings compared to small auditing firms. The fact of an additional premium for being a ‘Big Four’ company has also been indicated (DeAngelo, 1981; Haniffa & Cooke, 2002; Glaum & Street, 2003). The aforementioned relationship also results from the fact that these companies are more visible in the market of auditing companies and thus more exposed to serious image consequences in the event of an erroneous auditor's opinion (e.g. the case of Enron resulted in the collapse of the well-known auditing firm of Arthur Andersen, which was taken over by PricewaterhouseCoopers). This greater pressure and more significant consequences in the event of failure mean that the owners of large companies are more likely to choose the ‘Big Four’ firms as their auditors, believing that, thanks to their standards, their financial statements will be prepared in accordance with the relevant financial reporting framework and give a true and fair view of the financial position. Thus, the status of the ‘Big Four’ is associated with an additional premium for the companies’ reputation (Huang, Liu, Raghunandan, & Rama, 2007; Choi, C. Kim, Kim, & Zang, 2010; Wang, Sewon, Iqbal, & Smith, 2011; El-Gammal, 2012).
Based on these considerations, hypothesis H4 has been formulated: audit fees are positively dependent on whether a company is audited by one of the ‘Big Four’ firms or by another entity.
To date, other research hypotheses have appeared in the literature on audit fees, such as audit fees inversely depend on the time elapsed between the date of the auditor's opinion and the balance sheet date (Habib, Bhuiyan, & Rahman, 2019); audit fees are higher if a fiscal year ends in accordance with a calendar year than if a fiscal year ends at a different date (McMeeking, Peasnell, & Pope, 2006; Tee et al., 2017); the length of cooperation with an auditor is inversely proportional to the amount of audit fees due to the smaller effort of the auditor in the process of recognising the weakness of internal control (Okolie, 2014) or the closer relationship between the auditor and the audited entity (Barkess and Simnett, 1994; DeFond, Raghunandan, & Subramanyam, 2002; Carcello & Nagy, 2004). In turn, in his study, Knapp (1991) pointed out that, in the United States, the likelihood that an auditor will indicate significant irregularities increases in the first years of cooperation and then decreases reaching its minimum after 20 years of cooperation; reports other than the so-called clean opinions have a positive impact on the amount of audit fees (Verbruggen, Christiaens, Reheul, & Van Caneghem, 2015).
The study used data from published financial statements and reports on the activities of the management boards of companies listed in the WIG20, mWIG40 and sWIG80 indices in 2018. In the case of entities that form a corporate group, data from consolidated financial statements were studied. In the case of other entities, data were collected from separate financial statements. In the case of a financial year ending on a day other than 31 December 2018, the study covered the period ending during 2018.
Due to the need to ensure comparability of data, it was necessary to remove data from the research sample concerning: companies from the financial industry (banks, insurance companies, investment funds, debt collection companies and the WSE-listed company Giełda Papierów Wartościowych w Warszawie S.A.)—19 entities; foreign companies, which are listed on the WSE but whose headquarters are outside Poland—seven entities (Kernel Holding S.A., AmRest Holdings SE, ASBISc Enterprises Plc, Astarta Holding N.V., Ovostar Union PCL, IMC S.A., Play Communications S.A.); and companies for which data for the given period were incomplete or unavailable—three entities (Capital Group S.A. and Rainbow S.A.—the data were unavailable at the stage of data collection, and Mabion S.A.—the data were available but the company did not generate revenues in 2017 and 2018). Therefore, there was no data for four variables:
The analysis of data used in the study on audit fees for the mandatory audit of financial statements and an auditor's own experience related to work in an audit company allowed the selection of variables used in the linear regression model. The variables are described in Table 1. Basic statistics of the data set used in the model are presented in Table 2 (non-logarithmic values are given).
Description of the variables used in the study
N/A | Natural logarithm of the amount of audit fees for conducting a mandatory audit of an entity's financial statement in the period covered by the statement (including fees for reviews of financial statements) | |
+ | Natural logarithm of the total assets | |
+ | Discrete variable coded as 1 if a company's auditor is Deloitte, EY, KPMG or PwC, and 0 in other cases | |
+ | Discrete variable coded as 1 if there was a merger or acquisition of entities forming a corporate group during a financial year and 0 in other cases | |
+ | Company's debt to total assets ratio | |
+ | A company's total short- and long-term receivables and inventories | |
+ | The ratio of the number of foreign companies in a corporate group to the number of all companies forming the corporate group | |
+ | Natural logarithm of sales volume in 2018 |
Basic characteristics of the variables (non-logarithmic values for the variables
598,957 | 1,028,801 | 16,000 | 5,881,000 | |
5,478,254,619 | 12,263,775,906 | 34,686,420 | 75,905,000,000 | |
0.6306306 | 0.4848229 | 0 | 1 | |
0.2432432 | 0.4309865 | 0 | 1 | |
0.1638752 | 0.1459938 | 0 | 1 | |
0.3086383 | 0.2124534 | 0.0061615 | 0.8692479 | |
0.2534987 | 0.2651958 | 0 | 0.9545455 | |
4,488,839,727 | 11,919,499,823 | 17,486,560 | 109,706,000,000 |
Considering our main variable (
Correlation analysis shows that two variables,
Correlation between variables
1 | |||||||
0.4497* | 1 | ||||||
0.1461 | 1 | ||||||
0.1153 | 0.3038* | 0.1318 | 1 | ||||
−0.1528 | −0.2342* | −0.097 | 0.3808* | 1 | |||
−0.0311 | 0.0733 | −0.0311 | 0.118 | 0.0544 | 1 | ||
0.8593* | 0.3053* | 0.1612 | 0.2627* | 0.0893 | −0.1229 | 1 |
Significant at the confidence level of 5%.
In the initial version of the study, six discrete variables were classified:
The first version of the model assumed the use of 13 continuous variables. However, after performing the first regression, it was indicated that there would be premises to claim that some of these variables would be insignificant. The highest
The
In the next step, three subsequent variables were analysed:
Another variable that should be considered when determining the final value of the model is the variable of sales in 2017 (
The next step involved analysing the variables that were significant in the initial version of the model, that is,
In the case of the
The variable of revenue for 2018 (
After analysing the significance of continuous variables, those of
After taking a series of steps to determine the final version of the model, the final regression was carried out using the formula:
The results of the final version of the linear regression model are presented in Table 4. In this version of the model, there are no more insignificant variables (the
Final version of the linear regression model
To test the correctness of the presented model, Ramsey's RESET test was used. The result of
This article is based on data from WSE-listed companies for 2018 and describes the empirical study on the impact of various variables on audit fees. Having conducted a range of tests and the analysis of factors, we have selected variables that are significant in the final version of the linear regression model. According to the results presented in the final version of the model, it can be seen that the amount of audit fees depends positively on company size measured by the total assets, the sales volume of the audited company, the ratio of debt to the total assets, the number of foreign companies relative to the total number of companies in a corporate group, the fact of a merger or acquisition in the audited financial year and the fact that a company was audited by a ‘Big Four’ auditing firm. Moreover, audit fees depend negatively on the complexity of the total assets (measured as the sum of inventories and receivables relative to the total assets). Therefore, it should be stated that there are no grounds to reject some of the research hypotheses put forward at the beginning of this study. The study only has fully confirmed hypotheses H1 and H4, saying that the company size and the fact that a company was audited by a ‘Big Four’ firm positively affect audit fees. This correlation is also convergent with the results of international research on this topic. Hypothesis H3 on the positive effect of complexity factors has been partially confirmed. In this study, this hypothesis has been rejected by a negative result for the
In this study, the negative impact of business complexity on audit fees may be striking. Companies with a
The
The literature review shows that the number of studies on the determinants of audit fees in Central and Eastern Europe is very limited and requires further study. This article contributes to global research into audit fees. Based on the literature review, a model has been developed which uses data collected from the financial statements of WSE-listed Polish entities. In this model, the variables that have proved to be significant include: the variable regarding the total assets and revenues for 2018 (in a logarithmic form); business complexity calculated as the sum of inventories and receivables relative to the total assets; the company's debt ratio; the number of foreign companies relative to all companies forming a corporate group; and two discrete variables regarding the fact that an entity was audited by a ‘Big Four’ firm and that there was an acquisition or merger with another entity in a given financial year. The study has shown positive correlations of variables (except for the
The research on audit fees in Poland should be further developed. Interesting results could be obtained, for example, through the disaggregation of the
Considering the specificity of the Polish audit market and the fact that dynamic changes have been observed in the functioning of capital markets in Poland over the past 30 years, the results obtained in the study cannot be generalised to all Central and Eastern European countries. However, it should be noted that this is not the purpose of the study.
Thanks to the results obtained, this article is a complement to world literature and gives an overview of the determinants of audit fees in one of the countries of Central and Eastern Europe. The results are consistent with the results obtained in other countries of the world, although there are some differences in details concerning the conclusiveness of the tested model. The study certainly gives an insight into the specifics of one of the Central and Eastern European countries.