AUDIT FIRM TENURE, NON-AUDIT SERVICES AND INTERNAL
ASSESSMENTS OF AUDIT QUALITY
Timothy Bell
University of North Florida
Monika Causholli
University of Kentucky
W. Robert Knechel
University of Florida
April 2012
Draft: Please do not quote without permission.
1
AUDIT FIRM TENURE, NON-AUDIT SERVICES AND INTERNAL
ASSESSMENTS OF AUDIT QUALITY
Abstract
In this study, we use data from internal assessments of audit quality in one of the Big 4
accounting firms to investigate two issues of interest to researchers and regulatory policy:
the impact of audit-firm tenure and auditor-provided non-audit services (NAS) on audit
quality. We find that first-year audits are more likely to receive a lower assessment of audit
quality. Importantly, this result does not extend to years 2 and 3 of the audit engagement,
suggesting that the lower audit quality is limited to the first year of engagement. We also
find that the audit quality is sustained for very long tenure. In supplemental analysis, we
find lowballing for first-year engagements, but lowballing is not associated with less effort
from the audit team. Overall, our results do not support regulators’ perspective that long
audit firm tenure adversely affects audit quality. On the issue of NAS, we find that fees
received from management advisory services and fees from services related to new equity
offerings are positively associated with audit quality especially among publicly traded
clients. We find that tax services and other NAS are not significantly associated with audit
quality. None of our measures of NAS is negatively associated with audit quality. Overall
the results provide support for the knowledge spillover argument and that some NAS can
improve audit quality.
Key Words: auditor tenure, non-audit services, audit quality
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AUDIT FIRM TENURE, NON-AUDIT SERVICES AND INTERNAL
ASSESSMENTS OF AUDIT QUALITY
I. Introduction
In spite of extensive regulation in the past decade, two issues continue to be of key
interest to auditing regulators, practitioners, and academics, namely, the association
between audit firm tenure and fees from non-audit services and audit quality. Both of
these issues have been subject to extensive research and debate but the results and
conclusions have been decidedly mixed (U.S. Senate 1976; AICPA 1978; SEC 1994; GAO
2003; Levitt 2000; EC Green Paper 2010; EC Proposal 2011; PCAOB 2011). Typically,
interest in these issues intensifies following economic downturns when business
performance decline and business improprieties lead to litigation. Such was the case
following the dramatic slide of the NASDAQ market index in early 2000 and the
implosion of Enron and Worldcom, precipitating calls for mandatory audit firm rotation
and passage of the Sarbanes-Oxley Act of 2002 banning many auditor-provided non-audit
services. The financial crisis of 2008 reignited the debate surrounding these issues and
regulators worldwide are once again calling for mandatory audit firm rotation and new
restrictions on auditor-provided non-audit services (EC Proposal 2011; PCAOB 2011).
The first question we examine in this study is the association between audit firm
tenure and audit quality. Most prior research suggests that financial reporting quality is
lower when auditor tenure is short (see Myers et al. 2003). What is less clear is the cause
of this phenomenon. Is a decline in financial reporting quality after an auditor switch due
to lowballing and inadequate audit work, economic bonding with a client, or a lack of
3
knowledge on the part of the auditor? Audit firm tenure (i.e., the decision to switch
auditors) is endogenous. Conflicts between an auditor and client over financial reporting
choices can trigger auditor changes. Consequently, a negative association between
reporting quality and short auditor tenure may be attributable to the outgoing auditor, and
unrelated to the quality of the new auditor’s own effort.1 This has made regulators
somewhat reluctant to rely on academic studies for policy purposes when it comes to
setting new policies that relate to audit firm tenure.2 A second potential problem is the
absence of reliable measures of audit quality. The most common measures—discretionary
accruals and restatements—are jointly determined by management and the auditor, limiting
the ability of researchers to isolate the effect of auditors on financial reporting quality. In
this paper, we extend the current state of knowledge by examining data from internal
quality performance reviews in an international audit firm. The data comes from the
observations made by an internal review team comprised of staff with significant auditing
expertise. The review team examined selected engagements within the firm and directly
assessed the quality of the audit process along multiple dimensions. We use the evaluations
made by the review team as our measure of audit quality.
Our second research question examines the association between fees received from
auditor-provided non-audit services (NAS) and audit quality. For the most part, prior
research has failed to find a substantial link between NAS and audit quality (Habib 2009).
This may be partly explained by the presence of two potentially opposing effects. On one
1
We use the term audit firm tenure and auditor tenure interchangeably.
For example, in its release issued in 2011 the PCAOB noted that “A limitation of this literature is that
studies tend to focus on environments where auditor rotation is voluntary rather than mandatory. Voluntary
rotation may be associated with auditor issuer disagreements, other financial reporting issues, or economic
issues” (see PCAOB 2011, 16).
2
4
hand, NAS could exacerbate economic bonding between the client and auditor, impairing
auditor independence and audit quality. On the other hand, the presence of knowledge
spillovers could improve audit quality. The problem is compounded because different
types of NAS could have different consequences for audit quality (Kinney et al. 2004;
Beck et al. 1988; Paterson and Valencia 2011). Further, the lack of reliable measures of
audit quality in prior research is also relevant for assessing the effect of NAS on audit
quality. In this paper, we extend research on NAS by examining the effect of fees
received from NAS on internal assessments of audit quality while separately considering
the effect of management advisory services, tax services, services related to a new equity
offering, and other NAS.
The data we utilize in this study were collected by a large international audit firm
during its annual internal quality control reviews performed for a sample of audit clients
with 2002 and early-2003 fiscal year ends. These reviews occurred after the enactment of
the Sarbanes-Oxley Act of 2002 and the collapse of Arthur Andersen, but prior to the
effective date of SOX. During this period, audit firms expected that their audits, especially
those audits of newly-acquired Arthur Andersen clients, would receive increased public
scrutiny since their quality control processes would be scrutinized by a new regulator, the
Public Company Accounting Oversight Board (PCAOB). Our dataset includes direct
assessments of overall audit quality for 265 U.S. audit engagements.
Our findings can be summarized as follows. On the question of whether audit firm
tenure affects audit quality, we find that first year audits have lower audit quality but
quality rises to an “average level” in the second year and is sustained for even long tenure
5
engagements. This result is not consistent with some recent findings that suggest a nonlinear association between audit firm tenure and audit quality (see Davis et al. 2009). In
supplemental analysis, we also find fee lowballing associated with first-year engagements.
More importantly, however, lowballing is not associated with a drop off of auditor effort.
To the contrary, the evidence suggests higher levels of audit effort intensity during the
first-year. Higher intensity of effort expended in the first year is consistent with the
argument that auditors lack client-specific information and spend considerable time
learning about a client. Altogether, our findings suggest that tenure improves clientspecific knowledge capital resulting in improved audit quality.
With respect to our second research question, we find that of the different types of
NAS, fees received from management advisory services and fees from services related to
new equity offerings are positively associated with audit quality especially among publicly
traded clients. We find that tax services and other NAS are not significantly associated
with audit quality. None of our measures of NAS are negatively associated with audit
quality. Overall the results provide support for the knowledge spillover argument and that
some NAS can improve audit quality.
This research contributes directly to recent policy initiatives both in the U.S. and
abroad. The PCAOB has recently solicited input regarding the costs and benefits
associated with mandatory audit firm rotation. Our findings suggest that rotation can
impose significant costs related to the effectiveness of the audit because auditors may lack
adequate knowledge about a client during the period immediately after a change in
auditors. Our results should be informative to regulators worldwide as they consider new
6
policies related to NAS, e.g., the EU is considering a complete ban on NAS. Our study
also addresses recent calls for research to develop more precise proxies of audit quality.
As Bamber and Bamber (2009) note “…it is time to move beyond these generic proxies,
especially if we want regulators to act on our research…” We are able to overcome this
issue by using internal assessments of the overall quality of the audit.3
The remainder of the paper is organized as follows. Section 2 provides a review of
the relevant literature reviews and development of hypotheses. Section 3 explains the data
and research design. Section 4 analyses the results. Section 5 provides additional tests,
while section 6 concludes the paper.
II. Background and development of hypotheses
Audit quality is traditionally defined as the joint probability of discovering and
reporting a material misstatement (DeAngelo 1981). The auditor’s ability to discover a
material error, when one exists, depends on the auditor’s technical competence, whereas
the willingness to report a discovered error relates to the auditor’s independence, and both
these aspects may be affected by tenure. In this paper we examine two circumstances that
are believed to influence the quality of an audit: auditor tenure and non-audit services.
Auditor tenure and audit quality
The question of whether audit firm tenure impacts audit quality has long been one
of the major issues concerning auditing regulators. Some believe that lengthy auditor
tenure undermines independence and objectivity, while others believe that long tenure
3
The internal quality reviewers include some of the most experienced, best and brightest practicing auditors
within the firm giving credence to the reliability of our audit quality metric.
7
increases auditor knowledge and competence. The proponents of mandatory rotation have
argued that a lengthy auditor-client relationship can erode professional skepticism and
impair auditor objectivity and independence. One argument as to why this might occur is
because an economic bond forms when the auditor expects to receive a continuous stream
of revenue from the client. A second argument relates to the development of social ties
with management that result in a “slow, gradual, almost casual erosion of [an auditor’s]
honest disinterestedness” (Mautz and Sharaf 1961, 208). In either case, audit quality may
suffer. Regulators have often argued that limiting the number of years that the auditor can
serve a client can reduce the amount of audit fees receivable from the client, thus
mitigating the potential for economic bonding. In addition, rotation removes any
“coziness” between management and their auditor, and instills a fresh view about a client’s
financial reporting issues (U.S. Senate 1976; SEC 1994; EC Green Paper 2010; PCAOB
2011; EC Proposal 2011).
In the midst of corporate failures in the early 2000s, Congress re-visited the issue
but the Senate Banking Committee decided to not include mandatory firm rotation as part
of SOX. Instead, Congress charged the General Accounting Office (GAO) to study the
potential effects of mandatory rotation. As part of their study, the GAO concluded that
“mandatory audit firm rotation may not be the most efficient way to strengthen auditor
independence and improve audit quality” (GAO 2003, 8). The GAO also added that “the
most prudent course of action at this time is for the Securities and Exchange Commission
and the Public Company Accounting Oversight Board to monitor and evaluate the
effectiveness of existing requirements for enhancing auditor independence and audit
8
quality” (GAO, 5). Thus, the GAO left the issue open for discussion if SOX did not prove
to be effective. During the 2008 financial crisis, the debate surrounding mandatory audit
firm rotation was reignited (EC Green Paper 2010; EC Proposal 2011; PCAOB 2011).
Opponents of mandatory rotation argue that it will significantly impede the ability
to accumulate knowledge about a client which is important for accurately assessing risks
and interpreting audit evidence so as to conduct an effective audit. Specifically, auditors
develop a rich understanding of a client’s systems, transactions and risks over time through
repeated interactions with the client and its personnel. The resulting knowledge is
necessary for developing a deep understanding of a client’s business, operations and
financial reporting system (PCAOB AS #5, paragraph 9; PricewaterhouseCoopers 2012).
The accumulated client-specific knowledge can improve audit quality because it allows
auditors to properly plan the audit and identify areas of high risk. In particular, such
knowledge can assist the auditor with identifying emerging issues and with connecting
“the dots between what might otherwise appear to be isolated issues in different company
divisions” (Ernst & Young 2012, 7).
Another potential cost of short tenure that would result from mandatory audit firm
rotation is the significant burden placed on audit firms and clients related to the tendering
process, transition costs for the client, start-up costs for the auditor, and the steep learning
curve for all parties involved (Causholli 2012).4 For example, the GAO (2003) reported
that incremental costs in the initial year of an audit can be as high as 20 percent of the
4
Other undesired effects arising from mandatory audit firm rotation may include (1) less competition among
audit firms, (2) higher internal costs for clients, (3) capacity constrains and scheduling problems among
personnel in audit firms. (4) shifting focus and effort towards repeat preparation of proposals for new audit
engagements, (5) lower incentives to invest in specialization and developing expertise, and (6) higher audit
fees (GAO 2003;PCAOB 2011; Ernst and Young 2012)
9
overall audit cost. A third argument against mandatory rotation is that conflicting
economic incentives can also be present during a short tenure audit engagement. That is,
to the extent that auditors practice lowballing in order to obtain new clients, their
objectivity and independence may be influenced by the desire to retain a client long
enough to recover related start-up costs (Dye 1991).
Academic research has extensively investigated the relationship between audit firm
tenure and various indirect measures audit quality. Early research provided some indirect
evidence that short audit firm tenure is associated with lower audit quality. For example,
Palmrose (1987, 1991) and Stice (1991) show that auditors face higher litigation risk in the
earlier years of an audit relationship. Subsequent research focused on establishing a more
direct link between tenure and measures of audit quality. Although the results can be
characterized as mixed, the majority find that audit quality improves as tenure increases.
Johnson et al. (2002), Myers et al. (2003), Chung and Kallapur (2003), and Gul et al.
(2009) find that short tenure audits (defined as tenure of three years or less) have higher
and more dispersed accruals and lower earnings persistence. Similarly, Chen et al. (2008)
find that the absolute value of discretionary accruals declines as audit firm tenure lengthens
in Taiwan. Carcello and Nagy (2004) find that short tenure audits are associated with the
likelihood of a company being the focus of an Accounting and Auditing Enforcement
Release (AAER). Stanley and DeZoort (2007) find that financial reporting restatements
are more likely to occur in short tenure audits.
Taken together, these studies raise questions about the potential effectiveness of
mandatory audit firm rotation. However, regulators and other academics have correctly
pointed out that all of the cited studies are conducted under a regime of voluntary rotation.
10
Consequently, the research may not be a valid basis for drawing conclusions regarding the
benefits of mandatory rotation (PCAOB 2011). In order to overcome this criticism, some
studies have focused on settings more closely resembling a mandatory rotation
environment. Elizur and Falk (1996) use an analytical model to show that when an auditor
knows the end of their term, the quality of planning declines over time and is lowest for the
last period of a fixed term. Some research has utilized the dissolution of Arthur Andersen,
which forced many companies to engage new audit firms, to mimic mandatory rotation. In
this setting, Blouin et al. (2007) do not find significant improvements in the quality of
reporting for ex-Andersen clients, but Nagy (2005) and Cahan and Zhang (2006) find that
the quality of abnormal accruals increased for former Arthur Andersen clients after their
forced change to new auditors. These results provide some support for the view that short
tenure offers the benefit of a fresh perspective, leading to better audit quality.5 However, in
these cases, it is unclear whether the effect is attributable to lengthy audit firm tenure or the
unique incentives the new auditor had when dealing with an ex-Andersen client.
Other studies have used data from countries where some form of mandatory
rotation has been tried. Cameran et al. (2009) examine the effect of mandatory rotation in
Italy, where the rotation rule has been in effect for more than 20 years. They find that
financial reporting quality improves over time in a mandatory regime. But they also find
that forced changes are associated with lower audit quality while voluntary changes of
auditors tend to improve audit quality. Using data from Spain, where rotation of audit
firms was mandatory between 1988 and 1995, Ruiz-Barbadillo et al. (2003) find that the
likelihood of an auditor issuing a going concern opinion is lower during the period of
5
The result in Nagy (2005) is obtained only in the sample of small clients.
11
mandatory rotation. Kwon et al. (2010) examine the effect of mandatory audit firm
rotation in South Korea and find that since the implementation of the mandatory regime in
2006, audit quality either did not change or slightly decreased. Taken together, studies
using data from these environments do not provide much support for mandatory rotation.6
Prior research findings provide a very mixed picture regarding the association
between auditor tenure and audit quality. Importantly, the mixed findings could indicate
the dynamics of the trade-off between increased knowledge and decreased skepticism, both
of which can occur simultaneously with tenure. Alternatively, the results may reflect
problems in the metrics used to proxy for audit quality. Consequently, our first hypothesis
regarding auditor tenure is non-directional:
H1: Audit firm tenure is associated with the internally assessed quality of the audit
process.
Non-audit services and audit quality
Whether and how NAS impacts audit quality has been an issue of concern to
regulators, auditors, investors, and academics for decades. As was the case with auditor
tenure, there are two opposing views: Regulators argue that fees from NAS can exacerbate
the economic bond between an auditor and client which can be detrimental for audit
quality because the auditor is unwilling to challenge a client’s management on
questionable accounting choices for fear of losing lucrative NAS fees (U.S. Senate 1976;
AICPA 1978; Levitt 2000). It is primarily this perspective that has served as the basis for
6
Vanstraelen (2000) uses data from Belgium where renewable long-term audit mandates exist and reports
that auditors are less likely to qualify the opinion when tenure lengthens. Moreover, it is shown that auditors
are more likely to issue a clean opinion on the first two years of the mandate than in the last year. These
findings are interpreted as supporting mandatory rotation. Knechel and Vanstraelen (2000) also use data from
Belgium and do not find evidence that tenure impacts the likelihood of going concern opinions.
12
a regulatory ban included in SOX on auditor-provided NAS, e.g., the failure of Enron is
often attributed to the existence of high NAS fees paid to the auditor. Currently, the
European Union is also considering a similar ban (EC Proposal 2011).7
In spite of such bans, several theoretical arguments suggest that auditor-provided
NAS does not impair audit quality. First, auditor behavior is a function of other market
and regulatory-based mechanisms which can serve to discipline an auditor and limit the
effects of economic bonding, e.g., litigation and reputation risk (DeAngelo 1981; Palmrose
1988; Weber et al. 2008). Second, auditor-provided NAS may facilitate better audits
through knowledge spillovers (Simunic 1984; Beck et al. 1988; Antle and Demski 1991).
Specifically, NAS may constitute an important source of information that enriches
auditor’s knowledge about the client’s operations beyond the knowledge gained simply
through the audit process (Wu 2006). The incremental knowledge gained from NAS
enables the auditor to perform the audit more efficiently and effectively.
To date, empirical research that has examined the association between auditorprovided NAS and audit quality remains inconclusive. A handful of papers show some
evidence that auditor-provided NAS are associated with poor financial reporting quality.
For example, Frankel et al. (2002) shows that firms that purchase high levels of NAS from
their auditor exhibit low quality financial reporting as measured by larger discretionary
accruals and the propensity to meet or beat earnings. Similarly, Srinidhi and Gul (2007)
find evidence of a negative association between NAS and the quality of accruals measured
7
SOX prohibits bookkeeping, information systems design and implementation, appraisals or valuation
services, actuarial services, internal audits, management and human resources services, broker/dealer and
investment banking services, legal or expert services unrelated to audit services. Other non-audit related
services (e.g., tax services) are still allowed if approved by the Board.
13
by the extent to which accruals map into cash flows. Using data from Australia, Ye et al.
(2011) find that NAS fees are associated with a lower likelihood of issuing a going concern
opinion. Geiger and Blay (2011) find that the magnitude of NAS fees is negatively related
to the probability that the auditor issues a going concern opinion.
The findings of Frankel et al. (2002) are disputed by several follow-up studies.
Ashbaugh et al. (2003) find that the results are sample-specific and do not hold under
alternative tests. Consistent with Ashbaugh et al. (2003), the overwhelming majority of
papers find no evidence linking NAS to audit quality (Simunic 1984; Dopuch and King
1991; Barkess and Simentt 1994; DeFond et al. 2002; Chung and Kallapur 2003;
Raghunandan et al. 2003; Geiger and Rama 2003; Reynolds et al. 2004; Larcker and
Richardson 2004; DeFond and Francis 2005; Francis 2006; Schneider et al. 2006; Ruddock
et al. 2006; Bloomfield and Shackman 2008; Callaghan et al. 2009; Habib 2009).8 Further,
other research finds evidence of knowledge spillovers. For example, Antle et al. (2006)
use data from the UK and find that knowledge spillovers flow from NAS to auditing. Koh
et al. (2011) utilize fee disclosures during the period 1978 to1980 in the US and find that
NAS is positively associated with discretionary accruals, the propensity to meet or beat
earnings, and earnings response coefficients.9
One limitation of the above cited research stream is that it mostly treats all types of
NAS the same. Simunic (1984) points out that different types of NAS may have different
8
Some papers examine the effect of NAS on investor perceptions (Francis and Ke 2006; Koh et al. 2011).
Knechel et al. (2012) and Knechel and Sharma (2010) suggest that another benefit of NAS is shortened a
audit lag in New Zealand and US respectively.
9
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implications for audit quality.10 Recent empirical studies have examined the effect of
different types of NAS on audit quality, with the majority focusing on the issue of tax
services (which are still allowable under SOX). The evidence related to tax services is
somewhat mixed. Kinney et al. (2004) find a negative association between fees received
for tax services and the likelihood of a restatement implying that tax services improve
audit quality. Fees from tax services have been found to be associated with fewer
restatements, (Seetharaman et al. 2009), a higher incidence of going concern opinions
(Robinson 2008), and reduced earnings management (Krishnan and Visvanathan 2011).11
However, Elder et al. (2008) and Paterson and Valencia (2011) find some evidence that
provision of tax services is associated with lower audit quality,12 while Cook and Omer
(2012) fail to find an association between tax services and reporting quality.13
A handful of other studies have examined the effect of other types of NAS on audit
quality, including information services, internal auditing, and other audit-related services.
Kinney et al. (2004) do not find a significant effect of information services on measures of
10
The fact that the Sarbanes-Oxley banned only some, but not all, NAS suggests that different NAS can have
a differential effect on audit quality.
11
Gleason and Mills (2011) find that tax services lead to better estimate of tax reserves suggesting benefits to
having tax services from the external auditor.
12
Consistent with the prediction in Beck et al. (1988), Paterson and Valencia (2011) find that only nonrecurring tax services are associated with lower audit quality measured by the propensity to issue
13
Another line of research argues that because auditor behavior is a function of economic incentives and
other market-based mechanisms it is important to identify settings in which economic incentives dominate or
vice versa. Reynolds and Francis (2001) argue that reputational concerns exceed economic dependence
among large clients. Reynolds et al. (2004) find that auditors are more likely to yield to economic pressures
associated with NAS when auditing small, high-growth clients, suggesting that economic concerns override
other incentives in this setting. Larcker and Richardson (2004) find that economic bonding is particularly
strong in firms with good corporate governance. Krishnan et al. (2011) find that provision of harmful NAS those banned by SOX – can lead to lower audit quality. Causholli et al. (2012) suggest that independence
impairing nature of NAS, is particularly strong under severe compensation pressures that pressured partners
to pursue NAS growth prior to SOX. Lim and Tan (2008) find that the effect of NAS on audit quality is
conditional on auditor specialization and that auditor specialists have stronger incentives to provide higher
quality audits and are more likely to benefit from knowledge spillovers
15
audit quality, whereas Koh et al. (2011) find that information system services are
positively associated with audit quality. Using a proprietary dataset, Prawitt et al. (2011)
find that outsourcing the internal audit function to the external auditor results in lower
accounting risk relative to either in-house internal audit or outsourcing to a professional
service firm that is not the external auditor. Kinney et al. (2004) do not find a relationship
between internal audit services and audit quality but do find that “other” services are
negatively related to audit quality. Paterson and Valencia (2011) find that audit-related
services are negatively related to audit quality. The mixed results for different types of
NAS lead to our second, non-directional, hypothesis:
H2: Different types of non-audit services are differentially associated with
internally assessed audit quality.
III. Data and research design
Data
The data used in this study consist of audit quality assessments, audit firm tenure,
audit and NAS fees, total and staff-level audit labor hours and other key client and
engagement characteristics for 265 U.S. audits conducted by a Big 4 firm during the period
2002 to 2003. Audit firm personnel collected the data as part of their annual internal
quality reviews during the period of late spring through early fall of 2003. The data pertain
to the most recent annual audits at the time. Consequently, these audits all are for client
fiscal years ending before the effective date of the audit provisions of SOX. Firm policy
mandates compliance with quality reviews so the response rate was 100%.
The firm initially selected 307 audit engagements for internal quality review using
a stratified sampling approach that resulted in oversampling of engagements with higher
16
assessed auditor business risk and audit risk (the exact selection criteria is proprietary).
Approximately one-third of the original sample (113 out of 307 engagements) consisted of
first-year audits where Arthur Andersen LLP had been the predecessor auditor.14 We drop
19 engagements because of missing data and drop another 20 engagements in the
government and non-profit sectors. Our analysis is based on the 265 remaining audits
engagements. The engagements are from various industries: consumer and industrial
products (113), financial services (68), information, communications and entertainment
(57), and health care (27). Of the final sample, 120 are first-year engagements (96 of
which are former Arthur Andersen engagements) and 145 are continuing engagements.
Research Design
Audit quality measures
For each audit in the sample, a review team under the supervision of the firm’s risk
management department assessed the contents of the audit work papers, interviewed audit
personnel, and performed reasonableness tests on a variety of data provided by the audit
team (including audit labor hours, fees and other entity and engagement characteristics).
The members of the review team had not previously worked on the audits of clients they
reviewed. During the process, the review team assessed 55 individual audit activities for
each engagement. For each activity, the team judged whether audit-team performance was
14
Firm personnel indicate a subsample of about 50% of the 307 audit engagements was selected randomly,
i.e., without considering assessments of auditor business risks and audit risks.
17
satisfactory or deficient15 (see Appendix A for the list of the 55 activities and the frequency
of deficiencies for each activity and by audit phase).
At the conclusion of the review, the team evaluated their findings and made four
composite assessments: (a) the sufficiency of evidence obtained to support the audit
opinion, (b) the appropriateness of the accounting principles used, (c) the appropriateness
and completeness of presentations and disclosures embodied in the financial statement, and
(d) the appropriateness of the auditor opinion. The review team also made and documented
a final composite assessment of the overall audit quality for the engagement. The
following 4-point scale was used for each of these composite assessments: (1) unqualified
satisfactory, (2) satisfactory with comments, (3) needs improvement and (4) unsatisfactory.
Audit firm quality control policies mandate “a negative response form should be
completed and discussed with the reviewing partner in charge” for all engagements
receiving assessments other than “unqualified satisfactory” on any of the five composite
assessments.
Table 1, Panel A, presents the frequency distribution of overall audit quality for the
265 engagements used in this study. As shown, 112 (42%) audit engagements are assessed
“unqualified satisfactory,” 133 (50%) are assessed “satisfactory with comments” and 18
(7%) and 2 (1%) are assessed “needs improvement” and “unsatisfactory,” respectively.
For our primary tests, we create a dichotomous dummy variable AQ equal to 1 for audit
engagements rated “unqualified satisfactory,” and equal to 0 for the remainder of
engagements (i.e., the other three categories). As shown in Table 1, Panel A, AQ=1 for
15
Mean (median) hours incurred by review teams during this fieldwork portion of the reviews is 52 (41)
hours and the maximum hours incurred is 854.5. Reviews were conducted on a surprise basis for 25 (9%) of
the 265 sample engagements.
18
112 (42%) engagements and AQ=0 for the remaining 153 (58%). Panel A also presents
the frequency AQ ratings by industry sector. Audits of clients operating in the financial
services sector received the highest proportion of “unqualified satisfactory” assessments
(AQ=1 for 57 percent), followed by non-financial/non-health care (AQ=1 for 38 percent)
and health care (30%).16
Table 1, Panel B, presents the frequency distribution of the total number of
deficiencies per engagement (TOTDEFIC) for the 55 assessed individual audit activities.
As shown in Panel B, TOTDEFIC ranges between 0 and 12, with 17 percent of the
engagements having 0 deficiencies, 28 percent having only 1 deficiency, 33 percent having
2 or 3 deficiencies, and 22 percent having more than 3 deficiencies. Table 1, Panel C,
breaks down the distribution of TOTDEFIC into more detail by separating engagements
rated as “Unqualified Satisfactory” (RATING=1) from those that are rated “Satisfactory
with Comments” (RATING=2) and from those that are assessed as “Needs Improvement”
or “Unsatisfactory” (RATING=3). Notably, 94 percent of the engagements with
RATING=1 received two or fewer TOTDEFIC, while only 47 percent and 20 percent of
the engagements receiving RATING2 and RATING3 had fewer than three TOTDEFIC.
Table 1, Panel C, also presents descriptive statistics for the association between
TOTDEFIC and RATING and TOTDEFIC and AQ. Tukey tests for differences between
TOTDEFIC across pairs of ratings are all significant (i.e., 2 vs. 1, 3 vs. 1 and 3 vs. 2).
Also, a t-test for the difference between TOTDEFIC for engagements where AQ=1 vs.
The χ2 test for differences between observed and expected frequencies in the 2x3 table is significant at the
.01 level.
16
19
AQ=0 indicates that TOTDEFIC is significantly lower for engagements where AQ=1
(unqualified satisfactory).
We also create an alternative measure of overall audit quality (AQREV) where we
split the “satisfactory with comments” into two groups based on the logic that some of the
engagements assessed “satisfactory with comments” may have had only minor issues (e.g.,
use of terminology by ex-Andersen personnel that differed from the new firm’s customary
terminology) and, thus, could be considered engagements of sufficiently high quality to
warrant treatment as “unqualified satisfactory.” Since Table 1, Panel C, shows that no
engagement receiving a “needs improvement” or “unsatisfactory” assessment (i.e.,
RATING=3) had fewer than 2 deficiencies , we split the “Satisfactory with Comments”
category based on the number of comments received. As shown in Table 1, Panel D,
AQREV includes 31 additional observations in the “unqualified satisfactory” because they
received fewer than 2 individual audit deficiencies for a total of 143 observations (54%).
All remaining engagements (122 or 46%) remain in AQ=0.
Measures for tenure and non-audit services
Our primary measure for audit firm tenure is a dichotomous variable, FIRST,
which indicates first-year engagements for the audit firm. As shown in Panel A of Table 2,
first-year engagements comprise 45 percent of the sample.17 Panel A shows the mean
(median) level of audit-firm tenure for the full sample of 265 engagements is 6 (2) years
17
As discussed earlier in the paper, the majority of first year clients in our sample are former clients of
Arthur Andersen. In some cases, some members of the Arthur Andersen audit team may have followed their
clients to the new audit firm, in which case an audit team member’s tenure on the client, but not audit-firm
tenure, could be longer than one year. However, it is our understanding that ex-Arthur Andersen personnel
were trained in the new firm’s audit methodology. The fact that some first-year clients may not be staffed by
new auditors may run against us finding an association between tenure and audit efficiency. Alternatively, it
is possible that a greater proportion of qualified assessments were made for this subset of audits because the
Andersen auditors were not completely up to speed on the new firm’s audit methodology.
20
and tenure at the 90th percentile is 16 years. Audit-firm tenure exceeds 20 years for 16
engagements. We report tests of alternative measures for audit-firm tenure later in the
paper.
To test NAS, we split fees paid for non-audit services into five categories: tax
services (TAX), management advisory services (MAS), services pertaining to client public
securities offerings (OFFER), merger & acquisition activities (MA), and other unspecified
fees (OTHER). Descriptive statistics for NAS fees by type of service are shown in Panel B
of Table 2. For the full sample of 265 engagements, mean fees billed for TAX services are
the largest ($102,618), followed by OTHER ($27,162), OFFER ($24,778), MAS ($21,952)
and MA fees ($7,842). Panel B in Table 2 also shows that 67 percent of sample
engagements purchase TAX services, 17 percent purchase MAS services, 20 percent
purchase OFFER services, 28 percent purchase OTHER services, and only 7 percent
purchase MA services.18 In the analyses reported later in the paper, we combine MA fees
with OTHER.19 For testing purposes, we scale NAS fees by dividing fees for each type of
NAS by the square root of total assets. Specifically, the test variables TAXFEESQRT,
MASFEESQRT, OFFRFEESQRT, and OTHFEESQRT are equal to the ratio of TAX,
MAS, OFFER, and MA+OTHER fees to the square root of total assets, respectively.20
The Empirical Model
18
Mean fees (n) for subsamples including only those clients purchasing the indicated service type are:
Tax=$152,773 (178), MAS=$132,212 (44), OFFER=$126,270 (52), MA=$115,447 (18) and
OTHER=$97,270 (74).
19
Our results remain qualitatively equivalent when MA fees are tested separately.
20
Scaling fees by the square root of total assets helps to linearize the relation between fees and size, and to
reduce heterogeneity of variance due to size (see Simunic [1980]).
21
We use the following empirical model to test our hypotheses using our primary test
variables and a number of control variables:21
AQ/AQREV= a0 + a1(LAST) +a2(PUB) + a3(ROMM) + a4(LEV)
+ a5(FIRST) + a6(TAXFEESQRT) + a7(MASFEESQRT)
+ a8(OFFRFEESQRT) + a9(OTHFEESQRT) + u
(1)
where:
AQ = 1 for engagements receiving an “unqualified satisfactory” assessment for
overall audit quality; 0 otherwise.
AQREV = 1 for engagements for which AQ = 1 plus those engagements that
received a “Satisfactory with comments” assessment but had fewer than 2
deficiencies; 0 otherwise.
FIRST = 1 for first-year audit engagements; 0 otherwise;
TAXFEESQRT = fees received for tax services divided by the square root of total
assets.
MASFEESQRT = fees received for management consulting services divided by the
square root of total assets.
OFFRFEESQRT = fees received for services relating to the public security
offerings divided by the square root of total assets.
OTHFEESQRT = fees received for services relating to merger & acquisition
activities and other unspecified NAS services divided by the square root of total
assets.
LAST = natural log of total assets.
LEV = long-term debt divided by total assets.
ROMM = 1 if the assessed risk of material misstatement at the overall financial
statement level is moderate or high and equals 0 if the assessed risk of material
misstatement is low.
PUB = 1 if the client has publicly-listed equity securities; 0 otherwise.
21
The following studies use these or similar control variables in tests for associations between tenure, NAS
and audit quality: Pratt and Stice 1994; Frankel et al. 2002; DeFond et al. 2002; Ashbaugh et al. 2003;
Carcello and Nagy 2004; Nagy 2005; Gul et al. 2007; Carey and Simnett 2006; Lim and Tan 2008; Knechel
et al. 2009.
22
In addition to performing tests on the full sample of 265 audit engagements, we perform
tests on the subsample of audits including only public-listed clients (i.e., those of greatest
interest to audit regulators) and on a subsample excluding audits of clients in the financial
services and health care sectors (i.e., those studied most often in prior research).
IV. Results
Table 3 presents the correlation matrix of variables included in equation (1). AQ
and AQREV are positively correlated (by construction) with a correlation coefficient of
0.79 (p<.01). Both AQ and AQREV are highly correlated with TOTDEFIC—the
correlations between TOTDEFIC and AQ and AQREV are -0.55 and -0.70, respectively
(p<.01). First-year clients exhibit lower audit quality evidenced by the negative and
significant correlations between FIRST and AQ, AQREV, and TOTDEFIC (coefficients
are -0.15, -0.16 and 0.14, respectively). Pairwise correlations between NAS by servicetype and audit quality are not significant with the exception of OFFRFEESQRT and
AQREV (0.14) and OTHFEESQRT and TOTDEFIC (0.13). Correlations among the
independent variables indicate no problems with multicollinearity.
Tests of Hypothesis H1
Table 4 presents the results of our multivariate tests. In all analyses, we present our
multivariate results with and without control variables. Panel A presents the results for the
entire sample (265, i.e., both public and private companies), while Panel B presents the
results for publicly listed companies only (138). In the discussion that follows, we focus
primarily on results for the models that include control variables, i.e., columns 2 and 4 in
all panels. In this, and all subsequent analyses, all logit regressions show good fit as
23
evidenced by significant p-values (ranging between 0.0000 and 0.0026) and Naglekerke’s
r-squared (ranging between12 percent and 34 percent). The overall results for the control
variables are generally consistent with expectations. The association between assets and
measures of audit quality is negative and often significant, suggesting that audits of large
clients are more likely to receive lower quality ratings. Audit quality is often negatively
and significantly associated with leverage (LEV) and risk of material misstatement
(ROMM), and only marginally negatively associated with whether the client is public a
company (PUB).22
H1 asserts that audit quality will be associated with audit firm tenure. In Panel A
the coefficient for FIRST is negative for both AQ (-0.6237, p<.019) and AQREV (-0.6741,
p<.009).23 We get similar results for the subsample of public companies in Panel B (AQ: 0.7492, p<.046; AQREV: -0.8481, p<.019). These results indicate that first year audits are
more likely to receive a low audit quality assessment than other engagements.24 The
evidence is consistent with prior research which shows that short tenures are positively
associated with a higher propensity to restate earnings (Stanley and DeZoort 2007), lower
propensity to issue going concerns (Geiger and Raghunandan 2002), and lower quality of
abnormal accruals (Myers et al. 2003). It is also consistent with the notion that a lack of
client-specific information can have negative consequences for audit quality.
22
While we are unable to test the possibility, we speculate that the negative association is due to reviewers
being more conservative when judging the audits of large and risky clients.
23
All our tests are two-tailed.
24
We also run a test where we replace FIRST with a dummy variable that indicates an audit in the first 3
years of tenure (i.e., those included in FIRST plus second and third year audits). This variable is consistent
with prior research (Johnson et al. 2002). In an untabulated analysis, we find that our short tenure variable is
not significant so the primary effect of interest is experienced in the first year of the audit.
24
We repeat our tests of H1 using a subsample that excludes financial and health care
enterprises because these are essentially regulated industries. These results are presented
in Table 5. Panel A reports the results for both private and public entities, while Panel B
reports the results for public companies only. As in Table 4, the results suggest a negative
association between first-year clients and audit quality measures. In Panel A, the
coefficients on FIRST for AQ (-0.7596, p<.029) and AQREV (-0.8237, p<.012) are both
negative and statistically significant. Similar, but weaker, results are found in Panel B for
the public companies in the reduced sample for AQ (-0.6969, p<.110), although AQREV is
fully consistent with the full sample analysis (-2.1121, p<.035). These results suggest that
the link between audit quality and auditor tenure is not influenced by whether clients are in
a regulated industry.
Additional Analyses
As an alternative test, we re-estimate equation (1) with two tenure-related variables:
FIRST (as previously defined) and LONG, which takes a value of one for audits with
tenure of 9 years or more. This variable is based on prior research (Johnson et al. 2002;
Carcello and Nagy 2004). The results (untabulated) indicate that the coefficient on FIRST
remains significant and negative, suggesting that relative to medium tenured audits, firstyear audits are of lower audit quality. However, the coefficient on the dummy indicating
long tenure (LONG) is not significant, suggesting that audit quality remains relatively
constant even over long tenures. This result indicates that the primary quality effect occurs
in the first year of an audit.
25
A follow up question then arises as to the cause of lower quality in first-year audits.
Regulators are particularly concerned with this question because an auditor that obtains a
client via a lowball fee may have incentives to reduce the effort level for such audits. To
explore this issue in more detail, we examine the association between FIRST and audit fees
and auditor effort. We use a fee model similar to Bell et al. (2008) which includes the
usual controls for client and engagement specific variables (Hay et al. 2006) and a dummy
for first-year audits. Our general results (untabulated) are similar to those presented in Bell
et al (2008) and other prior research. The coefficient on FIRST is negative and significant
consistent with the presence of lowballing in first-year audits.
We next examine whether first-year audits are characterized by differences in the
intensity of audit effort. We use four metrics to proxy for audit intensity based on the
number of hours expended by each level of personnel rank—partners, in-charges,
managers, and staff—each divided by total assets. We then use a model similar to Bell et
al. (2008) with appropriate client and engagement-specific control variables, where the
dependent variable is each measure of audit intensity. We include a dummy for first-year
clients. Our results suggest that audit intensity is significantly higher for first-year audits
using all four measures of audit intensity. This result suggests that although first-year
audits are associated with lowballing of fees, this does not negatively affect audit effort
since such audits involve more time by staff, in-charges, managers and partners. That is,
auditors seem willing to do significantly more work in the first year of an engagement in
spite of a relatively low audit fee. This result is also consistent with the presence of a
significant learning curve reported by Causholli (2012).
26
Tests of Hypothesis H2
The results for H2 are also reported in Tables 4 and 5. H2 asserts that audit quality
will be associated with different types of auditor-provided non-audit services. For the full
sample (Panel A), we find no evidence that any of the 4 types of NAS are associated with
audit quality, either negatively or positively, based on AQ. However, for AQREV, we find
that OFFRFEESQRT is positively associated with audit quality (0.1917, p<.023). The
results are quite different when we only consider publicly listed companies (panel B).
Here we find that MASFEESQRT is positively associated with audit quality whether we
use AQ (0.9603, p<.015) or AQREV (1.061, p<.042). We find a marginal positive
relationship between AQREV and OFFRFEESQRT in Panel B (0.1593, p<.083).
TAXFEESQRT and OTHFEESQRT are not significant in any of our analyses. More
importantly, we do not find any evidence of a negative relationship between the various
types of NAS and audit quality.
The results for the sample excluding financial and health care clients are slightly
stronger and also fail to reveal any negative effects on audit quality from any NAS (see
Table 5). In the subsample, MASFEESQRT is found to be positive for the combined
private/public sample (Panel A) for both AQ (0.4540, p<.016) and AQREV (0.6088,
p<.021), although the results in Panel B are mixed with AQ remaining positive (1.252,
p<.036) but AQREV losing its significance (1.6758, p<.111). Taken together, the results
for MASFEESQRT suggest that there are knowledge spillovers to the audit (see also
Kinney et al. 2004 and Koh et al. 2011). In sum, none of the results are consistent with the
argument that NAS should be uniformly banned for all audit clients.
27
V. Summary and Concluding Remarks
In this study we use data from internal assessments of audit quality in one of the
Big 4 accounting firms to investigate two issues of interest to research and regulatory
policy: the impact of audit firm tenure and auditor-provided NAS on audit quality. We find
that first-year audits are more likely to receive a lower assessment of audit quality,
suggesting that short tenure can negatively impact audit quality. Importantly, this result
does not extend to years 2 and 3 of the audit engagement, suggesting that the lower audit
quality is limited to the first year of engagement. Additional analyses also reveal that the
improvement in audit quality continues even for audits with long tenure. Thus, our results
do not support the regulators’ perspective that a long tenure adversely affects audit quality.
In an attempt to understand the reasons that might cause audit quality to be lower in the
first year, we examine whether lowballing and audit labor intensity is different in first-year
engagements. The analyses reveal the presence of lowballing associated with first-year
engagements, however lowballing does not seem to cause auditors to work less. To the
contrary, the evidence suggests higher levels of audit effort intensity during the first-year,
where audit intensity is measured as the total audit hours expended by various staff levels
divided by total assets. Higher intensity of effort expended in the first year is consistent
with the argument that auditors lack client-specific information and spend considerable
time learning. Altogether, our findings do not provide support for mandatory rotation but
instead suggest that tenure improves client-specific knowledge capital resulting in
improved audit quality.
28
On the issue of NAS we find that different NAS types can have a different impact
on audit quality. Specifically, fees received from management advisory services and fees
from services related to new offerings are positively associated with audit quality
especially among publicly traded clients. We find that tax services and other NAS are not
significantly associated with audit quality. None of our measures of NAS is negatively
associated with audit quality.
Our study extends current research and may help to inform regulatory policy going
forward. Because our measures of audit quality focus strictly on the quality of the audit
process, as a separate activity within the financial reporting process, we are able to
circumvent two of the usual problems associated with prior research: endogenous auditor
tenure and proxies that impound management decisions about financial reporting. In
addition, on the research stream investigating the effects of audit firm tenure, our study
provides a more complete set of results that show not only the nature of the association
between audit firm tenure and audit quality, but also the potential causes for this
association as evidenced by our analysis of lowballing and audit labor intensity. Finally,
our study suggests that regulators should consider the potential and unique effect of each
NAS type on audit quality when developing policies regarding NAS restrictions.
Our study has limitations. First, the data come from only one of the big accounting
firms. To the extent the processes are unique to this firm, the results may not generalize to
other settings. Second, the data are from a time period characterized by an increased
awareness and scrutiny in the audit process. This may affect the rigor of internal audit
quality assessments and produce evaluations that are more stringent than those produced
29
during normal periods. However, the setting we use more closely resembles the current
regulatory environments in which audit firms are periodically evaluated by the PCAOB
inspectors. Third, although our measure of audit quality overcomes many of the problems
associated with audit quality measures used in prior research, it is nevertheless based on
judgments of individuals and therefore subject to the potential biases and limitations of
these individuals.
30
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38
TABLE 1
AUDIT QUALITY MEASURES
Panel A: Composite Review-Team Assessments for Overall Audit Quality
Assessment
Unqualified Satisfactory
Satisfactory with comments
Needs Improvement
Unsatisfactory
1
N
112
133
18
2
265
Percent
42%
50%
7%
1%
Dichotomous Measure of Overall Audit Quality (AQ)
Engagements receiving “Unqualified
112
Satisfactory” Assessment
0
Financial Services
Health Care
Non-Financial/NonHealth Care
Total
Engagements receiving other than
“Unqualified Satisfactory” Assessment
AQ = 1
39 (57%)
8 (30%)
65
AQ = 0
29 (43%)
19 (70%)
(38%)
105
112
153
(62%)
153
42%
58%
Total
68
27
170
265
Panel B: Frequency Distribution of Total Deficiencies (TOTDEFIC) Per Engagement
# of
TOTDEFIC engagements
0
44
1
75
2
53
3
34
4
22
5
18
6
8
7
2
8
4
9
3
11
1
12
1
percent
16.6%
28.3%
20.0%
12.8%
8.3%
6.8%
3.0%
0.8%
1.5%
1.1%
0.4%
0.4%
39
Panel C: Descriptive Statistics for Individual Assessed Deficiencies(2) By RATING
RATING(1)
N
1
2
Unqualified
Satisfactory
Satisfactory
with
Comments
3
Needs
Improvement
&
Unsatisfactory
112
133
20
Cumulative Distribution of Engagements
By RATING
42
2
0
(37.5%)
(1.5%)
(0.0%)
Total
Sample
44
(16.6%)
1
88
(78.6 %)
31
(23.3%)
0
(0.0%)
119
(44.9%)
Δ TOTDEFIC
Means for:
Signed
p-value
2
105
(93.8%)
63
(47.4%)
4
(20.0%)
172
(64.9%)
+.0000
***
3
109
(97.3%)
91
(68.4%)
6
(30.0%)
206
(77.7%)
RATING 2
minus 1
RATING 3
minus 1
4
111
(99.1%)
107
(80.5%)
10
(50.0%)
228
(86.0%)
5
112
(100%)
122
(91.7%)
12
(60.0%)
246
(92.8%)
6
112
(100%)
128
(96.2%)
14
(70.0%)
254
(95.8%)
7
112
(100%)
128
(96.2%)
16
(80.0%)
256
(96.6%)
8
112
(100%)
131
(98.3%)
17
(85.0%)
260
(98.1%)
AQ=1
AQ=0
9
112
(100%)
133
(100%)
18
(90.0%)
263
(99.2%)
.94
3.3
11
112
(100%)
133
(100%)
19
(95.0%)
264
(99.6%)
t-Statistic = 11.8
p-value = .0000***
12
112
(100%)
133
(100%)
20
(100.0%)
265
(100.0%)
TOTDEFIC
Means
(Standard
Errors)
.94
(.1564)
2.96
(.1435)
5.30
(.3701)
2.10
(.1290)
TOTDEFIC
0
Tukey Tests for
Differences in Means
+.0000
***
RATING 3
+.0000
minus 2
***
ANOVA Model
F-Statistic = 81.5, 2 df
p-value = .0000***
t-test for Difference in
Mean TOTDEFIC By AQ
Two audit engagements coded RATING=3 received the “Unsatisfactory” composite rating for Overall Audit Quality.
See APPENDIX A for abbreviated definitions of individual audit activities and frequencies of engagements with assessed deficiencies by
audit phase.
(1)
(2)
40
Panel D: Revised Measure of Overall Audit Quality (AQREV) for Sensitivity Tests
AQREV =
1
Engagements receiving “Unqualified Satisfactory”
RATING=1 plus the subset of engagements receiving
“Satisfactory with Comments” RATING=2 that also had less
than 2 assessed individual deficiencies
143
54%
0
Engagements receiving “Needs Improvement” or
“Unsatisfactory” RATINGs=3 or 4 plus the subset of
engagements receiving “Satisfactory with Comments”
RATING=2 that also had 2 or more assessed individual
deficiencies
122
46%
Financial firms
Health care firms
Non-financial/nonhealth care firms
Total
AQREV = 1
43 (63%)
12 (44%)
88
143
(52%)
AQREV = 0
25 (37%)
15 (56%)
82
(48%)
122
Total
68
27
170
265
*** denotes significance at .01 level
Variables:
RATING = 1 if review-team assessment for overall audit quality is “Unqualified Satisfactory,” 2 if review-team assessment
is “Satisfactory with Comments” and 3 if assessment is “Needs Improvement. or Unsatisfactory.”
AQ = 1 if review-team assessment for overall audit quality is “Unqualified Satisfactory,” 0 otherwise.
TOTDEFIC = total number of assessed deficiencies documented by review teams for 55 individual audit activities.
AQREV =1 for engagements with RATING=1 plus the subset of engagements with RATING=2 that also had less than 2
TOTDEFIC; 0 otherwise.
41
TABLE 2
AUDIT ENGAGEMENT CHARACTERISTICS
Panel A: Client variables
Assets
($thousands)
LEV
ROA
Tenure
PUB
ROMM
FIRST
Mean
Median
Std Dev
P10
P90
2,880,402
0.64
-0.048
5.89
0.52
0.52
0.45
261,038
0.60
0.016
2
1
1
0
16,600,000
0.503
0.676
8.743
0.50
0.50
0.50
37,809
0.16
-0.20
1
0
0
0
3,267,000
0.96
0.117
16
1
1
1
Standard
Deviation
563,021
74,129
198,527
74,348
42,816
79,517
0.37
0.47
0.40
0.25
0.45
P10
69,000
0
0
0
0
0
0
0
0
0
0
P90
647,000
83,000
293,000
80,000
0
84,000
1
1
1
0
1
Panel B: Audit and non-audit fee variables
Audit fees ($)
MAS fees ($)
TAX fees ($)
OFFER fees ($)
M&A fees ($)
Other fees ($)
MAS dummy
TAX dummy
OFFER dummy
MA dummy
OTHER dummy
Mean
361,862
21,952
102,618
24,778
7,842
27,162
0.17
0.67
0.20
0.07
0.28
Median
210,000
0
25,000
0
0
0
0
1
0
0
0
This table presents the descriptive statistics related to 265 audit engagements performed by an international accounting firm
prior to the effective date of the audit provisions of the Sarbanes-Oxley Act of 2002. The variables are defined as follows:
LEV is the ratio of long-term debt to total assets; ROA is the ratio of net income to total assets; Tenure is the number of years
for which a firm has been a client of the audit firm; PUB equals one for publicly traded companies, 0 otherwise; ROMM
equals 1 if the risk of material misstatement as assessed by the auditor is high, zero otherwise; FIRST equals 1 for first-year
engagements, 0 otherwise; FS equals 1 if the client is in the financial service industry; MAS equals 1 if the auditor performs
management consulting services, 0 otherwise; TAX equals 1 if the auditor performs tax services, 0 otherwise; OFFER equals 1
if the auditor provides services related to securities offerings, 0 otherwise; MA equals 1 if the auditor provides services related
to client M&A activity, 0 otherwise; OTHER equals 1 if the auditor provides other non-audit services that are not specified, 0
otherwise; Total NAS equals 1 if the auditor provides MAS, OFFER, MA, or OTHER, 0 otherwise; Total NAS + TAX equals
1 if the auditor provides MAS, OFFER, MA, OTHER or TAX, 0 otherwise.
42
TABLE 3
Correlation Matrix
AQ
AQREV
TOTDEFIC
FIRST
TAXFEESQRT
MASFEESQRT
AQ
AQREV
TOTDEFIC
FIRST
TAXFEESQRT
MASFEESQRT
OFFRFEESQRT
OTHFEESQRT
LAST
PUB
ROMM
LEV
1
0.79**
-0.55**
-0.15*
-0.05
-0.02
0.10
-0.06
-0.12*
-0.10
-0.06
-0.16**
1
-0.70**
-0.16**
-0.07
-0.05
0.14*
-0.07
-0.07
-0.08
-0.04
-0.11
1
0.14*
0.10
-0.04
-0.03
0.13*
0.07
0.13*
-0.04
0.02
1
-0.04
-0.03
-0.14*
0.01
-0.09
0.07
-0.02
0.03
1
0.00
0.00
0.06
-0.04
0.09
-0.04
0.04
1
-0.03
-0.06
-0.04
-0.09
0.02
0.21**
1
0.07
-0.08
0.16**
-0.04
-0.08
1
-0.02
0.15**
0.03
0.02
1
0.11
-0.07
-0.02
1
-0.02
-0.16**
1
0.10
OFFRFEESQRT
OTHFEESQRT
LAST
PUB
ROMM
1
LEV
AQ = 1 for engagements receiving an “unqualified satisfactory” assessment for overall audit quality, 0 otherwise; AQREV = 1 for engagements for which AQ =
1 plus those engagements that received a “Satisfactory with comments” assessment but had fewer than 2 deficiencies, 0 otherwise; FIRST = 1 for first-year audit
engagements, 0 otherwise; TAXFEESQRT = fees received for tax services divided by the square root of total assets; MASFEESQRT = fees received for
management consulting services divided by the square root of total assets; OFFRFEESQRT = fees received for services relating to the public security offerings
divided by the square root of total assets; OTHFEESQRT = fees received for services relating to merger & acquisition activities and other unspecified NAS
services divided by the square root of total assets; LAST = natural log of total assets; LEV = long-term debt divided by total assets; ROMM = 1 if the assessed
risk of material misstatement at the overall financial statement level is moderate or high and equals 0 if the assessed risk of material misstatement is low; PUB =
1 if the client has publicly-listed equity securities, 0 otherwise.
43
TABLE 4
Logit Analysis
Panel A: NAS fees, audit firm tenure, and audit quality on full sample of 265 engagements
Dependent Variables
Independent Variables
Constant
FIRST
TAXFEESQRT
MASFEESQRT
OFFRFEESQRT
OTHFEESQRT
AQ = 1, 0
AQ1 N = 112, AQ0 N = 153
(1)
(2)
Coeff.
p-value
Coeff.
p-value
0.0309
0.879
3.8899
0.010
-0.5720
0.026
-0.6237
0.019
-0.0158
0.428
-0.0137
0.509
-0.0099
0.745
-0.0023
0.942
0.0328
0.205
0.0337
0.256
-0.0450
0.296
-0.0302
0.483
Controls
LAST
PUB
ROMM
LEV
-
Model Fit
Model χ2
p-value
McFadden's Rho2
Cox and Snell R2
Naglekerke's R2
9.9646
0.0762
0.0276
0.0369
0.0496
-
-0.1503
-0.4559
-0.235
-1.0199
0.046
0.085
0.369
0.009
25.3694
0.0026
0.0703
0.0913
0.1227
AQREV = 1, 0
AQREV1 N = 143 AQREV0 N = 122
(3)
(4)
Coeff.
p-value
Coeff. p-value
0.5119
0.016
2.945
0.044
-0.5685
0.028
-0.6741
0.009
-0.0245
0.215
-0.0229
0.252
-0.0250
0.431
-0.0208
0.515
0.1597
0.037
0.1917
0.023
-0.0647
0.136
-0.0553
0.201
-
19.9879
0.0013
0.0547
0.0727
0.0971
44
-
-0.0954
-0.3466
-0.1823
-0.5119
27.5879
0.0011
0.0754
0.0989
0.1321
0.185
0.181
0.475
0.098
TABLE 4 continued
Panel B: NAS fees and audit quality on subsample of 138 public companies
Dependent Variables
Independent Variables
Constant
FIRST
TAXFEESQRT
MASFEESQRT
OFFRFEESQRT
OTHFEESQRT
Controls
LAST
ROMM
LEV
Model Fit
Model χ2
p-value
McFadden's Rho2
Cox and Snell R2
Naglekerke's R2
AQ = 1, 0
AQ1 N = 52, AQ0 N = 86
(1)
(2)
Coeff.
p-value
Coeff.
p-value
-0.6890
0.05
4.2578
0.049
-0.3316
0.398
-0.7492
0.046
0.0106
0.729
-0.0016
0.961
0.8109
0.021
0.9603
0.015
0.0384
0.136
0.0268
0.330
-0.0358
0.540
-0.0359
0.541
-
23.5567
0.0003
0.1288
0.1569
0.2137
-
-0.1868
-0.7722
-0.6377
0.089
0.043
0.325
32.8578
0.0001
0.1797
0.2119
0.2886
AQREV = 1, 0
AQREV1 N = 69 AQREV0 N = 69
(3)
(4)
Coeff.
p-value
Coeff. p-value
-0.1989
0.565
4.6265
0.027
-0.3802
0.318
-0.8481
0.019
0.0152
0.615
0.0026
0.933
0.8932
0.054
1.061
0.042
0.1542
0.064
0.1593
0.083
-0.0632
0.275
-0.0658
0.260
-
26.4897
0.0001
0.1385
0.1747
0.2329
-
-0.1803
-0.5602
-0.6369
0.084
0.128
0.312
33.8195
0.0000
0.1768
0.2173
0.2898
AQ = 1 for engagements receiving an “unqualified satisfactory” assessment for overall audit quality, 0 otherwise; AQREV = 1 for
engagements for which AQ = 1 plus those engagements that received a “Satisfactory with comments” assessment but had fewer than 2
deficiencies, 0 otherwise; FIRST = 1 for first-year audit engagements, 0 otherwise; TAXFEESQRT = fees received for tax services divided
45
by the square root of total assets; MASFEESQRT = fees received for management consulting services divided by the square root of total
assets; OFFRFEESQRT = fees received for services relating to the public security offerings divided by the square root of total assets;
OTHFEESQRT = fees received for services relating to merger & acquisition activities and other unspecified NAS services divided by the
square root of total assets; LAST = natural log of total assets; LEV = long-term debt divided by total assets; ROMM = 1 if the assessed risk
of material misstatement at the overall financial statement level is moderate or high and equals 0 if the assessed risk of material
misstatement is low; PUB = 1 if the client has publicly-listed equity securities, 0 otherwise.
46
TABLE 5
Logit Analysis using subsample of non-financial and non-health care firms
Panel A: NAS fees, tenure, and audit quality on subsample of 170 audit engagements in three industry sectors
Dependent Variables
Independent Variables
Constant
FIRST
TAXFEESQRT
MASFEESQRT
OFFRFEESQRT
OTHFEESQRT
Controls
LAST
PUB
ROMM
LEV
Model Fit
Model χ2
p-value
McFadden's Rho2
Cox and Snell R2
Naglekerke's R2
AQ = 1, 0
AQ1 N = 65, AQ0 N = 105
(1)
(2)
Coeff.
p-value
Coeff.
p-value
-0.2287
0.412
8.9054
0.000
-0.7202
0.031
-0.7596
0.029
-0.0099
0.686
-0.0150
0.588
0.251
0.094
0.4540
0.016
0.0292
0.236
0.0205
0.442
0.0044
0.933
0.0595
0.306
-
12.6238
0.0272
0.0558
0.0716
0.0973
-
-0.4187
-0.4674
0.0709
-1.2122
0.001
0.227
0.843
0.044
38.1512
0.0000
0.1687
0.2010
0.2733
47
AQREV = 1, 0
AQREV1 N = 88 AQREV0 N = 82
(3)
(4)
Coeff. p-value
Coeff. p-value
0.4743
0.102
4.9524
0.012
-0.8751
0.009
-0.8237
0.012
-0.0376
0.134
-0.0416
0.128
0.4495
0.051
0.6088
0.021
0.1624
0.089
0.1971
0.077
-0.0150
0.779
0.0328
0.571
-
-
-
-
24.6403
0.0002
0.1046
0.1349
0.1800
-0.1828
-0.5409
0.2493
-1.1606
38.3306
0.0000
0.1628
0.2019
0.2693
0.068
0.147
0.462
0.044
TABLE 5 continued
Panel B: NAS fees, tenure, and audit quality on subsample of 106 public companies in three industry sectors
Dependent Variables
Independent Variables
Constant
FIRST
TAXFEESQRT
MASFEESQRT
OFFRFEESQRT
OTHFEESQRT
Controls
LAST
ROMM
LEV
Model Fit
Model χ2
p-value
McFadden's Rho2
Cox and Snell R2
Naglekerke's R2
AQ = 1, 0
AQ1 N = 37, AQ0 N = 69
(1)
(2)
Coeff.
p-value
Coeff.
p-value
-0.7636
0.073
6.5906
0.015
-0.4470
0.335 -0.6969
0.110
0.0112
0.736 -0.0034
0.925
0.8672
0.049
1.252
0.036
0.0374
0.148
0.0216
0.411
-0.0130
0.836
0.0127
0.850
-
17.9610
0.0030
0.1310
0.1559
0.2148
-
-0.3202
-0.2861
-0.9892
0.023
0.529
0.228
29.6322
0.0002
0.2161
0.2439
0.3360
AQREV = 1, 0
AQREV1 N = 51 AQREV0 N = 55
(3)
(4)
Coeff.
p-value
Coeff.
p-value
-0.0999
0.813
4.3151
0.074
-0.6300
0.158
-2.1121
0.035
-0.0032
0.922
-0.0226
0.515
1.3000
0.124
1.6758
0.111
0.1688
0.086
0.1789
0.125
-0.0244
0.687
0.0115
0.870
-
23.5731
0.0003
0.1606
0.1994
0.2660
-
-1.2664
-0.3225
-1.883
0.295
0.747
0.060
31.643
0.0001
0.2156
0.2581
0.3443
AQ = 1 for engagements receiving an “unqualified satisfactory” assessment for overall audit quality, 0 otherwise; AQREV = 1 for
engagements for which AQ = 1 plus those engagements that received a “Satisfactory with comments” assessment but had fewer than 2
deficiencies, 0 otherwise; FIRST = 1 for first-year audit engagements, 0 otherwise; TAXFEESQRT = fees received for tax services divided
48
by the square root of total assets; MASFEESQRT = fees received for management consulting services divided by the square root of total
assets; OFFRFEESQRT = fees received for services relating to the public security offerings divided by the square root of total assets;
OTHFEESQRT = fees received for services relating to merger & acquisition activities and other unspecified NAS services divided by the
square root of total assets; LAST = natural log of total assets; LEV = long-term debt divided by total assets; ROMM = 1 if the assessed risk
of material misstatement at the overall financial statement level is moderate or high and equals 0 if the assessed risk of material misstatement
is low; PUB = 1 if the client has publicly-listed equity securities, 0 otherwise.
49
APPENDIX A
Definitions of Assessed Audit Activities and Frequencies of Engagements
With Assessed Deficiencies By Composite Ratings and Audit Phase
Appendix A presents abbreviated definitions (left-hand column) for each of the 55 individual
audit activities for which deficiencies were documented by the firm’s internal quality control
review teams. Individual audit activities were grouped by four audit phases in the review
documentation: (1) planning, (2) internal control evaluation and control risk assessment, (3)
substantive testing, and (4) audit wrap-up activities. For each individual audit activity the review
team assessed whether audit team performance was deficient or not (i.e., a dichotomous rating).
For example, for the Analytical Procedures-Precision activity within the substantive testing
phase, review teams assessed the following activity:
Did the engagement team perform planned analytical procedures at a
sufficient level of precision, and investigate and obtain explanations and
corroborative evidence for any variances from expectations outside an
acceptable difference? Yes or No?
Upon completion of these (and possibly other undocumented) assessments of individual audit
activities, review teams formed composite assessments for, among other things, “overall audit
quality.” The actual question addressed and rated by reviewers for the composite assessment is:
“What is your overall evaluation of the quality of this engagement?” Reviewers assigned one of
the following four assessments to each engagement reviewed: “Unqualified Satisfactory,”
“Satisfactory with Comments,” “Performance Improvement Necessary,” and “Unsatisfactory.”
No “Unsatisfactory” ratings were assigned to the sampled engagements for “quality of overall
audit evidence.”
Panels A through D below present frequencies of individual deficiencies (i.e., frequencies of “No”
answers to the respective questions for each individual audit activity) for the total sample of 265 audit
engagements and broken down by each assessment category for the overall audit quality composite rating.
Individual audit activities are grouped in separate panels within the appendix based on the respective
audit phase. Frequencies of total deficiencies per engagement are presented at the bottom of each panel.
50
APPENDIX A (continued)
Definitions of Assessed Audit Activities and Frequencies of Engagements
With Assessed Deficiencies By Composite Ratings and Audit Phase
Panel A: Audit Planning Activities
Abbreviated Definitions of
Individual Audit Activities
Business Understanding
Analytical Procedures
Fraud Risk Assessment
Business Risks & Processes
Client Information Technology
Integration-Tech. Specialists
Other Locations-Coordination
Oth. Locations-Documentation
Proper Audit Plan
Audit Plan Consistency w Risk
Evaluation of Internal Audit
Work of Another Auditor
Client’s Service Organizations
Client’s External Experts
Total
N
Assessment of Overall Audit Quality
Needs
Satisfactory
Improvement
Unqualified
with
or
Satisfactory Comments
Unsatisfactory
112
133
20
2
4
7
1
1
3
1
1
3
3
7
1
6
12
5
2
2
2
2
3
2
2
1
2
1
6
2
14
4
20
63
19
Total
Sample
265
2
12
4
5
11
23
2
4
5
2
3
2
9
18
102
# Assessed Deficiencies
Per Engagement
181
(68%)
68
(26%)
14
(5%)
2
(1%)
0
1
2
3
92
(82%)
20
(18%)
0
(0%)
0
(0%)
# of Engagements
(Percent)
83
6
(62%)
(30%)
38
10
(29%)
(50%)
11
3
(8%)
(15%)
1
1
(1%)
(5%)
Panel B: Internal Control Evaluation and Control Risk Assessment Activities
Abbreviated Definitions of
Individual Audit Activities
Cycle Approach – Proper
Understanding of Processes
Risk Assmt. & Control Eval.
Audit Programs
Controls Testing
Total
N
Total
Sample
265
6
5
5
22
21
59
Assessment of Overall Audit Quality
Needs
Satisfactory
Improvement
Unqualified
with
or
Satisfactory Comments
Unsatisfactory
112
133
20
5
1
1
3
1
2
3
3
15
4
5
15
1
11
41
7
215
(81%)
42
(16%)
7
(3%)
1
(0%)
# of Engagements
( Percent)
45
(75%)
13
(22%)
2
(3%)
0
(0%)
# Assessed Deficiencies
Per Engagement
0
1
2
3
161
(85%)
26
(14%)
2
(1%)
1
(0%)
51
9
(60%)
3
(20%)
3
(20%)
0
(0%)
APPENDIX A (continued)
Definitions of Assessed Audit Activities and Frequencies of Engagements
With Assessed Deficiencies By Composite Ratings and Audit Phase
Panel C: Substantive Testing Activities
Abbreviated Definitions of
Individual Audit Activities
Analytical Procedures-Precision
Tests of Details
Inventory Observation
Receivables Confirmations
Head-Office Consultations
Revenue Recognition
Client’s Tax Accounting
Review by Tax Specialist
Consolidations/ Equity Method
Business Combinations
Stock Options/Warrants/Rights
Equity Transactions
New Accounting Standards
Valuation & Asset Impairment
Derivative Instruments
Other Significant Estimates
Total
N
Total
Sample
265
32
23
7
15
7
14
62
10
12
9
10
1
6
32
6
22
268
Assessment of Overall Audit Quality
Needs
Satisfactory
Improvement
Unqualified
with
or
Satisfactory Comments
Unsatisfactory
112
133
20
4
22
6
8
11
4
6
1
3
11
1
2
4
1
3
8
3
13
39
10
2
7
1
10
2
1
4
4
1
8
1
1
1
4
1
4
24
4
1
4
1
3
13
6
46
176
46
113
(43%)
85
(32%)
36
(14%)
19
(7%)
7
(3%)
4
(2%)
1
(0%)
# of Engagements
(Percent)
35
(26%)
47
(35%)
30
(23%)
17
(13%)
2
(2%)
2
(2%)
0
(0%)
# Assessed Deficiencies
Per Engagement
0
1
2
3
4
5
6
73
(65%)
34
(30%)
4
(4%)
0
(0%)
1
(1%)
0
(0%)
0
(0%)
52
5
(25%)
4
(20%)
2
(10%)
2
(10%)
4
(20%)
2
(10%)
1
(5%)
APPENDIX A (continued)
Definitions of Assessed Audit Activities and Frequencies of Engagements
With Assessed Deficiencies By Composite Ratings and Audit Phase
Panel D: Wrap-Up Activities
Abbreviated Definitions of
Individual Audit Activities
Laws & Regulations
Sworn Statements by Officers
Management Certifications
Letter of Audit Inquiry
Mgmt. Representation Letter
Related Party Transactions
Subsequent Events
Debt Covenant Violations
Going Concern Evaluation
Final Analytical Procedures
F/S Consistency w Other Info
Presentation & Disclosure
Passed Audit Differences
Work Paper Documentation
Audit Checklists
Other Required Workpapers
Partner & Manager Reviews
Required In-Depth Reviews
Other Review Policies
Auditor’s Report
Total
N
Total
Sample
265
1
1
13
14
12
7
16
6
9
24
3
17
15
14
2
5
5
3
1
8
176
Assessment of Overall Audit Quality
Needs
Satisfactory
Improvement
Unqualified
with
or
Satisfactory Comments
Unsatisfactory
190
60
15
112
133
20
1
1
6
6
1
1
12
1
1
10
1
1
3
3
2
9
5
1
2
3
2
5
2
4
14
6
1
1
1
3
13
1
2
13
6
8
2
1
4
1
3
1
1
1
1
1
28
114
34
# Assessed Deficiencies
Per Engagement
0
1
2
3
4
5
6
149
(56%)
79
(30%)
24
(9%)
6
(2%)
5
(2%)
1
(1%)
1
(0%)
89
(79%)
19
(17%)
3
(3%)
1
(1%)
0
(0%)
0
(0%)
0
(0%)
53
# of Engagements
(Percent)
56
4
(42%)
(20%)
52
8
(39%)
(40%)
17
4
(13%)
(20%)
4
1
(3%)
(5%)
4
1
(3%)
(5%)
0
1
(0%)
(5%)
0
1
(0%)
(5%)