The Impact of Time Pressure on Key Audit Matters
Student name: Thijs Hengstman Student number: 2212331 MSc Accountancy University of Groningen June 2017 Abstract
This paper examines the impact of auditor time pressure on the contents of key audit matters in the extended auditor’s report. In order to objectively measure time pressure as experienced by an auditor, I use audit report lag as a proxy. Data are gathered from publicly available 2014 and 2015 auditor reports of UK public interest entities. I first examine whether audit report lag influences the amount of key audit matters. I also investigate whether audit report lag influences the specificity. The findings indicate that a there are no significant relationships between these variables.
Keywords: extended auditor’s report, key audit matters, time pressure.
Supervisor: prof. dr. D.A. de Waard RA MA Co-assessor: drs. L.M. Wielens RA
Word count: 6.176
Contents
1. Introduction ... 2
1.1. The Extended Auditor’s Report ... 2
1.2. Time Pressure Research ... 3
1.3. Significance Of The Study ... 3
2. Theory ... 4
2.1. The Time Pressure Issue ... 4
2.2. The Impact Of Time Pressure ... 5
2.3. The Subjective Nature Of Pressure ... 6
3. Methodology ... 7 3.1. Sample... 7 3.2. Dependent Variables ... 8 3.3. Independent Variable ... 9 3.4. Control Variables ... 9 3.5. Statistical Analysis ... 10 4. Results ... 11 4.1. Descriptive Statistics ... 11 4.2. Hypotheses Testing ... 13
5. Discussion and Conclusions... 15
5.1. Limitations and Suggestions ... 16
1. Introduction
Ever since its beginning, the accounting profession has been subject to many rules and legislations. By itself, these legislations have been subject to many changes due to several concerning developments. First, the well-known corporate accounting scandals early 21st century. The fraudulent financial
reporting of big corporate players such as Enron and WorldCom led to a legislation shift towards more investor protection and accuracy and reliability of corporate disclosures. A more recent development has been the global financial crisis. This crisis gave rise to a growing demand for extended auditor reporting (Nederlandse Beroepsorganisatie van Accountants, 2014; Public Company Accounting Oversight Board, 2016; Financial Reporting Council, 2015). To answer this call for extended reporting, starting financial year 2013 and 2014, the United Kingdom respectively the Netherlands are the first to oblige auditors to compose an extended auditor’s report for public interest entities (PIEs). As of financial year 2016, both the Public Company Accounting Oversight Board (PCAOB) and the International Auditing and Assurance Standards Board (IAASB) oblige this extended audit reporting to PIEs worldwide.
1.1. The Extended Auditor’s Report
In contrast to the standard auditor’s report, the extended report introduces responsibilities for the auditor to communicate key audit matters. The IAASB (2016) describes these key audit matters as “those matters that, in the auditor’s professional judgment, were of most significance in the audit of the financial statements of the current period” (p. 2). Even though the PCAOB mentions Critical Audit Matters (CAMs) whereas the IAASB mentions Key Audit Matters (KAMs), the scope of both definitions can be regarded as equivalent. Interesting however, neither the aforementioned international- and American auditing boards, nor the English Financial Reporting Council or the Dutch Institute of Chartered Accountants (in Dutch: NBA) mandate auditors to report specific key audit matters in specific situations. This allows for a situation in which auditors have complete control over which key audit matters they report.
Granted that this is part of the intention of the KAM-paragraph and has several advantages for investors (Köhler et al., 2016), it also makes this paragraph vulnerable to numerous internal influencing factors such as budget- and time pressure. These factors are, among others, underlying subjects for a number of audit quality indicators as presented in a recent PCAOB publication (2015). This publication states that “the responsibilities of the Public Company Accounting Oversight Board (…) are all ultimately directed at improving audit quality and thereby benefiting investors” (p. 2). One could say that the extended auditor’s report can therefore be seen as an act to improve audit quality. Remarkably, one of the subjects underlying the audit quality indicators is time pressure, which has previously been thoroughly researched.
1.2. Time Pressure Research
As early as 1978, Rhode found that time pressure poses a serious problem for auditors, as auditors themselves perceive these pressures as reducing audit quality. A few years later, Alderman and Deitrick (1982) elaborated on this research and found that time budget pressure is among auditors perceived to have the biggest impact on audit quality. In a more recently conducted research, Coram et al. (2004) concluded that under time budget pressure, auditors are more likely to commit reduced audit quality acts if there is a lower risk of misstatement. The outcomes of these studies suggest that auditors are aware of the impact time budget pressure has on the quality of their work and they use risk factors such as risk of misstatement to justify their reduced audit quality acts. This reveals a potentially concerning problem taking into account that the extended auditor’s report has been introduced in order to increase the audit quality and communicative value towards end-users. If these time budget pressures seem to influence the contents of the auditor’s report, the overall goal and purpose of the extended auditor’s report might be compromised since the informational value of the key audit matters will decrease.
Since the extended auditor’s report can be considered as fairly new and no research has been done on the determinants of these reports, it is unclear ex-ante whether time budget pressure increases, decreases, or has no effect at all on the contents of the extended auditor’s report. In this study, I will try to examine this effect as a determinant for the contents of this report. The goal of this study is to discover the effects of time budget pressures on the extended auditor’s report and to provide directions for future research regarding this extended report.
1.3. Significance Of The Study
This study is important from a managerial perspective for two reasons. First, the findings of this study might influence the value users of the annual report attach to the auditor’s report. Also, engagement managers and partners of an audit team might use the findings of this study to improve time and budget decisions. From a theoretical perspective, the findings of this study might also be interesting for international regulators such as the IAASB and PCAOB. Since this study focusses on the United Kingdom, where extended auditor reporting has been present since 2013, these regulators can make early adjustments to international legislations if necessary.
The research question of this study will be “Does time budget pressure impact the key audit matters in the extended auditor’s report?”. In order to help in structuring the topics within this paper, I will answer this question by answering two sub-questions: “How does time budget pressure affect the amount and specificity of key audit matters?”and “How can audit report lag be used as a proxy for time budget pressure?”.
The remainder of this paper is organized as follows. The next section will provide theoretical background information on this study and develops the paper’s hypotheses. Section 3 describes the research design. Section 4 reports the results, followed by section 5 where conclusions will be drawn and I will describe several limitations of this study.
2. Theory
In this section, I will present a theoretical background on the subjects of research and will use this background to develop the hypotheses used in this study. I will also elaborate on the use of a proxy for time pressure.
2.1. The Time Pressure Issue
In the 20th century, The Cohen Commission was amongst the first to identify the issue of pressure
experienced by auditors (American Institute of Certified Public Accountants, 1978). This report included a survey conducted by Rhode, concluding that some auditors chose to prematurely sign-off audit procedures and described time pressure as a main contributor to this choice. This survey, frequently called Rhode’s survey, has raised numerous concerns which has led to the start of a ‘time pressure research movement’. Following this movement, Alderman and Deitrick (1982) elaborated on Rhode’s survey and found that the premature sign-offs were most likely to happen during review and testing of internal controls. Although Alderman and Deitrick had their concerns about the results and conclusions of Rhode’s study, their study did find evidence supporting his conclusions. Raghunathan (1991) subsequently raised concerns about Rhode’s and Alderman and Deitrick’s surveys. Rhode’s survey was not detailed enough, especially concerning reasons behind a premature sign-off. In addition, Alderman and Deitrick’s survey focused on the perceptions of auditors rather than their actual behavior.
One year earlier, McDaniel (1990) was the first to focus on overall audit performance instead of premature sign-offs. Using a 4 x 2 factorial design with four levels of time pressure stretching from low (75 minutes) to high (45 minutes), she found that “auditor’s processing accuracy and sampling adequacy, as well as overall audit effectiveness, declined as time pressure increased” (p. 282). This can possibly be explained by research conducted by DeZoort (1998). He described that, due to stress, time pressure leads auditors to change processing strategies, restricting information processing and speeding
up efforts to collect information. If an auditor changes processing strategies, chances are that the newly chosen strategy does not cover the full scope of an effective audit and the auditor therefore will not be able to get reasonable assurance on his judgments. Also, speeding up efforts to collect information could mean that some essential audit evidence will be missed or misjudged.
Of course, auditors have more than 45 minutes to perform a regular audit, but this overall decline of audit effectiveness is cause for conflicts with the fundamental purpose of audits. As for several years, “the purpose of an audit is to enhance the degree of confidence of intended users in the financial statements” (International Auditing and Assurance Standards Board, 2016). While auditors have to perform these audits in an effective manner, time pressure may cause major problems reaching this intended degree of confidence and may possibly impact the key audit matters in the auditor’s report. This can be explained by research conducted by Willett and Page (1996). They conducted a survey researching the effect of time budget pressures on irregular audit practices. These irregular audits occur when auditors perceive some audit procedures to be unimportant to the final audit opinion. This reveals a potential danger that this perception is a false one. If so, the auditor might overlook some audit matters or might be unable to collect sufficient evidence to determine the significance of an audit matter. One could say that this has an impact on the key audit matters in the auditor’s report.
2.2. The Impact Of Time Pressure
Research conducted by Coram et al. (2004) examined the joint effects of time budget pressure and the risk of misstatement on auditors’ propensity to commit reduced audit quality acts (or as Willett and Page call it: irregular audit practices). They found that auditors are more likely to commit reduced audit quality acts under time budget pressure if they perceive the risk of financial reporting misstatement as low. This on itself is a comforting outcome since it shows that auditors are using their professional judgment when considering whether or not to commit reduced audit quality acts. However, recent research still finds supportive evidence that, consistent with prior research, time budget pressure is still being perceived to reduce audit quality (Christensen et al., 2016; Persellin et al., 2014). This suggests that professional judgment therefore does not diminish the effect of time pressure.
A different perspective of how time pressure can influence the key audit matters in the extended auditor’s report can be found in what is called the diffusion decision model. This model originates from cognitive- and neural science literature and describes decision-making as a process of noisy accumulation of evidence from a stimulus (Ratcliff et al., 2016, p. 260). As time goes by, more evidence will be accumulated, pushing a decision towards one of two alternative choices. This decision-making as a process of accumulation of evidence has a strong resemblance to the auditing process. As stated in the PCAOB’s Auditing Standard No. 5 (2007) “the auditor must plan and perform the audit to obtain competent evidence that is sufficient to obtain reasonable assurance about whether material weaknesses exist” (p. 20). Relating this process to the decision-making process, one could say that a time deadline might cut off the decision-making process at an inappropriate point, leading to less competent evidence
and a higher chance of faulty decision-making (e.g. the misjudgment of the significance of an audit matter). As a result, auditors cannot communicate certain key audit matters as they did not find enough evidence to do so.
Combining all of the above, one could say that more (less) time budget pressure will lead to less (more) key audit matters mentioned in the auditor’s report. Based on this assumption, I hypothesize the following:
Hypothesis 1. Time budget pressure is negatively associated with the amount of key audit matters mentioned in the auditor’s report.
Continuing the logic that an auditor experiencing time budget pressure performs a less effective audit, one can say that the contents of these audit matters will also be affected.
The Financial Reporting Council has published two separate reviews on the first and second year of the extended auditor’s report in the United Kingdom (FRC, 2015; FRC, 2016). Their review on the first year consisted only of analyses on the number of risks per industry, whereas the second year included a review of the risk descriptions themselves. Here, they make a distinction between specified risk- and non-specified risk descriptions.
The Dutch Institute of Chartered Accountants (NBA, 2016) also published a report in which they concluded their research on the first extended auditor’s reports for Dutch public interest entities. In this report they found that, besides some frequently mentioned general key audit matters, some auditor’s reports contain more firm-specific or sector-specific key audit matters. One could assume that, using this distinction, the key audit matters will be less (more) firm-specific and more (less) sector-specific or general overall if an auditor experiences more (less) time pressure. Based on this assumption, I hypothesize the following:
Hypothesis 2. Time budget pressure is negatively associated with the specificity of the key audit matters mentioned in the auditor’s report.
2.3. The Subjective Nature Of Pressure
Interestingly, most prior research on time budget pressure relied on the use of ‘subjective’ data such as surveys rather than ‘objective’ data. Granted, the experience of pressure itself is merely subjective and therefore can possibly be labeled as immeasurable, this study wants to use objective data as a proxy for time budget pressure. One type of objective data already evidently present in auditing literature is audit report lag.
Audit report lag is the time in days between the fiscal year end and the audit report date (Ashton et al., 1987). In most cases, the audit report dates are equal to the financial reporting dates, which are
mostly determined by filing deadlines imposed by (inter)national authorities such as the Securities Exchange Commission (SEC). Most of these filing deadlines are related to the fiscal year end, such as the 10-K filing instructions. These instructions state periods of 60, 75 or 90 days after the end of the fiscal year as a deadline. We can see these deadlines as being key determinants for audit report lag as they provide a fixed ending point. Of course, filing deadlines are not the only determinants of audit report lag. Abernathy et al. (2017) described poor financial performance, industry risk and internal control weaknesses as having an increasing effect on the audit report lag. However, this study will not focus on these determinants while these determinants can be categorized as company-related, whereas time pressure can be categorized as audit-related factors (Ika & Ghazali, 2012).
Recent research suggests that filing deadlines cause time pressures on the audits of registered firms and have a negative impact on audit quality (Lambert et al., 2017). This negative impact on audit quality is commonly found in other auditing literature. Given that Low & Tan (2011) found that auditors generally perform poorly under time constraints, we can assume that closer deadlines increase time pressure as they significantly shorten the time available to perform an audit. Shortening the time to perform a complete audit might decrease the effectiveness of certain audit procedures or increase the pressure experienced by auditors. A longer audit report lag will provide auditors more time to perform an effective audit and to find and report key, firm-specific, audit matters, whereas a shorter lag will increase the pressure experienced by the auditor and potentially lead to poorer audits. Based upon this assumption, audit report lag can be regarded as having a close correlation to time budget pressure and can therefore be used as a proxy.
Tanyi et al. (2010) identified audit report lag as being the only publicly observable quantitative proxy for the extent of an auditor’s work. Although there is no direct correlation between the extent of an auditor’s work and time budget pressure, the fact that they call it the only publicly observable quantitative proxy is interesting. Since almost all of an auditor’s work, let alone subjective information such as the experience of pressure, is not publicly visible, the generalizability of quantitative auditing research will always be questionable. Audit report lag might therefore also be the only publicly observable quantitative proxy for the extend of auditor time pressure.
3. Methodology
In this section, I will present and discuss the research methodology I have chosen to conduct my research with.
3.1. Sample
In this study, I focus on UK public interest entities. The UK can be considered as the most progressive country in the field of the extended auditor’s report. The UK was in 2013 the first to introduce the
extended auditor’s report, closely followed by The Netherlands in 2014 and internationally in 2016. Based on the market capitalization of spring 2015, I compiled a list of UK top 250 entities. Using hand-collected data from two years of auditor reports from 2014 and 2015, a dataset consisting of around 500 separate observations has been created. Public interest entities without an extended auditor’s report have been omitted from the dataset. This results in a dataset consisting of 395 auditor reports from 223 unique public interest entities.
3.2. Dependent Variables
In this section, I will elaborate on the choices made on how to measure the dependent variables of this research.
Amount of KAMs. To measure the amount of key audit matters mentioned in the extended
auditor’s reports, I will count all separate mentioned key audit matters or risks starting after the materiality- or, if applicable, the scope of the group audit paragraph. Counting will stop when I reach the responsibilities of the management- or, if applicable, the other relevant information paragraph. In this research, this variable will be labeled as D_AKAM.
Specificity of KAMs. As mentioned in the previous section of this paper, the Financial
Reporting Council distinguishes two categories of key audit matters: specific and non-specific. In this study, I will use this same categorization in order to make a distinction between the key audit matters. Using text-analysis software (WCopyfind), the similarity between audit reports will be determined. The preferences of the software are set to ignore letter case, ignore numbers, ignore all punctuation and to skip non-words. Also, the shortest phrase to match is set to 5 words. Phrases of 4 words or less will therefore not be matched to other auditor reports. The software is set to report if there is at least 1 match and allows for a maximum of 1 imperfection. This is the maximum number of non-matches between perfectly matching portions of a phrase where the software will still treat the phrase as a match. This way, any variation in word- and language preferences between auditors will be reduced to a minimum, thereby safeguarding the validity of this study.
As input for the software, I will use edited auditor reports in a PDF file format. Using Adobe Acrobat Professional, the auditor reports are edited in such a way that only the contents of the key audit matters remain. All key audit matters mentioned in one auditor’s report as a whole will be compared to all key audit matters mentioned in other reports. This way, a key audit matter will not be compared to other key audit matters mentioned in the same auditor’s report. Also, the key audit matters will be analyzed in batches. The first one being all key audit matters from the 2014 auditor reports, the second one containing the 2015 auditor reports.
The software will compare one auditor report against all other auditor reports in the specified dataset and returns a percentage of textual similarity for each comparison. For every audit report, all comparisons will be averaged. This resulting percentage will be used to define the specificity of key
audit matters. The lower the percentage, the less similar it is to the rest of the dataset and therefore more specific. In this research, this variable will be labeled as D_SKAM.
3.3. Independent Variable
Since pressure can be experienced in different ways by different people, measuring the full scope of pressure and control for all influencing factors would be very difficult. And if measured, the outcomes of the study will be hard to generalize and will therefore bring some limitations. I will therefore use audit report lag as a proxy for time budget pressure, since audit report lag is the only publicly observable quantitative proxy for the extent of an auditor’s work (Tanyi et al., 2010). As mentioned before, audit report lag is the time in days between the fiscal year end and the audit report date (Ashton et al., 1987). This data will emanate from the dates as they can be found in the auditor’s report. The difference in days has been calculated using the formula as presented below. In this research, this variable will be labeled as I_ARL.
𝐼_𝐴𝑅𝐿 = 𝐴𝑢𝑑𝑖𝑡𝑅𝑒𝑝𝑜𝑟𝑡𝐷𝑎𝑡𝑒 − 𝐹𝑖𝑠𝑐𝑎𝑙𝑌𝑒𝑎𝑟𝐸𝑛𝑑
A recent literature study described several determinants of audit report lag, of which client size is one (Abernathy et al., 2017). One could expect that client size has a positive relationship with audit report lag. After all, a larger (smaller) client will need more (less) extensive audit procedures in order to gather enough appropriate audit evidence, which takes time. The aforementioned study however provided evidence that a negative relationship exists. This means that auditing a bigger client will result in a shorter audit report lag. Continuing this logic, a smaller client will therefore result in a larger audit report lag. When solely researching audit report lag, a client size correction should be in place. However, I believe that client size influence is essential when using audit report lag as a proxy for time pressure and I will therefore not control for this influence.
3.4. Control Variables
In order to diminish the effect of other variables I will control for year- and firm-effects..
Year-effects. First, I will control for year effects. Since the extended auditor’s report is only a
few years old, one can assume that during the first few years there will be some sort of a learning curve. This can be explained by the mimetic isomorphism perspective.
Mimetic isomorphism, as described by Martínez-Ferrero & García-Sánchez (2017), “takes place in situations of uncertainty in which companies may adopt referenced behaviours of other organizations, industries or countries, modelling themselves on such behaviours” (p. 105). The introduction of the extended auditor’s report itself created a situation of uncertainty in which this mimetic isomorphism can take place. After the first year of extended reports, accounting firms will begin copying each other, resulting in more homogenous reports. Another example of this mimetic
behavior are the reports as published by the Financial Reporting Council on the first- and second-year experiences. Granted that the report on 2013 has been published in 2015 and its effect therefore can only influence the reports of 2015, these reports can in theory influence the contents of the extended auditor’s report. To diminish these differences, I will control for year-influences. In this research, this control-variable will be labeled as C_YE. I will create a dummy-variable that will take the value of 0 for 2014 audit reports, and will take the value of 1 for 2015 audit reports.
Firm-effects. I will also control for the difference in accounting firms. Different cultures and
firm-characteristics might influence the way time pressure is perceived or dealt with. Also, differences in planning or human resource capability can significantly affect the audit report lag. In order to solely research the effect of time pressure, these potential influences therefore have to be diminished. In this research, this control-variable will be labeled as C_FE. I will create a dummy-variable that will take the value of 0 if the annual report was audited by EY, 1 if it was audited by KPMG, 2 if it was audited by Deloitte, 3 if it was audited by PwC, 4 if it was audited by BDO, 5 if it was audited by Grant Thornton and 6 if it was audited by any other audit firm.
3.5. Statistical Analysis
In order to reliably test the hypotheses, I will conduct a regression analysis. In this study, I will research the individual relationships between one independent variable and two dependent variables. This results in two regression equations. The equations related to these regression analysis are presented below.
𝐴𝑚𝑜𝑢𝑛𝑡 𝐾𝐴𝑀𝑠 (𝐷_𝐴𝐾𝐴𝑀) = α + β1 ∗ I_ARL + β2 ∗ C_YE + εi + β3 ∗ C_FE + εi
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 𝐾𝐴𝑀𝑠 (𝐷_𝑆𝐾𝐴𝑀) = α + β1 ∗ I_ARL + β2 ∗ C_YE + εi + β3 ∗ C_FE + εi
In these equations, α represents the constant, βi represents the coefficients and εi represents the error term.
4. Results
This section provides the descriptives and results of this study.
4.1. Descriptive Statistics
The overall descriptive statistics of my sample are presented in table 1 and indicate that in the periods examined, on average, the audit report lag was 59.67 days. The shortest audit report lag was 23 days, while the longest lag measured in at 111 days. On average, 3.92 key audit matters were mentioned in the auditor’s reports. The minimum amount was 1, whereas the maximum amount was 9. On average, the specificity of the key audit matters mentioned was 3.01%. This means that on average only 3.01% of one audit report matched with other audit reports in the dataset. The lower this percentage, the more specific the audit report is. The minimum was 0,03% and the maximum was 39,92%.
TABLE 1
Overall Descriptive Statistics
N Min. Max. M SD
I_ARL 395 23 111 59.67 12.803
D_AKAM 395 1 9 3.92 1.574
D_SKAM 395 0.0003 0.3992 0.0301 0.0299
N = Number of Observations, M = Mean, SD = Standard Deviation
Table 2 presents the descriptive statistics of the dependent variables when taking into account the firm- and year-differences. It seems that, during the two-year period taken into account in this study, the average mentioned key audit matters have decreased from 4.06 in 2014 to 3.79 in 2015. This is consistent between all audit firms within the dataset. Out of all Big4 audit firms within the dataset, it seems KPMG reports the least key audit matters whereas PwC reports the most.
TABLE 2
Specified Descriptive Statistics of the Dependent Variables
D_AKAM D_SKAM Firms Year M SD M SD N PwC 2014 4.58 1.637 0.0342 0.0158 66 2015 4.31 1.854 0.0359 0.0226 70 Total 4.44 1.750 0.0351 0.0196 136 KPMG 2014 3.19 1.381 0.0321 0.0554 57 2015 3.05 1.395 0.0256 0.0247 58 Total 3.12 1.384 0.0288 0.0427 115 Deloitte 2014 4.33 0.997 0.0311 0.0116 40 2015 3.98 1.235 0.0247 0.0122 41 Total 4.15 1.130 0.0279 0.0123 81 EY 2014 4.15 1.586 0.0370 0.0498 27 2015 3.83 1.227 0.0152 0.0081 29 Total 3.98 1.408 0.0257 0.0364 56 BDO 2014 4.33 2.082 0.0116 0.0104 3 2015 2.50 2.121 0.0214 0.0273 2 Total 3.60 2.074 0.0155 0.0164 5 Grant Thorn. 2014 5.00 - 0.0111 - 1 2015 4.00 - 0.0037 - 1 Total 4.50 - 0.0074 0.0052 2 Total 2014 4.06 1.541 0.0329 0.0367 194 2015 3.79 1.599 0.0274 0.0211 201 Total 3.92 1.574 0.0301 0.0299 395
N = Number of Observations, M = Mean, SD = Standard Deviation
Concerning the independent variable, table 3 presents the descriptive statistics of the independent variable when taking into account the firm- and year-differences. The sample used in this study indicates a decrease of the audit report lag from 2014 to 2015. However, as this decrease is on average less than 1 day, it can be neglected. It seems that out of the Big4 audit firms, EY has the longest audit report lag and KPMG has the shortest.
TABLE 3
Specified Descriptive Statistics of the Independent Variable I_ARL Firms Year M SD N PwC 2014 58.65 10.508 66 2015 59.46 12.782 70 Total 59.07 11.698 136 KPMG 2014 58.54 12.439 57 2015 56.93 11.408 58 Total 57.73 11.905 115 Deloitte 2014 61.33 14.006 40 2015 57.98 11.945 41 Total 59.63 13.031 81 EY 2014 63.81 16.719 27 2015 63.79 14.715 29 Total 63.80 15.569 56 BDO 2014 61.00 9.644 3 2015 75.50 0.707 2 Total 66.80 10.474 5 Grant Thorn. 2014 81.00 - 1 2015 81.00 - 1 Total 81.00 0.000 2 Total 2014 60.04 12.895 194 2015 59.32 12.736 201 Total 59.67 12.803 395
N = Number of Observations, M = Mean, SD = Standard Deviation
4.2. Hypotheses Testing
This section will provide the results of the statistical analysis I have performed.
In order to conclude whether the hypotheses as stated in paragraph 2.2 are to be confirmed or rejected, a slight rewrite of these hypotheses is necessary. The hypotheses of the actual relationships that will be tested during this study are stated below.
Hypothesis 1. Audit report lag is positively associated with the amount of key audit matters mentioned in the auditor’s report.
Hypothesis 2. Audit report lag is positively associated with the specificity of the key audit matters mentioned in the auditor’s report.
As mentioned earlier, time pressure is supposed to increase when audit report lag decreases. The use of this proxy will therefore have an adverse effect on the initial hypotheses.
Control Variables. In order to analyze whether year- and firm-effects influence the amount
and specificity of key audit matters, I conducted a One-way Analysis of Variance (ANOVA) on all relationships. First, I found that firm-effects have a significant influence on the amount of key audit matters, F(5, 389) = 10.470, p = 0.000 but not on the specificity of key audit matters F(5, 389) = 1.600, p = 0.159. Second, I found that year-effects also have a significant influence on the amount of key audit matters, F(1, 393) = 2.824, p = 0.094 and also have a significant influence on the specificity of key audit matters, F(1, 393) = 3.339, p = 0.068.
Based on these outcomes, both year- and firm-effects will be controlled for when analyzing the amount of key audit matters. However, only year-effects will be taken into account when analyzing the specificity of key audit matters.
Dependent Variables. The results of the regression analysis on the amount and specificity of
key audit matters are presented in table 4. Column 1 shows the variables used in the analysis, column 2 and 3 represent the analysis conducted on the amount of key audit matters. Column 3 and 4 represent the analyses conducted on the specificity of key audit matters. The first regression for every dependent variable only includes the control-variable(s) year-effects and/or firm-effects, whereas the second regression adds audit report lag.
TABLE 4 Regression Results Variable 1) 2) 3) 4) Intercept 3.490) ** 3.818) ** 0.033) ** 0.041) ** C_YE (0.263) * (0.267) * (0.005) * (0.006) * C_FE 0.313) ** 0.311) ** -) -) I_ARL -) (0.005) -) 0.000) Adjusted R-squared 0.052) 0.052) 0.006) 0.007) F-value 11.854) ** 8.169) ** 3.339) * 2.406) * Highest VIF 1.000) 1.001) 1.000) 1.001) ** and * coefficients are statistically significant at 1 and 10 percent, respectively.
The results of the regression analysis on the amount of key audit matters, Adj. R² = 0.052, B = (0.005), t(394) = (0.900), p > 0.1, shows a slightly negative however not significant relationship between audit report lag and the amount of key audit matters. I find that there is evidence to reject my first hypotheses that time budget pressure is negatively associated with the amount of key audit matters mentioned in the auditor’s report.
The results of the regression analysis on the specificity of key audit matters, Adj. R² = 0.007, B = 0.000, t(394) = (1.212), p > 0.1, shows a negative however also not significant relationship between audit report lag and the specificity of key audit matters. Based on this outcome, I find that there is evidence to reject my second hypotheses that time budget pressure is negatively associated with the specificity of key audit matters mentioned in the auditor’s report.
5. Discussion and Conclusions
In this paper, I examine the role of time budget pressure in relation to both the amount and specificity of the key audit matters as mentioned in the extended auditor’s report. I hypothesized that time budget pressure experience by auditors had a negative impact on key audit matters, more specific the amount and specificity. To increase the validity of this research, audit report lag was used as a proxy for time budget pressure.
Using a sample of 395 auditor reports from UK-listed entities of public interest from 2014 and 2015, I find evidence to reject both my first and my second hypothesis. It seems that time budget pressure does not significantly impact the amount or specificity of key audit matters. Instead, I found a slightly negative but insignificant relationship between audit report lag and the amount of key audit matters and no relationship with specificity at all. Although both relationships are not found to be significant, it suggests that more time budget pressure increases rather than decreases the amount of key audit matters mentioned in auditor reports. This effect can possibly be explained by auditors getting insufficient audit evidence. This insufficient evidence increases the risk of the audit firm. Auditors might feel the need to report more key audit matters in order to decrease this risk.
Another explanation can be that the key audit matters are formulated when planning the audit instead of at audit completion. In that case, the KAMs are not influenced by auditor time pressure at all. However, if that is the case, this might also impact the true informative value of key audit matters as intended by the different regulators. Future research might elaborate on this topic to clarify whether this effect exists.
Auditors might also be unaware of the effects of the diffusion decision model as mentioned in paragraph 2.2. Even if auditors are aware of these effects, due to budget reasons they will probably plan the audit so that from their perspective just enough audit evidence will be collected. This (un)awareness might significantly influence the amount of key audit matters reported in the audit report.
This study uses two control variables, year- and firm-effects. As mentioned earlier, based on the mimetic iso-morphism effect, I expected a decrease of specificity through the years. However, the results of this study suggest that the specificity of the key audit matters mentioned increases rather than decreases. This effect can be explained if auditors are copying previously mentioned key audit matters, and chose to elaborate on them. The effect can also be explained by the institutional iso-morphism effect. The FRC published their report on the first year of extended auditor reporting in 2015. Auditors might have already implemented some suggestions mentioned by the FRC in the 2015 auditor reports. Further research on iso-morphism might elaborate on this effect.
Concerning firm-effects, I found that there are significant differences between audit firms in the amounts of key audit matters mentioned, but not in the specificity of these audit matters. This effect might be explained by the difference in culture, policies and procedures between these firms. One audit firm might be more risk-averse than another, and therefore inherently reports more key audit matters. Given the outcome that there is no relationship to be found between audit firms and the specificity of their key audit matters suggests that all audit firms, once identified, have the same understanding of the impact of a risk. It might be interesting for further research to investigate the specific effects of cultural differences of audit firms on the key audit matters.
5.1. Limitations and Suggestions
This research has some possible limitations that may influence the reliability of the results.
First, the fact that this study uses an objective proxy to measure a subjective type of data significantly affects the validity of this study. Even though in theory this relationship should exist, no prior research has been done on whether audit report lag actually can be used as a proxy for time pressure. Also, although audit report lag might be the only observable measure of the extent of an auditor’s work, it does not fully reflect this extent. An audit might have begun one week past fiscal year end or in most cases, a few months before. Due to the sensitivity of this information, these data are not publicly available. Further research might conduct a case-study on this phenomenon, however, these results will probably not be generalizable.
Also, the difference in word- and language preferences between auditors might have impact on the data used in this study. Even though this preference was taken into account when analyzing the key audit matters, not all word- and language choices can be effectively controlled for.
Third, the choice to only focus on UK public interest entities impacts the generalizability of this study. Although most Big 4 audit firms have international policies and procedures, the sample used in this study might be biased by certain English characteristics. Also, due to this choice of data, there seems to be an inequality between the short, average and long audit report lags. Most of the companies and corresponding audit reports had an audit report lag of around 60 days. This is probably caused by filing deadlines set by the English authorities. Further research could try to create a random sample with equal ratios of short, average and long audit report lags.
Although there might be some limitations, this study is one of the first to research the extended auditor reports. The outcomes of this study might give direction to further research or to legislators.
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