1Going-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.

21. 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.

3auditors 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).

4clearly 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 clients fee is a large proportion of an audit firmstotal income. Unfortunately, data on total fees are unavailable for small audit firms. However, this is unlikely to be a problem as

52.1.2 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 boards 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.

6variables - 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.

7probabilities 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.

82.3 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.

9Third, 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.

[INSERT TABLE 3 HERE]

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.

[INSERT TABLE 4 HERE]

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.

[INSERT TABLE 5 HERE]

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

eaaaaaaaaaa

++++++++++=

- 19876

543210*

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

(1)

where:

.0 if 0

1 if 0*

*

= 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 itit GG - is negative ( 01

14

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

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

ititititititit ALAGRBLAGGGS wqqqqq ++++-+= )ln()ln()ln()( 432*0*110* (3)

where:

.0 if 0

1 if 0*

*

=