An Analysis of Audit Fees Following the
Passage of Sarbanes-Oxley
Paul A. Griffina and David H. Lontb*
a
University of California
b
University of Otago
Abstract
This study analyzes audit fees following SOX, in particular, the residual increase in audit fees
controlling for those factors predicted to change such fees but for the Act. We find significant
relations between residual audit fees and incremental audit risk, audit effort, and auditor changes.
These factors are noticeably more influential in the period following SOX that includes the
implementation of section 404 on internal control. Our results imply that SOX most likely caused
an increase in the auditing profession’s share of the risk of defective financial statements and
client companies’ resources to audit a costlier accounting system.
JEL Classifications: K22, L80, M41, M42
Keywords: Sarbanes-Oxley, audit fees, SEC certification, section 404, internal control
1. Introduction
This study examines the impact of the Sarbanes-Oxley Act of 2002 (hereafter, SOX
or the Act) on audit fees and provides evidence that supports hypotheses about key
factors that explain that impact. SOX changed substantially the overall scope, quality,
and cost of an audit by requiring an integrated audit of company financial statements
and disclosures and the internal controls that form the basis for those statements and
Corresponding author: Paul A. Griffin, Graduate School of Management, University of California, Davis,
95616. Tel: 1-530-752-7372. Fax: 1-425-799-4143. We thank Jesse Gentry, Timothy Lashua, Lisa Whiting
(KPMG), Joe Cyr (Audit Analytics), Michael Maher, Prasad Naik, Chih-Ling Tsai (University of California,
Davis), Donald Stokes (University of Technology, Sydney), Stephen Taylor (University of New South Wales),
David Marginson (University of Manchester), and Tim Fairhall (Victoria University of Wellington) for
their useful comments. We also thank a reviewer for this journal. Previous versions of this paper have been
presented at the Victoria University of Wellington, University of Otago, University of Technology, Sydney,
and University of California, Davis. An earlier version was also presented at the 2005 National Meetings of
the American Accounting Association, San Francisco. Michael Bowers assisted in the data collection. All
errors and omissions are the responsibility of the authors.
*
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disclosures. SOX also changed the oversight of the auditing profession by creating the
Public Company Accounting Oversight Board (PCAOB). These changes in regulation
and oversight of financial accounting and auditing – possibly the most far-reaching since
the securities acts of the 1930s – created new challenges and fee opportunities for the
auditing profession.
In 2002 and 2003, for example, SOX mandated significant changes in financial
reporting such as the provision (section 302) for certification of financial statements (SEC
Release 33-8124, August 29, 2002), reconciliation of non-GAAP financial measures (SEC
Release 33-8176, January 22, 2003), and enhancement of disclosures about special
purpose entities and other off-balance sheet items (SEC Release 33-8182, January 28,
2003). A major provision of the Act was the 2004 requirement for management to assess
and report on internal controls over financial reporting and for auditors to attest to that
assessment and to report on internal control (section 404). The SEC issued a final release
on internal control in early 2004 (SEC Release 33-8392, February 24, 2004), after
extending filing compliance to fiscal year ends from November 15, 2004, due mainly
to companies’ and auditors’ concerns about the “substantial time and resources needed”
for proper implementation. The PCAOB released Auditing Standard No. 2 on attestation
engagements under section 404 on March 9, 2004 (PCAOB 2004). That standard set
forth in detail auditors’ requirements for performing an audit of internal control over
financial reporting in accordance with SOX.1
How costly were these provisions? The SEC provided only partial information
on the likely costs imposed on companies by these provisions, and an earlier release
(SEC Release 33-8238, June 5, 2003) explicitly excluded an estimate of the additional
audit fees – which it noted could be substantial – in a calculation of section 404 annual
compliance costs of US$1.24 billion (US$91,000 per company). Others, too, have
estimated and/or commented on the overall impact of SOX on company costs, often with
disparate views (e.g., Committee on Financial Services 2005, Butler and Ribstein 2006).
But none to our knowledge has singled out audit fees and documented with controls
how much they have changed in response to SOX, which is an initial goal of this paper.
This paper aims to capture the response to SOX as the residual audit fee following the
Act, that is, the difference between the actual audit fee and the audit fee expected in the
absence of the Act (discussed further below).
A second goal is to test propositions about the reasons to explain residual audit fees.
This paper posits that residual audit fees following SOX can be partially explained
by two factors – audit risk and audit effort. In the first case, higher audit fees should
be observed in the event that SOX lowers auditors’ thresholds regarding the risks of
defective financial statements, including litigation risk. Second, higher audit fees should
also be observed if SOX increases the time and resources a company applies to operate
its accounting system, including the additional effort for reporting and attestation on
financial statements and internal controls. Section 404 of SOX, for example, specifically
mandates that auditors evaluate management’s assertions about internal controls, test
1
During this same period and, in part, as a response to the same corporate scandals and bankruptcies
that preceded the Act, the profession adopted and/or revised other auditing standards such as the standards
on enhanced responsibility for fraud detection and communication (Statement on Auditing Standards No. 99,
2002), and revenue recognition (SEC Staff Accounting Bulletin No. 104, 2003).
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those controls, and issue an independent opinion based thereon. Auditors prior to SOX
were required to test internal controls only if they chose to rely on such to reduce
substantive testing.
Hypotheses about the influence of two related factors are also tested. It is reasoned
that audit fees should change because of auditor realignments in response to SOX.
Such propositions are introduced because, as is noted in section 3, the frequency of
resignations and dismissals has increased significantly in the past few years, and most
of these have occurred after the passage of SOX (see, also, Ettredge et al. 2006). If an
auditor resigns, for example, because the fee is too low for the additional risk under the
Act, it is hypothesized that subsequent fees should increase (e.g., DeFond et al. 1997,
Krishnan and Krishnan 1997). Conversely, if a company dismisses its auditor because
the fee is excessive, it should be observed that subsequent fees decrease, including the
effects of possible fee discounting (e.g., Simon and Francis 1988, Sankaraguruswamy
and Whisenant 2004). This paper also compares the significance of the risk and effort
proxies to explain residual audit fees over time and hypothesizes that such effects should
explain more of the later audit fee residuals to the extent that the auditor applies more
time and resources to the internal control requirements rather than the earlier provisions
on certification and disclosure.
The distinction between audit risk and audit effort in setting audit fees is important
because it helps us understand the profession’s response to the opportunities and
challenges of SOX. If risk factors predominate, this model implies significant additional
risk sharing and price protection on the part of the auditor following SOX, since the
auditor shares in – and is compensated for – the additional risk of defective financial
statements, including litigation risk.
Auditing Standard No. 2 (PCAOB 2004), for example, under the integrated audit
concept, imposes additional risk by requiring the auditor to evaluate all controls that
address the possibility of fraud that could have a material impact on the financial
statements. Auditing Standard No. 2, in fact, sets an unusually low risk threshold
(Committee on Capital Markets Regulation 2006). The standard not only imposes higher
costs by requiring auditors to look for “significant deficiencies” in internal controls and
to provide “reasonable assurance” that “no material weaknesses” exist, but also defines
a deficiency as significant and a weakness as material if there is “more than a remote
likelihood” that a material misstatement of the annual or interim financial statements
will not be prevented or detected.2
On the other hand, if effort factors predominate, our theory suggests that the audit
fee increases following SOX will more likely reflect the additional time and resources
to audit a costlier accounting and reporting system, and such costs fall more squarely on
company shareholders, apart from financial statement risk sharing.
To implement this study, a measure of residual audit fee is constructed as the
difference between actual audit fee in a post-SOX period and predicted audit fee in that
2
The costs of a low risk threshold are compounded by possible additional management and auditor
liability under section 906 of SOX, which subjects CEOs and CFOs to criminal sanctions for material
misrepresentations, including knowledge of internal control weaknesses.
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same post-SOX period conditional on a model of audit fee in the absence of SOX.3 An
extensive literature on audit fee determinants (section 2) helps us specify that model.
The paper then examines whether this prediction error can be explained by proxies for
audit risk and audit effort in the post-SOX period. Also included are variables to control
for residual audit fees’ response to auditor realignments and time-related shifts more
generally, for example, in response to the earlier (section 302) or later (section 404)
requirements.
The results, based on an initial sample of more than 20,000 company-year audit fee
observations for Big 4/5 audit firms for 2000-2004, generally confirm the hypotheses
about the direction and amount of residual audit fee following SOX and the reasons for
such. First, based on a logarithmic model, this paper documents a dollar-equivalent mean
(median) residual increase in audit fees per company of US$1.1 million (US$320,000)
from the fiscal year immediately prior to passage of the Act (July 25, 2002) to fiscal year
2004 and, of these amounts, slightly less than one-half reflects an unexpected jump in
fees from 2003 to 2004, presumably in relation to section 404.
These residual audit fee increases, however, are not uniform across the Big 4 firms.
For example, Price Waterhouse Coopers gains the most in every post-SOX year, both in
dollar terms (e.g., a US$1.6 million mean increase to 2004) and as an increase in fees
from one year prior to the passage of the Act (e.g., a 172% mean increase to 2004).
It is also found that these dollar-equivalent results are not substantially different from
the actual mean audit fee change from before SOX to 2004 and, therefore, they may not
be surprising, especially from a practical standpoint. One implication is that the actual
changes in audit fees following SOX may, therefore, be mostly unanticipated changes, a
notion that has been assumed rather than documented in the literature thus far. However,
such fee increases based on dollar-equivalent or actual means can be influenced by
outliers (e.g., large audit fee changes) and these can generate unreliable results. The
hypothesis tests in the paper use logarithmic regressions to reduce the impact of outliers.
Second, regression analysis indicates that both the audit risk and audit effort proxies,
and the auditor realignment variables, all significantly explain residual audit fees
following SOX in ways that support our hypotheses. Companies in the post-SOX period
with greater litigation risk and negative earnings (our audit risk proxies) experience
significantly higher residual audit fees (supports H1). This is consistent with higher than
expected post-SOX audit risk as a fee driver. Larger companies, those with December
31 fiscal year ends, and those with more days from year end to auditor signature date (our
audit effort proxies) also experience significantly higher residual audit fees, consistent
with higher than expected post-SOX audit effort as a second fee driver (supports H2).
Residual audit fees also increase significantly following an auditor resignation in the
post-SOX period. This is consistent with the view that an incoming auditor charges
more to reflect increased audit risk, whereas residual audit fees decline significantly for
3
For consistency, the term “residual audit fee” is used throughout the paper as actual audit fee less
predicted audit fee. This term, however, could be equivalently represented as “residual change in audit fee,”
defined as the difference between actual audit fee change and predicted audit fee change, where predicted
audit fee change is the difference between predicted audit fee next period (conditional on an audit fee model)
and actual audit fee this period.
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companies that dismiss their auditor in the post-SOX period, consistent with decreased
audit effort and/or fee discounting by the incoming auditor (supports H3).
Additionally, it is found that our audit risk and audit effort proxies are more
influential in explaining residual audit fees following the later SOX requirements, in
particular, section 404 on internal controls (supports H4). These results are robust to
different regression estimation approaches, variable definitions, and other reliability
checks.
The remainder of the paper is organised as follows. Section 2 states a theoretical
foundation for the hypotheses and specifies the empirical models to test these
hypotheses. Section 3 identifies and describes the data and characteristics of the sample.
Section 4 presents the results and examines their robustness to alternatives. Section
5 summarizes the conclusions and discusses their implications for professionals and
researchers.
2. Theory and Models
2.1. Theoretical Analysis
The analysis of unexpected or residual audit fees – the primary variable of interest
– requires a model of expected audit fees in the absence of SOX. We build upon an
extensive literature on the determinants of audit fees, dating back to Simunic (1980).
This seminal study models audit fees as an element of the cost of the company’s
accounting system, where a profit maximizing company seeks to minimize the expected
cost of financial reporting. This cost consists of three components: (1) the cost of
operating the internal accounting system, va, where v is the per unit cost of utilizing a
units of internal accounting resources, (2) the cost of external auditing, pq, where p is
the per unit equilibrium price of utilizing q units of external auditing resources (including
a normal return to the auditor), and (3) the company’s share of expected losses from
defects in the audited financial statements, E(d|a,q)(1-E(φ)), where E(d|a,q) are the
expected losses conditional on the auditing and accounting system resources utilized,
and E(φ) and 1-E(φ) are the auditor’s and company’s shares, respectively, of those
expected losses. The auditor’s problem is to supply q units of external auditing resources
at an equilibrium price per unit, p, to the point of incremental expected total cost to the
auditor, where such cost comprises the cost of external auditing, cq, and the auditor’s
share of expected losses from defects in the audited financial statements, E(d|a,q)E(φ).
With competition, the auditor establishes a fee, pq, which is equal to the incremental
expected total cost, or pq = E(C) = cq + E(d|a,q)E(φ).
Several studies (see below, for example) use this theory to model and estimate
the determinants of audit fees, for instance, to establish a baseline audit fee to test
whether fees are too high or too low, to test for the incremental effects of additional
or experimental variables, and to assess methodological alternatives that might better
represent possible interplay among the determinants. The extensiveness of more than
two decades of literature on this topic is recognized (see, also, Appendix 1).
The preceding theory, as with prior research, is used to predict the impact of audit
risk and audit effort on audit fees. For example, Seetharaman et al. (2002) predict the
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impact on audit fees of differences in the litigation environment of the country in which
an auditor operates. They reason that in a more litigious situation the auditor will assess
higher levels of E(d|a,q) and E(φ), and this leads to an increase in audit fees. This paper
reasons similarly in that SOX lowers the litigation threshold for SEC registrants and
auditors. Our first hypothesis, in the alternate form, may, thus, be stated as follows: that
audit fees following SOX, at least in the short term, should increase as a result of an
increased assessment of audit risk, E(d|a,q)E(φ) (H1).
The theory also predicts a positive relation between residual audit fee changes
following SOX and post-SOX audit effort. It is reasoned here that to the extent that SOX
increases the cost of operating the company’s internal accounting system, va, especially
the internal accounting resources a utilized, it also would necessarily increase the
resources required to audit that system. The cost of auditing the additional accounting
resources in response to SOX should be reflected in a higher cq. Assuming c is constant,
or comparatively unchanged, a second hypothesis is offered, stated in the alternate
form, that audit fees should change in response to a change in q, in other words, the
incremental audit effort in response to SOX (H2). There may, of course, be an offsetting
effect on E(d|a,q) and audit risk to the extent that increases in a and q reduce the cost of
defective financial statements. But this should make a test of H1 more difficult to reject.
As discussed earlier, this paper also hypothesizes a positive relation between residual
audit fee changes after SOX and auditor resignations (higher audit risk) and a negative
relation between residual audit fee changes after SOX and auditor dismissals (reduced
audit effort and/or fee discounting) (H3). Finally, this paper interacts the effects of
the audit risk and effort proxies on audit fees with the timing of the provisions and
hypothesizes that audit fees will be more responsive to audit risk and effort factors later
in the study period, especially to the extent that section 404 on internal controls absorbs
more auditing resources than the earlier provisions (H4).
2.2. Empirical Models
This section states the empirical models to test the hypotheses. Model 1 regresses
audit fee determinants on audit fees in a control period (fiscal periods prior to SOX)
and this model is used to predict audit fees in the fiscal periods following SOX. Model
2 regresses proxies for audit effort and audit risk, and auditor realignment variables,
on residual audit fees, that is, the difference between actual audit fees in the post-SOX
period and audit fees predicted by model 1 conditional on the actual values of the audit
fee determinants in the post-SOX period (model 2).
As a supplement to model 2, a third model is also stated to pool the pre- and postSOX audit fee data into a single model (model 3). This model combines the variables
in models 1 and 2 and includes interaction variables to test for possible time-dependent
impacts such as whether the audit risk or audit effort variables are more influential later
rather than earlier in the post-SOX period. The models are specified without subscripts
for company i and year t for convenience.
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Model 1 is stated as follows:
Log(Aud) = α + β1,1 Log(AudRel) + β1,2Log(Tax) + β1,3Log(OthNA) + β1,4Litig
+ β1,5NegEPS + β1,6Log(Zquin) + β1,7GoingCon + β1,8Issues + β1,9Tenure +
β1,10FYRDec31 + β1,11 Days2Sign + β1,12Mkt/Book + β1,13Log(Mcap) + β1,14Log(Size) +
β1,15Segm + β1,16Frgn + β1,17Log(Cash&CE) + β1,18Log(Rec&Inv) + β1,19Log(OffBS) +
β1,20XI&DisC+ β1,21IndyLeader+ β1,22IndySize+
β1,23Instit + Σj =-1,…4β24,jAudCh + ε
(1)
We define the variables below and rely on prior research to support the expected
signs of the coefficients. This model is consistent with Simunic’s (1980) audit fee model
and similar to other audit fee models in the literature.4 In addition to these studies,
separate variables for non-audit, tax, and other non-audit fees are included along
with other variables less well documented in the literature, such as the extent of prior
securities litigation against the company, number of reportable events, days to auditor
signature, and type of auditor realignment (e.g., dismissal, resignation). Appendix 1 lists
key prior research pertaining to the expected sign of the relation of each variable to audit
fees. ε represents estimation period random error.
Sign
Definition
#
Variable
0
Log(Aud)
1
Log(AudRel)
+
Log10 of audit-related fees for fiscal year.
2
Log(Tax)
+
Log10 of total tax-related fees for fiscal year.
3
Log(OthNA)
+
Log10 of other (non-tax, non-audit related) non-audit fees for fiscal
year.
4
Litig
+
Litigation risk = 1 if the company has been subject to a securities class
action, issued an SEC NT filing, or restated earnings in the year prior
to the audit year, otherwise 0.
5
NegEPS
+
Fiscal year earnings per share before extraordinary and discontinued
operations less than zero=1, otherwise 0.
6
Zquin
+
Quintile ranking of Altman Z-score times -1.
7
GoingCon
+
Going concern qualification =1, otherwise 0.
8
Issues
+
Issues=1 if the company makes at least one non-standard reportable
event disclosure in the 8-K filing, otherwise 0.
Log10 of audit fees for fiscal year.
4
For a more general review of the literature on audit fee models, see inter alia Hay et al. (2006), who
examine 186 analyses in 147 studies over 1977-2003 based on data from 20 different countries. The most
pervasive audit fee determinant from these studies is company size. Other reviews include Yardley et al. (1992),
Turpen (1995), and Simunic and Stein (1996) (mostly on litigation risk). Other studies have addressed whether
audit or non-audit fees threaten auditor independence, and have tested variations of the hypothesis that higher
non-audit fees are associated with a greater incidence of earnings management, where the latter offers indirect
evidence of weakened auditor independence. These studies use SEC Release 33-7919 disclosures for fiscal
years 2000 and 2001 and include Frankel et al. (2002), Chung and Kallapur (2003), Kinney et al. (2004), and
Larcker and Richardson (2004).
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9
Tenure
+
Number of years company audited by incumbent auditor.
10
FYRDec31
+
Fiscal year ended December 31=1, otherwise 0.
11
Days2Sign
+
Days from fiscal year end to auditor’s signature > median Days to
Signature =1, otherwise 0.
12
Mkt/Book
+
Ratio of market capitalization to common book equity at end of fiscal
year.
13
Log(Mcap)
+
Log10 of market capitalization of common shares at end of fiscal year,
millions.
14
Log(Size)
+
Log10 of total assets for fiscal year, millions.
15
Segm
+
Number of segments at end of fiscal year.
16
Frgn
+
Ratio of foreign sales to total sales for fiscal year, %.
17
Log(Cash&CE)
−
Log10 of cash and cash equivalents at end of fiscal year, millions.
18
Log(Rec&Inv)
+
Log10 of receivables and inventory at end of fiscal year, millions.
19
Log(OffBS)
+
Log10 of sum of operating lease commitments at end of fiscal year,
millions.
20
XI&DisC
+
Extraordinary items and discontinued operations for fiscal year not
equal to zero=1, otherwise 0.
21
IndyLeader
−
Audit firm has greatest number of clients in 3-digit NAICS category=1, otherwise 0.
22
IndySize
+
Decile ranking of number of companies in 3-digit NAICS code.
23
Instit
+
Ratio of institutional common shares held to total shares outstanding
at end of fiscal year, %.
24,1
Dismiss
−
Dismissal=1 in incoming auditor change year, otherwise 0.
24,2
Resign
+
Resignation=1 in incoming auditor change year, otherwise 0.
24,3
AudChOther
?
Auditor change reason unstated=1 in incoming auditor change year,
otherwise 0.
24,4
AudChFromAA
?
Andersen dismissal due to indictment=1, otherwise 0.
Model 1 is used to predict residual audit fees for company i in period t following SOX,
namely, ^εit = Log(Audit) – PredLog(Audit| model 1), where PredLog(Audit| model 1) =
^ + Σj=1,…,24 β^j Determinantitj, where the j determinants in the t post-SOX periods are
α
multiplied by β^ estimated over fiscal periods prior to SOX. Residual audit fees are used,
j
in turn, as the dependent variable in our second-stage model 2. This model regresses key
audit risk and effort proxies on post-SOX residual audit fees, ^εit. This model is stated,
without i and t subscripts, as follows.
^ε = α + Σp=1,…,P γ1pAudRiskp + Σq=1,…,Q γ2qAudEffortq + Σr=1,…,R γ3rAudRealignr + ω (2)
where AudRiskp = Litig, NegEPS; AudEffortq = FYRDec31, Days2Sign, and Log(MCap);
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AudRealign = unit variables for Dismiss, Resign, AudChOther for the fiscal periods
following SOX, and ω is a random error term. It is posited that the estimated γ
coefficients should be positive for the audit risk and audit effort proxies, and negative
and positive for dismissals and resignations, respectively. No prediction regarding the
sign of γ for other auditor changes is made.
The choices of the proxies for audit risk and audit effort are guided by a desire
to employ as direct measures as possible. Prior research has tended to use less direct
measures, such as stock price volatility (e.g., Lys and Watts 1994) or leverage (Gul
and Tsui 1997) as a proxy for litigation risk, which may explain their mixed results.
Companies with prior litigation (and the potential for litigation as evidenced by a
restatement or late filing) and/or negative earnings should be riskier to audit than
others. Companies whose incumbent auditor has resigned should also impose more
audit risk than otherwise similar companies. Of course, there may be other reasons for a
resignation. It is also reasonable that larger companies and those with December 31 year
ends and longer audit periods should require more audit effort. Market capitalization
is selected as a proxy for size-related audit effort because this includes assets (and
liabilities) not recognized in the accounting statements. Unrecognized amounts (e.g.,
intangibles and contracts) can constitute a substantial fraction of company net assets to
which auditing resources are applied. Moreover, this could be increasingly the case for
many companies in recent years, including our sample. Nonetheless, other size proxies
(e.g., total assets, revenues) are tested and these are commented on in a later section. An
incoming auditor following a dismissal, on the other hand, should complete the audit for
a lower fee than the incumbent. It is recognized, however, that some of these variables
may not uniquely reflect audit risk or audit effort. For example, as the audit period
increases, this could be a sign of delay to complete the audit, which could increase audit
risk. Further, a lack of clear theory to select the proxies necessarily implies an arbitrary
element in their choice, although as is discussed later, these results are robust to other
risk and effort proxies and model estimation in a non-SOX period. It is also recognized
that the explanatory power of the audit effort proxies could be mitigated in those
situations when audit fee effort is alleviated, for instance, when the auditor receives
additional (audit-related) compensation from internal control design.
The third model uses the entire study period to estimate the parameters of the audit
fee model and includes multiplicative interaction variables to capture the incremental
effects of audit effort and audit risk in the post-SOX period. This model, also, uses
interaction variables to distinguish between the initial period following the Act (SOXA),
which covers implementation of the certification provisions, and the later period, from
April 1, 2003, which covers implementation of section 404 on internal control (SOXB).
We choose April 1 as the fiscal year cutoff date for the SOXA period so as to precede
the first issue date of the section 404 rules (June 5, 2003) by one quarter. As already
noted, hypothesis 4 states that the SOXB coefficients should be more influential than the
SOXA coefficients in explaining post SOX audit fees. We state model 3, without i and t
subscripts, as follows:
Log(Aud) = α + Σ j=1,…, 24β jDeterminant j + δ 1SOX A + δ 2SOX B + Σ A, BSOX T{(Σ p=1,2
η1p AudRiskp) + SOXT(Σq=1,2,3 η2qAudEffortq) + SOXT(Σr=1,2,3 η3rAudRealignr)} + μ,
(3)
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where the Determinantj variables are those in model 1; the AudRiskp, AudEffortq, and
AudRealignr variables are those in model 2; SOXT = SOXA or SOXB, where SOXA = 1 for
observations from July 25, 2002 to April 1, 2003, otherwise 0, SOXB = 1 for observations
from April 1 to December 31, 2004, otherwise 0; and μ reflects random error. Following
Brambor et al. (2006), we include both “mean” and “slope” coefficients in the same
model for the interaction of SOXT and the risk and effort proxies. In sum, model 3
controls for the determinants of expected or normal audit fees and then tests whether
the relations between post-SOX audit fees and audit effort, audit risk, and realignment
(coefficients ηp, ηq, and ηr for audit risk, audit effort, and realignment, respectively) are
larger or smaller for the SOXA sub-period than the SOXB sub-period. The model also
controls for a mean shift effect of SOX on audit fees (coefficients δ1 and δ2). To the
extent that one or more of the βj parameters in model 3 may reflect some of the effects
of SOX because, for example, such βj parameters are estimated over the entire study
period, this approach may be a more conservative test of the impact of SOX on audit
fees. The ηp, ηq, ηr, and βj coefficients may also be threatened by collinear independent
variables in the model. We comment on this in a later section on robustness checks.
3. Data and Sample Characteristics
3.1. Data
SEC registrants presently disclose two years of audit fee data in their DEF14a proxy
statements, or Form 10-K filings, pursuant to SEC Release 33-8183 (January 28, 2003),
and provide certain information about auditor changes in their Form 8-K pursuant to
SEC Release 33-8400 (March 16, 2004). Audit fee and auditor change data for 25,851
company-years are obtained from Audit Analytics.5 These data cover 7,424 individual
SEC registrants audited by a Big 4/5 firm with fiscal year ends from the first quarter of
2000 to December 31, 2004. This is essentially the Big 4/5 audit fee population for that
period. Our analysis is restricted to companies audited by a Big 4/5 firm to increase the
homogeneity of the sample and, thus, the power of the tests. The auditor realignment
observations, therefore, exclude non-lateral and non-Big 4/5 auditor changes. These
may be associated with different kinds of company-auditor realignments such as those
from a company restructuring or changed need for service (e.g., Sankaraguruswamy and
Whisenant 2004).
Restated audit fee amounts are used when such amounts are restated as a result of the
newer SEC definitions and combine the audit and non-audit fee amounts of different Big
4/5 auditors when a change in the auditor occurs during the fiscal year. When a company
splits “other” non-audit fees, other than tax or audit-related fees, into different categories
(e.g., benefit plan related, financial information system design and implementation,
miscellaneous), these are combined into one category.
Securities class action litigation data on 3,230 securities class action lawsuits filed
against 2,708 SEC companies since 1980 are obtained from a database maintained
5
Audit Analytics is an on-line data service available from Ives, Inc.
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171
by Institutional Shareholder Services, Inc. Because ISS states that it provides
comprehensive coverage of shareholder litigation events, it is reasonably assumed that
companies not in this sample have not been sued in securities class actions. Since the
database reports the date of the corrective disclosure or restatement that triggers the
class action, it is also possible to pinpoint prior litigation relative to the fiscal year of
the audit fee. We gather additional auditor and financial data from Compustat and SEC
EDGAR.
3.2. Sample
Table 1 summarizes the sample by year and Big 4/5 firm. Panel A shows that the
sample comprises at least 4,000 companies per year, spread across five accounting
firms. However, the number of Andersen audited companies drops off rapidly after
2001 following its indictment in March 2002 (SEC Release 2002-37), although the
increasing percentages of the other Big 4 after 2001 suggest that such companies
migrated mostly to other Big 4 auditors. Panels B and C indicate that the audit fee data
are substantially skewed. For example, whereas mean Big 4/5 audit fees per company
start at US$513,016 in 2000 and increase to US$1,787,427 in 2004, median audit fees
per company start much lower at US$176,000 in 2000 and increase to US$721,525 in
2004.
Table 1
Audit Fee Sample Characteristics By Year and Audit Firm1
Fiscal Year
Andersen
Deloitte &
Touche
Ernst &
Young
KPMG
Price
Waterhouse
Coopers
Total Big
4/5
A: Distribution of Company-Year Observations
2000
2001
2002
2003
2004
All years
19.84%
17.87%
5.71%
0.09%
0.00%
15.86%
17.07%
20.23%
21.59%
21.95%
23.49%
23.84%
28.01%
30.42%
28.78%
17.38%
17.52%
19.95%
21.61%
23.19%
23.44%
23.70%
26.10%
26.29%
26.08%
4,023
5,752
6,215
5,747
4,114
25,851
B: Mean Audit Fee, in dollars
2000
534,506
536,437
410,916
450,920
627,327
513,016
2001
443,151
539,081
393,501
415,224
679,501
498,806
2002
646,041
713,730
665,532
657,085
832,055
715,941
2003
2004
313,700
na
857,708
1,727,562
786,877
1,471,556
848,919
1,756,450
1,067,156
2,213,895
888,859
1,787,427
181,500
183,714
220,004
271,473
719,000
168,000
160,250
194,000
257,534
645,635
186,000
190,000
228,748
302,503
883,000
176,000
180,000
219,000
278,200
721,525
C: Median Audit Fee, in dollars
2000
2001
2002
2003
2004
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180,950
185,000
248,000
245,000
na
159,000
166,429
223,250
272,000
671,577
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172
D: Total Audit Fees, in millions of dollars
2000
2001
2002
2003
2004
426.54
455.56
229.34
1.57
na
342.25
529.38
897.16
1,064.42
1,559.99
388.32
539.49
1,158.69
1,375.46
1,742.32
315.19
418.55
814.78
1,054.36
1,675.65
591.57
926.16
1,349.59
1,612.47
2,375.51
2,063.86
2,869.13
4,449.57
5,108.28
7,353.47
E: Distribution of Big 4/5 Lateral Auditor Realignments2
Dismissal
2000
2001
2002
2003
2004
Andersen
Other Big 4
Total Big 4/5
Resignation
Other
Total
0
15
698
299
0
7
78
96
122
83
7
93
794
421
83
2
9
21
18
23
12
77
141
83
52
21
179
956
522
158
Notes
1
2
Based on the availability of a DEF14A filing for fiscal years from January 1, 2000 to December 31, 2004.
Audit fee data are for Big 4/5 non-auditor change and Big4/5 lateral auditor change companies.
A Big 4/5 lateral auditor realignment reflects a change in auditor from one Big 4/5 firm to another Big 4/5
firm.
Consistent with prior research, skewness is reduced by transforming the data
logarithmically. Panel D shows aggregate annual audit fees, which for this sample have
increased by US$5.29 billion, from US$2.06 billion in 2000 to US$7.35 billion in 2004.
Individually, Price Waterhouse Coopers garners the greatest share of this increase,
that is, US$1.78 billion or 34% of the aggregate US$5.29 billion amount. It is later
addressed (section 4) whether such fee increases would have occurred for reasons other
than SOX or whether such fee increases are primarily a consequence of SOX and cannot
be explained by other factors. Finally, panel E reports the distribution of Big 4/5 auditor
realignments over the study period. As expected, the frequency of Andersen dismissals
jumps substantially in 2002. But non-Andersen dismissals and resignations jump
substantially too, starting in 2001 and 2002, and remain elevated for the remainder of
the study period. It is examined later whether these higher rates of auditor realignment
might be associated with residual audit fees following SOX in response to audit risk and
audit effort.
3.3. Univariate Analysis
Table 2 provides descriptive statistics for the log of audit fees for 2000-2004 (our
dependent variable for model 1) and partitions these data based on certain audit risk
and effort proxies. These proxies are litigation risk (1 if company has been subject to a
securities class action, issued an SEC NT filing, or restated earnings in the year prior to
the audit year, otherwise 0), company size (relative to median total assets in the audit
year), company profitability (1 if earnings per share before extraordinary items and
discontinued operations are negative, otherwise 0), the busy season (1 if the company
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173
has a December 31 fiscal year end, otherwise 0),6 and the number of days from fiscal
year end to the auditor’s signature date. Table 2 offers the following observations. First,
a logarithmic transformation of audit fees reduces substantially skewness, which is
essentially zero over all years. Second, with the exception of days to signature, each
of the other audit risk or effort proxies systematically and significantly explains audit
fee differences in the direction predicted or as indicated in prior research for each of
the years 2000 through 2004. In other words, audit fees in general, and apart from
any hypothesized effects of SOX, are significantly higher for companies with greater
litigation risk (panel B), larger companies (panel C), less profitable companies (panel D),
and when most audit effort occurs in the busy season (panel E). It is expected that the
variables in table 2 that explain differences in audit fees on a univariate basis will also
be significant in a multivariate regression analysis that controls for common effects.
Table 2
Descriptive Statistics for Log of Audit Fees By Year
Fiscal Year1
Variable
Total
2000
2001
2002
2003
2004
mean
std. deviation
skewness
median
count
5.43
0.63
0.14
5.39
25,851
5.29
0.53
0.47
5.25
4,023
5.28
0.55
0.30
5.26
5,752
5.35
0.63
0.06
5.34
6,215
5.43
0.66
(0.08)
5.44
5,747
5.86
0.58
0.02
5.86
4,114
mean
median
mean
median
t value
signif.7
5.75
5.66
5.36
5.34
37.37
***
5.53
5.41
5.26
5.22
11.67
***
5.55
5.45
5.23
5.22
15.93
***
5.71
5.61
5.28
5.29
19.50
***
5.80
5.72
5.36
5.39
19.46
***
6.08
6.04
5.80
5.82
12.63
***
mean
median
mean
median
t value
signif.7
5.71
5.69
5.14
5.14
73.48
***
5.51
5.45
5.08
5.07
23.76
***
5.52
5.50
5.05
5.06
32.40
***
5.67
5.65
5.14
5.16
34.33
***
5.71
5.70
5.15
5.17
33.44
***
6.02
6.00
5.39
5.38
32.77
***
5.67
5.61
5.47
5.40
24.86
***
5.51
5.43
5.24
5.18
15.12
***
5.53
5.45
5.29
5.24
16.59
***
5.63
5.57
5.46
5.38
10.70
***
5.73
5.66
5.53
5.47
11.66
***
5.89
5.89
5.81
5.81
4.30
***
A. Audit Firm
Big 4/52
B. Litigation Risk3
Higher
Lower
Difference
C. Company Size4
Higher
Lower
Difference
D. Company Profitability5
Higher
Lower
Difference
6
mean
median
mean
median
t value
signif.7
December 31 year end companies comprise 69.87% of the sample.
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E. Fiscal Year End
Dec. 31
non-Dec. 31
Difference
mean
median
mean
median
t value
signif.7
5.49
5.44
5.27
5.28
25.60
***
5.33
5.27
4.92
4.82
14.74
***
5.34
5.28
5.16
5.18
11.65
***
5.43
5.39
5.18
5.21
14.63
***
5.50
5.49
5.28
5.34
12.13
***
5.97
5.96
5.63
5.60
18.61
***
5.55
5.46
5.59
5.54
(1.61)
ns
5.96
5.96
5.30
5.24
na
ns
5.44
5.37
5.38
5.30
1.24
ns
5.51
5.42
5.47
5.42
1.04
ns
4.97
4.93
4.94
4.51
0.13
ns
5.79
5.78
5.87
5.86
(1.41)
ns
F. Days to Signature6
Greater than 90
Less than 90
Difference
mean
median
mean
median
t value
signif.7
Notes
1
Fiscal years from January 1, 2000 to December 31, 2004. Audit fee data are for Big 4/5 non-auditor
realignment companies and Big 4/5 lateral auditor realignment companies only.
2
Big 4/5 = Arthur Andersen & Co, Deloitte & Touche, Ernst & Young, KPMG, and PriceWaterhouse
Coopers.
3
Litigation risk = 1 if the company has been subject to a securities class action, issued an SEC NT filing, or
restated earnings in the year prior to the audit year, otherwise 0.
4
Total assets and earnings per share are relative to the median in the fiscal year.
5
Based on earnings per share before extraordinary items and discontinued operations.
6
Days from end of fiscal year to auditor’s signature date.
7
Significance of t statistic versus null hypothesis of no difference in the means (two tailed test): ***=less
than .0001; **=less than .001, *=less than .01, +=less than .05, ++=less than .10, and ns=not significant.
4. Regression Analysis
4.1. Model 1
Table 3 summarizes the results of estimating model 1 and reports the coefficients
for three estimation periods: Observations from January 1, 2000 to (1) December 31,
2004 (all observations), (2) April 1, 2003 (observations prior to section 404 on internal
control), and (3) July 25, 2002 (observations prior to the passage of SOX). Crosssectional ordinary least squares (OLS) regression procedures applied to each estimation
period are used to derive the coefficients. These estimation period coefficients are then
used to condition our prediction of residual audit fees following SOX. For example,
model 1 predicts residual audit fees for the period from April 1, 2003 (the SOXB period)
conditional on audit fee coefficients estimated over the period to April 1, 2003. Model 1
also predicts residual audit fees for the period from July 25, 2002 (the SOXA and SOXB
periods) conditional on audit fee coefficients estimated over the period to July 25, 2002.
Table 3 documents that the coefficients are mostly consistent in sign and significance
across the three estimation periods. The coefficients for the audit risk proxies such
as Litig, NegEPS, Zquin, GoingCon, and Issues are positive and significant, as
expected. The coefficients for the audit effort variables such as FYRDec31, Days2Sign,
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Log(Mcap), and Log(Size) are also predictably positive and significant across the
different estimation periods. In addition, the coefficients for the non-audit fee variables
Log(AudRel), Log(Tax), and Log(OthNA) are positive and significant. This last result is
consistent with the view that such variables are not fully endogenous to the model, that
is, they represent determinants not jointly reflected in the other variables.7 Most other
variable coefficients are consistent with the literature. Audit fees are higher the longer
the incumbent auditor has been engaged, the more the company operates internationally,
the higher the off-balance sheet liabilities, and when there are more extraordinary items.
However, some variables shown to be significant in explaining audit fees in earlier
studies are not uniformly significant in the present study, for example, the numbers of
segments and resignations are associated with a significant increase in audit fees based
on all observations but are not significant in the pre-SOX period. Audit fees following
Andersen and other Big 4 dismissals do not change significantly either. These factors are
examined further in the model 2 regressions that focus on the post SOX period.
Table 3
Regression Estimation of Log of Audit Fee
Estimation Period
Variable2
Intercept
Log(AudRel)
Log(Tax)
Log(OthNA)
Litig
NegEPS
Zquin
GoingCon
Issues
Tenure
FYRDec31
Days2Sign
Mkt/Book
Log(Mcap)
Log(Size)
Segm
Frgn
Log(Cash&CE)
Log(Rec&Inv)
1. Observations to
12/31/2004
Coeff.
1.8499
0.0379
0.0444
0.0270
0.1301
0.1647
0.0049
0.1670
0.2581
0.0455
0.1395
0.2011
0.0035
0.1900
0.1725
0.0220
0.0012
-0.0069
0.0399
Signif.1
***
***
***
***
***
***
+
***
***
***
***
***
***
***
***
**
***
++
***
2. Observations to
4/1/2003
Coeff.
1.9807
0.0233
0.0334
0.0370
0.0921
0.1346
0.0046
0.1762
0.2975
0.0465
0.1039
0.1542
-0.0007
0.0526
0.2971
0.0036
0.0002
0.0414
0.0144
Signif.1
***
***
***
***
***
***
++
***
***
***
***
***
+
***
***
ns
ns
***
***
3. Observations to
7/25/2002
Coeff.
2.1184
0.0219
0.0311
0.0490
0.0895
0.1193
0.0058
0.1776
0.1445
0.0425
0.0926
0.1472
- 0.0006
0.0437
0.2850
0.0019
0.0002
0.0379
0.0225
Signif.1
***
***
***
***
***
***
++
***
+
***
***
***
++
***
***
ns
ns
***
***
7
An earlier version of this paper compares the impact on audit fees of the non-audit fee variables based
on a joint estimation approach versus an ordinary least squares (OLS) approach. Unlike Whisenant et al. (2003),
who document that non-audit fees do not appear to affect audit fees directly after controlling for the joint
determination of both fee variables, we find that each of the non-audit fee variables does affect audit fees after
controlling for joint estimation. It is also documented that the results from OLS are qualitatively similar to
those from joint estimation.
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176
Log(OffBS)
XI&DisC
IndyLeader
IndySize
Instit
Dismiss
Resign
AudChOther
AudChFromAA
Adjusted R2
No. of observations
0.0065
0.0552
-0.0581
0.0071
0.0013
0.0109
0.1694
-0.0240
-0.0197
65.10%
20,731
++
***
***
***
***
ns
***
ns
ns
0.0170
0.0439
-0.0403
0.0066
0.0001
0.0117
0.0380
-0.0448
0.0005
71.53%
12,333
***
***
***
***
ns
ns
ns
ns
ns
0.0234
0.0275
-0.0377
0.0056
0.0000
0.0310
-0.0956
-0.0975
0.0507
70.67%
7,607
***
*
***
***
ns
ns
ns
+
ns
Notes
1
Tests of significance: ***=less than .0001; **=less than .001, *=less than .01, +=less than .05, ++=less than
.10, and ns=not significant. Tests are relative to a zero regression coefficient.
2
Definitions of the variables:
#
Variable
Definition
Source
0
Log(Aud)
Log10 of total audit fees for fiscal year.
DEF14A
Log(Tax)
Log10 of total tax-related fee for fiscal year.
1
2
Log(AudRel)
3
Log(OthNA)
4
5
Log10 of total audit-related fee for fiscal year.
DEF14A
DEF14A
Log10 of other (non-tax, non-audit related) non-audit fees for
fiscal year.
DEF14A
Litig
Litigation risk = 1 if the company has been subject to a securities
class action, issued an SEC NT filing, or restated earnings in the
year prior to the audit year, otherwise 0.
ISS, 8-K
NegEPS
Fiscal year earnings per share before extraordinary and
discontinued operations less than zero=1, otherwise 0.
Compustat
6
Zquin
Quintile ranking of Altman Z-score times -1
Compustat
7
GoingCon
Going concern qualification=1, otherwise 0.
8-K
8
Issues
9
10
Tenure
FYRDec31
11
Days2Sign
12
Mkt/Book
13
Log(Mcap)
14
Issues=1 if the company makes at least one non-standard
reportable event disclosure in the 8-K filing, otherwise 0.
8-K
Number of years company audited by incumbent auditor.
Compustat
Fiscal year ended December 31=1, otherwise 0.
Compustat
Days from fiscal year end to auditor’s signature > median Days
to Signature=1, otherwise 0.
Compustat
Ratio of market capitalization to common book equity at end of
fiscal year.
CRSP/
Compustat
Log10 of market capitalization of common shares at end of fiscal
year, millions.
Compustat
Log(Size)
Compustat
15
Segm
Log10 of total assets for fiscal year, millions.
16
Frgn
17
Log(Cash&CE)
Ratio of foreign sales to total sales for fiscal year, %.
18
19
Log(Rec&Inv)
Log(OffBS)
05_Griffin Lont.indd 176
Number of segments at end of fiscal year.
Log10 of cash and cash equivalents at end of fiscal year, millions.
Log10 of receivables and inventory at end of fiscal year, millions.
Log10 of sum of operating lease commitments at end of fiscal
year, millions.
Compustat
Compustat
Compustat
Compustat
Compustat
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177
20
XI&DisC
Extraordinary items and discontinued operations for fiscal year
not equal to zero=1, otherwise 0.
Compustat
21
IndyLeader
Audit firm has greatest number of clients in 3-digit NAICS
category=1, otherwise 0.
NAICS
22
IndySize
Decile ranking of number of companies in 3-digit NAICS code.
NAICS
23
Instit
Ratio of institutional common shares held to total shares
outstanding at end of fiscal year, %.
Compustat
24.1
Dismiss
Dismissal=1 in incoming auditor change year, otherwise 0.
8-K
24.2
Resign
Resignation=1 in incoming auditor change year, otherwise 0.
8-K
24.3
AudChOther
Auditor change reason unstated=1 in incoming auditor change
year, otherwise 0.
8-K
24.4
AudChFromAA
Andersen dismissal due to indictment=1, otherwise 0.
Direct
4.2. Model 2
Table 4 summarizes the results of estimating model 2, which is used to test
hypotheses H1, H2, and H3. The table shows two sets of regressions. The first set
regresses audit risk and audit effort on residual audit fees over the period from July 25,
2002 to December 31, 2004. This period combines the SOXA and SOXB sub-periods. The
second set regresses audit risk and audit effort on residual audit fees from April 1, 2003
to December 31, 2004. Hence, this second period covers the SOXB sub-period only.
Regressions 1 and 3 exclude the auditor realignment variables, whereas regressions 2
and 4 include the auditor realignment variables. Regressions 1 and 2, also, include an
intercept variable for the SOXB sub-period to control for a possible post-SOX mean shift
from the first to the second regression period in conjunction with the other explanatory
variables.
From regression 1, it is observed that the coefficients on Litig(γ 11=0.044) and
NegEPS(γ12=0.116) (audit risk proxies) are positive and significant, at alpha levels
of less than 0.1%. This result supports H1 (in the alternative form). In other words,
regression 1 documents a positive relation between residual audit fees in the post-SOX
period and post-SOX audit risk after controlling for those factors expected to explain
audit fees in a non-SOX period, including “normal” audit risk, effort and other factors.
This is interpreted as implying that the higher audit fees following SOX not predicted
by a pre-SOX audit fee model are partially attributable to higher levels of post-SOX
audit risk, which apparently auditors “shift” to the client as a higher audit fee. Given our
theory, this implies additional risk sharing and price protection on the part of the auditor,
presumably in response to SOX.
Likewise, the model 2 coefficients on FYRDec31 (γ21=0.092), Days2Sign (γ22=0.044),
and Log(MCap) (γ23=0.114) (audit effort proxies) are positive and significant at alpha
levels of less than 5%. This supports H2 (in the alternative form), namely, that residual
audit fees following SOX are positively associated with post-SOX audit effort, again,
after controlling for those factors that would explain audit fees in a non-SOX period.
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Table 4
Regression Analysis of Residual Audit Fees Following SOX
Estimation
period
Pre 7/25/2002
Pre 4/1/2003
Regression
period
Post 7/25/2002
Post 4/1/2003
Indep. Var.2
Coeff.
Regression #
1
Intercept
Litig
NegEPS
FYRDec31
Days2Sign
Log(Mcap)
SOXB
Dismiss
Resign
AudChOther
Adjusted R2
Number of
observations
-0.964
0.044
0.116
0.092
0.044
0.114
0.168
11.80%
13,124
Sig.1
Coeff.
Sig.1
2
***
***
***
***
+
***
***
-0.954
0.041
0.117
0.093
0.043
0.114
0.156
-0.106
0.285
0.064
12.40%
13,124
Coeff.
Sig.1
3
***
**
***
***
+
***
***
***
***
++
-1.290
0.139
0.101
0.039
0.159
0.056
10.28%
8,398
Coeff.
Sig.1
4
***
***
***
ns
***
***
-1.278
0.054
0.139
0.101
0.039
0.158
***
**
***
***
ns
***
-0.110
0.149
0.015
10.56%
8,398
***
+
ns
Notes
1
Tests of significance of coefficients: ***=less than .0001; ** =less than .001, *=less than .01, + =less than
.05, ++ =less than .10, and ns=not significant. Tests are relative to a zero regression coefficient.
2
The dependent variable for each regression is residual audit fees (log of audit fees less predicted log of audit
fees), ^εit, where predicted log of audit fees is based on the regression coefficients estimated in table 3 (columns
2 and 3) using the actual values of the independent variables in the post April 1, 2003 or post July 25, 2002
periods. SOXB is a unit variable that equals one for observations after April 1, 2003 and zero otherwise. See
table 3 for definitions of the other independent variables.
The second regression in table 4 includes the auditor realignment variables as they,
too, may capture changes in audit risk and effort. These regression results support
hypothesis H3 (in the alternative form). The Dismiss variable is significantly negative
(γ31=-0.106), consistent with the view that incoming auditors following a dismissal in
the post-SOX period utilize fewer resources to conduct the audit, including possible fee
discounting. Conversely, the Resign variable is significantly positive (γ32=0.285), which
supports the view that incoming auditors in the post-SOX period increase their fees to
compensate for the additional audit risk following a resignation.
As a sensitivity check, we run regressions 3 and 4, which are based on residual audit
fees from model 1 when the model 1 estimation period includes the SOXA sub-period.
As such, these (model 2) regressions control for both audit fee determinants in general
and the effects on audit fees, if any, of the Act’s provisions in the SOXA sub-period. The
results are qualitatively unchanged when the residual audit fee regressions are based
on the later period only. For example, regression 4 documents positive and significant
coefficients for Litig (γ11=0.054) and NegEPS (γ12=0.139) (audit risk proxies), positive
05_Griffin Lont.indd 178
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179
and significant coefficients for FYRDec31 (γ21=0.101) and Log(MCap) (γ23=0.158) (audit
effort proxies), and negative and positive coefficients for dismissals (γ31= -0.110) and
resignations (γ32=0.149), respectively. In other words, when we focus only on residual
audit fees from April 1, 2003 (the SOXB sub-period) conditional on an estimation period
that includes the SOXA sub-period, we still find results that support hypotheses H1, H2,
and H3. This may be a more conservative test of the hypotheses in that the impact of
earlier provisions such as section 302 on certification are controlled for by including the
effects of SOXA in the estimation period prior to predicting residual audit fees.
4.3. Model 3
The third phase of the analysis examines differences in the impact of SOX on audit
fees conditional on the timing of the different provisions, in particular, the earlier
section 302 provisions and the later section 404 provisions. The results from model 3 are
summarized in table 5. As before, the fiscal periods are partitioned following the passage
of the Act into SOXA and SOXB sub-periods. Model 3 is then used to test whether the
effects of the audit risk and audit effort proxies on residual audit fees differ on the basis
of the two sub-periods. Regression 1 includes unit variables for SOXA and SOXB and
interacts these variables with each of the audit risk and audit effort proxies. Regression 2
includes unit variables for SOXB only. Table 5 reports, also, the results of model 1 from
table 3 for comparison purposes since model 1 and model 3 differ only in that model 1
excludes the SOX interaction variables.
The first regression in table 5 (regression 1) shows significant incremental effects
for audit risk proxy SOXANegEPS (η12=0.061) and SOXBNegEPS (η12=0.089) but not for
SOXALitig (η11=0.001) or SOXBLitig (η11=0.027). This regression also shows significant
incremental effects for the audit effort proxies, SOXAFYRDec31 (η21=0.056) and SOXB
FYRDec31 (η 21=0.130), and SOX ALog(MCap) (η 23=0.025) and SOX BLog(MCap)
(η23=0.107). Predictably, incrementally significant coefficients are also documented
for SOXAResign (η32=0.202), SOXBResign (η32=0.229), and SOXBDismiss (η31=-0.117)
but not for SOX ADismiss (η 31=-0.045). Regression 2 shows similar results for the
SOXB coefficients. Both audit risk proxies are positive and significant (η11=0.028 and
η12=0.066) and two of the three audit effort proxies are positive and significant (η21=0.109
and η23=0.098). Also, SOXBDismiss is significant (η31=-0.101), but SOXBResign is not
significant (η32=0.111). Finally, it is observed that the coefficients for regressions 1 and 2
are qualitatively similar to those of regression 3. In other words, the addition of the SOX
variables in model 3 has only limited effect on the estimation of the control variable
coefficients, presumably because of an absence of significant collinearity among the
SOX and control variables (see, also, section 4.5).
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180
Table 5
Regression Estimation of Log of Audit Fee with SOX Unit Variables
1. SOXA and SOXB
Unit Variables
2
Variable
Intercept
Log(AudRel)
Log(Tax)
Log(OthNA)
Litig
NegEPS
Zquin
GoingCon
Issues
Tenure
FYRDec31
Days2Sign
Mkt/Book
Log(Mcap)
Log(Size)
Segm
Frgn
Log(Cash&CE)
Log(Rec&Inv)
Log(OffBS)
XI&DisC
IndyLeader
IndySize
Instit
Dismiss
Resign
AudChOther
AudChFromAA
2. SOXB
Unit Variables
3. Table 3, Column A
Coefficient
Signif.
Coefficient
Signif.
Coefficient
Signif.1
2.2222
0.0316
0.0369
0.0363
0.1184
0.1145
0.0047
0.1707
0.2429
0.0500
0.0821
0.1690
0.0028
0.1362
0.1824
0.0215
0.0011
-0.0046
0.0374
0.0072
0.0478
-0.0568
0.0069
0.0010
0.0674
-0.0327
-0.0847
-0.0054
***
***
***
***
***
***
+
***
***
***
***
***
***
***
***
**
***
ns
***
+
***
***
***
***
+
ns
++
ns
2.1568
0.0330
0.0394
0.0350
0.1164
0.1370
0.0048
0.1752
0.2429
0.0495
0.1012
0.1877
0.0028
0.1426
0.1830
0.0213
0.0011
-0.0039
0.0367
0.0072
0.0487
-0.0552
0.0068
0.0010
0.0489
0.0885
-0.0288
-0.0002
***
***
***
***
***
***
+
***
***
***
***
***
***
***
***
**
***
ns
***
+
***
***
***
***
+
ns
ns
ns
1.8499
0.0379
0.0444
0.0270
0.1301
0.1647
0.0049
0.1670
0.2581
0.0455
0.1395
0.2011
0.0035
0.1900
0.1725
0.0220
0.0012
-0.0069
0.0399
0.0065
0.0552
-0.0581
0.0071
0.0013
0.0109
0.1694
-0.0240
-0.0197
***
***
***
***
***
***
+
***
***
***
***
***
***
***
***
**
***
++
***
++
***
***
***
***
ns
***
ns
ns
-0.2163
-0.8705
0.0010
0.0265
0.0609
0.0893
0.0561
0.1296
0.0151
0.0508
0.0247
0.1073
**
***
ns
ns
***
***
**
***
ns
ns
*
***
-0.7946
***
0.0276
++
0.0664
***
0.1093
***
0.0323
ns
0.0976
***
1
1
SOX Unit Variables3
SOXA
SOXB
SOXA.Litig
SOXB.Litig
SOXA.NegEps
SOXB.NegEps
SOXA.FYRDec31
SOXB.FYRDec31
SOXA.Days2Sign
SOXB.Days2Sign
SOXA.Log(Mcap)
SOXB.Log(Mcap)
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Asia-Pacific Journal of Accounting & Economics 14 (2007) 161–192
SOXA.Dismiss
SOXA.Resign
SOXA.AudChOther
SOXB.Dismiss
SOXB.Resign
SOXB.AudChOther
Adjusted R2
No. of observations
-0.0454
0.2019
0.0882
-0.1170
0.2291
0.0632
66.66%
20,731
ns
++
ns
**
+
ns
-0.1009
0.1111
0.0077
66.54%
20,731
181
***
ns
ns
65.10%
20,731
Notes
1
Tests of significance of coefficients: ***=less than .0001; ** =less than .001, *=less than .01, + =less than
.05, ++ =less than .10, and ns=not significant. Tests are relative to a zero regression coefficient.
2
Audit fee data are for Big 4/5 non-auditor change companies and Big 4/5 lateral auditor change companies
only. The dependent variable is log of audit fee.
3
SOXA is a unit variable that equals one for observations after July 25, 2002 and before April 1, 2003,
otherwise zero. SOXB is a dummy variable that equals one for observations after April 1, 2003, otherwise
zero. See table 3 for definitions of the other independent variables.
The results from table 5 are interpreted as follows. First, they provide an alternative
test of hypotheses H1, H2, and H3. This may be a more conservative test in that the
control variable coefficients are estimated over the entire study period, which includes
the impact of SOX, rather than over a prior period independent of the Act, which is
the approach followed in the tests based on model 2. Yet, despite this, table 5 still
documents significant incremental effects for the fiscal periods following SOX for the
audit risk, audit effort, and the auditor realignment variables. Moreover, it is observed
that these effects are common to both the SOXA and SOXB sub-periods.
Second, a comparison of the coefficients for the SOXA and SOXB interaction variables
enables a test of whether interaction effects differ between the two sub-periods (H4).
Regression 1 shows that for each of the two audit risk, three audit effort, two auditor
realignment variables, the SOXB interaction coefficients all exceed in absolute value
the SOXA interaction coefficients. For example, SOXBLitig (η11=0.027) > SOXALitig
(η11=0.001), SOXBNegEPS (η12=0.089) > SOXANegEPS (η12=0.061). Assuming a null
hypothesis that the probability that the later SOXB coefficients exceed the earlier SOXA
coefficients is 50%, the chances that all later coefficients would exceed all earlier
ones is essentially zero. In other words, based on a binomial test, the notion that such
differences could occur by chance can be rejected in favor of the alternative notion that
the SOXB interaction coefficients exceed the SOXA coefficients.
These results, therefore, support H4 – that residual audit fees following the Act relate
more to audit effort and audit risk changes in the SOXB period, for example, in response
to section 404 on internal control, rather than to changes in the earlier SOXA period, for
example, in response to the certification and related provisions. As an alternative test
of H4, model 3 is also estimated including the SOXA interactive effects only. Consistent
with the preceding, these interactive effects are insignificant, presumably because the
audit risk and audit effort control variables already impound the statistically significant
incremental impacts of the audit risk and audit effort proxies in the SOXB period.
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Asia-Pacific Journal of Accounting & Economics 14 (2007) 161–192
4.4. Dollar Impact of Residual Audit Fees
The results thus far, in logarithmic form, may not be readily interpretable. This
section calculates the dollar equivalent of the log of residual audit fees and compares
this amount with pre-SOX audit fees, based on average audit fees in the fiscal year prior
to residual fees. Mean and median residual audit fees (over the same set of companies)
are calculated for fiscal year ends from (a) the passage of SOX to December 31, 2002,
2003, and 2004 and (b) April 1, 2003 to December 31, 2003 and 2004 (the SOXB subperiod only). These residual amounts are compared with the mean and median actual
change in audit fees from fiscal years 2001 or 2002 to 2004. These latter calculations
provide a benchmark to assess how much of the actual change in audit fees following
SOX is a residual based on an audit fee model.
Table 6 summarizes the results. Panel A reports a mean residual audit fee per
company, from July 25, 2002 (SOX passage) to December 31, 2004, of US$1,127,709,
of which US$566,343 occurs prior to 2004. PWC (Price Waterhouse Coopers) shows
the largest mean and median residuals of US$1,600,341 and US$403,677, respectively.
These are well in excess of the other Big 4 firms. The medians are less because of a
small number of outlier companies with large fees. Similar results are observed when the
residual fees are from April 1, 2003 (the SOXB period). Panels C and D report that the
mean and median residual fees to December 31, 2004 are US$967,195 and US$275,763,
respectively.
Table 6
Mean and Median Residual Audit Fees Following SOX, in Dollars
Fiscal Year
Andersen
Deloitte &
Touche
Ernst &
Young
KPMG
PWC
Grand
Mean
A: Mean Unexpected Increase in Audit Fee, in dollars, from July 25, 20022
2002
2003
2004
Pre-SOX base1
Ratio of 2004 to
Pre-SOX
Ratio of Actual
2004-2001 to 2001
289,962
na
na
583,680
na
477,267
586,760
1,178,257
788,444
1.49
366,163
467,464
881,069
555,465
1.59
351,883
449,621
865,627
531,750
1.63
572,747
765,303
1,600,341
928,411
1.72
431,359
566,343
1,127,709
700,515
1.61
na
1.39
1.88
1.93
1.50
1.71
B: Median Unexpected Increase in Audit Fee, in dollars, from July 25, 20022
2002
2003
2004
Pre-SOX base1
Ratio of 2004 to
Pre-SOX
Ratio of Actual
2004-2001 to 2001
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(13,454)
na
na
245,000
na
41,311
77,343
287,394
257,650
1.12
66,822
122,759
358,875
250,630
1.43
25,464
57,919
220,929
201,000
1.10
67,657
114,244
403,677
295,000
1.37
46,394
97,648
319,547
250,000
1.28
na
1.70
2.02
2.24
2.16
2.00
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183
C: Mean Unexpected Increase in Audit Fee, in dollars, from April 1, 20033
2003
2004
Pre-SOX base1
Ratio of 2004 to
Pre-SOX
Ratio of Actual
2004-2002 to 2002
na
na
na
na
590,923
1,013,663
1,037,369
0.98
434,706
718,827
841,830
0.85
427,918
710,650
775,730
0.92
750,295
1,440,043
1,125,642
1.28
549,203
967,195
940,533
1.03
na
0.81
0.83
0.91
1.01
0.93
D: Median Unexpected Increase in Audit Fee, in dollars, from April 1, 20033
2003
2004
Pre-SOX base1
Ratio of 2004 to
Pre-SOX
Ratio of Actual
2004-2002 to 2002
na
na
na
na
59,024
247,748
352,000
0.70
95,232
311,349
347,000
0.90
39,448
192,833
262,300
0.74
93,573
354,600
366,000
0.97
76,420
275,763
335,000
0.82
na
1.01
1.19
1.56
1.42
1.24
Notes
1
Pre-SOX base is the mean/median audit fees calculated over 12 months prior to July 25, 2002 or April 1,
2003. Audit fee data are for Big 4/5 non-auditor change and Big 4/5 lateral auditor change companies only.
2
Residual audit fees based on regression coefficients estimated over January 1, 2000 to July 25, 2002 (table 3,
column 3). Statistics based on firms with common audit fee observations in 2001 through 2004.
3
Residual audit fees based on regression coefficients estimated over January 1, 2000 to April 1, 2003 (table 3,
column 2). Statistics based on firms with common audit fee observations in 2002 through 2004.
These data also allow a comparison of the mean (median) residual fees in the later
SOXB period. For example, whereas the mean and median fee residuals in such period
are US$967,195 and US$275,763, respectively, the mean and median residuals in the
earlier SOXA period are US$160,514 (US$1,127,709 – US$967,195) (panels A and C)
and US$44,184 (US$319,547 – US$275,363) (panels B and D). The residual audit fees
earned in the earlier period are, thus, clearly much less that those earned in the later
period.
Finally, table 6 reports the ratio of the 2004 mean (median) residual fee relative to
a pre-SOX base and the ratio of actual mean (median) fee audit fee increase relative to
actual 2001. This latter calculation requires no prediction of audit fees in the absence
of the Act. The following is observed. Panels A and C show mean residual audit fees of
1.61 (1.03) times the pre-SOX base versus an actual increase in mean fees of 1.71 (0.93)
times 2001. Panel B, on the other hand, shows median residual audit fees of 1.28 (0.82)
times the pre-SOX base versus an actual increase in median fees of 2.00 (1.24) times
2001 fees. Hence, based on mean audit fees, the dollar increases in audit fees from 2001
are not substantially different from dollar equivalent residuals from the models. On
the other hand, the dollar equivalent median residuals are substantially smaller, in part,
because they reduce the effects of outliers from the analysis. This suggests that while
the increases in mean dollar-equivalent audit fees from the regressions are similar to
the actual fee increases, these amounts appear to be influenced by a few large audit fee
observations that skew the results. This is not the case with the logarithmic regressions,
however, on which we base our tests of hypotheses.
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184
As a further introspective, this paper reports the distribution of the residual log of
audit fees as figure 1. Three observations are offered. First, the distribution of residual
log of audit fees is highly symmetric, consistent with an appropriate transformation of
the data. Second, the mean residual log of audit fees is significantly greater than zero
(mean=0.292 from July 25, 2002). As has already been documented, this indicates an
overall positive effect on fees following SOX.
Figure 1
Distribution of Residual Audit Fees
12%
Percent in each 0.1 frequency bin
10%
8%
Post July 25, 2002
Post April 1, 2003
6%
4%
2%
-2.0
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
-0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0%
Log Audit Fee less Predicted Log Audit Fee
This plot shows the frequency distribution of the residual audit fees (log of audit fees less predicted
log of audit fee), ε^ it , where the predicted log of audit fee applies the regression coefficients in table
3 (estimated over the two earlier periods – from January 1, 2000 to July 25, 2002 and January
1, 2000 to April 1, 2003) to the actual values of the independent variables in the post July 25 or
post April 1 periods. The plot uses 40 frequency bins of width 0.10 based on 8,398 observations
common to the post July 25, 2002 and post April 1, 2003 periods.
Third, the residual log of audit fees from April 1, 2003 (mean = 0.242) is
significantly less than the change from July 25, 2002. The difference of 0.050 is
significant at p<.0001 based on a t test. In other words, while the mean residual log of
audit fees following passage of the Act is 0.292, most of that occurs after April 1, 2003,
that is, in the SOXB period, which includes the implementation of section 404.
4.5. Robustness and Sensitivity Tests
First, we conduct several tests to check the sensitivity of our results to alternative
definitions and variables. Without changing model 1, model 2 is re-estimated
substituting Log(Size) (based on total assets or revenue) for Log(Mcap) and with Litig
defined only in relation to the existence of a prior securities class action filing. We
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185
also move the cut-off date for the SOXA and SOXB sub-periods to June 5, 2003 (date of
SEC Release 33-8238). The signs of the audit risk, effort, and realignment coefficients
in table 4 do not change appreciably when we make these changes. The variables and
definitions applied in table 4 exhibit a modestly higher explanatory power than the
alternatives.
Model 1 is also re-estimated excluding those variables whose sign and significance
are not consistent across the three regression periods as shown in table 3 (e.g., Segm,
Frgn, Insit, Mkt/Book), thereby re-estimating residual audit fees following SOX, that is,
the dependent variable in model 2. The signs of the audit risk, effort, and realignment
coefficients in table 4 do not change qualitatively when a reduced-form model is used.
We are cautious, though, about removing too many variables from model 1 as this
could transfer to residual audit fees the impact of certain “normal” audit risk or audit
effort variables that might mistakenly be interpreted to reflect incremental post-SOX
audit risk or audit effort. For example, if the auditor realignment variables were to be
excluded from model 1, then the coefficients for such in model 2 would capture both
pre- and post-SOX effects. Model 2 is also estimated based on positive residual audit
fees only, in light of the possibility that some firms experiencing negative residual fees
may be affected by other (unknown) factors correlated with the independent variables in
the model, and this could bias our results. These unreported results are not appreciably
different from those in table 4, which are based on positive and negative residual audit
fees.
Second, as a check on reliability, model 2 is estimated over an earlier, pre-SOX
period – from July 26, 2001 to July 25, 2002. If the effects of SOX vary positively with
additional litigation risk and audit effort in the post-SOX period, as is hypothesized in
H1 and H2, then those variables should be less positive or insignificant when model 2 is
applied to a pre-SOX period. To test this notion, model 1 is estimated based on audit fee
data through July 25, 2001. Audit fees are then predicted for the period July 26, 2001 to
July 25, 2002 (the pre-SOX period) conditional on the actual values of the independent
variables. Unreported results indicate that the effects of our audit effort and litigation
proxies are both smaller and/or insignificant in the pre-SOX period. This lends credence
to the use of our audit risk and audit effort proxies.
Third, as a potential additional factor to explain residual audit fees following SOX,
it is examined whether audit fee effort might be moderated in those situations where the
audit firm receives additional compensation from audit-related fees. This is examined in
two ways. First, we partition the sample on the basis of high and low audit-related fees
in the post-SOX period and estimate model 2 for each partition. It is found that the audit
effort coefficients in model 2 are qualitatively unchanged for both the high and low
partitions. Second, model 2 is estimated with log of audit-related fees in the post-SOX
period as an additional independent variable. This version of Model 2 is used to test
whether the audit effort coefficients in model 2 are less positive or insignificant to the
extent that residual audit fees are explained more by audit-related fees and less by audit
effort and/or litigation risk factors. It is found that the audit effort and litigation risk
coefficients in model 2 including log of audit-related fee as an additional variable are
qualitatively the same as those reported in table 4. These results suggest that additional
audit-related fees paid to an audit firm in the post-SOX period (e.g., for internal control
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Asia-Pacific Journal of Accounting & Economics 14 (2007) 161–192
design) do not change the reliability of our findings regarding the influence of audit
effort and litigation risk as two significant drivers of residual audit fees following the
passage of SOX.
Fourth, this paper evaluates the possibility that collinearity among the independent
variables in models 1 and 3 may threaten the tests of hypotheses. The steps outlined in
Judge et al. (1988) and others are followed to examine such possibility. As expected,
several of the variables in those models (e.g., firm size and market capitalization) are
highly correlated. However, none of the individual regression coefficients in models 1
or 3 is of the opposite sign from what is predicted or unexpectedly insignificant, which
are two indications of non-substantial collinearity. A more formal test is also conducted
by calculating the variance inflation factor associated with each of the highly correlated
independent variables in models 1 or 3 (where corr.(xi,xj) >.4). According to Neter
et al. (1990) and others, a variance inflation factor of greater than ten is evidence of
substantial collinearity. Unreported tests reveal a maximum variance inflation factor of
less than three.
Finally, it is noted that the regression models thus far use OLS to estimate the
coefficients, which assumes that the off-diagonal covariances are zero. This may not be
literally true, however, because of industry factors and pooling over time. This paper,
therefore, reviews the results when the coefficients in tables 3, 4, and 5 are estimated
using generalized least squares (GLS software from SAS Institute, Inc.). The results are
qualitatively unchanged, in that the same audit risk, effort, and realignment variables
that are significant in model 2 under OLS estimation are also significant under GLS
estimation.
5. Summary and Conclusions
This paper examines the impact of the passage of SOX on audit fees controlling for
those determinants that could be reasonably expected to influence fees in the absence of
the Act. The sample includes all companies audited by a Big 4/5 auditor over 2000-2004.
While, not surprisingly, the study finds that audit fees have increased following SOX,
this paper quantifies these amounts and relates them to the earlier and later provisions
of the Act with controls for other factors. For example, the study documents a mean
residual audit fee in response to the earlier section 302 certification and disclosure
provisions of US$160,514 per company. This pales by comparison to a higher mean
residual audit fee associated with the later section 404 internal control provisions of
US$967,195 per company. This paper also tests and documents significant positive
relations between residual audit fees following SOX and proxies for incremental audit
risk and audit effort, two key factors that our theory predicts explain residual audit fees.
Auditor realignments following SOX further explain residual audit fees. Lastly, it is
documented that residual audit fees are more associated with incremental audit risk and
audit effort in the later (internal control) period rather than the earlier (certification and
disclosure) period.
This paper contributes to the literature by testing hypotheses about why audit fees
have increased in response to SOX. The results suggest two key reasons – first, that
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Asia-Pacific Journal of Accounting & Economics 14 (2007) 161–192
187
changes in audit risk thresholds following SOX prompted auditors to increase audit fees
to compensate for higher expected losses. Such audit fee increases are consistent with
risk sharing and price protection on the part of the auditor in response to the additional
risk imposed by SOX for faulty financial statements and deficient controls. The finding
that residual audit fees increase in association with higher rates of auditor resignation is
a further manifestation of this view. The theory and results support a second reason for
an increase in audit fees following the Act – that SOX simply required auditors to apply
more time and resources to examine and evaluate a costlier accounting and disclosure
system. Without risk sharing, shareholders bear these costs directly as a loss of equity
value.
While it is shown that both factors significantly explain residual audit fees, this
paper is unable to discern quantitatively whether one factor dominates the other.
However, both factors appear to drive the overall fee increases, and these increases,
of course, have not been inconsequential. For example, relative to 2001 audit fees,
it is calculated that companies in our sample paid their auditors from 2002 to 2004
aggregate additional audit fees of slightly more than US$8 billion. Importantly, also,
most of this, as these models show, cannot be readily explained by variables that would
have increased fees in those years in the counterfactual situation, that is, in the absence
of the Act. While changes in audit risk and effort and auditor realignments suggest key
reasons for the fee increases, and these are consistent with our theory, an examination
of other possible considerations must be left to future research. For example, auditing
fees should diminish in the future if the higher fees observed reflect in part the cost of
reviewing and documenting internal controls for the first time.8 Auditing fees could
also diminish because more auditing may lead to better governance, which in turn may
induce a decrease in audit and control risk. Finally, it is cautioned that this paper is
unable to discern the exact counterfactual situation for empirical analysis other than by
the use of models to predict audit fees but for the Act. Model structure and coefficients
based on data prior to SOX, for example, may be inappropriate for the later periods and,
if based on the entire period, run the risk of over-fitting, thereby blurring the effects to
be identified at the outset.
Appendix 1
Prior Research on Audit Fee Determinants in Model 1
#
Determinant in
Model 11
Exp.
Sign
Examples of Prior Research.2
1
Log(AudRel)
+
2
Log(Tax)
+
Simunic (1984), Palmrose (1986b), Turpen (1990), Davis et al. (1993),
Parkash and Venable (1993), O’Keefe et al. (1994), Frankel et al.
(2002), Whisenant et al. (2003). Some are total non-audit fees; others
split between tax and other non-audit fees.
Palmrose (1986b), Davis et al. (1993), O’Keefe et al. (1994).
8
Preliminary survey data suggest a drop in fees from 2004 to 2005 of between 13% and 30-43% (Committee
on Capital Markets Regulation 2006).
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Asia-Pacific Journal of Accounting & Economics 14 (2007) 161–192
188
3
4
Log(OthNA)
Litig
+
+
5
NegEPS
+
6
7
Zquin
GoingCon
+
+
8
9
10
Issues
Tenure
FYRDec31
+
+
11
12
13
14
Days2Sign
Mkt/Book
Log(Mcap)
Log(Size)
+
+
+
+
15
Segm
+
16
17
Frgn
Log(Cash&CE)
+
–
18
Log(Rec&Inv)
+
19
20
21
Log(OffBS)
XI&DisC
IndyLeader
+
+
–
22
23
24.1
24.2
24.3
24.4
IndySize
Instit
Dismiss
Resign
AudChOther
AudChFromAA
+
+
–
+
?
?
Hoitash et al. (2005).
Lys and Watts (1994), Simunic and Stein (1996), Gul and Tsui (1997).
Litig (prior securities litigation) not studied separately.
Simunic (1980), Francis (1984), Craswell and Francis (1999),
Whisenant et al. (2003), Hay et al. (2006) (39 studies).
Stice (1991), Whisenant et al. (2003).
Simunic (1980), Palmrose (1986), Francis and Simon (1987), Simon
and Francis (1988), Turpen (1990), Simunic and Stein (1996), Hay et
al. (2006) (46 studies).
Hertz (2006), Raghunandan and Rama (2006).
Simunic (1980), Beck et al. (1988), Stice (1991), Copley et al. (1994).
Palmrose (1986a), Palmrose (1989), Craswell and Francis (1999),
Francis and Wang (2005), Hay et al. (2006) (32 studies).
Gul (1999), Whisenant et al. (2003), Ettredge et al. (2006).
Whisenant et al. (2003).
Stice (1991).
Simunic (1980), Francis (1984), Palmrose (1986a), Hay et al. (2006)
(87 studies).
Simunic (1980), Francis and Simon (1987), Hay et al. (2006)
(7 studies).
Simunic (1980), Francis and Simon (1987), Craswell et al. (1995).
Whisenant et al. (2003), Francis and Wang (2005) (liquidity
measures).
Simunic (1980), Francis and Simon (1987), Hay et al. (2006)
(43 studies).
Not studied separately.
Whisenant et al. (2003).
Eichenseher and Danos (1981), Palmrose (1984), Craswell et al.
(1995), Asthana et al. (2004).
Market share proxy, Asthana et al. (2004).
Whisenant et al. (2003), Asthana et al. (2004).
Ettredge and Greenberg (1990), Turpen (1990).
Sankaraguruswamy and Whisenant (2004).
Not studied separately.
Asthana et al. (2004).
Notes
1
Table 3 states the definitions of these variables.
2
This appendix identifies selected studies that analyze and offer evidence in support of the predicted relation
between the audit fee determinants in model 1 and the log of audit fees. We recognize more than 25 years
of literature on the subject. We also recognize that the particular empirical definitions used in the earlier
literature may vary from those used in model 1. Hay et al. (2006) use a meta analysis to identify variables
common to this literature. Other reviews include Yardley et al. (1992), Turpen (1995), and Simunic and
Stein (1996).
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189
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