Managerial Auditing JournalMandatory audit firm rotation and audit qualityAndrew B. Jackson Michael Moldrich Peter Roebuck

Article information:To cite this document:Andrew B. Jackson Michael Moldrich Peter Roebuck, (2008),"Mandatory audit firm rotation and auditquality", Managerial Auditing Journal, Vol. 23 Iss 5 pp. 420 - 437Permanent link to this document:http://dx.doi.org/10.1108/02686900810875271

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Users who downloaded this article also downloaded:David S. Jenkins, Thomas E. Vermeer, (2013),"Audit firm rotation and audit quality: evidence fromacademic research", Accounting Research Journal, Vol. 26 Iss 1 pp. 75-84Sandra K. Gates, D. Jordan Lowe, Philip M.J. Reckers, (2006),"Restoring public confidence in capitalmarkets through auditor rotation", Managerial Auditing Journal, Vol. 22 Iss 1 pp. 5-17Winifred D. Scott, Willie E. Gist, (2013),"Forced auditor change, industry specialization and audit fees",Managerial Auditing Journal, Vol. 28 Iss 8 pp. 708-734

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Mandatory audit firm rotationand audit quality

Andrew B. JacksonSchool of Accounting, The University of New South Wales, Sydney, Australia

Michael MoldrichKPMG, Sydney, Australia, and

Peter RoebuckSchool of Accounting, The University of New South Wales, Sydney, Australia

Abstract

Purpose – The purpose of this paper is to investigate the effect that a regime of mandatory audit firmrotation would have on audit quality.

Design/methodology/approach – Using two measures of audit quality, being the propensity toissue a going-concern report and the level of discretionary accruals, the paper examines the switchingpatterns of clients in their current voluntary switching capacity, and the levels of audit quality.

Findings – The main finding is that audit quality increases with audit firm tenure, when proxied bythe propensity to issue a going-concern opinion, and is unaffected when proxied by the level ofdiscretionary expenses. Given the additional costs associated with switching auditors, it is concludedthat there are minimal, if any, benefits of mandatory audit firm rotation.

Research limitations/implications – A limitation of this study is that only actual audit quality isexamined. While the results suggest that actual audit quality is associated with the length of audittenure, the perception of audit quality is not addressed, which may increase with audit firm rotation.

Originality/value – The results go against the move towards mandatory audit firm rotation, andsuggest that other initiatives may need to be considered to address concerns about auditorindependence and audit quality.

Keywords Auditing, Auditors, Laws and legislation, Australia

Paper type Research paper

IntroductionConsiderable research has examined the effect that the length of the auditor-client tenurehas had on audit quality, but commonly fails to consider the financial characteristics ofclients in the years preceding a switch. This study examines the financial attributes ofclients in the years preceding and succeeding an audit firm switch, as well as voluntaryauditor switching behaviour to determine whether such auditor movements would befavourable under a scheme of mandatory rotation. The ability of the top-tier audit firmsand industry-specialists to provide consistently high levels of audit quality is also studied.

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0268-6902.htm

The views expressed in this paper are not necessarily the views of KPMG.Financial assistance for this study was kindly provided by the Capital Markets and

Co-operative Research Centre and the Australian School of Business, UNSW. The authors wouldalso like to acknowledge the helpful comments of participants at the 2005 Faculty of Commerceand Economics UNSW National Honours Colloquium, Liz Carson, Jeff Coulton, Asher Curtis,Rob Czernkowski, Andrew Ferguson, Gerry Gallery, Caitlin Ruddock, Roger Simnett,Stephen Taylor, and two anonymous reviewers. All errors remain the authors’ responsibility.

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Managerial Auditing JournalVol. 23 No. 5, 2008pp. 420-437q Emerald Group Publishing Limited0268-6902DOI 10.1108/02686900810875271

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Following recent legislative changes imposed on the auditing profession throughthe introduction of the Corporate Law Economic Reform Program (Audit Reform &Corporate Disclosure) Act 1999 (CLERP 9), there is a need to determine whether thecurrent regulations are enough, or whether further regulatory changes, such as asystem of mandatory audit firm rotation, are desirable. There has also been a call forfurther research on this topic by both the international standard setters and academics(Government Accountability Office – GAO, 2003; Nagy, 2005). This study is furthermotivated by a lack of research examining characteristics of the client in the yearsprior to the audit firm switch, which may have an impact on subsequent audit quality.

The aim of this study is to understand whether the client’s financial characteristicsunder the predecessor auditor have an impact on audit quality under the incumbentauditor. An additional aim is to determine whether current voluntary switchingpatterns would be conducive to a system of forced rotation, and whether the top-tieraudit firms and industry specialists are able to provide higher levels of audit qualityover a period of time.

We find that audit quality increases with audit firm tenure, when proxied by thepropensity to issue a going-concern opinion, and is unaffected when proxied by thelevel of discretionary accruals (DA). Given our results, we conclude that mandatoryaudit firm rotation will not improve audit quality. Considering the costs involvedduring the early stages of an auditor-client relationship, requiring firms to rotate theirauditors will place unnecessary costs on both the auditor and the client with minimalbenefits. In order to address concerns that have arisen surrounding auditorindependence issues, we conclude that other initiatives are more likely to have agreater impact than mandatory audit firm rotation.

Background and empirical predictionsAudit firm rotationA system of mandatory audit firm rotation would require companies to rotate theirindependent auditor periodically. Currently, listed companies in Italy and Brazil arerequired to rotate their independent auditor every nine and five years, respectively. InAustralia, there is currently no legislative requirement for reporting entities to rotatetheir independent audit firm, although periodic rotation of lead audit partners is nowobligatory under s324DA of the Corporations Act 2001 (Cth).

Advocates of audit firm rotation believe a scheme of compulsory rotation wouldprevent auditors from becoming too aligned with managers, impacting on theirindependence. A client may be a significant source of revenue for an auditor, and theauditor may be reluctant to jeopardise this revenue stream (Hoyle, 1978). Firm rotationmay also help to prevent large-scale corporate collapses. Morgan Stanley estimates themarket capitalisation loss of the collapses of WorldCom, Tyco, Quest, Enron andComputer Associates to be $US460 billion. Firm rotation can help restore confidence inthe regulatory system, which was found to be the case in Italy (Healey and Kim, 2003).Further, if a client seeks a new auditor, auditors will compete with other audit firms towin the tender and differentiate themselves in terms of service, improving audit quality(Hoyle, 1978). Despite the increased start-up costs which are involved with introducinga new auditor, supporters of audit firm rotation propose that the costs of corporatecollapses, which may not have occurred had audit quality been higher, outweigh theincrease in audit costs involved when introducing a new auditor. From this

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perspective, a new auditor brings in more objectivity as they are not familiar with theclient, potentially improving the quality of the audit.

On the contrary, mandating firm rotation would lead to a loss of client knowledgewhen the auditor is forced to resign. Auditors experience a significant learning curvewith new clients (Knapp, 1991), and much of the knowledge acquired during an audit isclient-specific (Kinney and McDaniel, 1996). Audit failures are generally higher in thefirst years of the auditor-client relationship as the new auditor becomes familiar withthe client’s operations (Arel et al., 2005). Audit costs would also rise due to theadditional work needed by the new audit firm. The GAO (2003) estimated thatcompanies would incur additional auditor selection costs equal to 17 per cent of theirfirst year audit fees (GAO, 2003). Opportunity costs would also arise because of amismatch between the client’s needs and those which the auditor can offer (Arrunadaand Paz-Ares, 1997). Auditor resignations provide valuable signals to the market(Wells and Loudder, 1997). Under mandatory rotation, if a client is experiencingconflicts with its auditor over accounting treatments and the auditor is forced to rotate,the market misses out on valuable signals that would have taken place undervoluntary rotation. The largest accounting firms may also increase their market shareunder mandatory rotation, as has been the case in Italy (Buck and Michaels, 2005),leading to a less-competitive environment.

Even if research has generally not found significant positive effects of firm rotationon audit quality, rotation may nevertheless be effective in increasing perceivedaudit quality. Audit quality comprises actual and perceived quality (Taylor, 2005).Actual quality is the degree to which the risk of reporting a material error in thefinancial accounts is reduced, while perceived quality is how effective users of financialstatements believe the auditor is at reducing material misstatements. Higher perceivedaudit quality may then help promote investment in audited clients.

Related literature and empirical predictionsIt has been argued that companies switch auditors to avoid receiving qualified auditreports. This argument assumes that managers dislike qualified reports and thatmanager’s influence the appointment decision.

The first assumption is relatively uncontroversial. A qualified report may signal toinvestors that managers are poor stewards of the company’s affairs, or that managershave attempted to present an over-favourable view of the company’s performanceand/or position. In addition, qualified reports cause share prices to fall, reducingmanagerial utility if managers own shares or if their compensation is directly related tomarket value (Firth, 1978; Banks and Kinney, 1982; Fleak and Wilson, 1994; Chen andChurch, 1996; Jones, 1996).

The second assumption is more controversial. By law in Australia, auditors areappointed by shareholders. However, managers may exert considerable influence overauditor appointments. Incumbent auditors could be dismissed by managers withoutconsulting shareholders, with the shareholders merely voting on whether to accepttheir recommendation regarding the appointment of a new auditor or there-appointment of the incumbent. Secondly, managers have some influence over theappointment of a new auditor or the re-appointment of the incumbent auditor.Managers set meeting agendas when auditor appointments are proposed, and they

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typically have the proxy votes of a large number of shareholders. Thus, managers haveconsiderable influence over auditor hiring and firing.

If managers dislike qualified reports and have some influence over auditorappointment, they may try to use auditor switching to avoid receiving qualifiedreports. Teoh (1992) usefully identifies two ways in which this could occur. First, amanager may actively use the auditor switch decision to avoid receiving a qualifiedreport. If a new auditor is less likely to give a qualified report compared to theincumbent auditor, the manager may choose to switch. Similarly, if a new auditor ismore likely to give a qualified report compared to the incumbent, the manager maychoose not to switch. Second, if auditors earn client-specific rents, a manager mayobtain a more favourable report from an incumbent auditor by threatening to switch toa new auditor. However, post-Enron, HIH and the CLERP Act 2004, the top 300 listedcompanies are required to have an audit committee, which limits the ability formanagers to exercise such influence.

Geiger and Raghunandan (2002) find that auditors are more likely to issue anunqualified audit opinion prior to a client filing for bankruptcy in the early years of theauditor-client relationship. Myers et al. (2003) on the other hand find that as auditortenure increases, auditors place greater constraints on the degree of discretionary andcurrent accruals allowed by management. These results suggest that mandatory auditfirm rotation may have adverse effects on audit quality, as audit quality is lower in theearlier years of the auditor-client relationship.

A number of other reasons have been proffered as to why clients decide to changeauditors. Chow and Rice (1982) find that the incidence of a qualified report was asignificant reason for clients to switch auditors. Schwartz and Menon (1985) find thatfailing clients had a greater propensity to switch auditors, while Williams (1988) arguesthat financially distressed clients have greater incentives to change auditors than healthyclients in order for managers to portray a good image of the company. Hence, there is someevidence that a large proportion of switching clients may be financially distressed.

However, a change in auditor is not always initiated by the client, but rather may beinitiated by the audit firm. Prior research indicates that audit firms by virtue of their owninternal quality procedures have a tendency to shed risky clients. An audit firm with arisky client may decide to drop the client from its portfolio in order to reduce theirengagement risk ( Johnstone and Bedard, 2004). Auditors generally resign from clientswith high-financial distress and in receipt of a modified (particularly going-concern)opinion (Krishnan and Krishnan, 1997). Shu (2000) also finds that an auditor resignationis positively related to client legal exposure. The preceding arguments suggest that as aresult of risky clients deciding to change auditors, or auditors deciding to resign fromrisky clients, a large proportion of clients that do switch will be financially unsound.

A large body of research underscores the higher levels of audit quality that thetop-tier audit firms can provide to their clients. DeAngelo (1981) argues that audit firmswith more clients have greater incentives to supply higher quality audits. Teoh andWong (1993) find that clients of Big N audit firms generally have higher earningsresponse coefficients to audited earnings announcements, while Francis et al. (1999)find that Big N audit firms were able to reduce the level of DA reported by their clients,indicating a more effective assertion of independence. The prior literature suggeststhat firms with higher levels of DA are able to manage earnings which lead to loweraudit quality.

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Some audit firms differentiate themselves from their competitors by specialising inauditing clients in particular industries. Craswell et al. (1995) find thatindustry-specialists command a fee premium of around 16 per cent over non-industryspecialists, indicating that clients are willing to pay more for the services of such anauditor. Schauer (2002) finds that clients of industry specialists had lower bid-askspreads, signifying lower levels of information asymmetry associated, and Krishnan(2003) observes that clients of industry-specialists reported lower levels of accruals.

From the prior research, it appears that audit quality as measured by the propensityto issue a going-concern opinion (GCO) and the level of DA is impacted by a change inauditor. Therefore, we propose the following hypothesis, stated in the null:

H0. Audit firm rotation does not affect audit quality.

Sample selection and research designSample selectionThis study examines auditor switches occurring between 1995 and 2003 for Australianlisted entities. It was decided to study the period from 1995, as data were readilyavailable for the year, and follows many of the Big N audit firm mergers. The period1995-1999 also offers a comparable time period with 2000-2003. The period from 2000has been marked by a number of considerable changes and events. The RamsayReport, issued in 2001, highlighted a number of threats to auditor independence,including the provision of non-audit services along with recommendations for auditpartner rotation, which is included in CLERP 9. In addition, international high-profilecorporate collapses, including Enron, WorldCom, and HIH, brought auditor-clientrelationships under even greater examination.

The initial sample consisted of 772 auditor switches for listed ASX entities between1995 and 2003. Financial sector firms were excluded due to the inherent differences intheir reporting nature. After excluding clients where DA data were not available, thosewith insufficient data, those reporting in a foreign currency, and for clients where amatched entity could not be found, a total of 205 auditor switches resulted. The totalsample was used to measure changes in the level of DA with auditor tenure. Bothswitching client firm-year observations and non-switching client firm-yearobservations were included, yielding a total of 1,750 firm-year observations.

Each listed entity’s independent auditor was identified from Craswell’s Who AuditsAustralia database from 1994 to 2003. The age of clients was obtained from the ASXweb site and Aspect Huntley’s DatAnalysis. Financial statement balances were alsoobtained from Aspect Huntley’s DatAnalysis. Takeover announcements were collectedfrom Connect 4, while debt and equity issues data were collected from Thompson’sSDC Platinum New Issues Database. Market capitalisation data were collected fromCRIF. Any missing data were hand collected from relevant sources. Variables werewinsorised at the fifth and 95th percentiles to remove the effect of significant outliers.

Research designAudit quality has been defined in numerous ways, ranging from the relative degree towhich the audit conforms to applicable auditing standards (Krishnan and Schauer,2001; Tie, 1999; McConnell and Banks, 1998; Cook, 1987), the market-assessedprobability that the financial statements contain material errors and that the auditorwill discover and report them (DeAngelo, 1981), the accuracy of the information

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reported on by auditors (Titman and Trueman, 1986; Beatty, 1989; Krinsky andRotenberg, 1989), and a measure of the audit’s ability to reduce noise and bias andimprove fineness in accounting data (Wallace, 1980). Any metric used to measure auditquality, however, are not perfect. Proxies for audit quality can only be devised in mostcases using publicly available information, and not private information known to theauditor. The true audit quality is when the audit does not result in a Type I or II error –a failing company being given an unqualified report or a non-failing company beinggiven a qualified report.

In order to test our hypothesis that a change in audit firm has no effect on auditquality, we estimate the following model:

AQ ¼ aþ b1TENURE þ b2FRISK þ b3SIZE þ b4LEV þ b5CLEV

þ b6RETURN þ b7LDISTRESS þ b8INVEST þ b9FEERATIO

þ b10SCFO þ b11PRIOR þ b12BIG_N þ b13LEADER

þ b14INDUSTRY þ 1

ð1Þ

where AQ is audit quality, TENURE is the number of continuous years the incumbentauditor has been with the client; FRISK is the client financial risk as measured by theZmijewski (1984) financial distress score[1]; SIZE is measured as the natural log of totalassets, LEV is the ratio of liabilities to assets, CLEV is the percentage change in LEVduring the year, RETURN is the percentage change in the book value of net assets overthe year, LDISTRESS is a dummy variable indicating if the client was financiallydistressed[2] in the previous year, INVEST is investment securities measured bycurrent assets less-current debtors and inventory scaled by total assets, FEERATIO isfee dependence as measured by non-audit fees divided by non-audit and audit fees paidto the incumbent auditor, strong cash flows from operations (SCFO) is the net cashflows from operations scaled by lagged total assets, PRIOR is a dummy variableindicating if the client received a going-concern opinion in the prior year, BIG_N is adummy variable indicating if the firm was audited by a Big N auditor, LEADER is adummy variable indicating if the audit firm is a leader in the firm’s industry, andINDUSTRY is a dummy variable indicating if a firm is in the mining sector.

Two measures of audit quality are employed within this study. First, audit qualityis measured as the propensity of the auditor to issue a GCO after controlling for otherfactors that might affect this decision. A finding that auditors have a lower (higher)propensity to issue going-concern opinions with increased tenure would provideconvincing evidence in favour of (in opposition to) mandatory rotation, i.e. if there islower propensity to issue GCO with increased tenure, then independence becomesimpaired. As the dependent variable in this measurement of audit quality is adichotomous variable, being the propensity to issue a going-concern opinion, a logisticregression is run.

Second, the level of DA is used. DA are accruals that do not relate to normaloperating activities, and so a higher level of these accruals may indicate thatmanagement has been able to exert its power over the auditor by being able to reporton terms favourable to management. As this second measurement of audit quality is acontinuous variable, an OLS regression is sufficient.

To measure DA, a performance-matched modified-Jones (1991) DA model was used.Dechow et al. (1995) find that the modified Jones model had the highest statistical

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power in detecting earnings management, while Kothari et al. (2005) suggest matchingfor performance helps to control for changes in accruals models associated with clientperformance levels. Performance matched firms are matched by year and industry. DAare estimated by:

TACC ¼ a1 þ a2ðDSales 2 DRecÞ þ a3PPE þ a4LTACC þ a5Growth þ 1 ð2Þ

where TACC is total accruals (operating net profit after tax – cash flows fromoperations), DSales is the change in sales for the year scaled by lagged total assets,DRec is the change in accounts receivable during the year scaled by lagged total assets,PPE is the gross property, plant and equipment scaled by lagged total assets, Growthis the ratio of next year’s sales to this years, and the residual from the regression, 1, isthe measure of DA. The higher the level of the residual indicates a lower level ofaccrual quality.

The model employed in this study is based closely on that used by DeFond et al.(2002) and Carey and Simnett (2006). The Zmijewski (1984) probability of bankruptcyscore (FRISK) is included because clients closer to bankruptcy should have a higherchance of receiving a going-concern report. SIZE is included because larger clients willhave more assets to sell in the event of financial difficulty, and should be less prone toreceiving a going-concern report. LEV and CLEV are employed because higher levelsof debt relative to total assets indicate higher risk, and greater changes in leverage maysuggest that the client is close to violating a debt covenant. RETURN is included,because clients with higher levels of growth should be less likely to fail.

ResultsDescriptive statisticsDescriptive statistics are presented in Table I. Panel A provides the results for the fullsample, with Panels B and C providing the results for the switching and non-switchingfirms, respectively. Means of the variables are consistent with prior research. Of the totalsample, 4.06 per cent of firm-year observations result in a GCO being issued, whichincreases to 5.37 per cent for switching firms (3.88 per cent for non-switching firms).

Table II outlines the correlation coefficients between the variables, using bothPearson and Spearman rank correlations. Firms that were financially distressed in theprior year have a high-negative correlation with both RETURN and SCFO.

Going-concern opinionTable III presents the results of the logistic regression using the propensity to issue agoing-concern audit opinion as a proxy for audit quality. Panel A provides the resultsfor the full sample, with Panels B and C providing the results for the switching andnon-switching firms, respectively.

Results from Table III indicate that audit-client tenure increases the likelihood of theauditor issuing a going-concern audit opinion. This result is inconsistent with theresults of Geiger and Raghunandan (2002) who found no statistically significantrelationship, and with those of Choi and Doogar (2005) who found a significantlynegative relationship between audit quality and tenure.

As expected, FRISK was positively associated with the propensity to issue agoing-concern opinion, indicating that firms with higher probabilities of bankruptcyare more likely to receive a going-concern opinion. SIZE was found to have a

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Var

iab

leM

ean

Std

Min

Qu

arti

le1

Med

ian

Qu

arti

le3

Max

PanelA:full-sampledescriptive

statistics(n

¼1,750)

GC

O0.

0406

0.19

740.

0000

0.00

000.

0000

0.00

001.

0000

DA

20.

0239

0.13

962

1.04

762

0.07

582

0.01

680.

0342

0.86

06T

EN

UR

E7.

2954

5.45

321.

0000

3.00

006.

0000

10.0

000

32.0

000

FR

ISK

22.

3819

1.69

202

8.11

902

3.31

022

2.48

052

1.64

054.

1519

SIZ

E17

.965

91.

8758

11.4

616

16.6

620

17.7

435

19.1

076

24.4

907

LE

V5.

8128

15.0

874

0.00

000.

0086

0.15

961.

9684

63.0

075

CL

EV

0.30

750.

8741

20.

6120

20.

1122

0.05

530.

3602

3.57

36R

ET

UR

N0.

1170

0.46

002

0.67

972

0.08

690.

0559

0.21

491.

5453

LD

IST

RE

SS

0.57

540.

4944

0.00

000.

0000

1.00

001.

0000

1.00

00IN

VE

ST

0.13

890.

1748

20.

5415

0.03

110.

0713

0.17

401.

0000

FE

ER

AT

IO0.

3238

0.23

890.

0000

0.13

160.

3078

0.49

020.

9779

SC

FO

0.03

760.

2022

20.

9795

20.

0246

0.06

470.

1260

0.60

41P

RIO

R0.

0063

0.07

910.

0000

0.00

000.

0000

0.00

001.

0000

BIG

_N

0.69

830.

4591

0.00

000.

0000

1.00

001.

0000

1.00

00L

EA

DE

R0.

1977

0.39

840.

0000

0.00

000.

0000

0.00

001.

0000

IND

US

TR

Y0.

5394

0.49

860.

0000

0.00

001.

0000

1.00

001.

0000

PanelB:sw

itchingclientsdescriptive

statistics(n

¼205)

GC

O0.

0537

0.22

590.

0000

0.00

000.

0000

0.00

001.

0000

DA

20.

0168

0.15

492

0.92

692

0.07

102

0.00

690.

0427

0.63

90T

EN

UR

E2.

1951

3.15

931.

0000

1.00

001.

0000

1.00

0018

.000

0F

RIS

K2

2.22

181.

7884

25.

4695

23.

4345

22.

5547

21.

4187

4.12

62S

IZE

17.6

379

1.96

6511

.461

616

.329

017

.488

618

.858

424

.490

7L

EV

10.2

942

19.0

199

0.00

000.

0211

0.81

497.

7183

63.0

075

CL

EV

0.36

100.

9785

20.

6120

20.

1527

0.07

890.

4448

3.57

36R

ET

UR

N0.

1534

0.55

692

0.67

972

0.16

170.

0555

0.31

641.

5453

LD

IST

RE

SS

0.64

390.

4800

0.00

000.

0000

1.00

001.

0000

1.00

00IN

VE

ST

0.15

420.

1871

0.00

020.

0371

0.08

480.

1964

1.00

00F

EE

RA

TIO

0.28

190.

2548

0.00

000.

0228

0.23

650.

4762

0.90

77S

CF

O2

0.01

230.

2277

20.

9795

20.

0815

0.04

060.

1154

0.60

41P

RIO

R0.

0537

0.22

590.

0000

0.00

000.

0000

0.00

001.

0000

(continued

)

Table I.Sample descriptive

statistics

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Var

iab

leM

ean

Std

Min

Qu

arti

le1

Med

ian

Qu

arti

le3

Max

BIG

_N

0.61

950.

4867

0.00

000.

0000

1.00

001.

0000

1.00

00L

EA

DE

R0.

1951

0.39

730.

0000

0.00

000.

0000

0.00

001.

0000

IND

US

TR

Y0.

4634

0.49

990.

0000

0.00

000.

0000

1.00

001.

0000

PanelC:matched

non-switchingclientsdescriptive

statistics(n

¼1545)

GC

O0.

0388

0.19

330.

0000

0.00

000.

0000

0.00

001.

0000

DA

20.

0249

0.13

752

1.04

762

0.07

672

0.01

750.

0332

0.86

06T

EN

UR

E7.

9722

5.33

431.

0000

4.00

007.

0000

11.0

000

32.0

000

FR

ISK

22.

4031

1.67

832

8.11

902

3.30

432

2.47

422

1.67

574.

1519

SIZ

E18

.009

41.

8598

11.9

939

16.7

108

17.7

731

19.1

437

23.5

549

LE

V5.

2182

14.3

888

0.00

000.

0074

0.14

271.

5702

63.0

075

CL

EV

0.30

040.

8594

20.

6120

20.

1088

0.05

210.

3528

3.57

36R

ET

UR

N0.

1121

0.44

552

0.67

972

0.07

740.

0560

0.20

871.

5453

LD

IST

RE

SS

0.56

630.

4957

0.00

000.

0000

1.00

001.

0000

1.00

00IN

VE

ST

0.13

690.

1731

20.

5415

0.03

090.

0698

0.17

220.

9721

FE

ER

AT

IO0.

3294

0.23

630.

0000

0.14

400.

3140

0.49

400.

9779

SC

FO

0.04

430.

1977

20.

9795

20.

0163

0.06

810.

1274

0.60

41P

RIO

R0.

0000

0.00

000.

0000

0.00

000.

0000

0.00

000.

0000

BIG

_N

0.70

870.

4545

0.00

000.

0000

1.00

001.

0000

1.00

00L

EA

DE

R0.

1981

0.39

870.

0000

0.00

000.

0000

0.00

001.

0000

IND

US

TR

Y0.

5495

0.49

770.

0000

0.00

001.

0000

1.00

001.

0000

Notes:

GC

Ois

ad

um

my

var

iab

lein

dic

atin

gif

afi

rmre

ceiv

eda

goi

ng

-con

cern

opin

ion

;DA

isa

mea

sure

ofth

ele

vel

ofd

iscr

etio

nar

yac

cru

als;

TE

NU

RE

isth

en

um

ber

ofco

nti

nu

ous

yea

rsth

ein

cum

ben

tau

dit

orh

asb

een

wit

hth

ecl

ien

t;F

RIS

Kis

the

clie

nt

fin

anci

alri

skas

mea

sure

db

yth

eZ

mij

ewsk

i(1

984)

fin

anci

ald

istr

ess

scor

e;S

IZE

ism

easu

red

asth

en

atu

ral

log

ofto

tal

asse

ts;L

EV

isth

era

tio

ofli

abil

itie

sto

asse

ts;C

LE

Vis

the

per

cen

tag

ech

ang

ein

LE

Vd

uri

ng

the

yea

r;R

ET

UR

Nis

the

per

cen

tag

ech

ang

ein

the

boo

kv

alu

eof

net

asse

tsov

erth

ey

ear;

LD

IST

RE

SS

isa

du

mm

yv

aria

ble

ind

icat

ing

ifth

ecl

ien

tw

asfi

nan

cial

lyd

istr

esse

din

the

pre

vio

us

yea

r;IN

VE

ST

isin

ves

tmen

tse

curi

ties

mea

sure

db

ycu

rren

tas

sets

less

-cu

rren

td

ebto

rsan

din

ven

tory

scal

edb

yto

tal

asse

ts;F

EE

RA

TIO

isfe

ed

epen

den

ceas

mea

sure

db

yn

on-a

ud

itfe

esd

ivid

edb

yn

on-a

ud

itan

dau

dit

fees

pai

dto

the

incu

mb

ent

aud

itor

;SC

FO

isth

en

etca

shfl

ows

from

oper

atio

ns

scal

edb

yla

gg

edto

tal

asse

ts;P

RIO

Ris

ad

um

my

var

iab

lein

dic

atin

gif

the

clie

nt

rece

ived

ag

oin

g-c

once

rnop

inio

nin

the

pri

ory

ear;

BIG

_N

isa

du

mm

yv

aria

ble

ind

icat

ing

ifth

efi

rmw

asau

dit

edb

ya

Big

Nau

dit

or;L

EA

DE

Ris

ad

um

my

var

iab

lein

dic

atin

gif

the

aud

itfi

rmis

ale

ader

inth

efi

rm’s

ind

ust

ry;

and

IND

US

TR

Yis

ad

um

my

var

iab

lefo

rfi

rms

inth

em

inin

gse

ctor

Table I.

MAJ23,5

428

Dow

nloa

ded

by I

QR

A U

NIV

ER

SIT

Y A

t 04:

58 2

0 Se

ptem

ber

2014

(PT

)

GC

OD

AT

enu

reS

IZE

FR

ISK

LE

VC

LE

VR

ET

UR

NL

DIS

TR

ES

SIN

VE

ST

FE

ER

AT

IOS

CF

OP

RIO

R

GC

O0.

0537

(0.0

245)

20.

0156

(0.5

147)

20.

2043

(,0.

0001

)0.

2327

(,0.

0001

)0.

1130

(,0.

0001

)0.

0320

(0.1

806)

20.

1016

(,0.

0001

)0.

1298

(,0.

0001

)0.

0062

(0.7

947)

20.

0485

(0.0

426)

20.

1984

(,0.

0001

)0.

0911

(0.0

001)

DA

0.06

27(0

.008

7)2

0.00

68(0

.776

3)0.

0365

(0.1

267)

0.02

27(0

.343

5)2

0.01

54(0

.519

3)0.

0576

(0.0

160)

20.

0105

(0.6

612)

0.05

53(0

.020

7)2

0.12

40(,

0.00

01)

0.03

03(0

.205

2)2

0.52

03(,

0.00

01)

0.05

01(0

.036

0)T

EN

UR

E2

0.01

21(0

.614

5)2

0.01

94(0

.418

0)0.

2193

(,0.

0001

)2

0.02

47(0

.302

6)2

0.14

15(,

0.00

01)

20.

0751

(0.0

017)

20.

0167

(0.4

839)

20.

0869

(0.0

003)

20.

0962

(,0.

0001

)0.

0405

(0.0

905)

0.09

98(,

0.00

01)

20.

0880

(0.0

002)

SIZ

E2

0.21

12(,

0.00

01)

0.02

01(0

.401

5)0.

1976

(,0.

0001

)0.

0022

(0.9

260)

20.

3326

(,0.

0001

)2

0.07

13(0

.002

8)0.

0933

(,0.

0001

)2

0.27

14(,

0.00

01)

20.

3188

(,0.

0001

)0.

2694

(,0.

0001

)0.

3476

(,0.

0001

)2

0.05

07(0

.033

8)F

RIS

K0.

1552

(,0.

0001

)0.

0369

(0.1

229)

0.02

32(0

.332

3)0.

1146

(,0.

0001

)0.

1094

(,0.

0001

)0.

0295

(0.2

172)

20.

3190

(,0.

0001

)0.

1584

(,0.

0001

)2

0.19

93(,

0.00

01)

20.

0283

(0.2

360)

20.

1827

(,0.

0001

)0.

0808

(0.0

007)

LE

V0.

1157

(,0.

0001

)2

0.00

05(0

.982

2)2

0.16

71(,

0.00

01)

20.

4679

(,0.

0001

)0.

0184

(0.4

415)

0.00

28(0

.908

5)2

0.06

94(0

.003

7)0.

0409

(0.0

874)

0.10

75(,

0.00

01)

20.

0977

(,0.

0001

)2

0.17

22(,

0.00

01)

0.03

10(0

.195

0)C

LE

V2

0.01

24(0

.602

8)0.

0331

(0.1

665)

20.

0949

(,0.

0001

)0.

0357

(0.1

349)

0.09

87(,

0.00

01)

20.

0225

(0.3

467)

0.25

98(,

0.00

01)

0.10

15(,

0.00

01)

0.04

17(0

.081

4)0.

0162

(0.4

996)

20.

1065

(,0.

0001

)0.

0177

(0.4

583)

RE

TU

RN

20.

1151

(,0.

0001

)0.

0366

(0.1

255)

0.00

71(0

.765

2)0.

1639

(,0.

0001

)2

0.29

73(,

0.00

01)

20.

0950

(,0.

0001

)0.

1467

(,0.

0001

)2

0.18

47(,

0.00

01)

0.05

95(0

.012

7)0.

0805

(0.0

007)

0.09

20(0

.000

1)0.

0474

(0.0

475)

LD

IST

RE

SS

0.12

98(,

0.00

01)

0.03

42(0

.152

9)2

0.08

01(0

.000

8)2

0.27

68(,

0.00

01)

0.11

73(,

0.00

01)

20.

0146

(0.5

410)

0.00

40(0

.866

5)2

0.29

10(,

0.00

01)

0.14

26(,

0.00

01)

20.

0974

(,0.

0001

)2

0.35

05(,

0.00

01)

0.02

48(0

.299

1)IN

VE

ST

20.

0134

(0.5

762)

20.

1622

(,0.

0001

)2

0.07

78(0

.001

1)2

0.26

34(,

0.00

01)

20.

1938

(,0.

0001

)0.

1393

(,0.

0001

)2

0.03

10(0

.194

9)0.

0219

(0.3

608)

0.11

09(,

0.00

01)

0.03

07(0

.199

2)2

0.17

34(,

0.00

01)

20.

0149

(0.5

322)

FE

ER

AT

IO2

0.05

22(0

.029

1)0.

0191

(0.4

251)

0.05

06(0

.034

4)0.

2686

(,0.

0001

)0.

0020

(0.9

329)

20.

0924

(0.0

001)

0.05

97(0

.012

5)0.

0655

(0.0

061)

20.

0979

(,0.

0001

)0.

0299

(0.2

112)

0.04

96(0

.038

1)2

0.03

28(0

.170

7)S

CF

O2

0.22

52(,

0.00

01)

20.

5004

(,0.

0001

)0.

1082

(,0.

0001

)0.

3684

(,0.

0001

)2

0.12

16(,

0.00

01)

20.

1744

(,0.

0001

)0.

0329

(0.1

689)

0.29

97(,

0.00

01)

20.

3901

(,0.

0001

)2

0.04

73(0

.047

9)0.

0861

(0.0

003)

20.

0558

(0.0

195)

PR

IOR

0.09

11(0

.000

1)0.

0513

(0.0

320)

20.

1159

(,0.

0001

)2

0.05

11(0

.032

5)0.

0528

(0.0

270)

0.01

87(0

.433

9)2

0.02

38(0

.319

1)0.

0238

(0.3

189)

0.02

48(0

.299

1)2

0.00

13(0

.955

7)2

0.03

62(0

.130

1)2

0.06

01(0

.012

0)

Notes:

Pea

rson

(Sp

earm

anra

nk

)co

rrel

atio

nab

ove

(bel

ow)

the

dia

gon

al;t

he

two-

tail

edp-

val

ue

isp

rov

ided

inp

aren

thes

esw

ith

the

corr

elat

ion

.GC

Ois

ad

um

my

var

iab

lein

dic

atin

gif

afi

rmre

ceiv

eda

goi

ng

-con

cern

opin

ion

;DA

isa

mea

sure

ofth

ele

vel

ofd

iscr

etio

nar

yac

cru

als;

TE

NU

RE

isth

en

um

ber

ofco

nti

nu

ous

yea

rsth

ein

cum

ben

tau

dit

orh

asb

een

wit

hth

ecl

ien

t;F

RIS

Kis

the

clie

nt

fin

anci

alri

skas

mea

sure

db

yth

eZ

mij

ewsk

i(1

984)

fin

anci

ald

istr

ess

scor

e;S

IZE

ism

easu

red

asth

en

atu

ral

log

ofto

tal

asse

ts;L

EV

isth

era

tio

ofli

abil

itie

sto

asse

ts;

CL

EV

isth

ep

erce

nta

ge

chan

ge

inL

EV

du

rin

gth

ey

ear;

RE

TU

RN

isth

ep

erce

nta

ge

chan

ge

inth

eb

ook

val

ue

ofn

etas

sets

over

the

yea

r;L

DIS

TR

ES

Sis

ad

um

my

var

iab

lein

dic

atin

gif

the

clie

nt

was

fin

anci

ally

dis

tres

sed

inth

ep

rev

iou

sy

ear;

INV

ES

Tis

inv

estm

ent

secu

riti

esm

easu

red

by

curr

ent

asse

tsle

ss-c

urr

ent

deb

tors

and

inv

ento

rysc

aled

by

tota

lass

ets;

FE

ER

AT

IOis

fee

dep

end

ence

asm

easu

red

by

non

-au

dit

fees

div

ided

by

non

-au

dit

and

aud

itfe

esp

aid

toth

ein

cum

ben

tau

dit

or;S

CF

Ois

the

net

cash

flow

sfr

omop

erat

ion

ssc

aled

by

lag

ged

tota

lass

ets;

and

PR

IOR

isa

du

mm

yv

aria

ble

ind

icat

ing

ifth

ecl

ien

tre

ceiv

eda

goi

ng

-con

cern

opin

ion

inth

ep

rior

yea

r

Table II.Pearson and Spearman

correlations

Audit firmrotation and

audit quality

429

Dow

nloa

ded

by I

QR

A U

NIV

ER

SIT

Y A

t 04:

58 2

0 Se

ptem

ber

2014

(PT

)

VariableCoefficientestimate Std error Wald x 2

Panel A: full-sample (n ¼ 1750)Intercept 4.3094 * * 2.0190 4.56TENURE 0.0570 * * 0.0267 4.55FRISK 0.3071 * * * 0.0692 19.67SIZE 20.4710 * * * 0.1163 16.41LEV 0.0038 0.0068 0.31CLEV 20.0189 0.1391 0.02RETURN 20.1800 0.2737 0.43LDISTRESS 0.6623 * 0.4024 2.71INVEST 21.2595 0.8223 2.35FEERATIO 0.8203 0.5938 1.91SCFO 21.2163 * 0.6272 3.76PRIOR 1.8439 * * 0.7959 5.37BIG_N 20.6020 * * 0.2984 4.07LEADER 20.1912 0.4567 0.18INDUSTRY 0.6559 * * 0.3007 4.76

Log likelihood 594.416

Panel B: switching clients (n ¼ 205)Intercept 10.7286 7.7614 1.91TENURE 20.1666 0.4192 0.16FRISK 0.4614 * * 0.2031 5.16SIZE 20.7299 * 0.4305 2.87LEV 20.0205 0.0200 1.05CLEV 0.1401 0.3529 0.16RETURN 20.8198 0.7122 1.33LDISTRESS 0.1693 1.3866 0.01INVEST 1.0830 2.1641 0.25FEERATIO 23.2259 2.2570 2.04SCFO 3.2308 2.7457 1.38PRIOR 2.1499 * * 1.0357 4.31BIG_N 21.6093 1.0410 2.39LEADER 29.4295 293.4000 0.00INDUSTRY 0.6150 0.8476 0.53

Log likelihood 85.751

Panel C: matched non-switching clients (n ¼ 1,545)Intercept 3.8100 * 2.1499 3.14TENURE 0.0570 * 0.0295 3.74FRISK 0.2864 * * * 0.0782 13.42SIZE 20.4556 * * * 0.1247 13.34LEV 0.0099 0.00741 1.78CLEV 20.1288 0.1627 0.63RETURN 20.1550 0.3196 0.24LDISTRESS 0.7063 * 0.428 2.72INVEST 21.7941 * 0.9389 3.65FEERATIO 1.353 * * 0.6602 4.20SCFO 21.9129 * * * 0.7395 6.69BIG_N 20.6204 * 0.3303 3.53LEADER 20.1675 0.4693 0.13

(continued )

Table III.Logistic regression –going-concern opinion

MAJ23,5

430

Dow

nloa

ded

by I

QR

A U

NIV

ER

SIT

Y A

t 04:

58 2

0 Se

ptem

ber

2014

(PT

)

significant negative coefficient, consistent with the expectation that larger firms willhave more opportunities to get out of financial difficulties, and thus be less likely toreceive a going-concern opinion. LDISTRESS and PRIOR both have positivelysignificant coefficients as per expectations, consistent with prior findings (DeFondet al., 2002; Choi and Doogar, 2005). Additionally, firms in the mining sector are alsofound to have a higher propensity to receive a going-concern opinion, consistent withmany firms in this sector being speculative or loss making firms.

Firms with larger investments (INVEST) and SCFO are less likely to receive agoing-concern opinion, as per expectations, as indicated with statistically significantnegative coefficients. Firms audited by an industry leader are found to have a lowerpropensity to receive a going-concern audit opinion, however, the coefficient estimatesare not significant at any meaningful level.

Discretionary accrualsTable IV presents the results of the model using DA as the proxy of audit quality.Again, Panel A provides the results for the full sample, with Panels B and C providingthe results for the switching and non-switching firms, respectively.

The main variable of interest in this study, TENURE, is both economically smalland statistically insignificant. This suggests that there is no significant change in auditquality over time, leading to our conclusion that there may be no need to rotateauditors. Results show that larger clients have higher levels of performance-matchedDA. Consistent with Johnson et al. (2002) and Ferguson et al. (2004), leverage ispositively related to the level of DA. There was a significant negative coefficient forcash flow from operations and for firms operating in the mining sector. Companies thatexperience higher growth in net assets were found to report lower levels of DA,although statistically insignificant. This may be similar to industry growth, although

VariableCoefficientestimate Std error Wald x 2

INDUSTRY 0.7044 * * 0.3304 4.55Log likelihood 507.451

Notes: GCO ¼ a þ b1TENURE þ b2FRISK þ b3SIZE þ b4LEV þ b5CLEV þ b6RETURN þb7LDISTRESS þ b8INVEST þ b9FEERATIO þ b10SCFO þ b11PRIOR þ b12BIG_N þb13LEADER þ b14INDUSTRY *, * *, * * * significant at the 10, 5 and 1 per cent levels, respectively.GCO is a dummy variable indicating if the firm received a going-concern opinion; TENURE is thenumber of continuous years the incumbent auditor has been with the client; FRISK is the clientfinancial risk as measured by the Zmijewski (1984) financial distress score; SIZE is measured as thenatural log of total assets; LEV is the ratio of liabilities to assets; CLEV is the percentage change inLEV during the year; RETURN is the percentage change in the book value of net assets over the year;LDISTRESS is a dummy variable indicating if the client was financially distressed in the previousyear; INVEST is investment securities measured by current assets less-current debtors and inventoryscaled by total assets; FEERATIO is fee dependence as measured by non-audit fees divided bynon-audit and audit fees paid to the incumbent auditor; SCFO is the net cash flows from operationsscaled by lagged total assets; PRIOR is a dummy variable indicating if the client received agoing-concern opinion in the prior year; BIG_N is a dummy variable indicating if the firm was auditedby a Big N auditor; LEADER is a dummy variable indicating if the audit firm is a leader in the firm’sindustry; and INDUSTRY is a dummy variable for firms in the mining sector Table III.

Audit firmrotation and

audit quality

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VariableCoefficientestimate Std error t-Stat

Panel A: full-sample (n ¼ 1750)Intercept 20.2259 * * * 0.0334 26.77TENURE 0.0000 0.0005 20.05FRISK 20.0114 * * * 0.0018 26.52SIZE 0.0134 * * * 0.0018 7.36LEV 20.0004 * 0.0002 21.88CLEV 0.0038 0.0032 1.20RETURN 20.0070 0.0065 21.08LDISTRESS 20.0238 * * * 0.0059 24.02INVEST 20.1559 * * * 0.0167 29.32FEERATIO 0.0075 0.0116 0.64SCFO 20.4625 * * * 0.0149 231.15PRIOR 0.0572 * 0.0337 1.70BIG_N 20.0117 * 0.0065 21.81LEADER 0.0053 0.0070 0.75INDUSTRY 20.0131 * * 0.0054 22.41Adjusted R 2 0.3796

Panel B: switching clients (n ¼ 205)Intercept 20.3674 * * * 0.1267 22.90TENURE 0.0036 0.0030 1.21FRISK 20.0298 * * * 0.0059 25.05SIZE 0.0199 * * * 0.0069 2.90LEV 0.0003 0.0006 0.56CLEV 0.0140 0.0096 1.46RETURN 20.0167 0.0180 20.93LDISTRESS 20.0495 * * * 0.0211 22.35INVEST 20.1736 * * * 0.0537 23.23FEERATIO 20.0254 0.0371 20.68SCFO 20.4301 * * * 0.0463 29.28PRIOR 0.1063 * * 0.0409 2.60BIG_N 20.0289 0.0216 21.34LEADER 0.0079 0.0247 0.32INDUSTRY 20.0201 0.0181 21.11Adjusted R 2 0.3472

Panel C: matched non-switching clients (n ¼ 1545)Intercept 20.2102 * * * 0.0342 26.14TENURE 20.0003 0.0005 20.65FRISK 20.0093 * * * 0.0018 25.11SIZE 0.0129 * * * 0.0019 6.86LEV 20.0004 * 0.0002 21.82CLEV 0.0023 0.0034 0.67RETURN 20.0061 0.0069 20.87LDISTRESS 20.0203 * * * 0.0061 23.33INVEST 20.1535 * * * 0.0175 28.77FEERATIO 0.0099 0.0123 0.80SCFO 20.4711 * * * 0.0157 230.02BIG_N 20.0117 * 0.0067 21.74LEADER 0.0031 0.0073 0.43

(continued )Table IV.OLS regression – DA

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Myers et al. (2003) and Blouin et al. (2005) did not find any significant relationshipbetween industry growth and DA. Firms audited by an industry leader are found tohave higher levels of DA but not at any meaningful level of significance.

Sensitivity analysisThe TENURE variable was replaced by two dummy variables indicating length oftenure greater than five and six years. Untabulated results are consistent with theearlier results, using both the propensity to issue a GCO and DA as proxies for auditquality. The implication of these results suggest that contrary to an argument formandatory audit firm rotation, the length of audit tenure does not have aneconomically or statistically significant effect on audit quality, as measured by thelevel of DA, and the propensity to issue a going-concern audit opinion increases withthe length of audit firm tenure.

Carson et al. (2006) report that since 2001 there has been an increase in the percentageof firms that receive a going-concern opinion. To test our results to the sensitivity ofchanges in audit behaviour, we included a dummy variable for firm years from 2001 tothe end of our sample period. Including this variable does not alter our results.

Conclusions and limitationsUsing two proxies for audit quality, being the propensity to issue a going-concern auditopinion and the level of DA, we find that audit quality is not negatively affected byaudit firm tenure. Using the propensity to issue a going-concern opinion, the length ofaudit tenure actually increases audit quality. However, when using the level of DA tomeasure audit quality there is neither an increase nor a decrease in audit qualityconditional on the length of auditor tenure. Given this result, we conclude that thereare minimal, if any, benefits of imposing mandatory audit firm rotation onto

VariableCoefficientestimate Std error t-Stat

INDUSTRY 20.0111 * 0.0057 21.95Adjusted R 2 0.3912

Notes: DA ¼ a þ b1TENURE þ b2FRISK þ b3SIZE þ b4LEV þ b5CLEV þ b6RETURN þb7LDISTRESS þ b8INVEST þ b9FEERATIO þ b10SCFO þ b11PRIOR þ b12BIG_N þb13LEADER þ b14INDUSTRY *, * *, * * * significant at the 10, 5 and 1 per cent levels, respectively.DA is a measure of discretionary accruals; TENURE is the number of continuous years the incumbentauditor has been with the client; FRISK is the client financial risk as measured by the Zmijewski (1984)financial distress score; SIZE is measured as the natural log of total assets; LEV is the ratio ofliabilities to assets; CLEV is the percentage change in LEV during the year; RETURN is the percentagechange in the book value of net assets over the year; LDISTRESS is a dummy variable indicating if theclient was financially distressed in the previous year; INVEST is investment securities measured bycurrent assets less-current debtors and inventory scaled by total assets; FEERATIO is fee dependenceas measured by non-audit fees divided by non-audit and audit fees paid to the incumbent auditor;SCFO is the net cash flows from operations scaled by lagged total assets; PRIOR is a dummy variableindicating if the client received a going-concern opinion in the prior year; BIG_N is a dummy variableindicating if the firm was audited by a Big N auditor; LEADER is a dummy variable indicating ifthe audit firm is a leader in the firm’s industry; and INDUSTRY is a dummy variable for firms in themining sector Table IV.

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Australian firms. Further, given the costs involved in switching auditor, it does notappear that mandatory audit firm rotation would be beneficial to the market. In orderto address the concerns that have arisen recently around auditor independence andaudit quality, other initiatives are more likely to have a greater impact than imposingmandatory audit firm rotation.

However, there are other potential benefits of mandatory audit firm rotation that wedo not consider in this context which may detract from the generalisation of our results.As indicated prior, audit quality can be divided into perceived audit quality and actualaudit quality (Taylor, 2005). This study only examines levels of actual audit quality.While we conclude that actual audit quality does not improve for firms that rotateauditor, the perception of audit quality may indeed have increased. Further research isrequired to investigate the perception of audit quality on mandatory audit firm rotation,as well as total audit quality combining both actual and perceived quality.

The proxies used in this study to measure audit quality, however, are not perfect.Proxies for audit quality can only be devised in most cases using publicly availableinformation, and not information known to the auditor. The first proxy used, that beingthe propensity to issue a going-concern report, attempts to capture the level ofindependence of an auditor. However, a weakness of this proxy is that the propensityto issue a going-concern report is conditional on a firm being in need of such a report.

The second proxy for audit quality, that being the level of DA, attempts to capturethe amount of influence management has over the auditor in the sense that firms withhigher levels of DA are more likely to be able to push the boundaries of generallyaccepted accounting principles by manipulating the accrual component of earnings. Inthe current study, a performance-matched modified Jones (1991) model has been usedto measure DA, which itself has received criticism in the literature. However, thismodel has been shown to outperform other attempts at estimating the level ofmanipulation in financial reporting through accruals.

Additionally, the signal that an audit firm switch sends to the market may be ofinterest to investors, and send a valuable signal which mandatory audit firm rotationwould remove. To fully understand the signal, information about the reasons for theswitch, and who instigated the switch, be it the client or the audit firm, would need tobe known. In the Australian environment, however, this information is not publiclyavailable. Alternatively, mandatory audit firm rotation may increase the perception ofaudit quality, which in and of itself is an important component to the efficientoperations of financial markets.

Notes

1. Calculated as per Carcello et al. (1995): FRISK ¼ 24.803 2 3.6 (net profit/total assets) þ5.4(total liabilities/total assets) 2 0.1 (current assets/current liabilities).

2. The measure of financial distress employed is negative cash flows from operations and/or aloss after abnormal items.

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