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Managerial Auditing JournalEmerald Article: Earnings management and the audit opinion: evidence from MalaysiaShireenjit Johl, Christine A. Jubb, Keith A. Houghton
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To cite this document: Shireenjit Johl, Christine A. Jubb, Keith A. Houghton, (2007),"Earnings management and the audit opinion: evidence from Malaysia", Managerial Auditing Journal, Vol. 22 Iss: 7 pp. 688 - 715
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Earnings management andthe audit opinion: evidence
from MalaysiaShireenjit Johl
School of Accounting and Law, RMIT University, Melbourne, Australia
Christine A. JubbDeakin Business School, Deakin University, Malvern, Australia, and
Keith A. HoughtonCollege of Business and Economics, Australian National University,
Australian Capital Territory, Australia
Abstract
Purpose – This study aims to examine auditor reporting behaviour in the presence of aggressiveearnings management (EM) in the context of the Asian Economic Crisis as it affected Malaysia. In thevein of Bartov, Gul and Tsui, the interaction between discretionary or abnormal accruals and auditquality (AQ), as indicated by auditor size and auditor industry specialisation, is examined.
Design/methodology/approach – A logistic regression model adapted from various prior studiesis utilised to test the hypotheses.
Findings – As per earlier findings using Western data, Big 5 auditors in Malaysia appear to qualifymore frequently than their non-Big 5 counterparts when high levels of abnormal accruals are present.However, the interaction between auditor industry specialisation and abnormal accruals is notsignificant in predicting the incidence of qualification.
Originality/value – This study extends the current literature on AQ differentiation and specificallyit attempts to address the gaps in the literature with respect to auditor reporting behaviour in thepresence of aggressive EM. In addition, this study provides additional evidence on Big 5/industryspecialist quality differentiation in an emerging market (an under-researched area), Malaysia,arguably with less transparent and weaker governance structures than the developed economies suchas the USA, UK, and Australia.
Keywords Auditing, Earnings, Malaysia, Quality
Paper type Research paper
IntroductionAuditors play a vital role in ensuring the maintenance and issuance of high-qualityfinancial reports. The question of whether auditors adequately play this role insafeguarding accounting information by ensuring credible reporting has recentlyreceived much attention. This attention has focused on Asia and the 1997 Asian Crisis,and more recent (2001) very public collapses of two corporations, Enron in the USAand HIH in Australia. Against this backdrop, this paper investigates in the emergingmarket of Malaysia an aspect of audit quality (AQ) product differentiation inassociation with financial reporting discretion – audit outcome (audit opinion) andearnings management (EM).
Auditors are usually placed under increased strain and public scrutiny duringeconomic crises due to increased likelihood of corporate failure. During the Asian
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Managerial Auditing JournalVol. 22 No. 7, 2007pp. 688-715q Emerald Group Publishing Limited0268-6902DOI 10.1108/02686900710772591
Crisis, the World Bank questioned the quality of audits by Big 5 auditors operating inAsia, in that many East Asian corporations, having received clean audit reports fromBig 5 auditors, subsequently demonstrated that those opinions might have not beenappropriate (Accountancy, 1998a, b). Based on the notion of a differentiated auditproduct, the empirical issue examined in this paper is whether Big 5 auditors/industryspecialist auditors more frequently issue qualified audit opinions as the level ofaggressive abnormal accruals increases ceteris paribus, compared to other auditors.
Specifically, this paper argues that aggressively high levels of absolute abnormalaccruals, as can be expected in periods of economic crisis and have been found to bepresent in the context of the Asian crisis (Johl et al., 2003), should be associated withaudit opinion qualification, contingent on AQ. Although there are several publishedstudies that examine audit opinions in various settings (e.g. auditor switching,audit-related litigation, financial distress, etc.), few studies (Francis and Krishnan, 1999;Bartov et al., 2000; Bradshaw et al., 2001) examine the likelihood of a company receivinga qualified audit report in association with the level of accruals or abnormal accruals.These studies, all using US data, find a positive association between abnormal (andtotal) accruals and qualifications. However, only Bartov et al. (2000) examines Big 5differential quality by including an interaction between Big 5 and abnormal accruals.The interaction variable is found not significant and the authors attribute the result tothe small number of sample companies with non-Big 5 auditors. This study tackles thisproblem by using a matched-pair sample – matching amongst other things on auditorsize. In Malaysia, the non-Big 5 audit a similar proportion of listed companies (about20 per cent) to that featured in some US studies (e.g. about 17 per cent in Becker et al.(1998)) and so this setting is appropriate to compare with prior results.
This study contributes to the literature by testing the issue in a different, emergingeconomy, institutional setting. In addition, given that both auditor and auditee take theother’s presence into account (Hansen and Watts, 1997), this study utilises two models –the qualification (QUAL) model with audit opinion as the dependent variable, and theEM model with absolute abnormal accruals as the dependent variable, to test therelationship between each of audit opinion and abnormal accruals with AQ.
The remainder of this paper is organised as follows. The next section discussesbriefly the Malaysian corporate and regulatory background, followed by discussion ofthe relevant audit literature and hypotheses development. The fourth and fifth sectionsdiscuss the model development, the selection and measurement of variables andsample selection and information regarding data collection is discussed. Results arethen reported with conclusions, implications, limitations and ideas for further researchappearing in the last section.
BackgroundMalaysia is argued here to provide a setting “less transparent with low levels of publicscrutiny” compared to the West, in which to test the propensity of auditors to issue aqualified audit opinion when EM is not constrained. It is a country where reporting andauditing practices are heavily influenced by common-law sources given their historicalinfluence in the setting of International Financial Reporting Standards andInternational Standards on Auditing (ISAs), facilitating comparison with researchresults in the Western World. However, although there has been much emphasis onstrengthening the accounting and disclosure standards in Malaysia, the same perhaps
Earningsmanagement andthe audit opinion
689
cannot be said with respect to auditing practices (Thillainathan, 1999). Effort has beenmade by the International Federation of Accountants (IFAC) to improve the uniformityof auditing practices and related services throughout the world. This is evidenced bythe formation of the IFAC Forum of Firms (FOF) and the Transnational AuditorsCommittee (TAC) in January 2001. The FOF is a voluntary body made up ofinternational audit firms performing audits across national borders. These firms agreeto meet certain requirements and undergo a global independent quality review[1]. TACis an executive committee of IFAC devoted to representing and meeting the needs ofthe members of FOF. It plays a major role in encouraging member firms to meet highstandards in the international practice of auditing.
With respect to the market for audit services in Malaysia, as of 1998, 83 per cent ofpublic companies were audited by the then Big 5. An important feature of the Big 5operating in Malaysia is the existence of link-ups with local counterparts. It isimportant to note here, that for the purposes of this study, these local affiliated firmsare categorised as Big 5 auditors.
The Financial Statements Review Committee established under the MalaysianInstitute of Accountants (MIA) undertakes an annual review of published accounts toensure compliance with legal and professional requirements. However, the work of thiscommittee is said to be very limited with it reviewing no more than 25 annual reportsin any one year (Tay, 1995). Further, the results of the review are not made public andso are without scrutiny by legal, financial or public oversight. To date there are noreported cases of disciplinary action against members by the MIA (Tay, 1995).
Also, there has been no litigation against auditors within Malaysia.Favere-Marchesi (2000) analyses AQ in ASEAN countries based on the legalenvironment faced by auditors in those countries. The study notes the existence ofdifferential AQ among the ASEAN countries, with auditor independence seriouslycompromised in some countries (e.g. Brunei, Vietnam and Philippines) and the lack of aliability regime faced by auditors. With respect to Malaysia, the study notesimprovements for statutory auditors are required, including the mandating of aproficiency examination and the expansion of civil liability.
Hence, reputational damage resulting from publicity with respect to either litigationor malpractice is not of the same importance in Malaysia as in Western countries. It isof importance to investigate whether Western indications that auditors issue deservedqualified audit opinions when abnormal EM is present, continue to hold given thislower external discipline and monitoring of auditors.
Literature review and hypothesis developmentTo date, there are limited published studies examining the association between EMmeasured by abnormal accruals and the issuance of audit qualifications, Bartov et al.,2000, discussed earlier, is an important exception. Also of relevance are Francis andKrishnan (1999) and Bradshaw et al. (2001), which examine the relationship betweentotal accruals and audit opinion. Francis and Krishnan (1999) argue that becauseaccounting accruals are managers’ subjective estimates of future outcomes, and assuch cannot be confirmed objectively pre-occurrence, audits of high-accruals auditeesexhibit greater uncertainty than audits of low-accruals auditees. Given the underlyingaudit risk, auditors lower their issuance of a qualified opinion threshold for thishigh-accrual group of auditees. Consistent with their argument, Francis and Krishnan
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in a US setting find that high-absolute accruals auditees are more likely to receive amodified[2] audit report than low-absolute accruals auditees, with relative evidence ofreporting conservatism by the then Big 6 auditors. Their evidence is strongest forcompanies with abnormally large negative accruals.
On a similar issue, but with a slightly different rationale, Bradshaw et al. (2001) findthat high-positive accruals auditees are more likely to be subject to SEC enforcementfor GAAP violations. Because auditors are expected to issue an opinion with respect tofinancial statement conformity with GAAP, Bradshaw et al. (2001) argue that auditeesreporting high (positive) accruals should more frequently receive modifying auditopinions than those with low-accruals. However, they hypothesise that becauseauditors are poor users of accruals information, they are not likely to issue modifiedaudit opinions for auditees with high-levels of accruals. They find support for theirhypothesis and conclude that auditors fail to communicate to investors problemsarising from high-accruals reporting with respect to future earnings.
Because total accruals is a function of both actual (non-discretionary) and abnormal(discretionary) accruals, it can be inferred that high-total accruals should be associatedwith high-abnormal accruals – an indirect inference to EM. However, this inferencemay not hold in all circumstances and therefore may not demonstrate the ability ofauditors to constrain use of a technique most suited to measuring EM – the level ofabnormal accruals. Bartov et al.’s (2000) objective is to evaluate the ability of thevarious accruals models to detect EM by examining the association between abnormalaccruals and audit qualifications. They assert that qualified audit reports are issuedbecause of scope limitation and departures from GAAP and therefore are likely to beassociated with EM, in that a positive relationship is expected between thesephenomena but this is contingent on AQ. They find a positive relationship (only twomodels exhibit significant coefficients) between audit qualification and abnormalaccruals, whilst the interaction term between abnormal accruals and Big 5 is notsignificant in any of the models[3].
Regardless of the reason for the observance of abnormally high-abnormal accruals,ideally their presence should be accompanied by an audit qualification. Typically (atthe time the data were collected for this paper) there were three forms of qualifiedopinion in Malaysia – “except for”; adverse; and disclaimer opinions. These wereissued, depending on materiality, on grounds such as:
. limitation of scope of the audit;
. disagreement with management regarding the financial report (includinginherent uncertainty not adequately disclosed); and
. a limitation on the scope of the audit (ISA 700[4]), respectively.
It is important to note here that although ISA 700 – The Auditor’s Report on FinancialStatements was issued in 1996, it was mandatory for all MIA members to observe withrespect to audits commencing on or after July 1998. Prior to this date, there were fourforms of qualified opinion – subject to; except for; adverse; and disclaimer opinionarising from circumstances such as those mentioned earlier and inherent uncertainty(e.g. going concern). Emphasis of mater paragraphs can be included in any of thesetypes of qualifications, but do not, in themselves, constitute a qualification.
It is acknowledged that companies with audit qualifications may have a high levelof abnormal accruals for justifiable reasons such as company performance and
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691
troubled-company incentives, reasons that are more relevant in the crisis andpost-crisis periods of the study[5]. Notwithstanding this possible bias, and based on thenotion of a differentiated audit product, it is expected that Big 5/industry specialistauditors will more frequently issue qualified audit opinions as the level of unjustifiablyhigh-abnormal accruals increases ceteris paribus, compared to other auditors. Theforegoing discussion and rationale leads to the following hypothesis[6]:
H1a. The level of absolute abnormal accruals and audit qualification incidence ispositively associated, irrespective of the macroeconomic period in the crisiscycle, ceteris paribus.
H1b. The level of absolute abnormal accruals and audit qualification incidence isassociated in interaction with the Big 5 (industry specialist), irrespective of themacroeconomic period in the crisis cycle, ceteris paribus.
MethodologyPre-requisite to the testing of hypotheses is the determination of the variable “earningsmanagement”. This study utilises the modified (m) Jones (1991) (Dechow et al., 1995)[7]model in decomposing total accruals into non-discretionary (expected) anddiscretionary (unexpected or abnormal) accruals. Since, this study involves periodsof economic upturn and downturn, it is likely that companies in the sample willexperience extreme negative earnings in periods of downturn. The Jones (1991) modelhas reduced reliability in such a situation, so an alternative methodology forcalculating abnormal accruals is used. In this alternative design, each non-Big 5auditee is matched to a Big 5 auditee from the same year, industry, and withcomparable earnings performance (return on sales). This approach is used by Teohet al. (1998a, b) and with a slight variation, by Kothari et al. (2005). As with most priorresearch involving EM, this study, utilises the cross-sectional method rather than thetime-series version of the Jones model (Francis et al., 1999; Becker et al., 1998; DeFondand Jiambalvo, 1994)[8].
Modified Jones modelThe cross-sectional version of the m-Jones (1991) model is estimated separately for allfirms in each same industry. An advantage of using the cross-sectional approach, sincethe models are re-estimated each year, is that specific year changes in economicconditions affecting expected accruals are filtered out. This filtering is vital since theperiod of examination covers changes in firm and macroeconomic condition (Teoh et al.,1998a, b). The total accruals model, with company (i ) and year (t) subscripts, is:
TAit
Ai;t21¼ a
1
Ai;t21
� �þ b1
{DREVit 2 DRECit}
Ai;t21
� �þ b2
PPEit
Ai;t21
� �þ 1it ð1Þ
where, TAit ¼ total accruals at time t is calculated as: [(Dcurrent assetsit – Dcashit) –(Dcurrent liabilitiesit – Dshort-term debtit) – (depreciation and amortisation expenseit),where D denotes the change between t and t 2 1[9]; Ai,t21 ¼ lagged (one year)total assets; DREVit ¼ change in operating revenues between t and t 2 1;DRECit ¼ change in net receivables between t and t 2 1; PPEit ¼ gross property,plant and equipment; and 1it ¼ error term (known as discretionary, unexpected orabnormal accruals (DA)).
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692
The modelH1a and H1b investigate the issue of whether ceteris paribus, the presence ofhigh-abnormal accruals is accompanied by an audit qualification and whether thisoutcome is contingent on the quality of the auditor. As such, the logistic regressionmodel adapted from various prior studies (Bradshaw et al., 2001; Bartov et al., 2000;Monroe and Teh, 1993; Dopuch et al., 1987) is utilised to test H1.
Most of these studies (Dopuch et al., 1987; Monroe and Teh, 1993) predict all types ofuncertainty qualifications (but exclude “except for” and “adverse opinions”), one studypredicts all types of qualification (Bradshaw et al., 2001) and one study (Bartov et al.,2000) predicts only scope limitation and disagreement types of opinion. In addition, ofall these studies, only two include a variable for either total accruals (Bradshaw et al.,2001) or abnormal accruals (Bartov et al., 2000). Like Bradshaw et al. (2001) this studydoes not attempt to discriminate between different types of audit qualifications (goingconcern, scope limitation or disagreement).
One possible limitation of taking all audit qualifications into account is that theobservance of an audit qualification, particularly a going concern qualification, maynot be associated with EM. One way to overcome this identification problem would beto select observations with an audit qualification that arises from scope limitations anddepartures from GAAP. However, the number of opinions in the sample period citingsuch reasons is too small to draw any statistical inferences. Not withstanding thislimitation, to the extent that financial health is successfully controlled for, it is possibleto investigate any differential propensity to render qualified opinions in the context ofEM. The qualification model takes the following form:
QUAL ¼ aþ b1AQ1 þ b2iMKTCAP þ b3BKMKTi þ b4LOSSi þ b5DEi
þ b6QUALGi þ b7LASSETi þ b8TIMEi þ b9INVTAi þ b10RECTAi
þ b11ABDAi þ b12ABDA*AQi þ 1i
where the variables are defined in Table I and explained in the next section.
Selection and measurement of variablesThe QUAL modelDependent variable. Receipt of an audit QUAL by a firm is the dependent variable intesting H1a and H1b. QUAL is given a value of 1 if the auditee receives an auditqualification of any type in the current year and 0 otherwise (i.e. a clean or unqualifiedopinion is rendered).
Hypothesis variables. Absolute abnormal accruals ABDA is the first hypothesisvariable for testing of H1a. It is expected that higher levels of absolute abnormal accrualsare associated with an increased tendency for auditors to render a qualified audit opinion.This variable is the absolute value of the residual obtained from the m-Jones (1991) modeland so is continuous.
The second hypothesis variable of interest for testing H1b is the interaction termbetween absolute discretionary accruals and each of (separately) the two measures ofAQ, (ABDA *BIG5/ABDA *INDSPEC). Similar to H1a, a positive relationship is
Earningsmanagement andthe audit opinion
693
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Table I.Variables and predicteddirection for auditqualification (QUAL)model
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694
expected between QUAL and ABDA *AQ, in that a higher quality auditor is likely to bemore conservative and thus more likely to qualify when EM is high.
Audit quality. The ability to detect and willingness to report materialmanipulation/misstatements giving rise to material uncertainties or/and goingconcern problems is dependent on auditor quality. Consistent with previous auditqualification studies (Monroe and Teh, 1993; Mutchler et al, 1997; Lennox, 1999;Bartov et al., 2000; Bradshaw et al., 2001), AQ is included in the QUAL model to proxyfor AQ and to account for differing levels of expertise and reputation. Two differentproxies namely Big 5 and industry specialist are used. Given that Big 5 (or industryspecialist auditors) are seen as being higher quality, these auditors are expected toqualify more frequently than the non-Big 5 (or non-industry specialist), ceteris paribus.Thus, it is expected that there is a positive relationship between AQ and QUAL.
Control variables. Financial characteristics (MKTCAP, BKMKT, LOSS, DE,LASSET, QUALAG and TIME). Seven financial characteristic variables – marketcapitalisation (MKTCAP), book to market value (BKMKT), current year losses (LOSS),leverage (DE), total assets (LASSET), and number of years listed on the stock exchange(TIME) are included (Dopuch et al., 1987; Monroe and Teh, 1993; Bartov et al., 2000;Bradshaw et al., 2001). These financial ratios reflect the operational complexity,litigation risk, profitability and financial condition of the company.
As in Bartov et al. (2000) MKTCAP is included in the QUAL model to reflect theoperational complexity of the company, whilst the BKMKT reflects the company’slitigation risk and growth options, and a positive relationship is expected for both ofthese variables with QUAL. DE, and LOSS variables are included as indicators of theauditee’s financial health, and LASSET controls for size. DE reflects the leverage of thecompany and is a measure of financial risk and long-term solvency position of the firm.This variable was found important from an auditor’s point of view in Mutchler’s (1985)study and Levitan and Knoblett (1985) and Carcello et al. (2000) found this variablesignificant in models predicting audit qualification. Consistent with prior studies, DE isexpected to have a positive relationship with QUAL indicating that as financial riskincreases, higher qualification rates are expected. Current year loss, LOSS, is said toindicate a possible “sick” company or poor financial health (Monroe and Teh, 1993).LOSS was found significant in Dopuch et al. (1987). LOSS is given a value of 1 if theauditee experiences a negative profit in the current year and a positive coefficient forthis variable is predicted. LASSET is included in the QUAL model for the possibility oftwo conflicting reasons. Lys and Watts (1994) argue that larger firms are assumed toproduce more information asymmetries, which provide management with greaterdiscretion over decisions that are inadequately captured by the organization’s controls.Conversely, Monroe and Teh (1993) argues that size represents a firm’s financial healthand as such larger firms are generally seen to be healthy, making it more unlikely thata given uncertainty will be material. Owing to the possible above ambiguousrelationship between audit qualification and size, the direction of the association is notpredicted.
Prior studies (Mutchler, 1985; Bell and Tabor, 1991; Monroe and Teh, 1993; Lennox,1999) include QUALAG, finding that the prior year’s audit opinion is a useful decisiontool in predicting current year opinion. Consistent with these studies, QUALAG isincluded and is given a value of 1 if a qualification of any type was given in theprevious year, else 0. The coefficient for QUALAG is predicted to be positive indicating
Earningsmanagement andthe audit opinion
695
that a firm receiving a qualified opinion in the previous year is likely to receive aqualified opinion in the current year.
Time listed, TIME, is included to capture the probability of a firm remaining agoing concern for the next 12 months (Mutchler, 1985; Dopuch et al., 1987) becauseyounger firms are more likely to experience financial distress and may struggle tosurvive (and are possibly more likely to indulge in EM). Consequently, it is expectedthese younger firms will receive qualified opinions more frequently (Dopuch et al.,1987; Monroe and Teh, 1993). The TIME variable is a continuous variable – thenumber of years the company has been listed on the Kuala Lumpur Stock Exchange(KLSE).
Audit difficulty (RECTA and INVTA). Similar to prior studies (Bell and Tabor, 1991;Dopuch et al., 1987; Monroe and Teh, 1993), receivables as a proportion of total assets,RECTA, and inventory as a proportion of total assets, INVTA, are included to controlfor audit effort and risk. A positive relationship is predicted between these variablesand QUAL.
Sample selection and data collectionThe data are primarily hand-collected from annual reports of companies listed on theKLSE[10] covering financial periods between 1994 and 1999, where 1994-1996 isdeemed the pre-crisis period, 1997-1998 the crisis, and 1999 post-crisis. Annualreports are available in the KLSE and the Securities Commission (SC) library. Inaddition, incomplete and other required data were supplemented from other sourcesincluding:
. KLSE on disk.
. KLSE Handbook.
. Corporate Handbook.
. KLSE-RIAM online database.
. Worldscope database[11].
. Che Ahmad and Houghton’s (2001) dataset[12].
. Investor Digest.
The initial population from which the matched-pair sample is chosen comprisescompanies listed on the KLSE for years 1993-1999 since lagged variables are required.To be included companies had to report in Malaysian Ringgit, be audited by aMalaysian-based auditor; in an industry other than finance related and unit trustsectors[13]; in existence in all or any of the years 1993 through 1999 with all financialreport data including auditor data available; not newly listed (IPO) (since differentiallevels of EM are expected within these companies); and without a change in financialyear-end.
From the initial 1,512 observations meeting the data requirements, 298 pairs (596observations) are used for the performance matched-pair sample used in this study.The matching is performed first on year, second on industry, third on auditor size(Big5/non-Big 5) and fourth on return on sales. The sample size at various stages ofdata collection is presented in Table II.
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696
ResultsAudit qualification summaryPanel A of Table III presents the frequency of type of audit opinion rendered byauditors, Big 5 and non-Big 5 for the pooled years – 1994 to 1999, whilst Panels B-Dpresent the type of audit opinion frequencies by macroeconomic period – pre-crisis,crisis and post-crisis. Although only the matched pair sample is used for hypothesestesting and for the multivariate analyses, descriptives are provided also for the totalsample.
The descriptive analyses from Table III provide three major findings. First, only afraction – 4.22 per cent (4.82 per cent) of the matched pair (total) sample receive aqualified opinion over the seven years, and a substantial number of these qualifiedopinions are received during periods of economic/financial distress – the crisis andpost-crisis periods. For example, during the pre-crisis period only 0.92 per cent(1.50 per cent) of the matched pair (total) opinions issued are qualified as opposed to6.36 per cent (7.43 per cent) post-crisis and 6.02 per cent (6.83 per cent) crisis. As onewould expect, the frequency of the matched pair (total) except for/subject to typeopinion is greater than the adverse or disclaimer type opinion. Second, auditees withBig 5 auditors receive qualified opinions more frequently than non-Big 5 auditees. Big5 auditors issued 72 per cent of the matched pair qualified opinions over the sevenyears. In addition, of all opinions rendered, 6.06 per cent (5.46 per cent) of the matchedpair (total) Big 5 auditees had a qualified opinion compared with 2.36 per cent(2.29 per cent) for their non-Big 5 counterparts (and the test of proportion shows asignificance of z , 0.01). This finding is consistent for both crisis and post-crisisperiods, in that 9.09 per cent (9.02 per cent) of the matched pair Big 5 clients had aqualified opinion compared to 3.64 per cent (3.01 per cent) of the non-Big 5 auditeespost-crisis (crisis). Third, there appears frequent use of emphasis of matter unqualifiedopinions, especially in the crisis (1998) and post-crisis periods. For example,2.35 per cent of the matched pair opinions rendered over the seven-year period arerelated to emphasis of matter type of opinion.
No. of valid casesa
Selection criteria 1994 1995 1996 1997 1998 1999 Total
Approximate number of KLSE listed companies 478 529 621 708 736 757 3,351Less: finance/trust companies 47 47 56 61 63 63 290Less companies with incomplete financialdata and unavailable annual reportsb 280 285 278 316 334 416 1,478Less: IPO companies 2 11 15 14 2 2 46Less companies with change in financial year end – 1 2 4 5 7 19Usable sample (calculation of abnormal accruals) 149 185 270 314 332 270 1,520Less companies with incomplete auditor data 1 2 1 3 – 1 8Total sample 148 183 269 311 332 269 1,512Matched sample (by non-Big 5/Big 5, year,industry and return on sales)
48 60 110 132 136 110 596
Notes: Complete data were also collected for year 1993 (151 observations) as some variables requirelagged data. aIncludes both Main Board and Second Board of the KLSE with about 85 per cent of theobservations being from the Main Board (companies on the Main Board are larger in size); bdue to latereporting for year 1999 and missing reports in the KLSE library
Table II.Sample selection criteria
Earningsmanagement andthe audit opinion
697
Tot
alsa
mp
leM
atch
edp
air
sam
ple
Tes
tof
pro
por
tion
(z-v
alu
e)
Op
inio
nty
pe
Tot
al(p
erce
nt)
Big
5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Tot
al(p
erce
nt)
Big
-5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Tot
alsa
mp
leM
atch
edp
air
sam
ple
Panel
A:
Ove
rall
freq
uen
cyof
type
ofaudit
opin
ion
(1994-1
999)
Not
mat
eria
lan
dp
erv
asiv
e(e
xce
pt
for/
sub
ject
to)
45(2
.97)
38(3
.15)
7(2
.29)
18(3
.04)
11(3
.70)
7(2
.36)
4.65
6(0
.000
)0.
950
(0.3
42)
Mat
eria
lan
dp
erv
asiv
e(a
dv
erse
/dis
clai
mer
)28
(1.8
5)28
(2.3
2)0
(0.0
0)7
(1.1
8)7
(2.3
6)0
(0.0
0)5.
316
(0.0
00)
2.65
4(0
.008
)T
otal
qu
alifi
ed73
(4.8
2)66
(5.4
6)7
(2.2
9)25
(4.2
2)18
(6.0
6)7
(2.3
6)6.
990
(0.0
00)
2.22
3(0
.026
)U
nq
ual
ified
:em
ph
asis
ofm
atte
r46
(3.0
4)37
(3.0
6)9
(2.9
4)14
(2.3
5)6
(2.0
1)8
(2.6
8)4.
355
(0.0
00)
20.
538
(0.5
91)
Tot
alu
nq
ual
ified
1,44
1(9
5.18
)1,
142
(94.
54)
299
(97.
71)
568
(95.
78)
279
(93.
94)
289
(97.
64)
30.7
24(0
.000
)2
0.58
0(0
.562
)O
ver
all
tota
l(N
)1,
514
1,20
830
659
329
729
6
Panel
B:
Pre
-cri
sis
freq
uen
cyof
type
ofaudit
opin
ion
(1994-1
996)
Not
mat
eria
lan
dp
erv
asiv
e(e
xce
pt
for/
sub
ject
to)
7(1
.16)
6(1
.23)
1(0
.88)
2(0
.92)
1(0
.92)
1(0
.93)
1.89
5(0
.058
)0.
000
(1.0
00)
Mat
eria
lan
dp
erv
asiv
e(a
dv
erse
/dis
clai
mer
)2
(0.3
2)2
(0.4
1)0
(0.0
0)0
(0.0
0)0
(0.0
0)0
(0.0
0)1.
415
(0.1
57)
N/A
Tot
alq
ual
ified
9(1
.50)
8(1
.64)
1(0
.88)
2(0
.92)
1(0
.92)
1(0
.93)
2.34
2(0
.019
)0.
000
(1.0
00)
Un
qu
alifi
ed:
emp
has
isof
mat
ter
4(0
.67)
4(0
.82)
0(0
.00)
0(0
.00)
0(0
.00)
0(0
.00)
N/A
N/A
Tot
alu
nq
ual
ified
592
(98.
50)
479
(98.
36)
113
(99.
12)
215
(99.
08)
108
(99.
08)
107
(99.
07)
21.1
21(0
.000
)0.
096
(0.9
24)
Ov
eral
lto
tal
(N)
601
487
114
217
109
108
Panel
C:
Pos
t-cr
isis
freq
uen
cyof
type
ofaudit
opin
ion
(1999)
Not
mat
eria
lan
dp
erv
asiv
e(e
xce
pt
for/
sub
ject
to)
9(3
.35)
7(3
.33)
2(3
.39)
4(3
.64)
2(3
.64)
2(3
.64)
1.68
1(0
.093
)0.
000
(1.0
00)
Mat
eria
lan
dp
erv
asiv
e(a
dv
erse
/dis
clai
mer
)11
(4.0
9)11
(5.2
4)0
(0.0
0)3
(2.7
3)3
(5.4
5)0
(0.0
0)3.
351
(0.0
00)
1.74
4(0
.081
)T
otal
qu
alifi
ed20
(7.4
3)18
(8.5
7)2
(3.3
9)7
(6.3
6)5
(9.0
9)2
(3.6
4)3.
646
(0.0
00)
1.15
2(0
.249
)U
nq
ual
ified
:em
ph
asis
ofm
atte
r20
(7.4
3)13
(6.1
9)7
(11.
86)
9(8
.18)
3(5
.45)
6(1
0.91
)1.
635
(0.1
02)
21.
021
(0.3
07)
(con
tinued
)
Table III.Audit qualificationfrequencies
MAJ22,7
698
Tot
alsa
mp
leM
atch
edp
air
sam
ple
Tes
tof
pro
por
tion
(z-v
alu
e)
Op
inio
nty
pe
Tot
al(p
erce
nt)
Big
5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Tot
al(p
erce
nt)
Big
-5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Tot
alsa
mp
leM
atch
edp
air
sam
ple
Tot
alu
nq
ual
ified
249
(92.
57)
192
(91.
43)
57(9
6.61
)10
3(9
3.64
)50
(90.
91)
53(9
6.36
)11
.827
(0.0
00)
20.
405
(0.6
85)
Ov
eral
lto
tal
(N)
269
210
5911
055
55
Panel
D:
Cri
sis
–fr
equen
cyof
type
ofaudit
opin
ion
(1997-1
998)
Not
mat
eria
lan
dp
erv
asiv
e(e
xce
pt
for/
sub
ject
to)
29(4
.50)
25(4
.89)
4(3
.01)
12(4
.51)
8(6
.02)
4(3
.01)
3.94
4(0
.000
)1.
168
(0.2
42)
Mat
eria
lan
dp
erv
asiv
e(a
dv
erse
/dis
clai
mer
)15
(2.3
3)15
(2.9
4)0
(0.0
0)4
(1.5
0)4
(3.0
1)0
(0.0
0)3.
896
(0.0
00)
2.00
8(0
.045
)T
otal
qu
alifi
ed44
(6.8
3)40
(7.8
3)4
(3.0
1)16
(6.0
2)12
(9.0
2)4
(3.0
1)5.
522
(0.0
00)
2.03
1(0
.042
)U
nq
ual
ified
:em
ph
asis
ofm
atte
r22
(3.4
2)20
(3.9
1)2
(1.5
0)5
(1.8
7)3
(2.2
4)2
(1.4
9)3.
871
(0.0
00)
0.44
9(0
.653
)T
otal
un
qu
alifi
ed60
0(9
3.17
)47
1(9
2.17
)12
9(9
6.99
)25
0(9
3.98
)12
1(9
0.98
)12
9(9
6.99
)19
.074
(0.0
00)
20.
693
(0.4
88)
Ov
eral
lto
tal
(N)
644
511
133
266
133
133
Notes:
Of
the
qu
alifi
edop
inio
ns
88.8
8p
erce
nt
(95.
89p
erce
nt)
,fr
omth
em
atch
ed-p
air
(tot
al)
sam
ple
isin
her
ent
un
cert
ain
ty–
goi
ng
con
cern
typ
eof
qu
alifi
cati
on
Table III.
Earningsmanagement andthe audit opinion
699
Panel A of Table IV provides an overall descriptive summary in relation to abnormalaccruals by type of audit qualification for the matched-pair sample. Panels B-D of thetable present the same categories of descriptives based on macroeconomic periods.Analysis from Table IV provides five main findings. First, overall, on average, theabsolute abnormal accruals (deflated by total assets) for observations receiving aqualified opinion is 0.185, being higher than for those with unqualified opinions (0.114).Although not so for the pre-crisis, this finding is evident also in both the crisis andpost-crisis periods.
Second, the gross/signed abnormal accruals for qualified opinions is negative(20.131), whilst positive (0.014) for unqualified opinions pooled across the seven yearsof study. Examining by macroeconomic period, both the post and crisis periods displaynegative abnormal accruals as opposed to positive abnormal accruals for theunqualified sample. These findings seem to indicate that qualified opinions issuedduring the post and crisis periods are largely associated with negative abnormalaccruals indicating possible “big-bath” activity that is most likely to be financialdistress/performance related.
Third, with regards to differential AQ, Big 5 auditees (0.214) receiving qualifiedopinions have higher, and weakly significant ( p , 0.10) absolute abnormal accrualscompared to non-Big 5 qualified auditees (0.109). For unqualified opinions rendered,clients of Big 5 auditors (0.105) have lower absolute abnormal accruals compared toclients of non-Big 5 auditors (0.124), and the difference in the mean between these twotype of opinions is significant at p , 0.10 level on a one-tailed test. A similar result isobserved during the pre-crisis (caution is needed because only two observations arequalified), crisis (but insignificant) and post-crisis (significant at p , 0.05 level)periods. Taken together, the findings indicate a differential level of AQ displayed byauditors contingent on auditor size.
Fourth, of the total number of qualified opinions issued over the period of study,64 per cent are related to observations for which debt restructuring subsequentlyoccurred. The Malayasian Government put in place aid mechanisms post-crisisthrough the national asset management companies, Danaharta and CDRC, to ease theeffect of the crisis. Of the total debt-restructuring observations, 37 per cent receive aqualified opinion. Similar to the earlier point, this result likely indicates going-concernqualified opinions systematically rendered to companies experiencing debt-relatedproblems. Of the debt-restructuring Big 5 clients, 44 per cent had qualified auditopinions compared with 20 per cent of their non-Big 5 debt-restructuring counterparts,again indicating differential AQ (significant at z , 0.01 on a one-tail test).
Fifth, politically linked companies receive a qualified audit opinion less frequentlythan non-politically linked companies. Politically linked companies comprise a groupof privileged companies having significant, tight links with the Malaysian Governmentvia political parties and are deemed to be those identified by Johnson and Mitton (2003).Only 4 per cent of the politically linked companies receive a qualified opinion over theperiod of study. One possible reason for such an observation is that managers ofpolitically linked companies are more likely to succeed in avoiding a qualification dueto their political influence during the auditor-client interaction/negotiation. However,within the qualified politically linked audit opinions rendered, 75 per cent of Big 5clients receive a qualified opinion compared with 25 per cent for their non-Big 5counterparts (only significant at z , 0.10 on a one-tail test).
MAJ22,7
700
Tot
al(p
erce
nt)
Big
5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Tot
al(p
erce
nt)
Big
5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Qu
alifi
edU
nq
ual
ified
Panel
A:
Ove
rall
(1994-1
999)
Qu
alifi
ed(N
¼25
)U
nq
ual
ified
(N¼
568)
Tes
tof
mea
ns
orp
rop
orti
on)
(p(o
rz)
-val
ue)
AB
DA
(mea
n)
0.18
50.
214
0.10
90.
114
0.10
50.
124
21.
402
(0.1
74)
1.64
6(0
.100
)D
A(m
ean
)2
0.13
12
0.15
52
0.07
10.
014
0.01
20.
015
0.86
0(0
.399
)0.
1971
(0.8
44)
Ob
serv
atio
ns
wit
hd
ebt
rest
ruct
uri
ng
exer
cise
(fre
qu
ency
)16
(0.6
4)11
(44)
5(0
.20)
27(0
.05)
10(0
.02)
17(0
.03)
2.12
1(0
.033
)2
1.90
5(0
.057
)P
olit
ical
lyli
nk
edob
serv
atio
ns
(fre
qu
ency
)4
(0.1
6)3
(0.1
2)1
(0.0
4)93
(0.1
6)59
(0.1
0)34
(0.0
6)1.
414
(0.1
57)
3.66
7(0
.000
)
Panel
B:
Pre
-cri
sis
(1994-1
996)
Qu
alifi
ed(N
¼2)
Un
qu
alifi
ed(N
¼21
5)T
est
ofm
ean
sor
pro
por
tion
)(p
(or
z)-v
alu
e)A
BD
A(m
ean
)0.
047
0.04
90.
045
0.14
10.
125
0.15
8N
/A1.
378
(0.1
70)
DA
(mea
n)
0.00
20.
049
20.
045
0.02
30.
011
0.03
5N
/A0.
801
(0.4
24)
Ob
serv
atio
ns
wit
hd
ebt
rest
ruct
uri
ng
exer
cise
(fre
qu
ency
)0
(0.0
0)0
(0.0
0)0
(0.0
0)0
(0.0
0)0
(0.0
0)0
(0.0
0)N
/AN
/AP
olit
ical
lyli
nk
edob
serv
atio
ns
(fre
qu
ency
)0
(0.0
0)0
(0.0
0)0
(0.0
0)43
(0.2
0)14
(0.0
6)29
(0.1
3)N
/A3.
235
(0.0
01)
(con
tinued
)
Table IV.Descriptive summary of
abnormal accruals bytype of audit qualification
Earningsmanagement andthe audit opinion
701
Tot
al(p
erce
nt)
Big
5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Tot
al(p
erce
nt)
Big
5(p
erce
nt)
Non
-Big
5(p
erce
nt)
Qu
alifi
edU
nq
ual
ified
Panel
C:
Pos
t-cr
isis
(1999)
Qu
alifi
ed(N
¼7)
Un
qu
alifi
ed(N
¼10
3)T
est
ofm
ean
sor
pro
por
tion
)(p
(or
z)-v
alu
e)A
BD
A(m
ean
)0.
396
0.47
90.
187
0.10
20.
094
0.10
82
2.98
2(0
.031
)0.
689
(0.4
92)
DA
(mea
n)
20.
396
20.
479
20.
187
0.01
40.
002
0.02
52.
982
(0.0
31)
0.77
1(0
.442
)O
bse
rvat
ion
sw
ith
deb
tre
stru
ctu
rin
gex
erci
se(f
req
uen
cy)
6(0
.86)
4(0
.57)
2(0
.29)
14(0
.13)
6((
0.06
)8
(0.0
8)1.
155
(0.2
48)
20.
756
(0.4
50)
Pol
itic
ally
lin
ked
obse
rvat
ion
s(f
req
uen
cy)
1(0
.14)
1(0
.14)
0(0
.00)
15(0
.15)
8(0
.08)
7(0
.07)
N/A
0.36
5(0
.715
)
Panel
D:
Cri
sis
(1997-1
998)
Qu
alifi
ed(N
¼16
)U
nq
ual
ified
(N¼
250)
Tes
tof
mea
ns
orp
rop
orti
on)
(p(o
rz)
-val
ue)
AB
DA
(mea
n)
0.10
90.
117
0.08
60.
096
0.09
10.
101
20.
752
(0.4
64)
0.76
9(0
.442
)D
A(m
ean
)2
0.03
22
0.03
62
0.01
90.
006
0.01
92
0.00
50.
219
(0.8
29)
21.
313
(0.1
90)
Ob
serv
atio
ns
wit
hd
ebt
rest
ruct
uri
ng
exer
cise
(fre
qu
ency
)10
(0.4
0)7
(0.2
8)3
(0.1
2)13
(0.0
5)4
(0.0
2)9
(0.0
4)1.
789
(0.0
74)
21.
961
(0.0
50)
Pol
itic
ally
lin
ked
obse
rvat
ion
s(f
req
uen
cy)
3(0
.12)
2(0
.08)
1(0
.04)
35(0
.14)
22(0
.09)
13(0
.05)
0.81
6(0
.414
)2.
151
(0.0
31)
Notes:
AB
DA
–ab
solu
teab
nor
mal
accr
ual
s;D
A–
gro
ss/s
ign
edab
nor
mal
accr
ual
san
dis
calc
ula
ted
usi
ng
the
m-J
ones
(199
1)m
odel
(see
Ch
apte
rs6
and
7fo
rd
etai
lsan
dre
sult
sof
app
lyin
gth
ism
eth
od)
Table IV.
MAJ22,7
702
Panels A-D of Table V present an overall and period specific Big 5/non-Big 5comparative summary of abnormal accruals, debt-restructuring and politically linkedobservations with regards to emphasis of matter unqualified audit opinions versusnon-emphasis of matter unqualified opinions. Five main findings can be derived fromthe analyses. First, in contrast to qualified audit opinions, auditees receiving anemphasis of matter type of unqualified audit opinion report lower absolute abnormalaccruals than non-emphasis of matter unqualified opinion auditees. At first glance, theresult seems strange, as one would have expected otherwise. However, examining bynet abnormal accruals shows that clients receiving an emphasis of matter opinionreport negative abnormal accruals compared to non-emphasis of matter opinionclients, which tend to report positive net abnormal accruals. Taking the magnitudesinto account, as expected the emphasis of matter unqualified opinion abnormalaccruals (0.038) are larger than for the non-emphasis of matter unqualified opinions(0.015). Thus, it is likely that the negative signed abnormal accruals pertaining to anemphasis of matter unqualified opinions are associated with economic uncertainty –debt-related problems. Second, 64.29 per cent of the emphasis of matter unqualifiedopinions are rendered to debt-restructuring companies.
Third, similar to the earlier findings, but to a lesser extent, differential AQ isobserved in that 83.33 per cent of the debt-restructuring Big 5 auditees receive anemphasis of matter unqualified audit opinion compared with 50 per cent for theirdebt-restructuring non-Big 5 counterparts. However, after partitioning across themacroeconomic period the Big 5 effect appears to dissipate, in that during thepost-crisis period there appears no difference between the Big 5 and non-Big 5 auditeesreceiving an emphasis of matter opinion, whilst a marginally stronger Big 5/non-Big 5difference is noted during the crisis period. A similar finding is also observed betweenthe Big5 and non-Big 5 politically linked companies. Fourth, with regards to politicallylinked companies, only 14.29 per cent of the emphasis of matter opinions relate topolitically linked companies, indicating a possible liberality amongst auditees due topolitical influence/pressure.
Multivariate resultsTable VI presents the descriptive statistics and correlations for variables included inthe QUAL model. From the table, the highest correlation is 0.715 between MKTCAPand LASSET[14]. Table VII reports the overall (pooled over the period of study) resultsfor the logistic analyses that regresses the audit opinion on absolute values ofabnormal accruals, Big 5 (or industry specialist) (and interaction between abnormalaccruals and AQ) and other control variables. To test the hypotheses bymacroeconomic condition, the model is analysed separately for each period. Owingto insufficient opinion data variability, the logistic model is unable to perform theregression in the pre-crisis period (only two observations are qualified). Forthe post-crisis period, the logistic regression also cannot be performed because absoluteabnormal accruals above 0.291 predicts the outcome perfectly.
From Table VII using the pooled sample for the whole period, the variable ofinterest for H1a, ABDA is shown to be significantly associated (albeit weak) with auditqualification ( p , 0.10) after controlling for auditor, audit difficulty and financialcharacteristics. The positive relationship between QUAL and ABDA, indicates that, asexpected, auditors consider EM when formulating opinions.
Earningsmanagement andthe audit opinion
703
Tot
alB
ig5
Non
-Big
5T
otal
Big
5N
on-B
ig5
Em
ph
asis
ofm
atte
rN
on-e
mp
has
isof
mat
ter
Panel
A:
Ove
rall
(1994-1
999)
Em
ph
asis
ofm
atte
rN¼
14N
on-e
mp
has
isof
mat
ter
N¼
554
Tes
tof
mea
ns
orp
rop
orti
on)
(p(o
rz)
-val
ue)
AB
DA
(mea
n)
0.06
80.
032
0.09
50.
116
0.10
60.
125
1.45
5(0
.171
)0.
9434
(0.3
46)
DA
(mea
n)
20.
038
0.00
62
0.07
00.
015
0.01
30.
017
21.
421
(0.1
81)
0.88
1(0
.379
)O
bse
rvat
ion
sw
ith
deb
tre
stru
ctu
rin
gex
erci
se(f
req
uen
cyp
erce
nt)
9(6
4.29
)5
(83.
33)
4(5
0.00
)18
(0.0
6)5
(1.8
3)13
(4.6
3)0.
471
(0.6
37)
22.
667
(0.0
08)
Pol
itic
ally
lin
ked
obse
rvat
ion
s(f
req
uen
cyp
erce
nt)
2(14
.29)
2(3
3.33
)0
(0.0
0)91
(16.
43)
57(2
0.88
)34
(12.
10)
2.00
0(0
.046
)3.
410
(0.0
01)
Panel
B:
Pre
-cri
sis
(1994-1
996)
Em
ph
asis
ofm
atte
rN¼
0N
on-e
mp
has
isof
mat
ter
N¼
218
Tes
tof
mea
ns
orp
rop
orti
on)
(p(o
rz)
-val
ue)
AB
DA
(mea
n)
N/A
N/A
N/A
0.10
60.
124
0.15
6N
/A1.
3750
(0.1
71)
DA
(mea
n)
N/A
N/A
N/A
0.01
70.
011
0.03
4N
/A0.
7729
(0.4
40)
Ob
serv
atio
ns
wit
hd
ebt
rest
ruct
uri
ng
exer
cise
(fre
qu
ency
)N
/AN
/AN
/AN
/AN
/AN
/AN
/AN
/AP
olit
ical
lyli
nk
edob
serv
atio
ns
(fre
qu
ency
per
cen
t)0
(0.0
0)0
(0.0
0)0
(0.0
0)46
(21.
10)
31(2
8.44
)15
(13.
76)
N/A
22.
6875
(0.0
078)
(con
tinued
)
Table V.Descriptive summary ofabnormal accruals bytype of unqualifiedopinion (emphasis ofmatter vs non-emphasisof matter)
MAJ22,7
704
Tot
alB
ig5
Non
-Big
5T
otal
Big
5N
on-B
ig5
Em
ph
asis
ofm
atte
rN
on-e
mp
has
isof
mat
ter
Panel
C:
Pos
t-cr
isis
(1999)
Em
ph
asis
ofm
atte
rN¼
9N
on-e
mp
has
isof
mat
ter
N¼
101
Tes
tof
mea
ns
orp
rop
orti
on)
(p(o
rz)
-val
ue)
AB
DA
(mea
n)
0.06
00.
037
0.07
20.
106
0.09
80.
113
0.73
6(0
.485
)2
0.64
8(0
.518
)D
A(m
ean
)2
0.01
60.
028
20.
038
0.01
70.
001
0.03
32
1.06
0(0
.324
)1.
897
(0.0
61)
Ob
serv
atio
ns
wit
hd
ebt
rest
ruct
uri
ng
exer
cise
(fre
qu
ency
per
cen
t)6
(66.
67)
3(5
0.00
)3
(50.
00)
8(8
.51)
3(6
.38)
5(1
0.64
)0.
000
(1.0
00)
21.
000
(0.3
17)
Pol
itic
ally
lin
ked
obse
rvat
ion
s(f
req
uen
cyp
erce
nt)
1(1
1.11
)1
(33.
33)
0(0
.00)
14(1
4.89
)7
(14.
89)
7(1
4.89
)N
/A0.
000
(1.0
00)
Panel
D:
Cri
sis
(1997-1
998)
Em
ph
asis
ofm
atte
rN¼
5N
on-e
mp
has
isof
mat
ter
N¼
263
Tes
tof
mea
ns
orp
rop
orti
on)
(p(o
rz)
-val
ue)
AB
DA
(mea
n)
0.08
20.
027
0.16
50.
097
0.09
20.
101
1.45
0(0
.243
)0.
365
(0.7
15)
DA
(mea
n)
20.
076
20.
017
20.
165
0.00
80.
020
20.
003
21.
526
(0.2
24)
20.
989
(0.3
23)
Ob
serv
atio
ns
wit
hd
ebt
rest
ruct
uri
ng
exer
cise
(fre
qu
ency
per
cen
t)3
(60)
2(6
6.67
)1
(50.
00)
10(4
.08)
2(1
.69)
8(6
.30)
0.81
6(0
.414
)2
2.68
3(0
.007
)P
olit
ical
lyli
nk
edob
serv
atio
ns
(fre
qu
ency
per
cen
t)1
(20)
1(3
3.33
)0
(0.0
0)34
(13.
88)
21(1
7.80
)13
(10.
24)
N/A
1.94
0(0
.052
)
Notes:
Mos
tof
the
emp
has
isof
mat
ter
typ
eof
un
qu
alifi
edop
inio
ns
rela
teto
un
cert
ain
tyov
erth
eg
oin
gco
nce
rnst
atu
sof
the
com
pan
yd
ue
toec
onom
icu
nce
rtai
nty
;A
BD
A–
abso
lute
abn
orm
alac
cru
als;
DA
–g
ross
/sig
ned
abn
orm
alac
cru
als
and
isca
lcu
late
du
sin
gth
em
-Jon
es(1
991)
mod
el
Table V.
Earningsmanagement andthe audit opinion
705
NM
ean
SD
12
34
56
78
910
1112
1314
1516
1Q
UA
L59
30.
042
0.20
11
2B
IG5
596
0.50
00.
500
0.11
71
3IN
DS
PE
C59
60.
216
0.41
20.
088
0.52
21
4B
5NIN
DS
P59
60.
284
0.45
10.
049
0.63
22
0.33
11
5M
KT
CA
P56
15.
558
0.57
12
0.15
70.
059
0.13
92
0.06
11
6B
KM
KT
549
0.50
20.
502
0.27
70.
001
0.00
82
0.00
52
0.55
61
7L
OS
S59
60.
245
0.43
00.
288
0.02
10.
012
0.01
22
0.35
20.
322
18
DE
594
0.12
30.
130
20.
031
20.
073
20.
009
20.
073
0.09
00.
036
0.09
51
9Q
UA
LA
G59
60.
012
0.10
80.
288
0.09
60.
184
20.
061
20.
082
0.17
80.
131
20.
013
110
LA
SS
ET
596
13.2
431.
282
20.
066
0.04
20.
137
20.
078
0.71
52
0.08
62
0.15
70.
325
20.
048
111
TIM
E59
613
.490
10.8
170.
147
0.14
60.
104
0.06
70.
247
0.06
72
0.00
72
0.04
40.
072
0.23
21
12IN
VA
SS
T59
40.
158
0.26
40.
010
0.01
30.
054
20.
034
20.
091
0.08
90.
084
0.02
60.
012
20.
113
20.
050
113
RE
CA
SS
T59
60.
193
0.14
00.
070
0.10
50.
019
0.09
92
0.26
60.
012
0.08
82
0.12
40.
047
20.
221
20.
210
0.08
41
14A
BD
A59
60.
117
0.13
80.
064
20.
069
20.
073
20.
010
20.
044
20.
046
0.06
02
0.04
10.
053
20.
134
20.
132
0.01
60.
191
115
AB
DA
* BIG
559
60.
056
0.10
30.
170
0.54
90.
235
0.39
42
0.04
60.
017
0.03
32
0.11
70.
137
20.
076
0.00
72
0.00
40.
173
0.45
81
16A
BD
A* IN
DS
PE
C59
60.
022
0.07
00.
163
0.31
90.
612
20.
203
0.00
10.
076
0.07
82
0.06
50.
252
20.
008
20.
008
0.02
90.
107
0.25
30.
563
1
Note:
Ref
erto
Tab
leI
for
sum
mar
yof
var
iab
les
Table VI.Descriptive statistics andcorrelations for auditqualification modelvariables
MAJ22,7
706
Big
5/n
on-B
ig5
Ind
ust
rysp
ecia
list
/in
du
stry
non
-sp
ecia
list
Dep
end
ent
1(N
oin
tera
ctio
n)
2(I
nte
ract
ion
)3
(No
inte
ract
ion
)4
(In
tera
ctio
n)
var
iab
le:
QU
AL
OD
DS
R.
SE
za
OD
DS
R.
SE
za
OD
DS
R.
SE
za
OD
DS
R.
SE
za
BIG
53.
375
2.30
31.
780
**
1.61
41.
207
0.64
0IN
DS
PE
C3.
773
3.00
01.
670
**
2.55
52.
391
1.00
0B
5NIN
DS
P3.
187
2.34
81.
570
**
*3.
092
2.26
81.
540
**
*
MK
TC
AP
0.23
30.
212
21.
600
**
0.26
50.
236
21.
490
0.22
90.
209
21.
610
**
0.21
60.
198
21.
670
**
BK
MK
T1.
257
0.59
20.
490
1.28
10.
581
0.55
01.
250
0.59
60.
470
1.20
10.
587
0.38
0L
OS
S11
.053
7.71
93.
440
*12
.006
8.68
23.
440
*11
.186
7.91
23.
410
*10
.784
7.63
53.
360
*
DE
0.41
91.
026
20.
360
0.50
81.
142
20.
300
0.43
31.
068
20.
340
0.40
21.
008
20.
360
QU
AL
AG
6.23
96.
235
1.83
0*
*5.
445
5.33
11.
730
**
5.58
96.
111
1.57
0*
**
5.02
75.
303
1.53
0*
**
LA
SS
ET
b1.
154
0.38
80.
430
1.15
20.
384
0.42
01.
157
0.39
10.
430
1.19
10.
402
0.52
0T
IME
1.10
20.
028
3.81
0*
1.10
80.
029
3.93
0*
1.10
30.
028
3.85
0*
1.10
80.
029
3.90
0*
INV
AS
ST
0.50
91.
176
20.
290
0.47
71.
264
20.
280
0.48
01.
088
20.
320
0.37
91.
014
20.
360
RE
CA
SS
T6.
426
15.2
000.
790
11.6
0025
.397
1.12
06.
433
15.2
940.
780
6.78
316
.134
0.80
0A
BD
A6.
164
7.90
21.
420
**
*0.
660
1.97
82
0.14
06.
180
7.97
51.
410
**
*4.
279
6.15
31.
010
AB
DA
* BIG
517
4.98
962
8.89
51.
440
**
*
AB
DA
* IN
DS
PE
C17
.837
48.1
641.
070
N54
554
554
554
5x
256
.84
57.4
656
.19
56.4
4P
RO
B.
x2
0.00
00.
000
0.00
00.
000
Log
lik
elih
ood
251
.194
250
.075
251
.164
250
.866
Pse
ud
oR
20.
403
0.41
60.
403
0.40
7
Notes:
Cla
ssifi
cati
onac
cura
cy:
un
qu
alifi
ed99
.8p
erce
nt,
qu
alifi
ed35
per
cen
t,ov
eral
l97
.43
per
cen
t.R
efer
toT
able
Ifo
rsu
mm
ary
ofv
aria
ble
s.aO
ne-
tail
edte
stex
cep
tfo
rth
ose
var
iab
les
(wit
h(b
))w
her
ed
irec
tion
isn
otp
red
icte
d.
* Sig
nifi
can
tat
0.01
lev
el;
** s
ign
ifica
nt
at0.
05le
vel
;*
** s
ign
ifica
nt
at0.
10le
vel
Table VII.Multivariate result – H1a
and H1bLogistic regression –
qualification model(pooled 1994-1999)
Earningsmanagement andthe audit opinion
707
The interaction term ABDA *BIG5 included to test H1b captures the interactionbetween Big 5 auditors and the absolute level of abnormal accruals and is significantly(again albeit weak – p , 0.10) associated with qualification (regression 2). However,this association is insignificant when the interaction term ABDA *INDSPEC is used(regression 4) implying that industry specialisation make no difference to the rate ofqualification in the presence of abnormal accruals. One possible reason for the findingis the limited number of observations where ABDA *INDSPEC is greater than zero.The positive coefficient found for the interaction term in regression 2 (ABDA *BIG5)indicates that, as expected, the likelihood of a client receiving a qualified opinionincreases when a Big 5 auditor is confronted with abnormal accruals.
In regressions without the interaction terms (regressions 1 and 3) as expected boththe AQ variable coefficients are positive and significant at p , 0.05 level. Theassociation indicates that Big 5 auditors more frequently than other auditors qualifyaudit opinions, ceteris paribus, thus implying differentiated AQ. In regression 3, theindustry specialist auditor (INDSPEC) coefficient is more strongly significant than Big5 non-specialist (significant only at p , 0.10 level), implying that only a segment of Big5 auditees seem to more frequently than other auditees receive an audit qualification.
Other control variables found significant are MKTCAP, LOSS, QUALAG andTIME at conventional levels of p , 0.01, p , 0.05 and p , 0.10 level (see Table VII fordetails of the respective variable significance levels) for all four regressions. Thecoefficients for MKTCAP, LOSS, TIME, QUALAG are positive as predicted.
Robust (White (1980) sandwich estimator) logistic regression is used to adjust thestandard errors. The mean VIF, maximum and minimum variance inflation factors forthe regressions show multicollinearity is below problematic limits. The models forregressions 1 and 3 are significant (Wald x 2 ¼ 56 and prob . x 2 p ¼ 0.00) with aPseudo R 2 of approximately 40 per cent, classifying correctly 97 per cent of the545 observations in terms of the audit opinion rendered by an auditor. Similar toregressions 1 and 3, the models for regressions 2 and 4 are significant with a Pseudo R 2 ofapproximately 41 per cent. The Pearson x 2 and the Hosmer-Lemeshow goodness-of-fittests for regressions 2 and 4 also suggest that the model is an adequate fit.
The finding for the crisis and post-crisis periods supports the notion of AQdifferentiation as theorised by DeAngelo (1981). However, the auditor conservatismrationale (DeFond and Subramanyam, 1998; DeFond and Jiambalvo, 1994) may also bein place due to the possibility of heightened litigation risk post-crisis (although inMalaysia none of the auditors has been litigated against) and international pressureassociated with distressed companies as observed during the crisis and post-crisisperiods. To untangle which of the two notions is driving the result is difficult, but thefact that the interaction term between opinion and Big 5 (albeit weakly) is significantindicates a greater level of auditor conservatism observed for the Big 5 which, in itself,implies a differential level of audit qualify exhibited by top-tier auditors.
Further testsSince, most of the qualified audit opinions are going concern related, it is expected thatmanagers have incentive to indulge in big bath activity in order to enhance their casefor debt-restructuring and signal to lenders that they acknowledge their difficulties andare willing to take action. Following this scenario, companies receiving a qualifiedopinion should report large negative abnormal accruals. The results in the previous
MAJ22,7
708
section analyse the abnormal accruals in absolute terms (ignoring the sign of bothpositive and negative abnormal accruals), which removes the directional effect andconcentrates on the magnitude. Thus, this section attempts to provide some insight asto whether the observance of high-abnormal accruals together with the issuance of aqualified audit opinion is driven by EM and/or distress.
Table VIII provides descriptives of abnormal accruals, operating cash flow,leverage, size, total accruals, audit qualification, Big 5, non-Big 5, qualification *Big 5,qualification *non-Big 5, loss and the presence of debt-restructuring by percentile ofabnormal accruals (directional). As expected, the table confirms MIA that mostqualified opinions fall at the first decile with abnormal accruals of 20.303, 2 0.340and 20.265 for the overall, post-crisis and crisis periods, respectively. In addition therecipients of qualified opinions display high leverage, losses, negative return on assets,large negative accruals and tend to subsequently undertake some form ofdebt-restructuring, which is strikingly evident in the crisis and post-crisis periods(see table for details). Taking these results together, although it is apparent thatdistress is likely to be the main reason driving the issuance of audit qualifications, it isequally apparent that these qualified companies indulge in what might be construed asbig-bath activity (have large negative DA). Although the proportion of Big 5 andnon-Big 5 auditees is relatively the same within the first decile of abnormal accruals,the proportion of Big 5 auditees receiving an audit qualification is much higher than forthe non-Big 5 auditees, a reconfirmation of the presence of a differentiated auditproduct vis-a-vis differential auditor conservatism.
Conclusions, limitations and further researchThis paper seeks to provide evidence of AQ differentiation by testing one of theobservable outcomes of auditing, the audit opinion. It is argued that high levels ofabnormal accruals should be associated with an audit qualification. In other words, thequestion investigated here is whether in situations where EM is not constrained, thereis an accompanying qualified audit opinion. In addition, because Big 5 auditorsarguably supply higher quality audits, it is hypothesised that this group of auditorswill issue qualified opinions more frequently than the non-Big 5 when abnormalaccruals are high.
Based on the matched pair sample of companies listed on the KLSE, consistent withBartov et al. (2000), the results provide support for the hypotheses, in that high EMproxied by absolute abnormal accruals is positively associated with qualification. Inaddition, contrary to Bartov et al. (2000), the absolute level of abnormal accruals ispositively and significantly associated with qualifications in the presence of a Big 5auditor. One possible reason for the contrary results is that the sample in Bartov et al.is not matched by type of auditor (Big 5 – non-Big 5) as is done in this study.Partitioning by macroeconomic period suggests that the issuance of audit qualificationis more frequent in crisis and post-crisis than the pre-crisis and this is not surprising.One possible major concern with the validity of the results is with respect to possibilitythat the issuance of these qualifications is related to going concerns problems of thecompany rather than EM per se. However, distress is controlled for and the resultsshow high negative abnormal accruals (indicative of big bath activity) being associatedwith the issuance of audit qualifications, particularly in the presence of a Big 5 auditor,
Earningsmanagement andthe audit opinion
709
CE
NT
ILE
ofD
AN
DA
OC
FL
EV
LA
SS
ET
AB
TA
QU
AL
Big
5N
on-B
ig5
QU
AL
*
BIG
5Q
UA
L*
Non
-Big
5L
OS
SR
OA
Deb
tre
stD
ebt
rest
1
Panel
A:
Ove
rall
(1994-1
999)
159
20.
303
0.04
70.
871
12.7
310.
314
930
298
127
20.
126
1419
261
20.
129
0.11
60.
265
13.0
490.
104
234
271
114
0.38
42
63
582
0.07
10.
037
0.38
213
.279
0.10
73
3028
21
190.
000
815
461
20.
038
0.06
50.
297
13.3
770.
055
322
391
220
0.01
13
75
592
0.01
10.
042
0.30
213
.604
0.04
51
2732
10
180.
164
47
660
0.01
50.
026
0.32
913
.367
0.02
90
3129
00
140.
033
37
760
0.04
30.
018
0.26
513
.444
0.02
82
3228
20
100.
034
35
859
0.07
32
0.00
10.
265
13.3
000.
051
330
291
23
0.04
71
129
600.
142
20.
038
0.28
313
.267
0.07
71
3228
10
110.
039
410
1059
0.35
42
0.18
20.
336
13.0
040.
217
130
291
010
0.06
81
13
Panel
B:
Pre
-cri
sis
(1994-1
996)
120
20.
317
0.12
80.
229
12.8
590.
113
010
100
03
0.07
4N
/A4
230
20.
124
0.09
60.
220
13.0
830.
074
016
140
03
0.05
5N
/A3
323
20.
069
0.08
00.
253
13.5
480.
046
011
120
01
0.06
2N
/A4
425
20.
039
0.06
30.
229
13.2
590.
028
19
160
15
0.04
5N
/A3
517
20.
012
0.07
10.
215
13.8
450.
028
08
90
00
0.06
7N
/A1
617
0.01
50.
032
0.32
313
.154
0.03
60
116
00
10.
085
N/A
37
130.
042
20.
004
0.28
813
.297
0.04
61
58
10
20.
028
N/A
28
210.
073
0.01
00.
218
13.2
390.
056
011
100
00
0.07
5N
/A5
920
0.14
92
0.04
50.
282
12.9
490.
095
011
90
02
0.06
2N
/A3
1032
0.38
92
0.15
80.
353
13.2
830.
197
017
150
03
0.07
3N
/A9
(con
tinued
)
Table VIII.Qualification frequencyand variable descriptivesby percentiles based ondirectional abnormalaccruals
MAJ22,7
710
CE
NT
ILE
ofD
AN
DA
OC
FL
EV
LA
SS
ET
AB
TA
QU
AL
Big
5N
on-B
ig5
QU
AL
*
BIG
5Q
UA
L*
Non
-Big
5L
OS
SR
OA
Deb
tre
stD
ebt
rest
1
Panel
C:
Pos
t-cr
isis
(1999)
116
20.
340
20.
129
2.48
612
.332
0.63
46
88
51
122
0.09
78
82
52
0.13
80.
224
0.23
513
.636
0.15
90
05
00
20.
016
00
310
20.
072
20.
112
0.70
113
.513
0.26
11
64
01
62
0.02
94
44
92
0.04
10.
112
0.26
513
.491
0.09
00
27
00
32
0.02
21
15
82
0.00
70.
007
0.49
413
.458
0.08
30
26
00
70.
004
33
611
0.01
40.
046
0.38
414
.009
0.03
10
56
00
20.
003
00
719
0.04
50.
043
0.29
413
.372
0.02
20
154
00
40.
037
22
813
0.07
00.
051
0.23
913
.344
0.03
70
76
00
00.
014
00
913
0.14
50.
025
0.16
812
.809
0.04
90
76
00
30.
014
11
106
0.35
72
0.09
70.
138
12.4
790.
199
03
30
02
0.04
81
1
Panel
D:
Cri
sis
(1996-1
997)
123
20.
265
0.10
00.
353
12.8
970.
267
312
113
012
20.
406
67
226
20.
134
0.11
80.
322
12.8
970.
129
218
81
19
0.05
32
33
252
0.07
20.
057
0.37
212
.937
0.10
12
1312
20
122
0.07
14
74
272
0.03
70.
052
0.37
113
.448
0.06
92
1116
11
120.
017
23
534
20.
010
0.03
50.
299
13.5
170.
044
117
171
011
20.
039
13
632
0.01
50.
016
0.31
413
.260
0.02
50
1517
00
112
0.02
23
47
280.
042
0.01
10.
237
13.5
610.
024
112
161
04
0.03
41
18
250.
074
20.
038
0.31
713
.328
0.05
33
1213
12
30.
066
17
927
0.13
62
0.06
30.
339
13.7
240.
078
114
131
06
0.05
43
610
210.
299
20.
242
0.34
912
.731
0.25
21
1011
10
50.
109
03
Notes:
Ref
erto
Tab
les
Ian
dII
for
sum
mar
yof
var
iab
les;
RO
A–
Ret
urn
onA
sset
;DE
BR
ES
T–
deb
tre
stru
ctu
rers
(199
8an
d19
99);
DE
BT
RE
ST
1–
deb
tre
stru
ctu
rers
(199
4-19
99);
N/A
–n
otap
pli
cab
leb
ecau
sed
ebt
rest
ruct
ure
rsar
en
otid
enti
fied
pri
orto
1998
Table VIII.
Earningsmanagement andthe audit opinion
711
thus providing additional support to the notion of a differentiated audit product vis a visdifferential auditor conservatism.
The results of this study need to be interpreted with its limitations in mind. First, allqualifications are included with insufficient sub-sample sizes to examine by type ofqualification. Second, the matched pair sample, although creating a rigorouscalculation of discretionary accruals, tends to be smaller on average than the totalpopulation since the size of non-Big 5 auditees, to which were matched Big 5 auditees,is smaller on average than Big 5 auditees.
Several opportunities for further research arise from this study. Furtherinvestigation of the debt-restructuring and politically linked auditees, that appear tohave differential rates of qualification, needs to take place. The incentives in terms ofEM are different for these auditees and insights may be provided by examining thebehaviour of the discretionary accruals for these groups of auditees in association withthe behaviour of their auditors.
Overall, the results of this study support the findings of similar studies performedon data from the West. In the Malyasian setting and in the context of the AsianEconomic Crisis, the Big 5 do appear to qualify more frequently in the presence ofaggressive abnormal accruals than their non-Big 5 counterparts. However, no suchevidence was found for industry specialist auditors.
The study extends the current literature on AQ differentiation and specifically itattempts to address the gaps in the literature with respect to auditor reportingbehaviour in the presence of aggressive EM. In addition this study provides additionalevidence on Big 5/industry specialist quality differentiation in an emerging market (anunder-researched area), Malaysia, arguably with less transparent and weakergovernance structures than the developed economies such as USA, UK, and Australia.This study is expected to provide insights to the auditing and accounting profession,and to regulators with respect to the debate on EM, AQ and the audit opinionformation process.
Notes
1. The founder member firms are Andersen, BDO, Deloitte Touche, Ernst & Young, GrantThornton, KPMG and PricewaterhouseCoopers.
2. The USA use the term “modified” for audit reports that are other than unqualified, whereasMalaysia uses the term “qualified”. In the USA, the term “qualified” is reserved for “exceptfor” opinions. Malaysian auditing standards permit emphasis of matter paragraphs inrelation to going concern uncertainties.
3. They attribute the statistical insignificance to be a result of the small number of companieswith non-Big 6 auditors.
4. ISA are issued by the International Auditing Practice Committee (renamed as InternationalAuditing and Assurance Standards Board beginning 1 April 2002) of the IFAC.
5. Thus, it is possible that the observance of a qualified opinion in relation to firm performance(going concern problems) may not be related to earnings management. Thus, ideally oneway to overcome this identification problem would be to select only observations with auditopinions that arise from scope limitation and departures from GAAP for investigation.However, because the number of qualifications resulting from such reasons is too small todraw statistical inference, this study, not withstanding the mentioned limitation, utilises all
MAJ22,7
712
forms of opinion in its analyses. However, it controls carefully for financial health and to theextent this is successful, results can be interpreted for the earnings management variable.
6. An argument exists that both the level of abnormal accruals and the content of the auditreport are jointly determined (Hansen and Watts, 1997).
7. The m-Jones (1991) (refer Dechow et al., 1995) in comparison to the original Jones (1991)model differs with respect to the explanatory variable “change in sales”. The Jones (1991)model utilises change in sales, whilst Dechow et al. (1995) modifies this variable by adjustingfor change in receivables.
8. This is done since the time series approach requires at least eight years of data and thecurrent study has available to it limited data for the crisis and especially post-crisis periods,making the time series version not feasible.
9. Total accruals are not derived from cash flows because IAS 7 – Cash Flow Statement wasadopted only in 1996. Given the use of this indirect balance sheet approach, it is possible thatthe computations for the abnormal accruals are erroneous (Hribar and Collins, 2002) and assuch may lead biasness with respect to existence of earnings management. Nevertheless, dueto data constrains this study acknowledges this limitation.
10. As of 23 December 1999, 757 companies were listed on the KLSE, while a total of 413companies were listed in the year 1993.
11. The authors would like to thank Prof. Kulwant Singh, Head of the Management Departmentand the library at the National University of Singapore for their assistance in allowing theuse of the database.
12. The authors would like to thank Ayoib Che Ahmad for the use of his data.
13. Previous studies on earnings management have excluded financial institutions and utilitycompanies because the existing accruals model may not be able to capture the differences inthe accrual process of financial companies and different incentives to manage earnings mayexist for utility companies. It is expected both these arguments hold within the Malaysiancontext, and thus financial institutions and utility companies are excluded from the sample.
14. Leaving out either MKTCAP or LASSET does not change the significance of the results.
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Corresponding authorShireenjit Johl can be contacted at: [email protected]
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