The new audit report, the KAM paragraph size and its effect on the audit quality

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The new audit report, the KAM paragraph size

and its effect on the audit quality

Name: Reinald Lebbink Student number: 11274328

Thesis supervisor: E.d.o. Roos Lindgreen Date: June 25, 2018

Word count: 14938, 0

MSc Accountancy & Control, specialization Accountancy Faculty of Economics and Business, University of Amsterdam

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Statement of Originality

This document is written by student Reinald Lebbink who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

The aim of this research is to investigate whether the introduction of the new audit report effects the perceived audit quality. The Nederlandse Beroepsorganisatie van Accountants has decided in June 2014 to introduce the new audit report for all Dutch listed companies. After series of financial scandals and the financial crisis the society was looking for a higher degree of assurance and the users of the financial statements needed more information to rely on. The users were also interested in the materiality, the identified risks and the audit approach that is used in order to provide an opinion from the auditors. The accounting profession was put under scrutiny and they had to meet increasingly stringent requirements. On the other hand, auditors are now providing more information than before. They are taking a huge risk by doing this and could expect reputational damage when things are not going well. Being aware of this risk, auditors are now intentionally trying to provide audits of higher quality. By better communication and more disclosure, the audit quality should increase and the users of the financial statements will benefit more from this (Humphrey, Loft and Woods, 2009; Turner, 2007). According to prior latter study, the new audit report seems to have a positive effect upon the audit quality. Therefore, this research examined the new audit report and the size of a Key Audit Matter paragraph and its effect on the audit quality, using Dutch listed companies from book year 2014. Results in this research indicates that there is no relation between the new audit report and the perceived audit quality. There is no significant evidence found that the new audit report’s effect increases or decreases the audit quality. The contradiction between the results and the expectations of this study could be explained by the new paragraph (Key Audit Matters) that was added in the new audit report. It is possible that it take time to observe the effect of this, since the introduction of the new audit report and the Key Audit Matter paragraph was implemented recently. This research contributes to empirical studies by expanding the existing literature about the new audit report and the Key Audit Matter paragraph and enables the possibilities for future research.

Key words: Expectation gap, new audit report, Key Audit Matter, IAASB, discretionary accruals, audit quality, Big 4.

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List of images and tables

Images and tables

Image 1.1 Audit expectation-performance gap Table 1.1 Final sample selection

Table 1.2 Variables explanation

Table 3.1 Descriptive Statistics for hypothesis 1 Table 3.2 Descriptive Statistics for hypothesis 2

Table 4.1 Skewness/Kurtosis test for Normality for hypothesis 1 Table 4.2 Skewness/Kurtosis test for Normality for hypothesis 2 Table 4.3 Shapiro-Wilk W test for normal data for hypothesis 1 Table 4.4 Shapiro-Wilk W test for normal data for hypothesis 2

Table 5.1 Descriptive statistics of sample before winsorization for hypothesis 1 Table 5.2 Descriptive statistics of sample after winsorization for hypothesis 1 Table 5.3 Descriptive statistics of sample before winsorization for hypothesis 2 Table 5.4 Descriptive statistics of sample after winsorization for hypothesis 2 Table 6.1 Spearman rank correlations for hypothesis 1

Table 6.2 Spearman rank correlations with p-values for hypothesis 1 Table 6.3 Correlation for hypothesis 1

Table 6.4 Correlation with p-values for hypothesis 1 + VIF values Table 1.7 Regression Analysis model for hypothesis 1

Table 8.1 Spearman rank correlations for hypothesis 2

Table 8.2 Spearman rank correlations with p-values for hypothesis 2 Table 8.3 Correlation for hypothesis 2

Table 8.4 Correlation with p-values for hypothesis 2 + VIF values Table 1.9 Regression Analysis model for hypothesis 2

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1 Introduction

For decades the accounting world has dealt with different changes in the law and regulations in their role in detecting fraud and materiality in annual reports. This was the result for the financial crisis that escalated in 2008. The IAASB (short for International Audit and Assurance Standards Board) on his turn has requested transparency upon the standards for the audit and with a mainly focus on the audit report and audit quality. This came along with IAASB’s Clarity Project that has resulted in a new set of ‘clarified’ standards which are effective for audits of financial statements started in mid-December 2009. The aim of this project was to enhance the understandability of the ISAs that should improve the consistency in application and lead to an improvement in audit quality worldwide. The IAASB revised all the standards to determine the transparency and quality of an audit and this has led to a new Key Audit Matters paragraph within the new audit report. This should decrease the expectation gap that existed due to the lack of trust in auditors.

According to DeAngelo (1981) audit quality is described as the quality of the financial statements. The quality of the financial statements attends to be guaranteed. According to Johnson, Khurana and Reynolds (2002) this definition was not complete and suggested that it needed to be supplemented with the probability of financial statements that possibly could occur during an audit. The new auditor’s report provides more insight in the audit by communicating very important points of auditor’s interest and the risks the auditor identified. This should lead to a more transparent annual report (FRC, 2015). The new audit report was introduced in June 2014 by the NBA (short for Nederlandse Beroepsorganisatie voor Accountants) and is since then mandatory for all Dutch listed companies (oob’s: organisaties van openbaar belang). The users of the financial statements are in need of information about the materiality, the most important and identified risks and the audit to come to a conclusion. This ‘expectation gap’ between the required information and the available information regarding the audit, is what most studies have investigated. By providing more information to the end-users, it is believed that this will affect the audit quality positively. This will also be the hypothesis of this study.

There are a few studies done upon the relationship between the audit quality and the new audit report because of the difficulty to quantify audit quality. Yet, this is very interesting to examine. The new audit report could influence the audit quality due to the provided information. The information gap may be decrease, because of the reports that contain more information. The information that is provided could be useful for decision making processes. Thus, the more information is available the more it could be influence the decisions of the users of the financial statements. Also having more insight in the audit could eventually lead to more relevant

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information and a better perspective from a company for potential investors. Their opinion might change because of the way they might value the reported information to be more relevant.

In existing literature it is stated in several studies that the new audit report will not positively affect the audit quality. In a study of Cordoş, G. and Fülöp, M. (2015) they stated that parts within the new audit report, the going concern, does not reduce the expectation gap or influence the behavior or the decision making process of the user of financial statements. Though, they mention that the Key Audit Matter paragraph will have a positive impact on the audit. Yet, the accounting profession has been scrutinized over the last decade. In addition, the study of Church et al. (2008) stated that they do not recognize the benefits of the new audit report. They cannot see the importance of a detailed report to improve the quality of an audit, due to the lack of performance in communication to the users of the financial statements. On the other hand, in a study of Humphrey, Loft and Woods (2009) they suggests that the new audit report does improve the audit quality, due to this communication of materiality. In addition to the latter study, Christensen, Glover and Wolfe (2014) concludes that the financial statements’ users use the Key Audit Matter paragraph to depend their investment on, but only if this is enclosed. On top of that, in the study according to Turner, Mock, Coram and Gray (2010) they found that the audit could decrease the expectation gap once the information upon materiality is communicated and disclosed. Disclosing key points in the new audit report will not have a negative effect upon the decision process making by the users of the financial statements. They are more likely to say that it will be experienced as a positive contribution to their decision making process (Vanstraelen, Schelleman, Meuwisen et al., 2012).

Thus, by providing more relevant information the decisions could be influenced for the users of the financial statements for the decision making process, but also their view on the level of the perceived audit quality. This study it is of great interest to determine what effect the new audit report has on the audit quality, since there are different opinions on this topic. To distinguish companies that are using the new audit report and disclose information on materiality and companies that do it in the traditional way, and comparing them, gives this study the possibility to test this effect. Important to keep in mind is carefully picking out variables. In order to safeguard the results, systematically picking out variables detects possible flaws and exclude errors or biases to the result.

This study examines the effect of the new audit report on the perceived audit quality and bringing insight on this relation is the main objective of this study. The study takes only Dutch listed companies considering into account book year 2012 and 2014, because it was obligated for

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these type of companies in 2014 but it was only an opt back in 2012. This is in my opinion interesting to examine. Hence, this study will make a comparison of the perceived audit quality before the introduction of the new audit report and after the implementation of the new audit report. Also, the size of the new audit report regards the Key Audit matter will be taken into account in this study. To give sufficient answer to this research question, two hypothesis were developed in order to test this. The first hypothesis is as follow: The perceived audit quality will be better with the new audit report than without. And the second hypothesis is as follow: The size of a Key Audit Matter paragraph has a positive impact on the audit quality.

Overall, to examine the relationship between the new audit report and the perceived audit quality, several variables were taken into the study. The audit quality is supposed to be low when the accruals are high (Francis and Krisnan,1999). Hence, The dependent variable is the audit quality and described through one proxy, the discretionary accruals.

The independent variables vary between the first and second hypothesis. To determine if the perceived audit quality will be better with the new audit report than without, the independent variable ‘Year’ is added. This variable distinguishes the year 2012, where the new audit report was not obligated for Dutch listed companies and the year 2014, where it was made mandatory for Dutch listed companies to use the new audit report. For the second hypothesis the independent variable ‘Amount of subjects’ is added. This variable looks at the amount of subjects that is elaborated in the Key Audit Matter paragraph. Because of this the audit quality will be tested if the Key Audit Matter paragraph influences the audit quality in a positive manner. Based on prior literature the variables Assets, Leverage, Growth and Big 4 are added as proxies to examine the relationship between the new audit report and the perceived audit quality.

This study ran two regression tests, one for the first hypothesis The perceived audit quality will be better with the new audit report than without and the other for the second hypothesis The size of a Key Audit Matter paragraph has a positive impact on the audit quality. Both test results showed that there is no significant evidence found as a result. This means that there is no support found for accepting both hypotheses and no significant evidence found to reject the null hypothesis.

Based on prior literature and research, it is found that the new audit report would not increase the audit quality. Yet, other studies showed the exact opposite. This study contributes to the existing literature as the relation between the new audit report, the size of the Key Audit Matter paragraph and the perceived audit quality has, to my best knowledge, not been studied yet. So this study extends the existing literature on the influence of the Key Audit Matter paragraph and the new audit report. The rest of this thesis is divided as follows: section two contains the relevant

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theory and literature review that is required to gain a better focus and insight in the background. This theory is gathered in order to explain the relationship between the new audit report and the perceived audit quality. Also, in the same section the hypotheses are formed. In section three the measurement of the selected variables, the sample selection and the research design are displayed. Following, in the fourth section the research formulas and research design are elaborated as well as the final sample selection. In section five the results of the study is presented of the tested hypotheses. Finally, the conclusion of this study is given in section six.

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2 Literature review and theory

Unfortunately, the world of accounting has gone through a lot of scandals that has led the accounting profession to uncertainty in reliability and lack of trust. It has also led the accounting profession to an urgent need of change. This necessity change included the way the audit reporting was performed and the audit quality. This phenomenon (lack of trust) was the beginning of the ‘expectation gap’. According to Wolf, Tackett and Claypool (1999) this expectation gap is the gap what the society could expect from the auditor. And also what the accounting firm perceives is that the auditors role has worsened the crisis within the accounting profession. The expectation gap is seen by Porter (1993) as the difference between the expectations of the users from an external auditor on one side and what has really been audited on the other side.

In addition, Porter (2012) mentioned in a later study that the expectation gap is defined as a gap between the accounting firms observed performance and the society’s expectations of these auditors. The gap exists in two components, reasonableness and performance. The latter is subdivided into deficient performance and deficient standards. With the audit report the auditors can provide assurance in case of the trustworthiness and reliability of the health of the organization. This determines that the auditors are held partially responsible for the misstatements that are audited.

Image 1 – Audit expectation-performance gap

According to Litjens and Vergoossen (2012) there are different thoughts between investors and auditors. They concluded that the different views and opinions on the responsibilities and tasks of the auditors have caused this expectation gap. They studied the link between the audit report and society’s expectation of this audit. High expectations of the auditors and/or regulations that set boundaries for the services for the auditors are according to Litjens and Vergoossen (2012) some of the causes that lead to the expectations gap. The expectation gap could be divided into

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distorted regulations for the accounting profession, unrealizable expectations towards the accounting profession and lacking performance of the auditors. As mentioned earlier, Porter shares that same thought. Society’s expectation plays an important role for the expectation gap, for instance, the assurance and guarantee that the audit of an organization results in no frauds in any form at all and that all transactions have been verified by the auditors.

The International Auditing and Assurance Standards Board (hereafter IAASB), provided as a reaction to the comments on the gap between the users of the annual reports or the financial statements and the accounting profession, an updated version of the International Standard on Auditing (ISA) 700. The ISA’s 700 requirements are addressing an suitable balance between the need for comparability and uniformity in reporting. The information that is provided makes the auditor’s report more relevant to the users of the financial statements. It increases the value of reporting and the trustworthiness of the audit (ISA, 2014). Gold, Gronewold and Pott (2012) stated in their article that because of the updated ISA 700 the expectation gap did not increase any further. Another conclusion they mention in their article from their research is that the audit itself provides decent information for the users of the annual reports and financial statements that is relevant.

Disclosures of problems within an organization that is discovered during an audit could assist in decreasing the expectation gap (Church, Davis & McCracken, 2008). Manson and Zaman (2001) support this theory by stating in their article that another audit performance during the audit with regard to the going concern of an organization could also lead to a decrease of this gap. In addition, another component within the audit, which is clarified in different studies that could lead to a decrease in the gap, is when auditors report on materiality and on their responsibilities in cases such as fraud during the audit process. Turner (2008) showed in his letter to the Public Company Accounting Oversight Board that they failed on improving the quality of financial reporting for public companies. He mentioned that a certain decision rule is needed: “To be consistent, a decision rule for determining reporting materiality levels should have certain characteristics. First, materiality should reflect a primary measure common to all financial statements and known to be important to users. Second, both producers and users of financial statements should understand the basis on which materiality is established. Third, for comparability the same basis should be used for all financial statements.”. This is supported by Dan, Maria, Adina et al (2010). They stated in their study that poor standard requirements, with in mind that the problems that occur is resulting from understanding the concept of materiality, whose level would be valuable if it is mentioned in the audit report by the auditors so the users of the financial statements are having the opportunity to make decisions advisedly. As a result, users of the financial statements and the audit report would have the

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opportunity to appreciate the suitability of the materiality threshold size. In another study of Turner (2007) he claimed that the users of financial statements are benefitted more when the information about the materiality is provided.

The Public Company Accounting Oversight Board (PCAOB, 2013) and the IAASB (2013) suggested to improve the audit report as a reaction upon the findings according to Mock, Bédard, Coram et al. (2013). They stated that the users of the financial statements would rather have more information provided than that has been before. The most important element in the new regulation regarding the audit report is reporting on the key points of the audit. This is known as Key Audit Matters. The key points are integrated to provide a better audit and are specific for the organization where the audit is held (NBA, 2014). With the coming of the renewed audit report, it could make the financial statements more transparent, more reliable and for the decision making process more useful for the users of the financial statements (Turner, 2008).

2.1 Renewed audit report

The standard auditor’s report is less broad than what the renewed audit report offers (Meza, 2015). By using the audit report auditors can provide insight with the information to the users of the financial statements about the auditors findings that were discovered during the audit. Auditors provide information and the users of the financial statements have a high expectation of the information. According to Dan, Maria, Adina et al. (2010) the accounting profession has responded by hiding behind the expectation gap. They concluded that the auditees and the users of the financial statements placed too high expectations on the duties of the auditor when they compared to what auditors believed the perceived duties actually should be. In 2014, after years of discussion and developing there has been, by the approval of the IAASB, a new audit report introduced. The regulators in the United Kingdom requested that the companies were required to implement and apply the new audit report standards at the end of 2012. The Netherlands started with the implementation process of the audit report after the United Kingdom (NBA, 2014).

The Nederlandse Beroepsorganisatie van Accountants (hereafter NBA) announced in 2014 the new audit report. Auditors of public interested organizations (oob’s, organisaties van openbaar belang) provide more information about the duties of the accountant in their annual report of 2014 (NBA Nieuwe controleverklaring voor oob’s, 2014). According to the NBA the audit report has an important social role. With this report the accountant provides a fair view on the financial health and results of the organization. The users, investors, society and also the accounting profession requested and would prefer an extended audit report which also provide a report upon the key points that has been found in the organization during the audit (NBA

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Voorlichtingsbrochure controleverklaring, 2014). The new audit report is an international project. The IAASB, as is known as the international regulator for auditors has sketched the blue print for this report. This new audit report was provided internationally for the annual reports of 2016. Yet, the Netherlands implemented this change of audit reporting already in 2014, they are now ahead of business developments in comparison with international companies, except for the UK.

The most important changes in the new audit report are broken down into six components. The first component in the new auditor’s report is the auditor’s opinion. The audit report is better structured and starts in the renewed version with the most important part; the auditor’s opinion. This give the users of the financial statements immediately a clear and direct view on what the auditor finds of the annual financial statements. (NBA, 2014)

The second component is the section Key Audit Matters (KAM). This is new in the auditor report (NBA, 2014). These are the most important, most significant audit risks which could occur during an audit that is discovered and observed by the auditor. In the standard is mentioned the application to assist the auditor’s decision-making process. The main goal of providing a KAM paragraph into the audit report is to add value to this report. It is to communicate those matters that, in the auditor’s judgment, were of most significance in the audit of the financial statements and is selected from matters that are communicated with those charged with governance, for instance, by the Audit Committees to enhance the transparency. In this KAM paragraph all the complexities will be discussed and explained what they mean to the users of annual report or the users of the financial statements. The description in the auditor’s report intended to provide more insight in why the Key Audit Matter was determined by the auditor as a KAM. According to Humphrey, Loft and Woods (2009) the KAM paragraphs and the used and communicated materiality led to an increase to the audit quality. In addition, Christensen, Glover and Wolfe (2014) concludes that users of the financial statements depend their investment decisions on the KAM paragraph, if this is enclosed. The going concern opinion is the third component that is added in the auditor’s report (NBA, 2014). According to Hoogendoorn and Vergoossen (2012) the financial statements are based on two fundamentals: the going concern and the accruals.

The going concern means that the accounting of an organization is based upon the continuity of the company’s activities, meaning that the financial statements are drawn up and ensure its continuity. The accrual fundamental means transactions will be processed on the moment they occur. The downside of the going concern is an incorrect estimation made by the auditor. The auditor could assess the continuity too positive, yet in reality the continuity isn’t positive in the near future. This latter fundament needs to be closely investigated by the auditor and taken into account during the preparation of the audit report.

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‘Materiality’ is in the new auditor’s report the fourth new component. Another important component within this new report is formed by the ‘key audit matters’. The auditor is obligated to explain the materiality that is used based on standard 702N. This standard discusses the form and content of the auditor’s report that will be provided as a result of an audit. According to Turner, Mock, Coram and Gray (2010) disclosing of materiality that is used during the audit could lead to a decrease of the expectation gap. It should also make users of the financial statements more alert of price fluctuations as a reaction of additional information that is provided. If the value of materiality is taken into account during the audit report, the users will perceive a better and fair view of the company. As mentioned earlier, the study of Turner (2007) shows that users of financial statements are benefitted more when the information about the materiality is provided.

The fifth and sixth components are respectively the scope which the auditor used during the audit, which is in this section that the auditor explains which parts have been investigated. And the attention for readability. In the past the users of the financial statements criticize the ‘old’ audit reports, because it contained a lot of standard wordings which makes it less relevant for the reader and decreases the readability. These texts are now more clearly articulated and could put in the disclosures or refer to the website of NBA. This makes the new audit report better readable (NBA, 2014).

2.2 Audit quality

Audit quality is according to DeAngelo (1981) described as the quality of the financial statements that serves to be kept and guaranteed and the likelihood the detection of a misstatement in the financial statement that is stated. With regard to a misstatement that is discovered is according to DeAngelo (1981) dependent on the excellence of the auditor, the used approaches to measure the financial statement and to the client. However, Johnson, Khurana and Reynolds (2002) have stated that the definition is not yet complete. They suggest that the definition needs to be supplemented with the probability of financial misstatements could occur during the audit. Francis and Yu (2009) concluded that there is a narrow relationship between the materiality and misstatements in the financial statements and the independency of the accountant. Because of this close connection the audit is dependent on the faults the accountant makes. These mistakes should be studied and corrected. The corrections are gathered under the section ‘restatements’. A restatement means that there is an improvement upon earlier audit mistakes which were made by the previous auditor (Hennes, Leone & Miller, 2014). The foundations of the audit quality depends on the auditor and his independency (Keshore & Pishori, 2014). DeAngelo (1981) concludes the less an auditor is dependent, the fewer mistakes he probably makes.

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Theory suggests that audit quality can be measured in different ways. According to Becker, Defond, Jiambalvo et al. (2010) audit quality is of higher quality with Big Six auditors than at non-Big Six auditors. The non-Big Six and non-non-Big Six are hereafter considered as the non-Big 4 and non-non-Big 4. Consistent with their prior research, they measured audit quality as a dichotomous variable. Prior research stated that bigger auditing firms in comparison with smaller auditor firms provide a higher auditing quality (Lennox, 1999; Francis & Yu, 2009; Choi et al., 2010). Greiger and Rama (2006) studied over a period of 11 year the size of the auditor and the related audit quality. They conclude the existence of a significance relation between the size of an accounting firm and its corresponding quality. Furthermore, according to Greiger and Rama (2006), previous research suggest that the relationship between auditor’s company size and the audit quality has led to other results. Yet, their research created accuracy for the distinction between the Big 4 and non-Big 4 concerning the perceived audit quality.

Contrary to previously studies, Lawrence, Meza and Zhang (2011) argues that the differences in audit qualities between the big accounting firms and smaller accounting firms are not significant. According to them both big and small accounting firms have to follow up the same regulations. Thus, smaller accounting firms could compete with the bigger accounting firms and could not lead to a difference in audit quality. They also suggests that smaller accounting firms possess more knowledge about the local markets and maintain the relationship with their clients well. This could lead to a positive contribution detecting irregularities during an audit. This eventually leads to a better audit.

2.3 Audit quality and KAM

Regulators and the society demands more transparency in the way auditors draw their conclusions, in the materiality range and the way this number is set. When auditors communicate their information, they can reach the desired transparency in the conclusion given by the auditors. The most important change in the audit report is elaborating the key audit matters in this report. According to Vanstraelen, Schelleman, Meuwissen and Hofmann (2012) disclosing key points of the audit into the new audit report will not have a negative reaction by the users of the financial statements, and will be experienced as a positive contribution. Reid, Carcello, Li and Neal (2015) agreed upon that. They also mention the outcome will be of better audit quality once the changes of the requirements for the audit report is set. A higher transparency will contribute to a better accountability and credibility of the auditors. Disclosing information on the key points that was noted during the audit process could have an impact on the behavior of the investors or the users of the financial statements. If the scope of the external auditor is expanding and improved

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due to the audit report requirement changes, than it might be helpful to improve the expectation gap (Dan, Maria, Adina et al., 2010). As a result the audit can be improved by communicating the KAMs in the auditor’s report. This contributes to enhancing its informational value to the users of the financial statements (EY, 2014). According to Christensen et al. (2014) the effect of a Key Audit Matter paragraph is reduced when it is followed by a section that is offering the resolutions of the critical audit matters. They also find that investors who receive a standard audit report, which is an information effect, or investors who receive the same Key Audit Matter paragraph information mentioned in management’s footnotes, which is a source credibility effect, are less likely to change their investment decisions in comparison with investors who receive a Key Audit Matter paragraph in the auditor report.

There are not many studies done considering the Key Audit Matters or what the impact is on the audit quality, since the introduction of the new regulations in 2012 and the implementation and application in 2014 for public interested organizations. Therefore this archival study is to gain a better understanding what this new regulation mean for listed companies in the Netherlands.

2.4 Effects of KAM on the users and the audit quality

Key Audit Matters are the uncertainties or risks that is discovered and noted by the current auditor during the audit. The identification of these risks during its audit process have an impact on the audit strategy. More insight in the audit report and the communication about it leads eventually to a better trustworthiness on the performance of the auditor by the users (NBA 702N, 2014). Church et al. (2008) stated that one of the objectives of the PCAOB standard setting process would be addressing the mourned lack of content in the auditor’s report. They concluded that the auditor’s report contains figurative values, but auditors in essence have a lack of performance in communicating useful information to the users of the financial statements. According to Heymann (2010) disclosing information as Key Audit Matters lead to a disclaimer effect. Disclosures of Key Audit Matters functions as a certain signal. This means that the users of the financial statements should wisely pick out what is needed from these financial statements. Even though, the auditor provides assurance on the financial statements. Kachelmeier, Schmidt and Valentine (2016) also concludes that there is overall support on the fact that Key Audit Matters is not increasing assessments of auditor accountability when the Key Audit Matter is in the same area as the misstatement.

As mentioned before Christensen et al. (2014) concludes in their study that the investors who receive a Key Audit Matter paragraph in the audit report, where the audit issues are highlighted in combination with the audit of not certain fair value estimations, are more likely to

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change their decisions and even stop investing in the organization. A resolution paragraph that is provided after the KAM paragraph also leads to an impact on the behavior of the investor or user of the financial statements. Thus, it is unclear whether resolution of the critical audit matter helps the investors in a positive way. From their results they can conclude that communicating a resolution paragraph of the Key Audit Matter, as mentioned before, has a reducing effect on a KAM paragraph because of the redundant information. With this finding they suggest that the regulators need to discuss whether this is a desired outcome.

When Key Audit Matters are communicated in the auditor’s report, Key Audit Matters are having an attention directing impact according to Sirois, Bédard and Bera (2017). Users of the financial statements access Key Audit Matters related disclosures more rapidly and pay relatively more attention to them. Yet, when several Key Audit Matters exposed to an auditor’s report, users of the financial statements dedicate less attention to the other remaining components of the financial statements (Sirois, Bédard & Bera, 2017).

According to Cordoş and Fülöp (2015) the accounting profession has been scrutinized over the past ten years. Therefore, the audit quality and the audit reporting were in need of change. They examined if the users of audit reports agreed with the IAASB’s proposal, which includes and discloses the Key Audit Matters paragraph, in the audit report. The reason behind this proposal is to include more information upon the audit and enhance the audit communication. Overall, the users of the annual reports and the users of the financial statements agreed to the proposal of the IAASB. Yet, there were still legitimate concerns about the implementation of the Key Audit Matters and its effect on the audit reporting. Cordoş and Fülöp conclude that the introduction and application of the Key Audit Matters will have a positive effect in the audit reporting process. They believe that Key Audit Matters are an important component.

2.5 Earnings management

According to Becker, Defond, Jiambalvo and Subramanyam (1998) information asymmetries are reduced by auditing. The information asymmetries that exists between managers and the firms’ stakeheolders is reduced when this audit is done by outside auditors who are verifying the trustworthiness and fairness of the financial statements. The quality of the auditor is expected to vary due to the effectiveness of auditing and its ability to limit the earnings of the management. They suggest that auditing that is done by low-quality auditors in comparison to high-quality auditors are less likely to detect errors, irregularities and questionable accounting practices. In other words, auditing that is done by high-quality auditors is a discouraging factor for earnings management. The corresponding management’s reputation and the firm value is

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presumably affected when a misstatement is considered and revealed. Becker, Defond, Jiambalvo et al. concluded that earnings management occurs often in firms with low-quality audits, than it does in accounting firms with higher-quality auditors. In the same study it is concluded that lower audit quality is associated with more accounting flexibility.

Francis’ and Krisnan’s comparative study found out that only Big Six accountants show proof of reporting conservatism. This is an important finding since it shows why Big Six audits is seen as being of higher quality. In their study, which is supported by other studies (Francis, Maydew and Sparks 1999; Becker, Defond, Jiambavo and Subramanyam 1998), they found that with recent findings Big Six audited companies have smaller amounts of discretionary accruals which is consistent and with a higher audit quality. The difference between the total accruals and the non-discretionary accruals are the discretionary accruals. Discretionary accruals are accruals that aren’t the result of ordinary operational companies activities. These are accruals that are influenced by the managers. Earnings management plays a big role within these accruals. The Big Six auditors are more aware of conservatism due to the potential uncertainties that could occur during the audit posed by high-accrual firms. This conservatism appears in two ways. The first one is increasing the credibility of reported accruals and the other one is that the Big Six auditors are more likely to signal going concern problems and realizations of assets problems for high-accrual firms through modified audit reports.

In their study, Dechow, Sloan and Sweeney (1995), evaluates for detecting earnings management the alternative accrual based models. Several accrual based models that were analyzed by Dechow, Sloan and Sweeney are according to them specialized in measuring earnings management. Previous research has observed that the modified model, which is developed by Jones in 1991, provides the most powerful tests of earnings management. To determine the discretionary accruals more accurate calculates this model the parameters by the use of Ordinary Least Squares. According to Francis and Krisnan (1999) the audit quality is supposed to be high when the accruals are low. Jones distinguishes in his model discretionary accruals and non-discretionary accruals. In Jones’ opinion the non-non-discretionary accruals are volatile. This volatility is due to the changes in sales and changes in the value of fixed assets in comparison with previous book year. Managers are capable of making changes in the sales to meet their own goals. This is seen as earnings management and makes the company’s accounting not trustworthy.

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Based on the literature above the following hypothesizes that formed and are going to be tested will be:

H1: The perceived audit quality will be better with the new audit report than without H2: The size of a Key Audit Matter paragraph has a positive impact on the audit quality

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3 Research Method and Design

3.1 Data sample

To test the hypotheses the data is gathered considering a mainly focus on Dutch listed companies between 2012 and 2014. The reason behind this sample selection is due to the implementation of the new audit report standards that was taken place in 2014 and obligated for Dutch listed companies. These companies are listed at indexes:

- AEX; - AMX; - AScX

And other funds. As mentioned earlier the new audit report was introduced in 2014. Therefor the book years 2012 and 2014 will be compared. To make this comparison between the Financial Year 2012 and 2014, it is important to gather enough financial information from Company Info. The sample selection and the corresponding data is gathered through Datastream and the published financial statements enclosed with the audit report.

3.2 Dependent variable

The Modified Jones model is a renewed version of the Jones model. According to Dechow, Sloan and Sweeney, this model is adjusted to remove the manipulation out of the conjectured tendency to measure discretionary accruals with error when discretion is exceeding over revenues. The ‘old’ Jones Model assumed that in either the estimated period or the event the discretion is not exercising over revenue. In addition, the adjustment that is only made to the original Jones Model is that the revenue changes is adjusted for the difference in receivables in the event period. It also assumes that the changes in sales in resulted from earnings management in that event period. The reason behind this is according to Dechow et al. that managing earnings is less easy by exercising discretion over the recognitions of revenue on cash sales. It is easier to manage earnings by exercising discretions over the recognitions of revenue on credit sales. Once this modification is successful, then the estimate of earnings management should no longer be biased in samples where earnings management has taken place through the revenue management. Dechow, Sloan and Sweeney discussed the renewed model in their study. They conclude in their study that it is assumed that the non-discretionary accruals are the net turnover of the entity, while the discretionary accruals is assumed as the stock devaluation. This leads to a splitting of turnover in the non-discretionary and discretionary accruals (1995). Theory suggests that high accruals

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corresponds with a low audit quality. Or in other words high audit quality is related with low accruals according to Francis & Krisnan (1999). Therefor the dependent variable is the ‘audit quality’. This variable is calculated by the use of the Modified Jones model.

As mentioned before the non-discretionary accruals are calculated by subtracting discretionary accruals from the total accruals. These total accruals are according to Dechow et al. (1995) calculated by the use of the next formula:

Subsequently the non-discretionary accruals are calculated with the formula below:

Subtracting the non-discretionary accruals from the total accruals leads to the discretionary accruals.

3.3 Independent variable

The independent variable is the variable that has an impact on the dependent variable. This study investigated if there is a significant influence of the new audit report on the audit quality. For this research the independent variable is set to be a dummy variable with 0 = Unqualified opinion in accordance with the previous audit report or 1 = Unqualified opinion in accordance with the new audit report. This is important to test the first hypothesis. The first hypothesis that will be tested is if the new audit report will improve the perceived audit quality more than without. Since it is mandatory to audit on Key Audit Matters from book year 2014 by auditors, this independent variable is presented as a dummy variable ‘year’. Since 2014 it is obligated for Dutch listed companies to report on Key Audit Matters. In this study 0 = book year 2012 and 1 = book

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year 2014.

In the second and final hypothesis will be tested if the numbers of subjects within the Key Audit Matters paragraph has an influence on the audit quality. This independent variable will be marked as ‘Number of Subjects’.

This research focusses mainly on the audit reports dated from 2014 onwards, because reporting on the Key Audit Matters was made mandatory since then. In this study is briefly checked whether the oob’s companies followed up the new regulations upon the audit report. Companies who have not provide the financial statements with the new audit report when they were ought to, are excluded from this study.

For the first hypothesis are the audit reports from 2014 compared to those from 2012. And for the second and final hypothesis are the audit reports investigated for book year 2014.

3.4 Control variable

A control variable is taken into the research model to reduce systematical errors that are within this research. It provides a better perspective upon the results and makes this research model more reliable.

According to Choi, Jeong-Bon and Yoonseok there is a relationship between the size of the accounting firms and the corresponding audit quality. They suggest that a Big 4 accounting firm lead to a higher audit quality, because they have to implement certain strategies to provide a homogeneous level of audit quality. They also concluded that the risk on reputational damage is higher with the Big 4 than non-Big 4 (2010). This was also concluded in the study of Francis and Yu (2009). The former believed that the Big 4 has more experience and knowledge to detect material errors better than non-Big 4. This reduces the risk to gain reputational damage. It is also expected from the auditor to provide a certain level of quality continuously. Reputational damage for a Big 4 accounting firm has more impact than a non-Big 4 accounting firm (2009). Moreover, the study of Berglund, Eshleman and Guo made a comparison with non-Big 4 audit firms and concluded that the Big 4 accounting firms are less likely to provide a false-positive going-concern report. There is no evidence found that Big 4 firms fails in giving a going-concern report to a company which eventually went bankrupt (2014).

Big accounting firms are performing an audit for profit and non-profit organizations. On hand they are very leading, on the other hand there is a possibility that when the audit is underperformed the impact on these Big 4 accounting firms is bigger than on non-Big 4 accounting firms. Organizations that are audited by a Big 4 accounting firm is seen by the user as more reliable (Lennox, 1999). This study expects a positive relationship between high audit quality and a Big 4.

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The study of DeAngelo agrees upon the results of the study of Lennox(1981). DeAngelo is convinced that there will be less quality in the audits when it is performed by smaller accounting firms. This study states that a big accounting firm, who provided an incorrect audit report, will be more negatively affected than a smaller accounting firm and the corresponding costs that will be significantly higher. Big 4 accounting firms are also more experienced in detecting errors.

According to Greiger and Rama it has been noted in their study over a period of 11 year that the relation between the size of an accounting firm is corresponding with the degree of quality. Audit quality is taken into account and is in this research labeled as a control variable. This control variable is measured as a dummy variable for 0 = non-Big 4 accounting firm and 1 = Big 4 accounting firm. Also the factors ‘growth’, ‘leverage’ and ‘size’ are added to this model.

There is a relation between the growth potential of an organization and its corresponding audit quality, which could affect the dependent variable and thus the outcomes of this study. Firms that obtain a higher growth potential are more likely to choose not disclose information, which could lead to a decrease in reliability, resulting in less reliable financial statement. The user could assume that this is low audit quality. According to Becker, Defond, Jiambalvo et al. is lower audit quality associated with more accounting flexibility (2010). Therefor ‘growth’ is taken into account and added to the research model, because it could influence the result of this study and is associated with discretionary accruals. This study suggest that there is a positive relationship between the growth and the audit quality.

Dividing the total debt by the total equity results in the leverage. This variable obligates companies in paying interests and certain payments. There is according to Sierra, Zorio and Garcia Benau a relationship between a higher level of leverage and a higher risk of financial failure. They also concluded that a low level of leverage is corresponding with a lower information asymmetry. This leads to an increase in the perceived audit quality and is therefore added to the model.

According to Deis and Giroux the size of organizations could influence the audit quality (1992). In order to calculate and determine the size of a company, this research used the company’s total assets and is measured with a logarithm. This is a proxy for company size and should prevent influencing the results, which is the audit quality. And according to previous literature the audit quality is supposed to be high when the accruals are low. Referring to this study, there is a relationship between the audit quality and the accruals. In support of this study, other researchers concluded that Big 4 accounting firms have a smaller amount of discretionary accruals and is consistent with a higher audit quality. This study also expect that the Big 4 is positive related to a higher audit quality.

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4 Hypotheses research

4.1 Formulas and design

This study investigate if there is a) a positive relation between the audit quality and the new audit report and b) whether in what extent the new audit report has its influence on the audit quality. Based on the literature review there have been regression analyses made to reject or to support respectively hypothesis 1 and hypothesis 2.

For hypothesis 1 the logistic regression model has different variables in the table as below:

These variables are used as in the formula as following where the Audit quality is the dependent variable:

Audit Quality = α + β1 Dummy Year + β2 Size + β3 Leverage + β4 Growth + β5 Dummy Big 4/Non-Big 4

For hypothesis 2 the logistic regression model has one variable different than the aforementioned table and its variables:

And for this hypothesis the first variable replaces the first variable of the same formula:: Audit Quality = α + β1 Amount of subjects + β2 Size + β3 Leverage

+ β4 Growth + β5 Dummy Big 4/Non-Big 4 4.2 Sample selection

Based on different resources as Compustat, Datastream and company.info, this study gathered financial information of only listed companies from book year 2011, 2012, 2013 and 2014. As mentioned earlier in section 4 the companies were listed in indexes as AEX, AMX, AScX and other funds. To make this study more representative this study excluded financial institutions

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from its research and scope. This will lead to a less fluctuating balance sheet or capital structure. Lastly, there are companies that have not been taken into account due to missing information or if there was a case of outliers. Table 1 provides visually the calculations for the final sample selections for both hypotheses.

Table 1 – Final sample selection

Note: In this table are the final sample selection presented. Hypothesis 1 has 152 observation and hypothesis 2 has 76 observations.

The main focus that is taken into account in this research are the Dutch listed companies (oob’s, organisaties van openbaar belang). Also, for the second hypothesis there has been chosen to use book year 2014, since this was the year that the new audit report was obligated for Dutch listed companies.

The table below, table 2, provides the meaning of the variables that are used in the research model, where by the variable ‘Year’ 2012 is determined for hypothesis 1 and 2014 for hypothesis 2. The variable ‘BIG 4’ are the accounting firms PwC, EY, KPMG and Deloitte.

Table 2 – Variables explanation

Note: In this table are variables displayed. The dependent variable is Audit quality. The independent variables are Year, Amount of subjects, lnAssets, Leverage, Growth and Big 4. These independent variables are used for the hypotheses and regression model.

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5 Emperical results

5.1 Descriptive statistics

In table 3.1 and table 3.2 the descriptive statistics are presented below. Table 3.1 – Hypothesis 1 Descriptive statistics

Note: In this table are the descriptive statistics presented with an observation value of 152. Table 3.2 – Hypothesis 2 Descriptive statistics

Note: In this table are the descriptive statistics presented with an observation value of 76.

Looking into the descriptive statistics it is clearly shown that the discretionary accruals increased between book year 2012 and book year 2014 with 11,98% and it is also the mean of the samples. According to the study of Krishnan (2003), he finds that the value of the discretionary accruals is greater for organizations that are audited by a Big 4 accounting firm. In another study, Elshafie and Nyadroh (2014) tested with their hypothesis if discretionary accruals are lower in companies that received audits from a Big 4 accounting firm. Their study shows that companies that are audited by these accounting firms are having large discretionary accruals (for assets, sales and PPE). These companies are also more profitable and have a higher potential to grow. From this study they also concluded that they have lower amounts of discretionary accruals. In conclusion they stated that the discretionary accruals are lower in companies that have been audited by the Big 4.

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5.2 Outliers and Collinearity

5.2.1 Excluding outliers and test of assumptions

In addition to make this research more representative, this study investigated if the data is distributed normally. And if there are outliers, these are excluded from the data before providing the regressions. In the appendix section A, the tables 4.1 and 4.2 provide the results for the Skewness/Kurtosis test for normality. The tables 4.3 and 4.4, in the appendix section B, provide the results for the Shapiro-Wilk W test for normal data. The tests determines whether the distribution of the data is normally distributed or not. In conclusion, p-values under 0,05 indicates that there is a case of non-normal distribution of the data. The data was normalized using winsorization.

In order to eliminate outliers from the data this study uses the method winsorization. This method looks for the lowest and highest percentile, which are the 1st_{and 100}th_{and are equalized}

with the 2nd_{and 99}th_{percentile. It uses the mean of the variables of the sample as orientation point.}

After winsorization, it is assumed that the data is now distributed normally. Appendix A provides the descriptive statistics after winsorization. The skewness and kurtosis tests and Shapiro-Wilk test shows variable ‘Leverage’ significant 0,0686. The other variables are tested under a value of 0,05. This means that the other variables are non-normal distributed. Further, hypothesis 2’s variables provides the same and in this hypothesis also the variable ‘Amount of subjects’ is a normally distributed variable. According to Field (2013) is an outlier a certain observation that differs significantly from other observations in the same sample. As mentioned earlier winsorization is a method to eliminate outliers. This leads to a better shape in the data distribution and is assumed that the variables are now normally distributed. The winsorization is provided in the disclosures in the appendix under section C. In this section is displayed the variables before and after winsorization.

The VIF (short for Variance Inflation Factor) is a measure used in a regression model to determine the degree of multi-collinearity of the independent variable with other independent variables. The rule of thumb (most commonly is the rule of 10) is associated with the Variance Inflation Factor as serious multicollinearity or as a sign of severe (O’brien, 2007).

When the Variance Inflation Factors are crossing the threshold, the study attempts to reduce this by eliminating variables. In this study are, despite the significant values for correlation between variables, the VIF values implicating that there is no multicollinearity between the variables for hypothesis 1 (Discretionary accruals, Year, lnAssets, Leverage, Growth and Big 4)

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and hypothesis 2 (Discretionary accruals, Amount of subjects, lnAssets, Leverage, Growth and Big 4).

5.3 Results hypothesis 1

In this paragraph and in the paragraph hereafter the hypotheses will be discussed and tested. The first hypothesis is

“The perceived audit quality will be better with the new audit report than without.” To test this hypothesis this study uses a regression model that is discussed in paragraph 5.3.2. Before interpreting the regression analysis this study elaborate on Spearman analysis and collinearity.

5.3.1 Spearman and Collinearity

In other papers it is not uncommon to provide another test as Spearman rank correlations before generating the correlations. In the Spearman rank correlations all variables are ranked in the first place and based on the rank they are assigned with a new value. This test is used to be aware that observed correlations are not motivated by a few outliers or extreme values in the sample of the data (Veenman, 2013).

Table 6.1 displays Spearman rank correlations table for hypothesis 1. And in the appendix under section E is table 6.2 the Spearman rank correlations table with p-values provided.

Table 6.1 – Hypothesis 1 Spearman rank correlations

Note: In this table are the Spearman rank correlations presented for hypothesis 1. Negative values indicates a negative correlation. Value zero means no correlation. Value +1 means perfect positive correlation and -1 means perfect negative correlation.

Collinearity means that independent variables are too heavy correlated and could lead to wrong or not-representative results. When collinearity is assumed it is advised to apply multiple collinearity analyses. It is pretended that the variables of logistic regressions in a multiple collinearity is tested. Logistic regression is applied when the variable is dichotomous or binary.

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This is similar to other regression analyses a predictive analysis. It is used to interpret data and be able to explain the relationship between an independent variable that is nominal, ordinal or interval and a dependent binary variable. Multicollinearity is used in order to retrieve a better view upon the independent variables and to determine if they are unique as they have to be. To investigate this, all the work on the computer was carried out by using STATA to provide the following table: table 6.3. This table shows potential correlation between the independent variables that are used for the first hypothesis. The results of the correlation analysis are remarkable. Interesting correlation to mention is the one between the Leverage and lnAssets (19,6%, p = 0,0156) and the correlation between the Big 4 and lnAssets (47,2%, p = 0,000%). This indicates that the leverage and the assets are positively correlated. Assets within the Big 4 are shown to have a very positive relationship. Another interesting observation is the negative correlation between Year and Discretionary accruals. This negative correlation (-l,2%, p = 0,8852) indicates a weak negative correlation and coincides with the prediction. Furthermore, table 6.3 also confirms that the independent variables are not strongly correlating with other independent variables. The independent variables are in that sense unique.

Table 6.3 – Hypothesis 1 Correlation

Note: In this table are the correlations presented for hypothesis 1. Negative values indicates a negative correlation. Value zero means no correlation. Value +1 means perfect positive correlation and -1 means perfect negative correlation.

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The table below illustrates the p-values that are coherent with the correlation table above. Table 6.4 – Hypothesis 1 Correlation with p-values

Note: In this table are the correlations with p values presented for hypothesis 1. Negative values indicates a negative correlation. Value zero means no correlation. Value +1 means perfect positive correlation and -1 means perfect negative correlation. The correlation results are categorized in coefficients with fixed time effect. *** p<0.01, ** p<0.05, * p<0.1.

The VIF (short for Variance Inflation Factor), is used to determine the multicollinearity. Each variables is calculated with the VIF to measure the independency of each variable. The VIF value of a variable should be below 2 to make sure the independency between the variables is not an issue and to be sure of the variables uniqueness. In this case all the VIF values of all the variables are below 2. The VIF values table below confirms the uniqueness and the independency of all variables and assures that all variables are not (strongly) correlated. The VIF values of the variables lnAssets, Big 4, Leverage, Growth and Year are respectively 1.39, 1.35, 1.08, 1.02 and 1.01.

Yet, the VIF table shows that there are no multicollinearities between any variables. See the VIF table below for hypothesis 1.

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Table 6.4 (continued) – VIF values – Collinearity statistics for hypothesis 1

Note: In this table are the VIF values presented for hypothesis 1. Values below 2 indicates that the variables are not correlated and indicates their uniqueness. The variables are significant and there is no severe multicollinearity.

5.3.2 Regression analysis hypothesis 1

In order to examine the increase in audit quality a regression has run. This determines the increase in audit quality by introducing the new auditors report. These results are displayed in table 7. Yet, the Adj R-squared is 7,8%. This indicates that the variance for 7,8% is explained by this regression model.

Table 7 – Hypothesis 1 Regression Analysis

Note: In this table is the dependent variable Audit Quality presented and are the results of the regression shown for the first hypothesis. This regression model is based on 152 observations and includes the independent variables Year, lnAssets, Leverage, Growth and Big 4.

The regression analysis reported in the bottom half of table 7 that 10% of the variation in audit quality is explained by disclosed independent variables. In the previous table the coefficients and the p-values per independent variable are taken into account as well as the interconnected relations between the independent variables as the dependent variable. Interestingly, in this table only lnAssets has a remarkable p-value under 0,01. The variable lnAssets has significant p-value of 0,002. This indicates a certainty of more than 95% that there is a negative impact of lnAssets on the audit quality. For the other variables they don’t significantly seem to impact the dependent

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variable; the audit quality. The p-values of Year, Leverage, Growth and Big 4 are respectively .987, .204, .545 and .506.

From this table above, it is determined that there is no significant evidence to reject H0. This means that there is no evidence that the introduction of the new audit report has an effect on the audit quality. Also, based on the outcomes of this regression, it does not meet this studies’ expectations. Therefore, H1 is according to these results not accepted and H0 is not rejected.

5.4 Results hypothesis 2

In this research is the size of a Key Audit Matter paragraph taken into account to test if there is a relation. The size in this paragraph is interpreted as amount of subjects. These subjects within the Key Audit Matter Paragraph indicates the size. This relation between the Key Audit Matter paragraph and the audit quality is tested with a regression model. The hypothesis is as follows:

“The size of a Key Audit Matter paragraph has a positive impact on the audit quality.” To test this hypothesis this study used a regression model that is discussed in paragraph 5.3.2. Before interpreting the regression analysis this study elaborate on Spearman analysis and collinearity.

5.4.1 Spearman and Collinearity

In this section all variables are once again ranked in the first place. Then, they are assigned, based on the new rank, with a new value. This test is mostly used to observe correlations driven by a few outliers or extreme values. This does not represent the data (Veenman, 2013).

Table 8.1 below displays the Spearman rank correlations for the second hypothesis that was mentioned earlier in this paragraph. In the appendix under section E is table 8.2 provided that shows the Spearman rank correlations with the coherent p-values.

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Table 8.1 – Hypothesis 2 Spearman rank correlations

Note: In this table are the Spearman rank correlations presented for hypothesis 2. Negative values indicates a negative correlation. Value zero means no correlation. Value +1 means perfect positive correlation and -1 means perfect negative correlation.

This study tested with the correlation model computed from STATA to determine the collinearity between the independent variables in order to observe too heavy correlated variables that could eventually lead to a misinterpretation of statically evidence. In table 8.3 the correlation for hypothesis is provided below. This table illustrates the possible correlation between the variables Discretionary accruals, the amount of subjects, lnAssets, Growth and Big 4.

Table 8.3 – Hypothesis 2 Correlation

Note: In this table are the correlations presented for hypothesis 2. Negative values indicates a negative correlation. Value zero means no correlation. Value +1 means perfect positive correlation and -1 means perfect negative correlation.

The table below illustrates the p-values that are coherent with the correlation table above. This table illustrates the correlation between lnAssets and the Amount of subjects is strongly correlated (37,8%, p = 0,0008) and also Leverage and Amount of subjects is correlated (39,2%, p = 0,0005).

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Table 8.4 – Hypothesis 2 Correlation with p-values

Note: In this table are the correlations with p values presented for hypothesis 2. Negative values indicates a negative correlation. Value zero means no correlation. Value +1 means perfect positive correlation and -1 means perfect negative correlation. The correlation results are categorized in coefficients with fixed time effect. *** p<0.01, ** p<0.05, * p<0.1.

Since it significance level 0,01 is, and the previous observations are below, it is determined that they are strongly correlated. The lnAssets is next to its strong correlation with Amount of subjects, also strongly correlated with Big 4 variable (50,6%, p = 0,000). This is also the case between the variables lnAssets and Leverage (26,9%, p = .0188).

In the VIF table below is another VIF table provided as already was shown for hypothesis 1. Also for the second hypothesis a VIF test was computed from STATA to determine the collinearity. The VIF values of the variables of hypothesis 2 are also showing no correlation within the variables, since the values are below 2. The results are therefore confirming the uniqueness and the independency of the variables. The VIF values of the variables lnAssets, Big 4, Amount of subjects, Leverage and Growth are respectively 1.58, 1.39, 1.32, 1.24 and 1.02. See the VIF values for hypothesis 2 below.

The new audit report, the KAM paragraph size and its effect on the audit quality