going concern opinion in falling companies auditor dependence and opinion shopping

1

Going-concern Opinions in Failing Companies:

Auditor Dependence and Opinion Shopping

Clive S. Lennox*

Economics Dept., University of Bristol.

Abstract:

Contrary to public expectations, companies usually receive clean audit

opinions shortly prior to failure. This study examines whether audit reports in

failing companies are affected by auditor dependence or opinion shopping. I

find audit fees, auditor size, auditor-client tenures and dominant directors are

not significantly associated with going-concern opinions. This suggests audit

reports are not affected by auditor dependence. I also find companies

strategically appoint auditors who are less likely to issue going concern

opinions. This suggests failing companies successfully engage in opinion

shopping.

* I would like to thank the Nuffield Foundation and the Centre for Market and Public Organisation for financial assistance.

2

1. Introduction

The financial community and public expect auditors to disclose going-concern problems

before companies fail. Despite this, companies frequently fail after receiving clean audit

opinions. Companies may use auditor switching to avoid receiving going-concern opinions in

two ways (Teoh, 1992). First, auditors may face dismissal threats and may not disclose going-

concern problems if they lack independence. Second, even when auditors report

independently, companies may strategically dismiss (appoint) audit firms that are likely to

give going-concern (clean) audit opinions - I call such behavior ‘opinion shopping’. This

study examines whether failing companies avoid going-concern opinions because of auditor

dependence and opinion shopping.

Existing studies find audit opinions are not associated with proxies for auditor

dependence. Krishnan et al., (1996) find no significant association between audit reports and

switch probabilities, which suggests switch threats do not affect audit opinions. Since fees

might compromise independence, most EU countries ban the provision of some or all non-

audit services.1 However, researchers find no significant association between non-audit fees

and audit opinions in the UK and Australia, where non-audit services are not banned but fees

are publicly disclosed (Lennox, 1999a; Craswell, 1999). Since long auditor-client tenures may

increase auditor dependence, some countries require mandatory rotation of auditors.2 In the

US, AICPA and the SEC Practice Section have rejected calls for mandatory rotation of audit

firms (AICPA, 1978, 1992). Consistent with their position, Louwers (1998) finds no

significant relation between auditor-client tenures and audit opinions in the US.

Regulators respond to concerns about opinion shopping in a variety of ways. Several

EU countries require mandatory retention of audit firms to deter strategic switching.3 In

addition, most countries require communication between outgoing auditors, incoming

1 Belgium, France and Italy ban the provision of all non-audit services while other EU countries allow tax and financial advisoryservices. Bookkeeping services are banned in all EU countries except Denmark, Ireland, Luxembourg, Netherlands, Portugal,Sweden and the UK. Legal services are allowed in all EU countries except Belgium Denmark, France, Greece, Italy and Portugal.Corporate recovery services are allowed in all EU countries except Belgium, France, Italy and Portugal (Buijink et al., 1996).2 Listed companies in Italy are required to rotate audit firms every nine years . In the UK, the Cadbury Committee (1992)recommends rotation of individual audit partners but not the rotation of audit firms. The Australian Society of Certified PublicAccountants (1993) recommends partner rotation every seven years, but this is rejected by the Australian Joint StandingCommittee (1996). In the US, members of the SEC Practice Section are required to rotate partners every seven years.

3

auditors and shareholders.4 The aim of such communication is to prevent companies

switching auditors to conceal unfavourable information. Evidence on opinion shopping is

conflicting because researchers employ different methodologies. Some studies conclude that

companies do not successfully engage in opinion shopping, because post-switch opinions are

not modified less often than pre-switch opinions (Chow and Rice, 1982; Smith, 1986;

Krishnan, 1994; Krishnan and Stephens, 1995). More recently Lennox (2000a, 2000b) shows

this conclusion is flawed, because it is necessary to compare the reports that companies would

receive under opposite switch decisions. He finds the evidence strongly supports successful

opinion shopping by UK and US companies.

In contrast to the above studies, this paper focuses exclusively on failing companies

for two reasons. First, auditor dependence may be more apparent in distressed companies

since managers may fear that going-concern opinions increase the probability of failure (the

‘self-fulfilling prophecy’ hypothesis). By sampling failing companies, I therefore expect to

increase the power of my tests for auditor dependence. Second, the regulatory implications of

auditor dependence and opinion shopping are clearer in failing than surviving companies.

Going-concern opinions issued to surviving companies and clean opinions issued to failing

companies are frequently classified as reporting ‘errors’ (e.g., Koh, 1991; Lennox, 1999b).

Therefore, the number of reporting errors is lower if surviving companies avoid going-

concern opinions and higher if failing companies avoid going-concern opinions. It follows

there is a stronger case for regulatory intervention if failing companies use switch threats or

opinion shopping to avoid going-concern opinions.

This is not the first study to examine going-concern opinions in failing companies,

but it is the first to consider auditor dependence and opinion shopping. Previous studies find

failing companies receive going-concern opinions more often when financial conditions are

3 There is mandatory retention of audit firms in France (six years), Portugal (four years), Belgium, Spain and Italy (three years),.4 In the US, the SEC must be informed of auditor changes within five business days and companies have to disclosedisagreements with auditors and modified opinions in the two years preceding auditor changes. To ensure compliance and toidentify companies who file late, the SEC Practice Section requires independent disclosure by audit firms as well as companies.The US Public Oversight Board (1994) recommends auditors meet with boards of directors and audit committees at least once ayear and auditors discuss the appropriateness of financial statements. Communication requirements are less stringent in the UKthan in the US (Dunn et al., 1994; Lennox, 2000b).

4

clearly poor (Menon and Schwartz, 1987; McKeown et al., 1991; Mutchler et al., 1997;

Casterella et al., 1999). Consistent with these studies, I find auditors give clean opinions to

companies that appear healthy but which subsequently fail.

Section 2 explains how I test for auditor dependence and opinion shopping. Section 3

describes how I collect the sample and gives descriptive statistics. Section 4 tests for auditor

dependence and Section 5 tests for opinion shopping. Section 6 concludes with implications

for audit regulation.

2. Methodology

This section explains how I test for auditor dependence and opinion shopping and describes

the control variables shown to be important in previous studies.

2.1 Auditor dependence

2.1.1 Audit fees ( itAF )

When audit firms earn high fees, they may face economic pressures to give clean opinions in

order to deter clients from switching to other auditors. This suggests a negative association

between going-concern opinions and audit fees.5 However, auditors may give going-concern

opinions more often when audit fees are high. Auditors who exert more effort (and charge

higher fees) may be more likely to discover going-concern problems. Moreover, auditors may

exert more effort or charge higher risk premiums when companies face going-concern

problems. Therefore, the predicted relation between audit fees and going-concern opinions is

ambiguous. An important contribution of this study is that I use actual audit fees, which are

publicly disclosed by UK companies. Since US companies are not required to disclose fees,

previous studies use client characteristics such as size to capture the effects of fees (e.g.,

Louwers, 1998; McKeown et al., 1991).6

5 UK companies are only required to disclose non-audit fees since 1994. Since most sample companies fail prior to 1994, I donot test the association between non-audit fees and audit opinions.6 Threats to auditor independence may be more severe when an individual client’s fee is a large proportion of an audit firm’stotal income. Unfortunately, data on total fees are unavailable for small audit firms. However, this is unlikely to be a problem as

5

2.1.2 Audit firm size ( itAUD )

I control for auditor size using a dummy variable ( itAUD ), which equals one if the audit firm

is one of the Big Five and zero otherwise. Reputation and deep pockets theories predict a

positive association between audit firm size and audit quality. DeAngelo (1981) argues large

audit firms have more incentive to avoid reputation-damaging criticism compared to small

audit firms. Dye (1993) suggests large audit firms are more likely to disclose problems

because they have more wealth at risk from litigation. In addition, individual clients

contribute proportionately less to the total incomes of large audit firms. These arguments

mean large audit firms have more incentive to detect and report going-concern problems. I

therefore expect a positive relation between audit firm size and going-concern opinions.

2.1.3 Auditor-client tenure ( itTEN )

My tenure variable ( itTEN ) equals the number of years that firms audit their clients. When

auditors have long relations with their clients, expected future rents may be higher and may

increase the threat to auditor independence. This suggests a negative association between

auditor-client tenures and going-concern opinions. However, an opposite positive association

is also possible. Long tenures may mean audit firms better understand clients’ financial

conditions and are more likely to detect going-concern difficulties. Therefore, the predicted

relation between tenures and audit opinions is ambiguous.

2.1.4 Dominant directors ( itDOMS , itDOMR )

Dominant directors may exert more pressure on auditors to issue clean opinions compared to

boards where control is exercised democratically.7 I measure board dominance using two

large audit firms have more highly diversified client portfolios and I control for the association between audit firm size andgoing-concern opinions.7 For example, Robert Maxwell held over 99% of the board’s shares in Maxwell Communications (MCC) and MCC receivedclean opinions prior to failure. The Financial Times writes (17th June, 1992), “Maxwell was able to seize money so quicklybecause the sweeping powers he had secured as chairman of his companies allowed him to move money with little reference toanyone else. His policy of divide and rule concealed what he was doing from many . . . the audit for the year to April 1991 nevertook place. One of the ways Maxwell avoided detection was by the simple device of extending the audit period. He simplydeclared that the next one would be in December 1991, a gap of 21 months.”

6

variables - the proportion of board shares held by the director who owns most shares

( itDOMS ) and the proportion of board remuneration earned by the highest paid director

( itDOMR ). If dominant directors exert more pressure on auditors compared to democratic

boards, I expect a negative relation between director dominance and going-concern opinions.

To my knowledge, this is the first paper to examine whether dominant directors influence

audit opinions.

2.2 Control variables

2.2.1 Financial condition ( itBLAG , itR )

Previous studies find auditors disclose going-concern problems more often when companies

are close to failure. Consistent with previous studies, I include a bankruptcy lag variable

( itBLAG ) as an ex-post measure of financial condition (McKeown et al., 1991; Citron and

Taffler, 1992; Mutchler et al., 1997). The bankruptcy lag equals the number of calendar days

between audit opinions and failure. I expect a negative association between bankruptcy lag

and going-concern opinions since it is easier for audit firms to detect going-concern problems

when the bankruptcy horizon is short.8

Auditors may have difficulty in identifying going-concern problems when companies

fail with little warning. Therefore, an ex-ante measure of financial condition is also likely to

be correlated with audit opinions. Some studies use financial ratios or bankruptcy

probabilities predicted from accounting variables as ex-ante controls for financial condition

(Menon and Schwartz, 1987; McKeown et al., 1991; Mutchler et al., 1997; Casterella et al.,

1999).9 In contrast, I use stock returns ( itR ) for two reasons. First, predicted bankruptcy

probabilities likely do not capture all publicly available information about financial condition.

For example, the information content of financial ratios and predicted bankruptcy

8 Similarly, bankruptcy prediction models are more accurate over shorter bankruptcy horizons (e.g., Dambolena and Khoury,1980).9 Chen and Church (1996) show debt covenant violations significantly predict US going-concern opinions. Since UK companiesdo not generally disclose debt covenant violations, I am unable to test their association with audit opinions.

7

probabilities may be reduced if distressed companies choose accounting policies that cover up

poor performance (Murphy and Zimmerman, 1993). In contrast, share prices reflect all

publicly available information if the semi-strong efficient markets hypothesis holds. Second,

going-concern opinions and share prices are forward looking variables, whereas financial

statements are primarily backward looking. Therefore, going-concern opinions are likely

more strongly associated with stock returns than accounting variables. Since going-concern

problems are more apparent in companies with poor stock returns, I expect a negative relation

between rates of return and going-concern opinions.

2.2.2 Audit lag ( itALAG )

The audit lag is defined as the number of calendar days between financial year-ends and audit

opinions. Research shows auditors give going-concern opinions more often when audit

opinions are delayed (McKeown et al., 1991; Louwers, 1998). There are several possible

explanations for this. First, auditors may discover problems more frequently when they carry

out more audit tests. Second, auditors may undertake more tests if they expect going-concern

problems. Third, managers and auditors may engage in prolonged negotiations when there are

going-concern uncertainties. Finally, auditors may delay issuing audit reports in the hope that

companies can resolve their problems and avoid going-concern opinions. I expect a positive

association between audit lag and going-concern opinions.

2.2.3 Prior audit opinions ( 1−itG )

The audit report dummy ( itG ) equals one when auditors issue going-concern opinions and

zero otherwise. Several studies find auditors issue going-concern opinions more often when

prior opinions disclose going-concern problems (e.g., Mutchler, 1985). In other words, there

is persistence in audit reporting. Therefore, I expect a positive relation between prior and

current going-concern opinions.

8

2.3 Opinion shopping

I test for opinion shopping using the methodology employed by Lennox (2000a, 2000b). I use

an audit reporting model to predict the opinions that companies would receive if they switch

and if they do not switch. I include these predicted opinions in an auditor switching model to

test whether companies would receive going-concern opinions more often under opposite

switch decisions. Since auditor changes may be associated with financial distress, I control for

the effects of financial condition ( itBLAG , itR ) on auditor switching. I also include audit lag

( itALAG ) in the switching model, as newly appointed auditors may take longer to issue their

opinions compared to retained incumbent auditors.

3. The Data

3.1 Sample

My sample consists of UK companies traded on the London Stock Exchange (LSE), the

Unlisted Securities Market (USM) or the Alternative Investment Market (AIM). There are

355 companies that fail between 1980-99, where failure is defined as compulsory liquidation,

creditors’ voluntary liquidation, receivership or administration.10 I identify failed companies

using the “CGT Capital losses” publication. Fig. 1 shows the time-line for failing companies

and Table 1 describes how I obtain my final sample.

[INSERT TABLE 1 & FIG. 1 HERE]

I first require a minimum of two years’ accounts in order to identify auditor changes

and prior audit opinions. Where available, I collect final (t = -2) and penultimate (t = -3)

accounts from Companies House. There are 283 companies that meet this restriction. Second,

I require stock returns from Datastream and this results in the loss of a further 31 companies.11

10 I exclude voluntary liquidations by shareholders as these companies are typically non-distressed.11 In 9 companies there are insufficient data to calculate final annual returns because they become listed after the penultimateyear-end (t = -2). The remaining 22 companies are not listed by Datastream.

9

Third, I use accounts prior to penultimate year-ends in order to identify auditor appointment

dates and auditor-client tenures. In 15 companies I am unable to identify tenures because

accounts are not available for a sufficient number of years. My final sample consists of 237

companies and wherever possible I collect data for the last three year-ends (t = -2, -3, -4).

Although the potential sample size is 711 company-year observations (711 = 3*237), 51

observations are lost due to companies becoming listed during the sample period. Therefore,

my final sample consists of 660 company-year observations. There are 237 observations at

final year-ends (t = -2), 218 at penultimate year-ends (t = -3) and 205 at t = -4. With the

exception of the bankruptcy lag and audit opinions, I measure all variables at year-ends rather

than audit opinion dates.12

3.2 Descriptive statistics

Table 2 reports current and prior audit opinions for switching and non-switching companies.

There are 57 (8.64%) auditor changes and 90 (13.64%) going-concern opinions. Auditor

changes occur more frequently when prior opinions disclose going-concern problems. There

are 12 (28.57%) auditor changes when prior opinions disclose going-concern problems, but

only 45 (7.28%) auditor changes when prior opinions are clean. The difference between these

frequencies (28.57% and 7.28%) is statistically significant at the 1% level.

Auditor changes are significantly associated with changes in audit opinions. There are

13 (22.81%) changes in opinions when companies change audit firms, but only 67 (11.11%)

opinion changes when companies retain audit firms. The difference between these frequencies

(22.81% and 11.11%) is statistically significant at the 5% level.

[INSERT TABLE 2 HERE]

12 There is evidence that the market reacts negatively when going-concern opinions are announced (Firth, 1978; Banks andKinney, 1982; Fleak and Wilson, 1994; Jones, 1996). This means there is a potential reverse causality problem from auditopinions to stock returns. I avoid the reverse causality problem by measuring stock returns at year-ends rather than audit opiniondates.

10

Consistent with extant research, post-switch reports do not disclose going-concern

problems less often than pre-switch reports. Going-concern opinions are issued in 13

(22.81%) post-switch reports and 12 (21.05%) pre-switch reports. This does not refute the

opinion shopping hypothesis, as we shall see that prior opinions poorly proxy the reports that

companies would receive if they made different switch decisions.

Table 3 summarises auditor changes, audit opinions, bankruptcy lags and share

returns prior to failure. The frequency of auditor changes does not change significantly as

bankruptcy draws near. In contrast, the frequency of going-concern opinions rises from 5.37%

three periods prior to failure (t = -4) to 25.74% in final reports (t = -2). The median

bankruptcy lag falls from 1076 to 291 days between the third and final audit opinions while

the median lag between suspension and bankruptcy is only 3 days. Median (mean) stock

returns fall from 8.69% (26.46%) three periods prior to failure to –26.89% (-7.49%) at final

year-ends. Median (mean) returns are -75.93% (-67.10%) between final year-ends and

suspension. This suggests going-concern difficulties often do not become apparent until

shortly prior to failure.


Table 4 provides descriptive statistics on the auditor dependence and control

variables. Mean (median) audit fees are £96,450 (£43,000); large firms audit 58% of

companies; and, mean (median) auditor-client tenures are 7.33 (6) years. The mean (median)

proportions of board shares held by dominant directors are 67.61% (67.62%). The mean

(median) proportions of board remuneration earned by dominant directors are 32.41%

(29.48%).

Table 4 shows the audit fee ( itAF ), bankruptcy lag ( itBLAG ), returns ( itR ), and

audit lag ( itALAG ) variables have skewed distributions and contain outlying variables. To

account for this, I use log transformations ( )ln( ,)ln( ,)ln( ,)ln( itititit ALAGRBLAGAF ). In

11

unreported results, I find my conclusions are robust to using either untransformed or log

variables although explanatory power is higher with the latter.


Table 5 reports descriptive statistics for the explanatory variables across going-

concern and non-going-concern opinions. The univariate associations between opinions and

the auditor dependence variables are not statistically significant. In contrast, audit opinions

are significantly associated with financial conditions. Going-concern opinions are issued more

often when bankruptcy lags ( )ln( itBLAG ) are short and returns ( )ln( itR ) are low. In

addition, going-concern opinions are issued more often when audit lags ( )ln( itALAG ) are

long.


4. Auditor dependence

4.1 Model specification

In this section, I test the multivariate associations between going-concern opinions and the

auditor dependence variables ( )ln( itAF , itAUD , itTEN , itDOMS , itDOMR ). As

explained in section 2.2, I also control for financial condition ( )ln( itBLAG , )ln( itR ), audit

lag ( )ln( itALAG ) and prior audit opinions ( 1−itG ). Eq. (1) is the model of going-concern

opinions:

itititit

itititititit

GALAGRBLAGDOMRDOMSTENAUDAFG

εαααααααααα

++++++++++=

− 19876

543210*

)ln()ln()ln()ln(

(1)

where:

.0 if 0

1 if 0*

*

=<=≥

itit

itit

GG

GG

12

4.2 Estimation results

The probit estimation results for Eq. (1) are given in Table 6.13 Column (1) shows the

coefficients on audit fees ( )ln( itAF ), audit firm size ( itAUD ), tenure ( itTEN ) and director

dominance ( itDOMS , itDOMR ) are all statistically insignificant. Moreover, the coefficients

on audit firm size and director dominance have opposite signs to those predicted by the

auditor dependence hypothesis. Therefore, the auditor dependence variables do not explain

why failing companies avoid going-concern opinions.14


Columns (1) and (2) show auditors disclose going-concern uncertainties more often

when financial conditions are poor. The significant negative coefficients on bankruptcy lag

( )ln( itBLAG ) indicate more frequent going-concern opinions when companies are close to

failure. The significant negative coefficients on returns ( )ln( itR ) show auditors issue going-

concern opinions more often when companies have poor market performance. The significant

positive coefficients on audit lag ( )ln( itALAG ) show auditors give going-concern opinions

more often when audit reports are delayed.15 The significant positive coefficients on prior

opinions ( 1−itG ) reveal strong persistence in audit reporting. Audit firms give going-concern

opinions more often when companies receive prior going-concern opinions. The explanatory

power of the reporting model compares favourably with previous studies. The pseudo R2 is

41.6% in Column (2), compared with 36.4% in Casterella et al., (1999), 30.6% in Mutchler et

al., (1997), 24.7% in McKeown et al., (1987), and 10.5% in McKeown et al., (1991).

13 In unreported estimations, I find probit and logit results are very similar.14 In unreported estimations, I find average audit fees ( ).ln( iAF ) and abnormal audit fees ( ).ln()ln( iAFitAF − ) are not

significantly correlated with going-concern opinions. I also find no evidence of a non-monotonic relation between tenure andgoing-concern opinions.

13

5. Opinion shopping

5.1 Model specifications

In this section, I estimate an audit reporting model in order to predict the opinions companies

would receive if they switch or do not switch auditors. Eq. (2) omits the auditor dependence

variables as Section 4 shows them to be insignificant. It includes an auditor switch dummy

( itS ), which equals one if there is a change in audit firm and zero otherwise. Eq. (2) also

includes an interaction term between the switch dummy and prior opinions ( 1−ititGS ), to test

whether auditor changes are associated with less reporting persistence ( 06 <α ).

itititit

ititititit

GSSGALAGRBLAGG

εααααααα

+++++++=

−

−

165

143210* )ln()ln()ln(

(2)

where:

.0 if 0

1 if 0*

*

=<=≥

itit

itit

GG

GG

I use Eq. (2) to predict the opinions companies would receive if they switch ( *1̂itG ) or

do not switch ( *0̂itG ). My opinion shopping variable is the difference between these predicted

opinions ( *0*1 ˆîtit GG − ). When *0*1 ˆˆ

itit GG − > 0, companies are more likely to receive going-

concern opinions if they switch auditors. When *0*1 ˆîtit GG − < 0, companies are more likely to

receive going-concern opinions if they do not switch. If companies use auditor appointments

to avoid going-concern opinions, auditor changes occur when *0*1 ˆîtit GG − < 0 and do not

occur when *0*1 ˆîtit GG − > 0. I include the opinion shopping variable in Eq. (3) to test whether

companies receive going-concern opinions less often as a result of auditor switching. Under

the alternative hypothesis that companies successfully engage in opinion shopping, the

coefficient on *0*1 ˆîtit GG − is negative ( 01 <θ ). Under the null hypothesis that companies do

15 In unreported results, I find the abnormal audit lag ( ).ln()ln( iALAGitALAG − ) is significantly associated with going-

concern opinions, but its association is weaker than the unadjusted audit lag ( )ln( itALAG ).

14

not successfully engage in opinion shopping, 01 =θ . Eq. (3) also controls for financial

condition ( )ln( ,)ln( itit RBLAG ) and audit lag ( )ln( itALAG ).

ititititititit ALAGRBLAGGGS ωθθθθθ ++++−+= )ln()ln()ln()ˆˆ( 432*0*1

10* (3)

where:

.0 if 0

1 if 0*

*

=<=≥

itit

itit

SS

SS

Substituting Eq. (2) into Eq. (3) gives a reduced form model of auditor switching (Eq.

(4)):

itititititit GALAGRBLAGS ωαθθθθαθθ ++++++= − 161432510* ˆ)ln()ln()ln(ˆ (4)

where:

.0 if 0

1 if 0*

*

=<=≥

itit

itit

SS

SS

It is important to note that Eq. (3) includes the difference between predicted going-concern

opinions ( *0*1 ˆˆitit GG − ) while Eq. (4) includes prior audit opinions ( 1−itG ). Eq. (4) demonstrates

there is a positive association between prior going-concern opinions and auditor changes if

06̂1 >αθ . This condition holds if auditor changes are associated with less reporting

persistence ( 06̂ <α ) and companies successfully engage in opinion shopping ( 01 <θ ).

5.2 Estimation results

The probit estimation results for Eqs. (2)-(4) are given in Columns (1)-(3) of Table 7. Column

(1) shows the coefficient on the interaction term ( 1−ititGS ) is negative and statistically

significant. This means there is significantly less persistence in going-concern opinions when

there are auditor changes ( 06̂ <α ). In other words, audit opinions change more often when

there are changes in audit firms. The coefficients on the other variables are consistent with the

models in Table 6. Companies receive going-concern opinions more often when financial

15

conditions ( )ln( ,)ln( itit RBLAG ) are poor, audit lags ( )ln( itALAG ) are long, and prior

opinions ( 1−itG ) disclose going-concern uncertainties.


The results for the reporting model in Column (1) are used to predict going-concern

opinions if companies switch or do not switch auditors. When prior opinions disclose going-

concern problems, the mean predicted going-concern probabilities are 39.42% if companies

switch and 69.05% if companies do not switch. Therefore, companies are less likely to

receive repeat going-concern opinions if they change auditors. When prior opinions do not

disclose going-concern problems, the mean predicted going-concern probabilities are 12.21%

if companies switch and 10.01% if companies do not switch. Therefore, companies are more

likely to receive repeat clean opinions if they do not change auditors.

The results for the auditor switching models in Columns (2) and (3) are consistent

with successful opinion shopping. In Column (2), the significant negative coefficient ( 01 <θ )

on the opinion shopping variable ( *0*1 ˆˆitit GG − ) shows companies receive going-concern

opinions less often as a result of auditor changes. In Column (3), the significant positive

coefficient ( 06̂1 >αθ ) on prior reports ( 1−itG ) shows auditor changes occur more frequently

after companies receive going-concern opinions. This is what we would expect since Column

(1) shows that 06̂ <α . Auditor changes are not significantly associated with financial

condition ( )ln( ,)ln( itit RBLAG ). The significant positive coefficients on audit lag

( )ln( itALAG ) indicate newly appointed auditors take longer than retained incumbents to

issue their audit opinions.

6. Conclusions and implications for audit regulation

There are a number of regulatory measures that aim to strengthen auditor independence and

16

prevent opinion shopping. These include banning non-audit services, mandatory rotation,

mandatory retention and communication between outgoing auditors, incoming auditors and

shareholders. This paper investigates whether auditors give clean opinions to failing

companies due to auditor dependence or opinion shopping. I sample failing rather than

surviving companies in order to increase the power of my tests for auditor dependence and to

provide clearer recommendations for policy-makers.

Since bargaining between audit firms and clients occurs behind closed doors it is

arguably difficult to observe the effects of auditor dependence on audit opinions. Despite this,

I hypothesise managers are more likely to exert pressure and auditors are more likely to

acquiesce when: audit fees are high, audit firms are small, auditor-client tenures are long and

individual directors dominate boards. I find no significant association between these variables

and going-concern opinions, which suggests either failing companies do not pressurise

auditors or auditors report independently.

I test for opinion shopping by predicting the reports switching and non-switching

companies would receive under opposite switch decisions. My results suggest companies

would receive going-concern opinions significantly more often if auditor changes were

different to those actually observed. This suggests failing companies successfully engage in

opinion shopping.

My results indicate policy-makers should be more concerned with opinion shopping

than auditor dependence. Regulators might curb opinion shopping by introducing mandatory

retention of audit firms or by requiring greater disclosure about auditor changes. The need for

more communication between investors, outgoing and incoming auditors is particularly

relevant in the UK. Companies and auditors are not required to disclose auditor changes or

disagreements to the stock market and incoming auditors do not have access rights to the

working papers of outgoing auditors. However, policy recommendations such as increased

communication or mandatory retention carry an important caveat. If regulators deter opinion

shopping, the number of going-concern opinions is likely to increase in surviving as well as

failing companies.

17

t = -4 t = -3 t = -2 t = -1 t = 0

Third year-end Penultimate Final Suspension of Bankruptcyprior to failure year-end year-end share trading date

Fig. 1. The time-line for failing companies.

Table 1Derivation of the final sample.

Companies Company-yearobservations

Population of failing UK companies(1980-99).

355 .

Less: 72 companies where final andpenultimate accounts are unavailable.

(72) .

Less: 31 companies where stock returns areunavailable.

(31) .

Less: 15 companies where auditor-clienttenures are unavailable.

(15) .

Final sample of companies. 237 .

Less: 51 observations where companiesbecome listed during the sample period.

. (51)

Final sample of company-year observations. 237 660

Notes:Company-year observations are taken from the last three accounting year-ends (t = -4, -3, -2). See Fig. 1.

18

Table 2Current ( itG ) and prior ( 1−itG ) going-concern opinions.

Auditor retentions ( itS = 0)

itG = 1 itG = 0 Totals

1−itG = 1 20 10 30

1−itG = 0 57 516 573

Totals 77 526 603

Auditor changes ( itS = 1)

itG = 1 itG = 0 Totals

1−itG = 1 6 6 12

1−itG = 0 7 38 45

Totals 13 44 57

Notes:t = -4, -3, -2 at the last three year-ends prior to failure. See Fig. 1.

itS = 1 if company i changes audit firm at time t; 0 otherwise.

itG = 1 if company i receives a going-concern opinion at time t; 0 otherwise.

19

Table 3Auditor changes, audit opinions, and financial conditions prior to failure.

Time (t) -4 -3 -2 -1

No. (%) of auditor changes 16(7.80%)

21(9.63%)

20(8.44%)

.

.

No. (%) of going-concern opinions 11(5.37%)

18(8.26%)

61(25.74%)

.

.

Median (mean) bankruptcylag ( itBLAG )

1076(1098)

684(707)

291(321)

3(39)

Median (mean) returns ( itR ) 8.69%(26.46%)

-9.67%(6.58%)

-26.89%(-7.49%)

-75.93%(-67.10%)

Observations 205 218 237 237

Notes:t = -4, -3, -2 at the last three year-ends prior to failure and t = -1 at suspension. See Fig. 1.

itBLAG = Number of days between the audit opinion and the bankruptcy date.

1)1( −−−+= itSPitSPitDPSitSPitR

itSP = Share price of company i at time t.

itDPS = Dividend per share of company i at time t.

20

Table 4Descriptive statistics for the explanatory variables.

Mean Median Min MaxAuditor dependencevariables

itAF 96.45 43.00 0.10 3300

itAUD 0.58 1 0 1

itTEN 7.33 6 1 26

itDOMS 67.61 67.62 21.25 100

itDOMR 32.41 29.48 5.52 100

Control variables

itBLAG 690 673 17 2135

itR 7.70% -8.10% -98.86% 1622%

itALAG 135 122 27 548

Notes:t = -4, -3, -2 at the last three year-ends prior to failure. See Fig. 1. Observations = 660.

itAF = Audit fee (£000).

itAUD = 1 if audit firm is one of the Big Five; = 0 otherwise. An audit firm belongs to the ‘Big Five’ if it is

Ernst and Young, Price WaterhouseCoopers, Arthur Andersen, KPMG, Deloitte and Touche or a pre-mergerfirm (Arthur Young, Ernst & Whinney, Price Waterhouse, Coopers & Lybrand, Deloittes Haskins and Sells,Peat Marwick Thomson McLintock, Touche Ross, Spicer and Pegler, Spicer and Oppenheim).

itTEN = Number of years the audit firm has audited the client.

ngsshareholdi Boardngshareholdi sdirector' individualLargest *%100=itDOMS

onremunerati Boarddirector paidhighest of onRemunerati*%100=itDOMR


1)1( −−−+= itSPitSPitDPSitSPitR



itALAG = Number of days between the year-end and the audit opinion.

21

Table 5Descriptive statistics for going-concern and non-going-concern opinions.

Going-concernopinions ( itG = 1)

Non-going-concernopinions ( itG = 0)

Mean Median Mean MedianAuditor dependencevariables

)ln( itAF 10.75 10.67 10.69 10.66

itAUD 0.53 1 0.59 1

itTEN 7.46 5.50 7.32 6.00

itDOMS 72.67% 76.81% 66.81% 66.36%

itDOMR 34.16% 29.57% 32.14% 29.48%

Control variables)ln( itBLAG 5.76** 5.76** 6.43 6.58

)ln( itR -74.16%** -61.15%** -7.47% -3.90%

)ln( itALAG 5.24** 5.19** 4.75 4.76

Observations 90 570

Notes:** Significant difference between going-concern and non-going-concern opinions (1% level).t = -4, -3, -2 at the last three year-ends prior to failure. See Fig. 1.



itAUD = 1 if audit firm is one of the Big Five; = 0 otherwise. An audit firm belongs to the ‘Big Five’ if it is

Ernst and Young, Price WaterhouseCoopers, Arthur Andersen, KPMG, Deloitte and Touche or a pre-mergerfirm (Arthur Young, Ernst & Whinney, Price Waterhouse, Coopers & Lybrand, Deloittes Haskins and Sells,Peat Marwick Thomson McLintock, Touche Ross, Spicer and Pegler, Spicer and Oppenheim).





)1)ln(()ln( −+= itSPitDPSitSPitR




22

Table 6The association between going-concern opinions and auditor dependence.

Expectedsign

(1) (2)

Auditor dependencevariables

)ln( itAF ? -0.078(-1.098)

.

.

itAUD + -0.018(-0.107)

.

.

itTEN ? 0.015(0.999)

.

.

itDOMS - 0.004(1.177)

.

.

itDOMR - 0.001(0.176)

.

.Control variables

)ln( itBLAG - -0.370(-2.976)**

-0.352(-2.820)**

)ln( itR - -0.745(-6.066)**

-0.693(-5.684)**

)ln( itALAG + 1.526(6.092)**

1.543(6.534)**

1−itG + 1.710(6.037)**

1.729(6.082)**

CONSTANT ? -6.477(-3.644)**

-7.055(-5.126)**

Pseudo R2 42.36% 41.58%Notes:t = -4, -3, -2 at the last three year-ends prior to failure. See Fig. 1. Observations = 660.z-statistics reported in parentheses. ** Significant at the 1% level. * Significant at the 5% level.



itAUD = 1 if audit firm is one of the Big Five; = 0 otherwise. An audit firm belongs to the ‘Big Five’ if it is Ernst and

Young, Price WaterhouseCoopers, Arthur Andersen, KPMG, Deloitte and Touche or a pre-merger firm (Arthur Young,Ernst & Whinney, Price Waterhouse, Coopers & Lybrand, Deloittes Haskins and Sells, Peat Marwick ThomsonMcLintock, Touche Ross, Spicer and Pegler, Spicer and Oppenheim).









23

Table 7The association between going-concern opinions and opinion shopping.

Expectedsign

(1) Expectedsign

(2) (3)

Dependent variable *itG *

itS *itS

Opinion shopping variable*0*1 ˆˆ

itit GG − ..

- -0.555(-3.571)**

.

.Control variables

itS ? 0.174(0.522)

.

...

1−ititGS - -1.461(-2.447)*

.

...

)ln( itBLAG - -0.349(-2.773)**

- 0.080(0.776)

0.080(0.776)

)ln( itR - -0.709(-5.831)**

- -0.047(-0.423)

-0.047(-0.423)

)ln( itALAG + 1.608(6.428)**

+ 0.398(2.101)*

0.398(2.101)*

1−itG + 2.088(6.050)**

+ ..

0.811(3.571)**

CONSTANT ? -7.429(-5.233)**

? -3.803(-3.156)**

-3.899(-3.244)**

Pseudo R2 42.69% 5.50% 5.50%Notes:t = -4, -3, -2 at the last three year-ends prior to failure. See Fig. 1. Observations = 660.z-statistics reported in parentheses. ** Significant at the 1% level. * Significant at the 5% level.


.0 if 0*

;1 if 0* =<=≥ itGitGitGitG

firm.audit changes icompany if variableconcern-going Predicted*1̂ =itG

firm.audit changenot does icompany if variableconcern-going Predicted*0ˆ =itG

itS = 1 if company i changes audit firm at time t; 0 otherwise.

.0 if 0*

;1 if 0* =<=≥ itSitSitSitS






24

References

American Institute Of Certified Public Accountants, 1978. The commission on auditors’

responsibilities: Report, conclusions and recommendations.

American Institute Of Certified Public Accountants (SEC Practice Section), 1992. Statement

of position regarding mandatory rotation of audit firms of publicly held companies.

Australian Society Of Certified Practising Accountants and The Institute Of Chartered

Accountants in Australia, 1993. A research study on financial reporting and auditing:

Bridging the expectations gap.

Australian Society Of Certified Practising Accountants and The Institute Of Chartered

Accountants in Australia, 1996. Beyond the expectations gap.

Banks, D. and Kinney, W., 1982. Loss contingency reports and stock prices: An empirical

study, Journal of Accounting Research, Vol. 20, No. 1: 240-254.

Buijink, W., Maijoor, S., Meuwissen, R. and van Witteloostuijn, A., 1996. The role, position

and liability of the statutory auditor within the European Union, (final report of a study

commissioned by DG XV of the European Commission). Luxembourg: Office for

Official Publications of the European Communities.

Cadbury Committee, 1992. Report of the committee on financial aspects of corporate

governance.

Casterella, J., B. Lewis, P. Walker, 1999. Why do bankrupt companies receive unmodified

opinions? Research in Accounting Regulation, Vol. 13: 169-177.

Chen, K. and B. Church, 1996. Going concern opinions and the market’s reaction to

bankruptcy filings, The Accounting Review, Vol. 71, No. 1: 117-128.

Chow, C., Rice, S., 1982. Modified audit opinions and auditor switching. The Accounting

Review 57, 326-35.

Citron, D. and R. Taffler, 1992. The audit report under going-concern uncertainties: An

empirical analysis, Accounting and Business Research, Vol. 22: 337-345.

Craswell, A., 1999. Does the provision of non-audit services impair auditor independence?

International Journal of Auditing 3(1), 29-40.

25

Dambolena, I. and S. Khoury, 1980. Ratio stability and corporate failure, The Journal of

Finance, Vol. 35, No. 4.

Davis, R., 1982. An empirical evaluation of auditors’ ‘subject-to’ opinions, Auditing: A

Journal of Practice and Theory, pp. 13-32.

DeAngelo, L., 1981. Auditor size and audit quality, Journal of Accounting and Economics,

Vol. 3: 183-199.

Dunn, J., Puxty, A., Sikka, P., 1994. Auditor resignations from public limited companies:

Some preliminary findings. Working Paper.

Dye, R., 1993. Auditing standards, legal liability and auditor wealth, Journal of Political

Economy, Vol. 101: 887-914.

Firth, M., 1978. Qualified audit reports: Their impact on investment decisions, The

Accounting Review, pp. 642-650.

Fleak, S. and Wilson, E., 1994. The incremental information content of the going concern

audit opinion’, Journal of Accounting, Auditing and Finance, Vol. 9, No. 1: 149-166.

Jones, F., 1996. The information content of the auditor’s going concern evaluation, Journal of

Accounting and Public Policy, Vol. 15: 1-27.

Koh, H., 1991. Model predictions and auditor assessments of going concern status,

Accounting and Business Research, Vol. 21, No. 84: 331-338.

Krishnan, J., 1994. Auditor switching and conservatism. The Accounting Review 69: 200-15.

Krishnan, J., Krishnan, J., Stephens, R., 1996. The simultaneous relation between auditor

switching and auditor opinion: An empirical analysis. Accounting and Business Research

26, 224-36.

Krishnan, J., Stephens, R., 1995. Evidence on opinion shopping from audit opinion

conservatism. Journal of Accounting and Public Policy 14, 179-201.

Lennox, C., 1999a. Non-audit fees, disclosure and audit quality, European Accounting

Review, Vol. 8, No. 2: 239-252.

26

Lennox, C., 1999b. The accuracy and incremental information content of audit reports in

predicting bankruptcy, Journal of Business, Finance and Accounting, Vol. 26, Nos. 5 & 6:

757-778.

Lennox, C., 2000a. Do companies successfully engage in opinion shopping? The UK

experience, Journal of Accounting and Economics, 2000, Vol. 29, No. 1.

Lennox, C., 2000b. An empirical analysis of opinion shopping: The US experience. Working

Paper.

Louwers, T., 1998. The relation between going-concern opinions and the auditor’s loss

function. Journal of Accounting Research, Vool. 36, No. 1: 143-156.

McKeown, J., Mutchler, J., and Hopwood, W., 1991. Towards an explanation of auditor

failure to modify the audit opinions of bankrupt companies, Auditing: A Journal of

Practice and Theory, 10 (Supplement): 1-13.

Menon, K., and Schwartz, K., 1987. An empirical investigation of audit qualification

decisions in the presence of going concern uncertainties, Contemporary Accounting

Research (Spring): 302-15.

Murphy, K., Zimmerman, J. L., 1993, Financial performance surrounding CEO turnover,

Journal of Accounting and Economics, 16 273-315.

Mutchler J., 1985. A multivariate analysis of the auditor’s going-coincern opinion decision,

Journal of Accounting Research: 668-82.

Mutchler, J., Hopwood, W., and McKeown, J., 1997. The influence of contrary information

and mitigating factors on audit opinion decisions on bankrupt companies, Journal of

Accounting Research, 35 (2) (Autumn): 295-310.

Public Oversight Board Advisory Panel on Auditor Independence, 1994. Strengthening the

professionalism of the independent auditor.

Smith, D., 1986. Auditor ‘subject to’ opinions, disclaimers and auditor changes. Auditing: A

Journal of Practice and Theory 6, 95-108.

Teoh, S., 1992. Auditor independence, dismissal threats, and the market reaction to auditor

switches. Journal of Accounting Research 30: 1-23.

going concern opinion in falling companies auditor dependence and opinion shopping

Documents