hossain - 2013 - effect of regulatory changes on auditor independence and audit quality

Effect of Regulatory Changes
on Auditor Independence and
Audit Quality
Sarowar Hossain
Australian School of Business, University of New South Wales, Australia
This study investigates the impact of CLERP 9 on auditor
independence and audit quality. Audit quality is measured by
performance-adjusted discretionary accruals and the auditor’s
propensity to issue a going-concern opinion for a financially
distressed company. The results show a significant and
positive association between auditor-provided non-audit
services (NAS) fees and the propensity to issue a going-concern
opinion for a financially distressed company post-CLERP 9,
but an insignificant association pre-CLERP 9. The results show
a significant and positive association between NAS fees and
the performance-adjusted absolute value of discretionary
accruals pre-CLERP 9, but this significant association was
mitigated by the introduction of CLERP 9. To address the
potential impact of the level of abnormal NAS fees on auditor
independence, the analysis is extended by incorporating
predictions of abnormal NAS fees. Abnormal NAS fees are
significantly and negatively associated with the propensity to
issue a going-concern opinion for a financially distressed
company and positively associated with discretionary accruals
pre-CLERP 9, but they are not significant post-CLERP 9. The
results provide evidence of improved audit quality after the
implementation of CLERP 9. The results will be useful to
regulators for the justification of regulatory changes. The
findings provide evidence of the effectiveness of regulatory
changes, specifically the CLERP 9, on the improvement of
auditor independence and audit quality.

Key words: Going-concern, audit opinion, abnormal non-audit
fees, audit quality, discretionary accruals, non-audit fees, CLERP
9, auditor independence, regulatory changes
SUMMARY
This study investigates the effectiveness of
regulatory changes, specifically the Corporate Law
Economic Reform Program (CLERP) Act 2004
(Cth), on auditor independence and audit quality.
Correspondence to: Sarowar Hossain, Australian School of
Business, University of New South Wales, NSW 2052, Australia.
Email:
International Journal of Auditing doi:10.1111/ijau.12002
Int. J. Audit. ••: ••–•• (2013)
ISSN 1090-6738
© 2013 Blackwell Publishing Ltd
The first measure of audit quality is the propensity
of auditors to issue a going-concern opinion for
a financially distressed company, and the second
is the performance-adjusted absolute value of
discretionary accruals. Auditor independence is
measured by the auditor-provided non-audit
services (NAS) fees and abnormal NAS fees. The
study uses Australian company data for the period
2002-2007.
The results show a significant and positive
association between NAS fees and the propensity
to issue a going-concern opinion for a financially
distressed company post-CLERP 9, but this
association is not significant pre-CLERP 9. NAS
fees are significantly and positively associated

with the performance-adjusted absolute value
of discretionary accruals pre-CLERP 9, but are
not significant post-CLERP 9. To address the
potential impact of fee composition on auditor
independence, the analysis is extended by
incorporating predictions of abnormal NAS fees.
Abnormal NAS fees are derived from a fee
estimation model drawn from prior research.
Abnormal NAS fees are significantly and
negatively associated with the propensity to issue
a going-concern opinion for a financially distressed
company and positively associated with the
absolute value of discretionary accruals pre-CLERP
9, but are not significant post-CLERP 9. The
findings provide evidence of improved audit
quality after the implementation of CLERP 9.
The results will be useful to regulators for
justifying regulatory changes. The findings provide
evidence of the effectiveness of regulatory changes,
specifically the CLERP 9, on the improvement of
auditor independence and audit quality.
INTRODUCTION
This study examines the effectiveness of regulatory
changes, specifically the Corporate Law Economic
Reform Program Act 2004 (Cth) (hereafterCLERP 9)
on auditor independence and audit quality.
Auditor-provided non-audit services have been one
of the most debated issues for the last several
decades, with arguments that abnormally high fees
for auditor-provided non-audit services may

compromise auditor independence (DeAngelo,
1981; Teng, 2006). Hoitash, Markelevich and
Barragato (2007) argue that any association
between the fees paid to auditors and audit quality
is an important input to the ongoing debate on
how the accounting profession should be organized
and monitored. Following prior studies concerned
with auditor independence, this study uses auditor-
provided non-audit services (NAS) fees and
abnormal NAS fees as measures of auditor
independence (e.g., Craswell, 1999; DeFond,
Raghunandan & Subramanyam, 2002; Frankel,
Johnson & Nelson, 2002; Ashbaugh, LaFond &
Mayhew, 2003; Chung & Kallapur, 2003; Kinney,
Palmrose & Scholz, 2004; Cahan et al., 2008) and
investigates the extent to which those fees are
associated with audit quality in pre- and post-
CLERP 9 periods. Consistent with prior studies
(e.g., Carey & Simnett, 2006; Choi, Kim & Zang,
2006; Chen, Sun & Wu, 2010; Chi, Douthett & Lei,
2010), this study uses the propensity to issue a
going-concern opinion for financially distressed
companies and the absolute value of discretionary
accruals as proxies for audit quality.
Corporate governance failures have reduced
investor confidence and raised questions regarding
the integrity of the information provided to
investors (Jain & Rezaee, 2003; Jain, Kim & Rezaee,
2003; Cohen, Dey & Lys, 2005). The highly
publicized failures triggered the passage of the

Sarbanes Oxley Act (SOX) on 30 July 2002 in the US
and the CLERP 9 Act (2004) on 25 June 2004 in
Australia. Although CLERP 9 introduced sweeping
changes, the implications of the reforms are yet
to be ascertained. Examination of the impact of
the CLERP 9 on NAS fees and their associations
with audit quality will provide evidence of the
effectiveness of regulatory changes.
Effective for the reporting period commencing
on or after 1 July 2004, the CLERP 9 reforms require
the mandatory disclosure of specific categories of
NAS fees, although the NAS fees have been
disclosed in the annual reports for a long period of
time for Australian Securities Exchange (ASX)
listed companies. The Corporations Act 2001 (s300)
requires that the audit committee or, in the absence
of an audit committee, the board of directors is
required to formally attest to their satisfaction that
auditor independence was not compromised by the
provision of NAS. In annual reports, in accordance
with the requirements of s307C of the Corporations
Act 2001, the lead audit partner must state that
there were: (a) no contraventions of the auditor
independence requirements of the Corporations
Act 2001; and (b) no contraventions of any
applicable code of professional conduct in relation
to the audit. CLERP 9 also mandated the rotation
of both the lead and review audit partners every
five years due to concerns about the familiarity
2 S. Hossain

Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
between the auditor and audit clients and their
effects on auditor independence. There is presently
a lack of empirical evidence on the impact of
CLERP 9 on audit quality. Therefore, this study
seeks to provide such evidence.
The results show a significant and positive
association between NAS fees and the propensity
to issue a going-concern opinion for a financially
distressed company post-CLERP 9, but this
association is not significant pre-CLERP 9. The
results indicate that auditors are more likely to issue
a going-concern opinion for a financially distressed
company post-CLERP 9. The results also show a
significant and negative association between
abnormal NAS fees and the propensity to issue a
going-concern opinion for a financially distressed
company pre-CLERP 9, but this association is not
significant post-CLERP 9. Further, the association
between positive abnormal NAS fees and the
propensity to issue a going-concern opinion for a
financially distressed company is stronger pre-
CLERP 9 than post-CLERP 9. The results indicate
that auditors were less likely to issue a going-
concern opinion for a financially distressed
company pre-CLERP 9 than post-CLERP 9 when
auditors earn abnormally high NAS fees.
The association between NAS fees and the
absolute value of performance-adjusted
discretionary accruals is significant and positive

pre-CLERP 9, but this relationship is not significant
post-CLERP 9. The results indicate that auditors
tolerated a larger magnitude of accruals when
they earned higher NAS fees pre-CLERP 9, but
that significant association was mitigated by the
introduction of CLERP 9. Furthermore, abnormal
NAS fees are significantly and positively associated
with the absolute value of discretionary accruals
pre-CLERP 9, but this association is not significant
post-CLERP 9. In addition, the association between
positive abnormal NAS fees and the absolute value
of discretionary accruals is stronger pre-CLERP 9 as
compared to post-CLERP 9. Based on the results of
multiple proxies of auditor independence and audit
quality, the results provide evidence of improved
audit quality after the implementation of CLERP 9.
The results documented in this study make
significant contributions to the literature. Similar
studies have been conducted in the US; however,
the US legislative response (i.e., SOX) is quite
different from that in Australia. Thus, the current
paper address the question: Is the Australian
approach effective? This is an important question
for policy making to achieve an outcome with the
least compliance cost. This study provides evidence
as to whether there is an observable impact from
the CLERP 9 reforms. This has not been examined
in prior Australian studies; therefore, the paper
provides new evidence on the success of the
CLERP 9 approach to addressing problems with

audit practice.
The remainder of the paper is organized as
follows: The next section discusses the background
of the regulatory changes, followed by presentation
of the hypotheses. The fourth section describes the
research method and provides information about
the sample. The findings are reported in the fifth
section, and this is followed by conclusions in the
final section.
REGULATORY CHANGES
During the last decade, corporate collapses
throughout the world have received a great deal
of media attention (Fargher & Jiang, 2006),
questioning the adequacy of regulations to improve
auditor independence and audit quality. Following
these corporate failures, the adequacy of the
Australian regulations that aimed to ensure auditor
independence were questioned, which resulted in a
review of the independence of Australian company
auditors (Fargher & Jiang, 2006). This review
resulted in the publication of the Ramsay Report
in October 2001 (Ramsay, 2001), and subsequently
the CLERP 9 draft was proposed in September
2002. In the US, corporate legislation, SOX (2002),
was passed in response to a series of financial
scandals (Chambers & Payne, 2008). The debates in
the Ramsay Report (2001) and the CLERP 9
proposal focused on the joint provision of audit
and non-audit services (Fargher & Jiang, 2006). To
improve auditor independence and audit quality in

the joint provision of audit and non-audit services,
the Joint Committee of Public Accounts and Audits
(JCPAA, 2002) and the ASX Corporate Governance
Council issued reports on best practice guidelines
for listed companies (ASX, 2003). Australian
reporting entities adopted Australian equivalents
of International Financial Reporting Standards
(IFRS) for the reporting period commencing on or
after 1 January 2005. In annual reports, in
accordance with the requirements of s307C of the
Corporations Act 2001, the lead audit partner has
to declare whether there are: (a) any contraventions
of the auditor independence requirements of the
Corporations Act 2001; and (b) any contraventions
Effect of Regulatory Changes on Auditor Independence and Audit Quality 3
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
of any applicable code of professional conduct in
relation to the audit.
CLERP 9 does not ban any particular NAS
provided by the auditor. However, this Act stresses
that the auditor must identify and evaluate threats to
independence and apply safeguards to reduce any
threats to an acceptable level (Ramsay, 2001). Where
the provision of NAS to a client poses a threat that
cannot be reduced to an acceptable level, CLERP 9
prohibits the provision of that service (Ramsay,
2001). As part of the CLERP 9 reforms, the
Corporation Act 2001 was amended to require the
mandatory disclosure of fees paid for the specific
categories of NAS provided in companies’ annual

reports for the reporting period commencing on or
after 1 July 2004. Moreover, the reforms stipulated
that the financial statements must include a
statement by the audit committee (or board in its
absence) that it is satisfied that the provision of
NAS is compatible with auditor independence
(Corporation Act 2001, s300). This disclosure should
include an explanation of why certain problematic
NAS, such as IT systems services and internal audit
services, if contracted, did not compromise auditor
independence (CLERP 9, 2004).
Regulators and legislators throughout the world
apparently presume that providing NAS impairs
auditor independence, which may lead to lower
audit quality (Kinney et al., 2004). After the
implementation of SOX (2002), most NAS were
banned in the US, and SOX also requires prior
approval by a registrant’s independent audit
committee of any NAS allowed by law (Kinney
et al., 2004). Using pre- and-post SOX data, prior
studies (e.g., Hoitash et al., 2007; Li, 2009) find a
significant association between NAS fees and audit
quality during the pre-SOX period and the
association is not significant post-SOX. In
Australia, CLERP 9 has not banned NAS; however,
both the auditors and the audit committee
(or board in its absence), must declare that
the provision of NAS has not compromised
auditor independence. Therefore, the objective
of the current study is to investigate whether

the implementation of CLERP 9 mitigates the
association between NAS fees and audit quality.
DEVELOPMENT OF HYPOTHESES
Association between auditor-provided NAS
fees and audit quality
The objective of passing CLERP 9 was to improve
auditor independence and audit quality. CLERP 9
and the Corporations Act 2001 require auditors to
sign a declaration in the annual report stating that
the independence of the auditor has not been
compromised due to NAS. The audit committee (or
board in its absence) must also declare that the
external auditor is working without impaired
independence. CLERP 9 does not prohibit
auditor-provided NAS. However, CLERP 9
mandates disclosure of the types of NAS fees in
the annual report. It is expected that non-audit fees
will decrease due to the additional auditing
pronouncements and disclosure of types of NAS
and the prospect of greater regulatory reporting
requirements by companies following those
legislative reforms. In addition, after the
implementation of SOX in 2002, most NAS fees
were banned in the US. Big 4 audit firms applying
the international ruling can have the same effect in
Australia because Big 4 audit firms are international
audit firms and may apply the same policy in
auditing their Australian clients.
Auditor provided non-audit services have long
been regarded as a threat to auditor independence

by the regulators both in Australia and overseas
(Craswell, 1999). Investigating the effect of the
legal and regulatory changes in China, Chen et al.
(2010) find a negative association between client
importance at the audit partner level and modified
opinions during the pre-regulatory change period
and a positive association during the post-
regulatory change period. The findings of Chen
et al. (2010, p. 127) suggest that ‘institutional
improvements prompt auditors to prioritize the
cost of compromising quality over economic
benefits gained from important clients.’ Reynolds
and Francis (2001) find that client importance is
positively associated with the issuance of going
concern reports for Big N clients. Craswell, Stokes
and Laughton (2002) argue that if fee dependence
affects auditors’ independent judgements, then
auditors are less likely to issue qualified audit
opinions. Using Australian data, Craswell (1999)
reports that auditors’ decisions to qualify audit
opinions are not affected by the provision of
non-audit services. Other Australian studies (e.g.,
Wines, 1994) find a significant and negative
association between NAS and qualified opinions
and argue that NAS creates perceptions of
independence problems. In contrast, Barkess and
Simnett (1994) do not find a significant association
between NAS and qualified opinions. Using US
data, Li (2009) finds that client importance is not
significantly associated with the issuance of

4 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
going-concern opinions during the pre-SOX
period, but that there is a positive association
post-SOX. Based on the prior discussion, I expect a
significant positive association between NAS fees
and the propensity to issue going-concern opinions
pre-CLERP 9 and no or a significant negative
association post-CLERP 9. Thus, I propose the
following hypothesis:
H1a: There is a positive association between NAS fees
and the propensity to issue a going-concern opinion
for a financially distressed company post-CLERP 9
but not pre-CLERP 9.
Regulators and legislators apparently presume
that auditor-provided non-audit services impair
auditor independence, which leads to lower quality
audits (Kinney et al., 2004). The findings of prior
studies regarding the associations between NAS
fees and earnings management-based audit
quality measures are mixed. Frankel et al. (2002)
hypothesized that NAS increases the economic
bonding between auditors and clients and
therefore impairs auditor independence. Cahan
et al. (2008) argue that faster growth and longer
time period over which non-audit services are
purchased from auditors may reduce auditor’s
independence. However, they did not find any
support of a relationship between fee growth rates
and length of purchasing non-audit services and

discretionary accruals. Studies by Krishnan, Sami
and Zhang (2005) and Francis and Ke (2006) find
lower earnings response coefficients for firms
paying higher NAS fees. Ferguson, Seow and
Young (2004) find that client importance is
positively associated with the absolute value of
abnormal accruals. Ghosh, Kallapur and Moon
(2009) find that client importance is negatively
associated with earnings response coefficients.
Using pre- and-post SOX data, Hoitash et al. (2007)
find a significant and positive association between
NAS fees and discretionary accruals pre-SOX and
no significant association post-SOX.
In contrast, Reynolds and Francis (2001) find that
client importance is negatively associated with the
absolute value of abnormal accruals. The intention
of regulatory changes is to improve the quality of
financial statement audits and audit quality, which
will also influence earnings reliability (Chambers
& Payne, 2008). In Australia, effective after 1 July
2006, lead audit partner rotation was mandated
(Fargher & Jiang, 2008), and this new mechanism of
mandating audit partner rotation has given audit
standards legislative backing (Carey & Simnett,
2006). The reforms also included proportionate
liability for auditors and claims capping, which
provided auditors with some certainty on liability
claims (Fargher & Jiang, 2008). This could well
affect auditor behaviour regarding earnings quality
measures. As reduced earnings management is

used as one of the indicators of improved audit
quality (Wong, Jubb & Chalmers, 2007) vis-à-vis
financial reporting quality (see Becker et al., 1998)
and audit quality is affected by independence, it
follows that if the implementation of CLERP 9
increased auditor independence, it may have
consequently improved earnings management-
based measures of financial reporting quality.
Therefore, I expect a significant positive association
between NAS fees and the absolute value of
performance-adjusted discretionary accruals
pre-CLERP 9 and no or a significant negative
association post-CLERP 9. Thus, I propose the
following hypothesis:
H1b: There is a positive association between NAS
fees and the absolute value of discretionary accruals
pre-CLERP 9 but not post-CLERP 9.
Association between abnormal NAS fees and
audit quality
The objectivity and independence of auditors is
more likely to be influenced by the level of client
fees in excess of the auditor’s expectation of normal
fees, i.e., abnormal fees, rather than expected fees
(Choi et al., 2006). Choi et al. (2006) argue that when
an auditor earns more than the expected level of
NAS fees, the perceived net benefits become
greater than the associated costs, which increases
economic bonding and may decrease audit quality.
Kinney and Libby (2002) argue that strong
economic bonding between the auditor and the

client will reduce the quality of the reported
earnings through the auditor’s reduced willingness
to resist client-induced biases in reported
accounting information. Auditors may also be
reluctant to issue a going-concern opinion due to
the possibility of losing the client. Using pre- and
post-SOX data, Hoitash et al. (2007) find a
significant positive association between abnormal
NAS fees and accruals pre-SOX and no significant
association post-SOX. Hoitash et al. (2007) provide
evidence consistent with the view that clients with
higher abnormal NAS fees may have more
influence on auditors’ decisions that lead to
impaired auditor independence. Choi et al. (2006)
Effect of Regulatory Changes on Auditor Independence and Audit Quality 5
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
suggest that auditors’ incentives to compromise
audit quality differ depending on whether the
client pays more than or less than the normal level
of fees, which, in turn, leads to the audit fee–audit
quality association being based on the sign of
abnormal audit fees. Thus, I propose the following
hypotheses:
H2a: There is a negative association between
abnormal NAS fees and the propensity to issue a
going-concern opinion for a financially distressed
company pre-CLERP 9 but not post-CLERP 9.
H2b: There is a positive association between
abnormal NAS fees and the absolute value of
discretionary accruals pre-CLERP 9 but not

post-CLERP 9.
RESEARCH METHOD
Measurement of abnormal NAS fees
Following the procedures of Choi et al. (2006) and
Hoitash et al. (2007) of decomposing fees into two
components, namely the expected component
(normal fees) and the abnormal component
(abnormal fees), it is necessary to specify an
expectation model linking actual fees with their
determinants. On the basis of economic bonds,
client size, client complexity and client-specific
risk from prior studies (e.g. Simunic, 1980;
Francis & Stokes, 1986; Craswell et al., 1995;
DeFond et al., 2002; Frankel et al., 2002; Whisenant
et al., 2003; Choi et al., 2006; Hay et al., 2006) and
independence measures reported by Ashbaugh
et al. (2003) and Ruddock, Taylor and Taylor
(2006), this study uses the following ordinary
least squares (OLS) model to calculate abnormal
NAS fees for each year separately. The abnormal
NAS fees are the residuals of the estimated
model:
LnNAS LnTA B IG EQUITY
MERGACQS ROA LEVERAG
=+ + +
+++
ββ β β
βββ
01 2 3
456

4
EE
NEG_ROA GROWTH MB
LnSUBS FOROPS USLIST
+++
++ +
+
βββ
ββ β
β
789
10 11 12
113
INDUSTRY
∑
+
ε
(1)
where
LnNAS = natural log of auditor-provided non-audit
services fees;
1
Control variables
LnTA = natural log of total assets;
BIG4 = 1 if the audit firm is a Big 4 firm, 0
otherwise;
EQUITY = 1 if the company issued new shares in
the current year, 0 otherwise;
MERGACQS = 1 if the company has merger or
acquisition activities during the current year, 0

otherwise;
ROA = earnings before interest and taxes divided
by total assets;
LEVERAGE = total liabilities divided by total
assets;
NEG_ROA = 1 if the company reports a negative
return on assets in the current year, 0 otherwise;
GROWTH = change of assets from prior year;
MB = market-to-book value;
LnSUBS = natural log of number of subsidiaries;
FOROPS = 1 if the company has any foreign
subsidiaries, 0 otherwise;
USLIST = 1 if the company is cross-listed in the US,
0 otherwise;
∑INDUSTRY = there are 10 indicator variables for
11 Global Industry Classification Standard
(GICS) industry groups.
Definitions of the variables are provided in the
Appendix for ease of reference. The natural log of
total assets (LnTA) is used as a proxy for client size.
Demand for non-audit services is likely to increase
with firm size (Palmrose, 1986; Raghunandan et al.,
2003) and, therefore, it is expected that NAS fees
are positively associated with LnTA. Non-audit
services fees are likely to be higher for clients with
more complex business operations (Raghunandan
et al., 2003). LnSUBS, MERGACQS and FOROPS
are used to proxy for client complexity, and it is
expected that the variables representing client
complexity are positively associated with NAS

fees. NEG_ROA, LEVERAGE and ROA are used to
proxy for a client’s risk characteristics. Since an
auditor charges higher fees for riskier clients
(Simunic & Stein, 1996), the coefficients of
NEG_ROA and LEVERAGE are expected to be
positive and that of ROA to be negative. The
control variable, BIG4, is used to capture the
capacity of providing non-audit services and a
positive coefficient is expected with NAS fees. The
demand for non-audit services is greater for
high-growth firms than low-growth firms (Choi &
Wong, 2006). EQUITY, GROWTH and MB are used
to capture the effect of a client firm’s growth on
NAS fees, and positive associations with fees for
EQUITY, GROWTH and a negative association
6 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
with MB are expected. A control variable for the
US cross-listing (USLIST) is used owing to the
additional requirements in US regulations. Similar
to Ashbaugh et al. (2003) and Ruddock et al. (2006),
this study uses industry dummies to control for
cross-industry differences in fees. INDUSTRY is an
indicator variable equal to 1 if the company belongs
to an appropriate industry group, 0 otherwise.
Audit opinion model
The following logistic regression model is
estimated for the pre- and-post-CLERP 9 periods to
test the association between NAS fees, abnormal
NAS fees and the propensity to issue a

going-concern opinion for a financially distressed
company after controlling for the variables used by
Carey and Simnett (2006):
OPINION LnFEE PQUAL PBANK
LnTA LnAGE LEVERA
=+ + +
++ +
ββ β β
ββ β
01 2 3
45 6
GGE
CLEVERAGE ROA LLOSS
INVESTMENTS BIG
CF
+++
++
+
βββ
ββ
β
789
10 11
12
4
OO MINING++
βε
13
(2)
where

Dependent variable
OPINION = OPINION is coded as 1 if an auditor
issues a going-concern opinion for a financially
distressed company in the current year and as 0
otherwise;
Experimental variable
FEE = alternative measures of fees, such as: LnNAS
is the natural log of auditor-provided non-audit
services fees;
2
ABNAS fees are estimated from the
residuals of the LnNAS fee model (Equation 1);
Control variables
PQUAL = 1 if the auditor issued an opinion other
than an unqualified one in the previous year, 0
otherwise;
PBANK = probability of bankruptcy, as measured
by adjusted Zmijeswki score;
3
LnAGE = natural log of number of years the
company has been listed on the Australian
Securities Exchange (ASX);
CLEVERAGE = change in leverage during the year;
LLOSS = 1 if the client reported a loss in the
previous year, 0 otherwise;
INVESTMENTS = short- and long-term investment
securities (measured as current assets minus
debtors and inventory) divided by total assets;
CFO =operating cash flow deflated by total assets;
MINING = 1 if the company belongs to the mining

industry, 0 otherwise;
e=error term.
All other variables are as defined in Equation (1).
Prior year opinion (PQUAL) is a good predictor
of the current year’s opinion because the
going-concern problems may continue for a longer
period (Monroe & Teh, 1993). Higher values of
PBANK indicate a higher probability of
bankruptcy (Carey & Simnett, 2006). LnTA is
included because larger companies are less likely
to end up in bankruptcy, due to their financial
stability and greater negotiating power (Carey &
Simnett, 2006). LnAGE is controlled because
younger companies are more likely to encounter
financial distress (Carey & Simnett, 2006). Similar
to Carey and Simnett (2006), I use LEVERAGE and
CLEVERAGE to control for the risk of insolvency.
ROA and LLOSS capture the profitability of the
companies, as companies incurring a loss are more
likely to receive a going-concern opinion (Carey &
Simnett, 2006). CFO and INVESTMENTS proxy
for the liquidity risk of a company, and a liquidity
crisis may end in bankruptcy (Carey & Simnett,
2006). BIG4 is included in order to differentiate
the propensity of issuing going-concern opinions
by Big 4 and non-Big 4 audit firms. MINING is
controlled because the sample includes a large
number of mining companies, which have different
financial characteristics (Butterworth & Houghton,
1995; Carey & Simnett, 2006).

Earnings management model
Similar to Kothari, Leone and Wasley (2005), this
study estimates non-discretionary accruals using
the performance-adjusted modified Jones (1991)
model, and estimates abnormal accruals as the
residuals from the model. Subject to a minimum of
10 observations (excluding financial sector 40) in
each industry category for each year, this model is
estimated cross-sectionally for each two-digit GICS
(a six-digit for the Metals & Mining sector) industry
group in each of the years 2002–2007 as follows:
TACC REV REC
PPE LagROA
=+ −
()
++ +
αβ
ββ ε
1
23
ΔΔ
(3)
where
TACC = total accruals, being the difference
between operating income (OI) and cash flow
from operations;
DREV = change in revenues from period t - 1to
period t;
Effect of Regulatory Changes on Auditor Independence and Audit Quality 7
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd

DREC = change in accounts receivables from period
t - 1 to period t;
PPE = gross value of property, plants and
equipment;
LagROA = one-year lag of ROA;
e=error terms.
All variables, including the intercept (other than
LagROA), are scaled by the lagged total assets.
The model for examining the
association between test variables and
earnings management
This study uses the following model to examine the
association between NAS fees, abnormal NAS fees
and the absolute value of performance-adjusted
discretionary accruals for the pre- and post-CLERP
9 periods after controlling for the variables used in
Carey and Simnett (2006):
DACC LnFEE BIG PBANK
OPINION LnTA LEVERAGE
=+ + +
+++
αβ β β
βββ
14
123
456
++++
++++
βββ
βββε

789
10 11 12
LLOSS ROA LnAGE
GROWTH CF O MINING
(4)
where
Dependent variable
DACC = discretionary accruals estimated from the
residuals of Equation (3);
Experimental variable
FEE = alternative measures of fees, such as: LnNAS
is the natural log of auditor-provided non-audit
services fees; ABNAS fees is estimated from the
residuals of the LnNAS fee model;
Control variables
OPINION = 1 if the company has a modified
opinion during the current year, 0 otherwise;
All other variables are defined in Equations (1) and
(2).
Consistent with the arguments of Carey and
Simnett (2006), a number of variables (BIG4,
PBANK, OPINION, LnTA, LEVERAGE, LLOSS,
ROA, LnAGE, CFO, MINING) used in predicting
the propensity to issue a going-concern opinion are
expected to be associated with the level of
discretionary accruals. GROWTH is controlled for
changes in a company’s financial position and their
association with discretionary accruals.
Sample selection
CLERP 9 (2004) was enacted on 30 June 2004.

Hence, the first reflection of CLERP 9 is seen in
the annual reports prepared for the financial
period 2004–05. Therefore, this study uses data
from 2002, 2003, 2004 and balance dates between 1
January and 29 June 2005 for the pre-CLERP 9
and 2005 (balance date on 30 June), 2006 and 2007
for the post-CLERP 9. Data were collected up to
2007 because of the Global Financial Crisis in
2008, which might affect the results. The initial
sample consists of 9,736 firm-year observations
whose financial data were available in Aspect’s
FinAnalysis database for fiscal years from 2002 to
2007. NAS fees and audit opinions data were
hand-collected directly from the annual reports.
Consistent with Carey and Simnett (2006), the
sample for the audit opinion model is restricted
to financially distressed companies only. I
identified financially distressed companies based
on either the company reporting a loss or a
negative cash flow from operations during a
given year. The sample size is further reduced
because of data requirements for predicting the
type of audit opinions. The final sample consists
of 4,961 firm-year observations for the OPINION
model.
The sample of discretionary accruals models was
derived after excluding financial sector (GICS 40)
and data requirements for estimating discretionary
accruals. The final sample is 6,656 firm-year
observations for the DACC model. Table 1 shows

how the sample sizes are derived for this study.
Table 2 shows the industry representation of the
sample companies. The current study uses a two-
digit GICS code (a six-digit code for Metals &
Mining). There are 11 industry groups. Similar to
prior studies (e.g., Coulton, Taylor & Taylor, 2005),
the current study also excludes industry groups
for a particular year if the group has fewer than
10 companies when estimating discretionary
accruals.
Table 1: Sample selection (2002–2007)
Firm-year observations
OPINION DACC
Initial sample 9,736 9,736
Financial (4010 to 4040) – 563
Missing data and data
not available
1,712 2,517
Non-distressed
companies
3,063
Final sample 4,961 6,656
8 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
DATA ANALYSIS AND DISCUSSION
OPINION
Descriptive statistics
Table 3 shows the descriptive statistics for the
sample. The average size of the sample companies
pre-CLERP 9 was $610.464 million and

post-CLERP 9 the average size was $1,142.609
million and the difference is significant. The
average NAS fees are higher pre-CLERP 9
($128,812.616) than post-CLERP 9 ($67,502.291)
and the difference is significant. Other than LLOSS
and PQAUL, mean differences for all the control
variables are significantly different between the
pre-CLERP 9 and the post-CLERP 9 periods. The
maximum VIF value is 2.708, indicating that
multicollinearity is not a significant concern.
Association between NAS fees and OPINION
Table 4 provides the logistic regression results for
the association between NAS fees and the
propensity to issue a going-concern opinion for a
financially distressed company during the pre- and
post-CLERP 9. Consistent with Carey and Simnett
(2006), the sample is restricted to financially
distressed companies. The model is well-fitted with
pseudo R
2
s ranging from 0.239 to 0.252. The results
(Table 4, columns 2 and 3) show that the association
between the LnNAS fees and the propensity to
issue a going-concern opinion for a financially
distressed company is significant and positive
post-CLERP 9 (coefficient = 0.049, p = 0.006)
(one-tailed) and is not significant pre-CLERP 9
(coefficient =-0.021, p = 0.104). The findings
indicate that auditors are more likely to issue a
going-concern opinion for a financially distressed

company post-CLERP 9 when providing NAS
fees. This finding is consistent with the US study
by Li (2009), who finds that client importance is
not significantly associated with the issuance
of going-concern opinions pre-SOX, but that
association is significant and positive post-SOX.
The significant association between LnNAS
fees indicates the improvement of auditor
independence and audit quality post-CLERP 9.
Auditors earning more than the expected
level of NAS fees may compromise audit quality.
To test whether the association between abnormal
NAS fees and the propensity to issue
going-concern opinions remained the same before
and after the implementation of CLERP 9, this
study estimated abnormal NAS fees based on
the NAS fee model (Equation 1). Table 4 (columns
4 and 5) shows that the association between
the signed abnormal NAS fees is significantly
and negatively associated (coefficient =-0.036,
p = 0.005) with OPINION pre-CLERP 9, but is not
significant (coefficient = 0.017, p = 0.196) post-
CLERP 9. A separate analysis (not tabulated)
shows that the association between positive
abnormal NAS fees and OPINION is significant
and negative (coefficient =-0.090, p = 0.003) and
stronger pre-CLERP 9 than post-CLERP 9
(coefficient =-0.173, p = 0.040). These findings also
indicate that auditor independence and audit
Table 2: Industry representation of the sample companies (2002–2007)

Industry Group (GICS code) OPINION DACC
Firm-year
observations
Per cent Firm-year
observations
Per cent
1 Energy (10) 491 9.90 628 9.42
2 Materials (15) 57 1.15 180 2.70
3 Industrial (20) 384 7.74 946 14.19
4 Consumer Discretionary (25) 332 6.69 876 13.14
5 Consumer Staples (30) 138 2.78 290 4.35
6 Healthcare (35) 581 11.71 723 10.85
7 Financials (40) 563 11.35
8 Information Technology (45) 474 9.55 695 10.43
9 Telecommunication Services (50) 120 2.42 163 2.45
10 Utilities (55) 60 1.21 106 1.59
11 Metals and Mining (151040) 1,761 35.50 2058 30.88
Total 4,961 100.00 6,656 100.00
Two-digit GICS industry classification (6-digit for Metals & Mining)
Effect of Regulatory Changes on Auditor Independence and Audit Quality 9
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
Table 3: Descriptive statistics for the OPINION model (2002–2007)
Variables Pre-CLERP 9 Post-CLERP 9
t-statistics p-value VIF
(n = 2,192) (n = 2,769)
Mean Median Std. deviation Mean Median Std. deviation
TA ($M) 610.464 9,388 12,340.889 1,142.609 11.879 19,778.128 5.870 <0.001
NAS 128,812.616 9,000.000 2,136,337.525 67,502.291 5,159.500 406,373.659 18.452 <0.001
AGE 12.002 10.000 8.689 12.116 9.000 9.735 2.911 0.004
LnNAS 7.212 9.105 4.561 6.420 8.618 4.836 4.362 <0.001 2.450

ABNAS 0.261 0.000 0.439 0.225 0.000 0.418 -6.167 <0.001 1.825
OPINION 0.201 0.000 0.401 0.195 0.000 0.396 0.535 0.593 –
PQUAL 0.261 0.000 0.439 0.225 0.000 0.418 1.442 0.149 1.211
PBANK -1.157 -2.612 11.917 -2.284 -3.128 5.825 -17.168 <0.001 2.590
LnTA 16.145 16.055 1.843 16.473 16.290 1.877 -2.962 0.003 2.613
LnAGE 2.208 2.303 0.785 2.174 2.197 0.835 -2.161 0.031 1.052
LEVERAGE 0.613 0.236 2.739 0.360 0.436 0.922 7.952 <0.001 1.035
CLEVERAGE 1.384 0.036 2.689 1.420 0.235 3.941 -7.385 <0.001 1.004
ROA -0.468 -0.163 1.741 -0.389 -0.153 0.723 8.484 <0.001 2.708
LLOSS 0.874 1.000 0.332 0.788 1.000 0.409 -0.190 0.849 1.643
INVESTMENTS 0.309 0.204 0.301 0.372 0.282 0.304 -3.264 0.001 1.335
BIG4 0.536 1.000 0.499 0.415 0.000 0.493 5.870 <0.001 1.225
CFO -0.261 -0.113 0.740 -0.257 -0.104 0.476 18.452 <0.001 1.291
MININIG 0.329 0.000 0.470 0.374 0.000 0.484 2.911 0.004 1.169
Two-tailed p-value.
TA = total assets in million dollars; NAS = non-audit services fees; AGE = number of years that the company has been listed in ASX;
LnNAS = natural log of auditor-provided non-audit service fees; ABNAS = abnormal NAS fees; OPINION = 1 if the auditor issues a going-concern
opinion for a financially distressed company in the current year, 0 otherwise; PQUAL = 1 if the auditor has issued an other than unqualified opinion
in the previous years, 0 otherwise; PBANK = probability of bankruptcy, as measured by adjusted Zmijeswki score; LnTA = natural log of total
assets, which is used to measure the size of the entity; LnAGE = natural log of number of years that the company has been listed in ASX;
LEVERAGE = ratio of total liabilities to total assets; CLEVERAGE = change in leverage from the previous period; ROA = operating income divided
by average total assets; LLOSS = 1 if the company reported a loss in the previous year and 0 otherwise; INVETMENTS = short- and long-term
investment securities (measured as current assets minus debtors and inventory) divided by total assets; BIG4 = 1 if the firm’s auditor is a Big 4 firm
and 0 otherwise; CFO = operating cash flow deflated by total assets; 1 if the company belongs to the mining industry, 0 otherwise; MINING = 1if
the company belongs to the mining industry, 0 otherwise.
10 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
Table 4: Association between NAS fees, abnormal NAS fees and OPINION
Variables NAS fees Abnormal NAS fees
Pre-CLERP 9 Post-CLERP 9 Pre-CLERP 9 Post-CLERP 9

(2) (3) (4) (5)
Coefficient Coefficient Coefficient Coefficient
(Z-statistics) (Z-statistics) (Z-statistics) (Z-statistics)
LnNAS -0.021 0.049***
(-1.260) (2.520)
ABNAS -0.036*** 0.017
(-2.570) (0.860)
PQUAL 2.074*** 1.963*** 2.071*** 1.974***
(16.270) (16.220) (16.220) (16.330)
PBANK 0.024** 0.028** 0.024** 0.030**
(2.320) (2.070) (2.270) (2.180)
LnTA -0.120** -0.177*** -0.118** -0.150***
(-2.240) (-3.620) (-2.340) (-3.110)
LnAGE 0.123 -0.024 0.119 -0.023
(1.470) (-0.320) (1.420) (-0.310)
LEVERAGE -0.025 -0.002 -0.024 -0.002
(-1.110) (-0.340) (-1.090) (-0.390)
CLEVERAGE -0.015 -0.001 -0.014 -0.001
(-1.360) (-0.620) (-1.290) (-0.640)
ROA -0.153 -0.099 -0.156 -0.101
(-1.380) (-0.850) (-1.400) (
-0.870)
LLOSS 0.356 0.657*** 0.372* 0.643***
(1.580) (3.690) (1.650) (3.620)
INVESTMENTS -1.350*** -1.817*** -1.332*** -1.812***
(-5.200) (-8.080) (-5.120) (-8.070)
BIG4 -0.270** -0.183 -0.266** -0.157
(-2.070) (-1.440) (-2.040) (-1.230)
CFO -0.007 -0.319** -0.013 -0.331**
(-0.050) (-2.120) (-0.090) (-2.200)

MININIG -0.120 -0.317** -0.111 -0.355***
(-0.880) (-2.540) (-0.820) (-2.860)
_cons -0.193 0.917 -0.331 0.685
(-0.210) (1.060) (-0.360) (0.790)
N 2,192 2,769 2,192 2,769
LR c
2
(13) 525.600 687.340 530.620 681.700
Prob > c
2
0.000 0.000 0.000 0.000
Pseudo R
2
0.239 0.252 0.241 0.250
***, **, and * indicate significance at the 1, 5, and 10 per cent levels, respectively.
OPINION = 1 if the auditor issues a going-concern opinion for a financially distressed company in the current
year, 0 otherwise; LnNAS = natural log of auditor-provided non-audit service fees; ABNAS = abnormal NAS
fees; PQUAL = 1 if the auditor has issued an other than unqualified opinion in the previous years, 0 otherwise;
PBANK = probability of bankruptcy, as measured by adjusted Zmijeswki score; LnTA = natural log of total
assets, which is used to measure the size of the entity; LnAGE = natural log of number of years that the company
has been listed in ASX; LEVERAGE = ratio of total liabilities to total assets; CLEVERAGE = change in leverage
from the previous period; ROA = operating income divided by average total assets; LLOSS = 1 if the company
reported a loss in the previous year, 0 otherwise; INVETMENTS = short- and long-term investment securities
(measured as current assets minus debtors and inventory) divided by total assets; BIG4 = 1 if the firm’s auditor
is a Big 4 firm, and 0 otherwise; CFO = operating cash flow deflated by total assets; 1 if the company belongs to
the mining industry, 0 otherwise; MINING = 1 if the company belongs to the mining industry, 0 otherwise.
Effect of Regulatory Changes on Auditor Independence and Audit Quality 11
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
quality improved after the implementation of
CLERP 9.

A number of control variables are significantly
associated with OPINION. In the pre-CLERP 9
period, PQUAL (p < 0.001) and PBANK (p = 0.020)
are positively associated with OPINION. In
the post-CLERP 9 period, PQUAL (p < 0.001),
PBANK (p = 0.026) and LLOSS (p < 0.001)
are positively associated with OPINION.
Alternatively, in the pre-CLERP 9 period, LnTA
(p = 0.025), INVESTMENTS (p < 0.001) and BIG4
(p = 0.039) are negatively associated with
OPINION. In the post-CLERP 9 period, LnTA
(p < 0.001), INVESTMENTS (p < 0.001), CFO
(p = 0.034) and MINING (p = 0.011) are negatively
associated with OPINION. All other control
variables are not significantly associated with
OPINION.
Sensitivity analyses
To test the association between NAS fees and
OPINION for all the sample companies, regardless
of whether they are financially distressed, I ran
a separate regression (Equation 2) including
companies that are not financially distressed. The
results (not tabulated) show that NAS fees are
weakly and positively associated with OPINION
post-CLERP 9 (p = 0.097), but this association is not
significant pre-CLERP 9 (p = 0.213). The results are
robust, regardless of whether financially distressed
and non-distressed companies are included in the
sample.
There are concerns that mining companies are

more vulnerable and may have more going-
concern opinions, and around 35 per cent of the
sample is mining companies. Therefore, I also ran
a regression (Equation 2) after excluding mining
companies. The results are qualitatively the same as
those reported earlier (p = 0.510 pre-CLERP 9 and
p = 0.016 post-CLERP 9).
Consistent with Ruddock et al. (2006), I excluded
‘zero NAS’ observations (around 30 per cent) and
estimated Equation (2). The results (not tabulated)
are qualitatively similar for the associations
between NAS fees and OPINION (pre-CLERP 9:
n = 1,580, p = 0.458 and post-CLERP 9: n = 1,781,
p = 0.048). The results are also consistent for
abnormal NAS fees and OPINION, pre-CLERP 9,
the association is significant and negative (n =
1,580, p = 0.001) and post-CLERP 9, the association
is marginally significant and negative (n = 1,781,
p = 0.078).
Discretionary accruals
Descriptive statistics
Table 5 reports the descriptive statistics for the
variables in the DACC model. The means of
TACC and LTACC are almost same during the
pre-CLERP 9 (-0.088 and -0.093) and post-CLERP
9(-0.074 and -0.067). DACC is significantly
different in the pre- and post-CLERP 9 periods
(-0.091 and -0.070 respectively), and for the
same periods, the mean difference of ABSDACC
is also significantly different (0.097 and 0.083

respectively).
4
Association between NAS fees and
discretionary accruals
The regression results of the association between
NAS fees and discretionary accruals are
summarised in Table 6. The model is well-
fitted, with adjusted-R
2
s ranging from 0.226 to
0.332. The results (Table 6, columns 2 and 3)
indicate a significant and positive association
(coefficient = 0.001, p = 0.005) between NAS fees
and the absolute value of discretionary accruals
(ABSDACC) pre-CLERP 9, but not significant
post-CLERP 9 (coefficient = 0.000, p = 0.182)
(one-tailed). A significant and positive association
between LnNAS fees and ABSDACC indicates that
auditors earning higher non-audit services fees
tolerate a larger magnitude of absolute values of
discretionary accruals. The fact that the association
is significant pre-CLERP 9 and not significant
post-CLERP 9 indicates that audit quality improved
after the regulatory changes.
Earning abnormal NAS fees may make auditors
more dependent on clients, and thus they may
become more tolerant of higher accruals. Table 6
(columns 4 and 5) shows that abnormal NAS
fees are significantly and positively associated
with ABSDACC pre-CLERP 9 (coefficient = 0.002,

p < 0.001), but that they are not significant
post-CLERP 9 (coefficient = 0.001, p = 0.168). The
association between positive abnormal NAS fees
and ABSDACC (not tabulated) is stronger
pre-CLERP 9 (coefficient = 0.005, p < 0.001) than
post-CLERP 9 (coefficient = 0.003, p = 0.091). The
results also provide evidence of improved auditor
independence and audit quality after the
implementation of CLERP 9.
A number of control variables are significantly
associated with ABSDACC. During the pre-CLERP
9 period, BIG4 (p = 0.065), PBANK (p = 0.011),
12 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
OPINION (p < 0.001) and LLOSS (p = 0.003) are
significantly and positively associated with
ABSDACC. During the post-CLERP 9 period, BIG4
(p = 0.021), LLOSS (p < 0.001) and GROWTH
(p < 0.001) are significantly and positively
associated with ABSDACC. Conversely, during the
pre-CLERP 9, LnTA (p < 0.001) and LEVERAGE
(p < 0.001) are negatively associated with
ABSDACC. PBANK (p < 0.001), LnTA (p < 0.001),
LEVERAGE (p < 0.001), ROA (p < 0.001) and CFO
(p = 0.001) are negatively associated with
ABSDACC.
Sensitivity analysis
To test whether the association between NAS
fees and ABSDACC for the financial distressed
sample is consistent with the full sample, I

re-ran Equation (4) with only financially distressed
firms in the sample. The results (not tabulated)
show that NAS fees are significantly and
positively associated pre-CLERP 9 (p = 0.009),
but are not significant post-CLERP 9 (p = 0.809).
The results are consistent with those reported
earlier.
Table 5: Descriptive statistics for the DACC model (2002–007)
Variables Pre-CLERP 9 Post-CLERP 9 t-stat p-value
(n = 2,983) (n = 3,673)
Mean Median Std. deviation Mean Median Std. deviation
TACC -0.088 -0.049 0.334 -0.074 -0.029 0.283 -1.504 0.133
LTACC -0.093 -0.039 0.229 -0.067 -0.023 0.214 -3.279 0.001
1/TA 0.000 0.000 0.000 0.000 0.000 0.000 -1.096 0.273
DREV – DREC 0.047 0.013 0.387 0.054 0.020 0.458 0.314 0.754
PPE 0.247 0.142 0.271 0.338 0.188 0.384 -6.924 <0.001
LAGROA -0.147 -0.046 0.340 -0.174 -0.056 0.449 5.402 <0.001
DACC -0.091 -0.090 0.079 -0.070 -0.066 0.084 -4.099 <0.001
ABSDACC 0.097 0.091 0.071 0.083 0.068 0.071 5.199 <0.001
LnNAS 8.137 9.628 4.572 7.430 9.350 4.860 6.613 <0.001
BIG4 0.605 1.000 0.489 0.511 1.000 0.500 8.390 <0.001
PBANK -1.681 -2.746 10.117 -2.510 -3.007 4.857 4.536 <0.001
OPINION 0.186 0.000 0.389 0.169 0.000 0.375 0.188 0.851
LnTA 16.989 16.698 2.210 17.194 16.866 2.187 -4.371 <0.001
LEVERAGE 0.555 0.352 2.209 3.464 0.513 4.534 -16.533 <0.001
LLOSS 0.611 1.000 0.488 0.599 1.000 0.490 5.595 <
0.001
ROA -0.286 -0.050 1.504 -0.242 -0.064 0.658 -1.616 0.106
LnAGE 2.261 2.303 0.816 2.248 2.303 0.856 1.493 0.135
GROWTH 1.991 0.073 12.887 1.966 0.160 15.337 0.744 0.457

CFO -0.131 -0.025 0.649 -0.137 -0.036 0.443 0.291 0.771
MININIG 0.289 0.000 0.454 0.323 0.000 0.468 -3.671 <0.001
Two-tailed p-values.
TACC = total accrual is the difference between operating income (OI) and cash flow from operations scaled by
total assets; LTACC = lag of total accruals scaled by lag total assets; 1/TA = 1 divided by total assets;
DREV = change in revenues from period t–1 to period t; DREC = change in accounts receivables from period t–1
to period t; PPE = gross value of property, plants, and equipment scaled by total assets; LAGROA = one year lag
of ROA; DACC = discretionary accruals; ABSDACC = absolute value of discretionary accruals; LnNAS = natural
log of auditor-provided non-audit service fees; BIG4 = 1 if the firm’s auditor is a Big 4 firm, 0 otherwise;
PBANK = probability of bankruptcy, as measured by adjusted Zmijeswki score; OPINION = 1 if an auditor has
issued a going-concern opinion for a financially distressed company, 0 otherwise; LnTA = natural log of total
assets, which is used to measure the size of the entity; LEVERAGE = ratio of total liabilities to total assets;
LLOSS = 1 if the company reported a loss in the previous year, 0 otherwise; ROA = operating income divided by
average total assets; LnAGE = natural log of number of years that the company has been listed in ASX;
GROWTH = change in assets from the prior year; CFO = operating cash flow deflated by total assets; 1 if the
company belongs to the mining industry, 0 otherwise; MINING = 1 if the company belongs to the mining
industry, 0 otherwise.
Effect of Regulatory Changes on Auditor Independence and Audit Quality 13
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
The accruals model may be sensitive to the
inclusion or exclusion of mining companies due to
the vulnerability of their financial conditions and
around 35 per cent of the sample is mining
companies. Therefore, after excluding mining
companies, I re-ran Equation (4). The results are
consistent with the main results (p < 0.001
pre-CLERP 9 and p = 0.245 post-CLERP 9).
Further, I excluded ‘zero NAS’ observations and
re-ran Equation (4). The results are qualitatively
Table 6: Association between NAS fees and ABSDACC

Variables NAS fees Abnormal NAS fees
Pre-CLERP 9 Post-CLERP 9 Pre-CLERP 9 Post-CLERP 9
(2) (3) (4) (5)
Coefficient Coefficient Coefficient Coefficient
(t-statistics) (t-statistics) (t-statistics) (t-statistics)
LnNAS 0.001*** 0.000
(3.390) (1.350)
ABNAS 0.002*** 0.001
(4.740) (1.380)
BIG4 0.008*** 0.006*** 0.006* 0.007**
(2.990) (2.720) (1.850) (2.480)
PBANK 0.000** -0.002*** 0.001*** -0.002***
(2.060) (-7.690) (2.650) (-6.720)
OPINION 0.016*** 0.007** 0.015*** 0.004
(4.470) (2.480) (3.850) (1.200)
LnTA -0.010*** -0.006*** -0.013*** -0.009***
(-12.860) (-8.010) (-11.480) (-8.370)
LEVERAGE -0.002*** -0.001*** -0.002*** -0.001***
(-3.560) (-6.270) (-3.760) (-6.460)
LLOSS 0.022*** 0.040*** 0.014*** 0.041***
(7.490) (15.750) (2.710) (10.990)
ROA -0.003** -0.025*** -0.001 -0.022***
(-2.010) (-9.430) (-0.540) (-7.330)
LnAGE 0.000 0.000 0.002 0.002
(-0.050) (-0.430) (0.940) (1.320)
GROWTH 0.000 0.005*** 0.000 0.005***
(-0.480) (10.470) (-0.380) (8.850)
CFO -
0.003 -0.016*** 0.000 -0.013***
(-1.340) (-4.820) (-0.200) (-3.470)

MINING 0.010*** 0.002 0.003 0.000
(3.610) (0.740) (0.980) (-0.070)
_cons 0.241*** 0.133*** 0.296*** 0.191***
(17.290) (10.950) (14.670) (10.060)
N 2,983 3,673 2,983 3,673
F(13, 1941) 24.340 55.090 25.730 55.200
Prob > c
2
0.000 0.000 0.000 0.000
Adjusted R
2
0.226 0.332 0.226 0.331
***, **, and * indicate significance at the 1, 5, and 10 per cent levels, respectively.
ABSDACC = absolute value of discretionary accruals; LnNAS = natural log of auditor-provided non-audit
service fees; ABNAS = abnormal NAS fees; BIG4 = 1 if the firm’s auditor is a Big 4 firm, 0 otherwise;
PBANK = probability of bankruptcy, as measured by adjusted Zmijeswki score; OPINION = 1 if an auditor has
issued a going-concern opinion for a financially distressed company, 0 otherwise; LnTA = natural log of total
assets, which is used to measure the size of the entity; LEVERAGE = ratio of total liabilities to total assets;
LLOSS = 1 if the company reported a loss in the previous year, 0 otherwise; ROA = operating income divided by
average total assets; LnAGE = natural log of the number of years that the company has been listed in ASX;
GROWTH = change in assets from the prior year; CFO = operating cash flow deflated by total assets; 1 if the
company belongs to the mining industry, 0 otherwise; MINING = 1 if the company belongs to the mining
industry, 0 otherwise.
14 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
similar. The association between NAS and
ABSDACC is significant and positive (n = 2,321,
p < 0.001) pre-CLERP 9 and not significant post
CLERP 9 (n = 2,586, p = 0.216). The association
between abnormal NAS and ABSDACC is

significant and positive (n = 2,321, p < 0.001)
pre-CLERP 9 and not significant post CLERP 9
(n = 2,586, p = 0.156). Therefore, the results are
consistent with the main analyses.
Additional analyses
Following Choi et al. (2006), abnormal NAS fees are
calculated as the difference between estimated
NAS fees and actual NAS fees. Abnormal NAS
fees are used as a variable of interest when running
the regressions. The results are consistent (not
tabulated) for both the OPINION and DACC
models. This demonstrates the robustness of
estimation of abnormal NAS fees.
The current study uses data from three years
before the implementation of CLERP 9 and three
years after the implementation of CLERP 9,
although 2004 may be a noisy year because some
companies may have implemented the CLERP 9
requirements voluntarily before they became
mandatory. However, the results (not tabulated)
are consistent even when the 2004 data are
excluded from the OPINION and DACC models.
I also examined the changes in audit and
non-audit fees during the pre- and post- CLERP 9
periods for a balanced panel, i.e., the same
companies throughout the sample period. The
number of companies was 607. Table 7 shows that
audit fees increased from 2002 to 2007 and
non-audit fees decreased over the same period.
This indicates that CLERP 9 was effective in

reducing the purchase of non-audit services from
incumbent auditors. The decrease in non-audit
services purchased from incumbent auditors
indicates an improvement of audit independence
due to a decrease in fee reliance, which was a
concern of the regulators. A per-dollar amount of
audit fees to total assets was 8 cents during 2005,
which may be the result of the adoption of IFRS.
This remained constant during 2006 and 2007. A
per-dollar amount of non-audit fees to total asset
decreased after 2004 and remained steady from
2005 to 2007.
The results (not tabulated) of a logistic regression
for the association between the NAS fees and
OPINION are not significant during both the pre-
and post-CLERP 9 periods for the matched sample.
The association between NAS fees and ABSDACC
is also not significant. The results might be
explained by the fact that the matched sample
contains larger companies that survived for a long
period of time and the fact that larger companies
are less likely to end up in bankruptcy due to their
financial stability (Carey & Simnett, 2006).
Therefore, there is a lower probability of receiving
a going-concern opinion and larger companies
tend to report more stable accruals (Dechow &
Dichev, 2002; Chi et al., 2010) and are less likely to
manipulate earnings.
Consistent with Carey and Simnett (2006), I also
examined whether NAS fees are associated with

the just beats or misses earnings forecast during
the pre- and post-CLERP 9 periods. I used four
meeting or missing benchmarks: (1) BEATS_BE
(equals 1 when profit is less than 2 per cent of total
assets, and 0 otherwise), (2) MISSES_BE (equals 1
Table 7: Audit and non-audit fees using a balanced panel during 2002–2007
Variables N 2002 2003 2004 2005 2006 2007
Mean Mean Mean Mean Mean Mean
AF 607 172,485.350 177,013.890 196,471.110 224,010.190 248,417.600 268,501.950
NAS 607 189,680.460 137,798.060 134,265.650 124,483.200 112,937.170 109,519.350
TOTAL 607 362,165.810 314,811.950 330,736.750 348,493.390 361,354.770 378,021.300
FEERATIO 607 0.288 0.288 0.285 0.264 0.235 0.209
AF_TA 607 0.007 0.009 0.005 0.008 0.006 0.006
NAS_TA 607 0.007 0.004 0.004 0.002 0.002 0.002
TOTAL_TA 607 0.013 0.013 0.009 0.010 0.008 0.008
AF = audit fees; NAS = auditor-provided non-audit services fees; TOTAL = total of audit and non-audit services
fees; FEERATIO = non-audit fees scaled by total audit and non-audit fees; AF_TA = audit fees scaled by total
assets; NAS_TA = non-audit fees scaled by total assets; TOTAL_TA = total audit and non-audit services fees
scaled by total assets.
Effect of Regulatory Changes on Auditor Independence and Audit Quality 15
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
when losses are less than 2 per cent of total assets,
and 0 otherwise), (3) BEATS_LYR (equals 1 when
the increase in profit [or decrease in loss] over last
year’s profit/loss is less than 2 per cent of total
assets, and 0 otherwise), and (4) MISSES_LYR
(equals 1 when the decrease in profit [increase in
loss] over last year’s profit/loss is less than 2 per
cent of total assets, and 0 otherwise). The results
(not tabulated) show that BEAT_BE and BEAT_

LYR are not significantly associated with NAS
fees pre-CLERP 9. However, MISSES_BE and
MISSES_LYR are significantly and negatively
associated with NAS fees during the same period.
During the post-CLERP 9, none of the benchmarks
is significantly associated with NAS fees. The
results suggest that an audit independence
problem existed pre-CLERP 9, but has been
mitigated by regulatory changes.
CONCLUSION
This study provides evidence of the impact of the
CLERP 9 on audit quality by using data from the
pre- and post-CLERP 9 periods. Using multiple
proxies for auditor independence and audit quality,
I find consistent evidence that the implementation
of CLERP 9 improved audit quality. The findings
enhance our understanding of the effectiveness of
regulatory changes on auditor independence and
audit quality. Similar studies have been conducted
in the US; however, the US legislative response
(i.e., SOX) is quite different from that in Australia.
Therefore, the current paper addresses the
question: Is the Australian approach effective? This
is an important question for policy making to
achieve an outcome with the least compliance cost.
I find a significant and positive association
between non-audit fees and going-concern opinion
post-CLERP 9, which indicates that auditors are
more likely to issue a going-concern opinion when
providing non-audit services. The findings indicate

that auditor-provided non-audit services fees do
not impair audit quality post-CLERP 9. The finding
is consistent with the US study of Li (2009) for
the pre- and post-SOX periods. The results are
consistent using various sensitivity analyses.
The results of the earnings management proxy
show that auditors tolerate a larger magnitude of
absolute values of discretionary accruals when
earning higher NAS fees during the pre-CLERP 9
period, but the significant association is mitigated
by the implementation of CLERP 9. These findings
also provide evidence of improved auditor
independence and audit quality after the
regulatory changes. Wong et al. (2007) argue that
reduced discretionary accruals or corporate
earnings management activities are associated with
higher financial reporting quality. The findings are
consistent with the US study of Hoitash et al. (2007)
during the pre- and-post-SOX periods. The results
are consistent using various sensitivity analyses,
demonstrating the robustness of the findings.
The current study is subject to a number of
limitations. First, the audit opinion prediction
model is not perfect, and the possibility of an
unknown degree of model misstatement, omitted
variables, and their effects on the results cannot be
ruled out, even though this study uses a prediction
model based on prior literature. Second, abnormal
accruals are a noisy proxy for managements’
discretion over earnings, although, as in prior

studies, every step has been taken to control for the
effects of performance difference on accruals. The
results are consistent with the alternative measures
of earnings management used in prior research.
Third, this study did not separate other regulatory
changes that occurred during the period of the
study. Finally, there might be a sample bias in using
three years for the pre-CLERP 9 period and three
years for the post-CLERP 9 period because 2004
may be a noisy year. However, the results are
robust even when the 2004 data are excluded.
This study also provides some directions for
future research. Future studies could investigate
the impacts of corporate governance on earnings
quality after the regulatory changes. Future
research could also investigate the association
between the types of non-audit fees and audit
quality in light of the CLERP 9 requirement to
disclose the types of non-audit fees in the annual
reports.
ACKNOWLEDGEMENT
The author would like to thank the two anonymous
reviewers of this journal for their helpful
comments and suggestions on earlier drafts. The
author would also like to thank Gary Monroe,
Mark Wilson and the participants of the ANCAAR
2007 forum at ANU for their valuable comments
and suggestions on earlier versions of the paper.
NOTES
1. For log transformation, I substitute 1 for NAS

fees companies that did not have non-audit
16 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
services fees during the period. In a sensitivity
analysis, I exclude those companies (around 30
per cent of the sample companies) that had zero
NAS fees and the results are qualitatively the
same for both the opinion and discretionary
accruals models.
2. Carey and Simnett (2006) include a non-audit
fee ratio as the total of audit and non-audit fees
(FEERATIO) when predicting audit opinions.
I exclude the FEERATIO because the variable
of interest, LnNAS is highly correlated with
FEERATIO. However, I re-estimated all the
models after including FEERATIO, and it did
not change the significance levels of the variable
of interest.
3. Consistent with Carcello, Hermanson and Huss
(1995), I calculate the Zmijewski score as
b =-4.803 - 3.6 (net profit after tax divided
by total assets) + 5.4 (total liabilities divided by
total assets) - 0.1 (current assets divided by
current liabilities).
4. Davidson, Goodwin-Stewart and Kent (2005),
for instance, report mean absolute discretionary
accruals of 15.6 per cent with a standard
deviation of 17.6 per cent.
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18 S. Hossain
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd
reporting: Are Australia’s reforms likely to work?’
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AUTHOR PROFILE
Sarowar Hossain is a Lecturer at the Australian
School of Business, University of New South
Wales. He was previously at ANU and the
University of Dhaka, Bangladesh. Dr Hossain’s
teaching interests include financial accounting,
corporate accounting, and issues in financial
reporting and analysis for both undergraduate and
postgraduate levels. His research areas include
auditing, corporate interlocking, audit quality and
auditor independence.
APPENDIX: DEFINITIONS OF VARIABLES
Variable Definition
OPINION = OPINION is coded as 1 if an auditor issues a going-concern opinion for a
financially distressed company, 0 otherwise;
LnNAS = natural log of auditor-provided non-audit service fees;
ABNAS = abnormal NAS fees;
PQUAL = 1 if the auditor has issued an other than unqualified opinion in the previous year,
0 otherwise;
PBANK = probability of bankruptcy, as measured by adjusted Zmijeswki score;
LnTA = natural log of total assets;
LnAGE = natural log of number of years the company has been listed in the Australian
Securities Exchange (ASX);

LEVERAGE = total liabilities divided by total assets;
CLEVERAGE = change in leverage during the year;
ROA = earnings before interest and taxes divided by total assets;
LLOSS = 1 if the client reported a loss in the previous year, 0 otherwise;
INVESTMENTS = short- and long-term investment securities (measured as current assets minus
debtors and inventory) divided by total assets;
BIG4 = 1 if the audit firm is a big 4 firm, 0 otherwise;
CFO = operating cash flow deflated by total assets;
MINING = 1 if the company belongs to the mining industry, 0 otherwise;
GROWTH = change in assets from prior year;
TACC = total accruals measured via the difference between operating income (OI) minus
cash flow from operations;
DREV = change in revenues from period t–1 to period t;
DREC = change in accounts receivables from period t–1 to period t;
PPE = gross value of property, plants, and equipment;
LagROA = one year lag of ROA;
DACC = discretionary accruals;
ABSDACC = absolute value of discretionary accruals;
LTACC = value of total accruals in year t–1;
MERGACQS = 1 if the company has merger or acquisition activities during the current year, 0
otherwise;
NEG_ROA = 1 if the company reports a negative return on assets, 0 otherwise;
MB = market-to-book value;
LnSUBS = natural log of number of subsidiaries;
FOROPS = 1 if the company has any foreign subsidiaries, 0 otherwise;
USLIST = 1 if the company is cross-listed in US, 0 otherwise;
∑INDUSTRY
= there are 10 indicator variables for 11 GICS industry group.
Effect of Regulatory Changes on Auditor Independence and Audit Quality 19
Int. J. Audit. ••: ••–•• (2013)© 2013 Blackwell Publishing Ltd