An Empirical Analysis of Big N Auditor Switches: Evidence from the pre- and post-Enron Eras

Wayne R. Landsman,a Karen K. Nelson,b and Brian R. Rountree b

a Kenan-Flagler Business School, University of North Carolina

b Jones Graduate School of Management, Rice University

August 2006

Abstract

Using a comprehensive sample of lateral switches among the largest auditors (i.e., the Big N) this study documents that the probability of a lateral switch in Big N audit firms increases significantly in both the audit and financial risk of the client in the pre-Enron period but not in the post-Enron period. In both periods, clients switching downward to a non-Big N auditor pose similar audit and financial risks as lateral Big N switches, but are smaller and tend to have going concern opinions. We interpret our findings as evidence that the swapping of large, risky clients between Big N auditors is less prevalent in the post-Enron era, suggesting that Big N auditors may have become more sensitive to risky clients in recent years.

JEL classification: L14; L84; K22; M4

Keywords: Auditor switching; Audit risk; Financial risk;

We appreciate the helpful comments and suggestions of Bill Beaver, Allen Blay, Ling Lei, and workshop participants at the 2005 American Accounting Association Annual Meeting. Scott Whisenant generously provided some of the data for this study. We acknowledge funding from the Center for Finance and Accounting Research at UNC-Chapel Hill.

Corresponding author: Wayne Landsman, Kenan-Flagler Business School, University of North Carolina, Chapel Hill, NC, 27599-3490, wayne_landsman@unc.edu.

1. Introduction

Recent accounting scandals, including Enron, WorldCom, Global Crossing, and Qwest,

have brought about a sea of change in the audit industry, most notably the dissolution of Arthur

Andersen. The accounting industry has responded to the scandals in several ways, including an

assertion by the remaining top-tier accounting firms (i.e., the Big N) that they have since dropped

hundreds of clients that expose them to unacceptable levels of risk:

After watching former Big Five accounting firm Arthur Andersen implode after its Enron (ENRNQ) Corp. entanglement, the surviving Big Four aren't leaving much to chance. PricewaterhouseCoopers and Deloitte & Touche each have shed about 500 clients in the past 18 months because of liability concerns. With earnings being restated at a record clip, shareholder lawsuits have increased. We have tightened up our standards, says Gregory Weaver, the head of Deloitte's U.S. audit practice. Ernst & Young has parted ways with more than 200 clients. KPMG declined to comment. (Hindo, 2003)

Although risk avoidance has perhaps become more salient in recent years, it is certainly

not a new issue. Beginning in the early 1990s, the Big N reportedly became more likely to

avoid high-risk clients because of concerns that the profession faced increased liability (Cook et

al., 1992]; POB, 1993; Holland et al., 1993; Berton, 1995; MacDonald, 1997). As a result, risky

clients switching from one of the Big N firms are viewed as having little choice but to engage a

smaller auditor that lacks the reputation and cachet of the Big N.

Although prior academic studies generally show a positive correlation, on average,

between client risk and the probability of an auditor switch (e.g., Krishnan and Krishnan, 1997;

Shu, 2000; Johnstone and Bedard, 2004), this research typically pools auditor switches of all

types. i.e., upward, downward, lateral Big N, and lateral non-Big N. As a result, it is impossible

to infer from prior evidence whether risky clients are switching to a lower-tier auditor as claimed

or laterally to another Big N auditor. The purpose of this paper is to directly examine lateral

2

switches among Big N auditors, the most economically significant set of auditor switches, both

in the decade leading up to Enrons collapse and in the subsequent years.

To investigate whether client risk factors are associated with lateral Big N auditor

switches, we estimate a logit regression that models this type of auditor switch as a function of

client audit risk and financial risk, as well as several control variables. The null hypothesis

predicts that the risk factors will not be associated with lateral Big N auditor switches if risky

clients are indeed excluded from the Big N audit market. In other words, risky clients leaving

their incumbent Big N auditor will not be able to engage another Big N auditor. Alternatively, if

risky clients are not excluded from the Big N auditor market but instead are able to switch

laterally to another Big N auditor, there will be a significant association between client risk and

the lateral Big N auditor switches in our sample.

Our results indicate that the probability of a lateral switch among Big N auditors is

significantly increasing in both client audit risk and financial risk. Thus, even though risky

clients are more likely to switch auditors, another Big N auditor is willing to accept the

engagement. These results hold regardless of whether the auditor resigned from the engagement

or was dismissed by the client, and for all Big N auditors.

To provide further evidence on the nature of lateral Big N auditor switches, we compare

the risk profile of clients switching laterally to another Big N auditor to that of clients switching

downward to a non-Big N auditor. The results indicate that these two types of auditor switches

are associated with similar client-related risks. Companies excluded from the Big N audit

market, however, are much smaller and tend to have going concern audit opinions, suggesting

that large, risky companies are able to switch laterally to another Big N auditor while small

companies that pose less economic risk to the auditor switch downward to a non-Big N auditor.

3

We also show that our findings for lateral Big N auditor switches cannot be explained by

auditor realignment or clientele adjustment (Johnson and Lys, 1990; Shu, 2000). These theories

of auditor switching predict that clients will replace their incumbent auditor with a substantially

larger or smaller firm. Therefore, we expect auditor realignment to be a factor for companies

switching downwards to a non-Big N auditor, but not for companies switching laterally to

another Big N auditor. Our results support these predictions, thus confirming the results of prior

studies for switches between large and small auditors and extending the literature to provide

evidence of risky clients switching between large auditors.

Finally, we examine the risk profile post-Enron auditor switches to determine whether

sensitivity to client risk has changed. Although these results should be interpreted with caution

because of limited data availability for the 2002-2004 post-Enron period, we find some evidence

of changes in the market for auditor switches. Specifically, we document that lateral Big N

switches occur with relatively lower frequency and are no longer significantly associated with

client audit and financial risk. Downward switches in the post-Enron environment, however, still

occur primarily for small clients with going concern opinions.

Although the evidence in this paper is broadly consistent with claims that risky clients are

more likely to switch auditors, suggesting that audit or financial risk cannot be fully priced

(OKeefe et al., 1994; Bockus and Gigler, 1998; Bell et al., 2001), we extend prior literature to

show that these risky clients are able to engage another Big N auditor. It is important to note,

however, that our results do not necessarily imply suboptimal behavior on the part of Big N

auditors. One possible explanation for our findings is that the successor Big N auditor is willing

to accept the risk posed in hopes of higher fees in the future, and when these fees do not

materialize the risky client again switches auditors. It is also possible that the risk faced by the

4

incumbent and successor auditors differ, even though the clients risk is unchanged. In

particular, to the extent the successor auditor is not exposed to client risk arising from

transactions that occurred under the incumbent auditor, client risk may be lower for the successor

auditor, making the risky client profitable. Further understanding of the economic forces

underlying lateral Big N auditor switches is thus a fruitful area for additional research.

The remainder of the paper is organized as follows. Section 2 discusses prior research,

and explains how our study builds on this literature. Section 3 outlines our research design.

Section 4 describes the sample data and presents the empirical findings for the pre-Enron era.

Section 5 presents results for the post-Enron era. Section 6 summarizes and concludes the study.

2. Relation to prior literature

Auditors frequently cite risk avoidance as a primary factor in managing their client

portfolios (e.g., Holland et al., 1993; Berton, 1995; MacDonald, 1997; Hindo, 2003). Consistent

with these claims, empirical evidence generally documents a positive association, on average,

between client risk factors and auditor switches, particularly when the auditor resigns from an

engagement (e.g., Krishnan and Krishnan, 1997; Shu, 2000; Johnstone and Bedard, 2004).

Bradshaw et al. (2001), however, finds that auditor switches are less likely for high accrual

companies even though such companies are riskier to the extent that high accruals increase the

likelihood of GAAP violations.

In addition to divesting risky clients, evidence suggests that risk assessments factor into

auditors client acceptance decisions (e.g., Johnstone, 2000; Johnstone and Bedard, 2003, 2004).

A related stream of literature examines whether auditors accept risky clients, but attempt to

manage this risk by adjusting audit fees, audit procedures, and/or engagement personnel. The

evidence in this regard, however, is mixed. The findings in Johnstone (2000) are not consistent

5

with auditors adopting such risk management strategies, whereas Bell et al. (2001) and Johnstone

and Bedard (2003) report that auditors do appear to respond to client risk factors. Bell et al.

(2001) also notes, however, that risk management strategies cannot, in principle, eliminate or

reduce auditor business risk below a certain level.

Conventional wisdom suggests that risky clients leaving a Big N firm will be forced to

hire smaller, lower tier accounting firms (e.g., Holland et al., 1993; Berton, 1995; MacDonald,

1997; Hindo, 2003). Consistent with this perception, Bockus and Gigler (1998) analytically

demonstrates that auditors will resign from riskier clients, and that these clients then engage a

smaller (i.e., more wealth-constrained) auditor. However, despite the general view that risky

clients drop to a lower tier auditor, prior empirical research typically pools auditor switches of all

types, i.e., upward, downward, lateral Big N, and lateral non-Big N.1 As a result, there is very

little direct evidence on the role of client risk in determining whether companies are excluded

from the Big N audit market. In other words, simply because auditor switches are associated

with client risk in general, one cannot conclude that client risk plays a role in all types of auditor

switches, or that auditor switches involving risky clients generally result in the client switching

to a non-Big N auditor.

Based on 1986 data, Haskins and Williams (1990) finds that client financial distress, size,

and growth, along with audit firm industry dominance, are the most important factors associated

with lateral Big N auditor switches.2 For a sample of auditor switches by failing companies,

1 In addition to the papers cited above, other work that does not differentiate the type of auditor switch in the

empirical analysis includes Chow and Rice (1982), Francis and Wilson (1988), and Krishnan (1994). Although some of these studies present descriptive information on the frequency of auditor switches by type, none examines the risk profile of clients switching laterally within the Big N, or compare the lateral Big N switches to clients switching downward to a non-Big N auditor. 2 Unlike the other studies in the auditor change literature which rely on binary probability models, Haskin and

Williams (1990) employs a recursive partitioning algorithm that sequentially identifies the best model, i.e., the model with the smallest apparent error rate. This approach, however, is subject to concerns about overfitting tendencies.

6

Schwartz and Menon (1985) shows that downward switches to a non-Big N auditor (10

companies) are no more prevalent than lateral switches among Big N auditors (11 companies), or

upward switches to a Big N auditor (12 companies). In contrast, Shu (2000) finds that riskier

clients are less likely to engage another large auditor when the incumbent auditor resigns from

the engagement. However, Shu (2000) defines large auditor broadly to include not only Big N

auditors but also 18 non-Big N auditors with individual auditor codes on Compustat.

A related set of studies examines risk characteristics of Big N client portfolios across

periods of differing litigation risk. For a sample of small manufacturing companies, Jones and

Raghunandan (1998) shows that Big N auditors were less likely to audit risky clients over a

period of increasing litigation costs. Similarly, Choi et al. (2004) finds that the riskiness of Big

N client portfolios changes in response to changes in the litigation environment. Their results

show not only a significant increase since 1990 in the proportion of high risk clients departing

the Big N audit market, but also a significant increase in the proportion of high risk clients

entering the Big N audit market. Neither of these papers, however, examines the riskiness of

clients switching between Big N auditors.

We build on the prior literature in several important ways. First, we focus our analysis on

lateral Big N auditor switches, and directly investigate whether risky clients are excluded from

the Big N audit market. If this perception is correct, then risk factors should not play a role in

lateral Big N auditor switches as risky clients will be unable to engage another Big N auditor.

Contrary to this view, we present the first evidence of a significant association between lateral

Big N auditor changes and client risk. Second, we contrast the risk profile of companies

switching laterally between Big N auditors to that of companies switching downward to a non-

Big N auditor. This analysis provides evidence on whether the sensitivity to client risk differs

7

for lateral Big N and downward switches. Again contrary to popular perceptions, we find that

these two types of auditor switches are associated with similar client-related risks.

Third, we differentiate our findings for lateral Big N auditor switches from theories of

auditor realignment or clientele mismatch offered in prior research (e.g., Johnson and Lys, 1990;

Shu, 2000). These theories predict that clients will replace their incumbent auditor with a

substantially larger or smaller firm, and thus should not explain lateral Big N switches in which

the incumbent auditor is replaced with a firm of similar size. Consistent with our expectations,

we find that auditor realignment is not a factor in lateral Big N switches, but is a factor in

downward switches to a non-Big N auditor. Thus, while our study reinforces the evidence of

realignment between auditors of different sizes presented in these studies, we also provide new

evidence of the swapping of risky clients among the Big N audit firms.

Finally, we present the first empirical evidence comparing the risk profiles of pre -and

post-Enron auditor switches. Following Enrons collapse, some suggest that auditors,

particularly the Big N, have become more sensitive to risky clients (e.g., Hindo, 2003). We find

some evidence consistent with this view, as lateral Big N switches are less frequent and are no

longer significantly associated with client risk factors.

3. Research design and data

3.1. Lateral Big N auditor switches

We model lateral switches among Big N auditors as a function of client-specific risk

characteristics and various controls, including year and industry fixed effects to allow for

differences in mean switch rates across time and industries:

8

itititit

itititititit

itititititI It tit

M&ASIZEEXPERTLEVERAGELOSSROATENUREMODOPGC

NEGACCACCNEGACCACCGROWTHSWITCH

++++

++++++

+++++=

113112111

1101918171615

114131211

where the variables are defined as follows (Compustat data items in parentheses):

SWITCH = 1 if the client changed among Big N auditors during the year, and 0 otherwise;

GROWTH = total assets (#6) less beginning total assets, divided by beginning total assets;

ACC = performance adjusted discretionary total accruals following Kothari et al. (2005);

NEGACC = 1 if ACC is negative, and 0 otherwise; GC = 1 if the audit opinion is a going concern, and 0 otherwise;

MODOP = 1 if the audit opinion is modified for anything other than a going concern, and 0 if unqualified;

TENURE = number of years audited by the incumbent auditor, with a maximum of 10 years;

ROA = return on assets, defined as net income before extraordinary items (#18) divided by average total assets (#6);

LOSS = 1 if ROA < 0, and 0 otherwise; LEVERAGE = ratio of debt (#9 + #34) to total assets (#6);

EXPERT = 1 if the incumbent auditor has at least 5% more clients in a particular industry and state, and 0 otherwise;

SIZE = Natural logarithm of market value of equity (#25 #199); M&A = 1 if the client had a merger or acquisition (footnote code #1) in the

two most recent years , and 0 otherwise; i denotes client firm; t denotes year; and I denotes industry.

The regressors in the model are measures of client audit and financial risk identified in

the prior literature.3 The audit risk measures are GROWTH, ACC, GC, MODOP, and TENURE.

Stice (1991) finds a positive association between client growth and auditor litigation, and

conjectures that high growth may be accompanied by an ineffective internal control system and

3 As commonly defined, client financial risk is the risk of a decline in the clients economic condition, and audit risk

is the risk that the auditor will incorrectly give an unqualified opinion on financial statements that are materially misstated. A third type of risk, auditor business risk, captures the audit firms risk of loss resulting from the engagement. By definition, auditor business risk is significantly higher for public clients. Because our sample consists entirely of publicly-traded firms, we do not include a dichotomous variable for public/private status as in prior research (e.g., OKeefe, et al., 1994; Bell et al., 2001; Johnstone and Bedard, 2004). Client financial risk can affect both the auditors business risk and audit risk (OKeefe et al., 1994).

9

misleading financial statements. Accordingly, the predicted coefficient on GROWTH is positive.

Similarly, Heninger (2001) finds that the risk of auditor litigation increases for clients reporting

more positive (income-increasing) abnormal accruals. The model therefore includes

performance-matched discretionary accruals, ACC, an indicator variable, NEGACC, for negative

discretionary accruals, and the interaction of these two variables.4 Because audit risk increases

when reported financial results are inflated, we expect a positive coefficient estimate on ACC.

On the other hand, large negative discretionary accruals are consistent with auditor conservatism,

creating an incentive for clients to dismiss the incumbent auditor in hopes of finding a more

reasonable successor (DeFond and Subramanyan, 1998). The total coefficient for negative

discretionary accruals is 2 + 4.

The remaining audit risk variables capture client-specific aspects of the audit

engagement. Following Krishnan and Krishnan (1997) and Johnstone and Bedard (2004), we

expect that companies with other than a clean opinion are more risky, increasing the likelihood

of a change in auditors. Thus, we predict a positive coefficient on GC and MODOP. Stice

(1991) and Krishnan and Krishnan (1997) assert that audit risk also relates to the tenure of the

auditor-client relationship; shorter tenure with a client results in less client-specific knowledge

and a greater likelihood of audit failure resulting in a negative prediction for the coefficient on

TENURE.

Following Johnstone and Bedard (2004), our measures of financial risk are ROA, LOSS,

and LEVERAGE. More profitable companies pose less financial risk to the auditor, and thus we

expect the coefficient estimate on ROA to be negative and that on LOSS to be positive.

4 Earlier research on the relation between auditor litigation and total accruals yields inconclusive results (e.g., Stice,

1991; Lys and Watts, 1994), and thus we focus on measures of discretionary accruals. Untabulated results indicate that inferences are unchanged if we use deflated total accruals as in Krishnan and Krishnan (1997) and the portfolio equivalent as in Bradshaw et al. (2001).

10

Similarly, higher debt levels pose more financial risk, which we expect will result in a positive

coefficient estimate on LEVERAGE.

Finally, in addition to year and industry fixed effects, we include three other controls in

the regression model, audit firm expertise (EXPERT), client firm size (SIZE), and an indicator

variable for merger and acquisition activity (M&A). Audit firms have been shown to exhibit

general tendencies consistent with investment in industry expertise (Hogan and Jeter, 1999). As

such, companies may switch auditors for expertise reasons unrelated to their risk profile.

Because the costs of changing auditors are expected to be higher for larger clients (DeAngelo,

1981), we predict a negative coefficient estimate on SIZE. We include M&A because companies

are more likely to change auditors after a merger or acquisition if the newly-combined entities

had previously engaged different auditors, and hence we expect a positive coefficient estimate on

this variable.

We estimate the auditor change model using two complementary approaches. The first

pools dismissals and resignations. The second permits coefficient estimates to differ for

dismissals and resignations using a multinomial logit technique. Multinomial logit is an

extension of the binary logit model to multiple choices. The procedure estimates the probability

of a particular alternative relative to the probabilities of all other alternatives. In the analysis of

lateral Big N auditor switches, there are three alternatives: (i) no change in auditor, (ii) client

dismissal, or (iii) auditor resignation. An advantage of multinomial logit is that it controls for the

probability of changing auditors when testing for coefficient differences between the dismissal

and resignation subsamples. Prior research finds that auditors are more likely to resign rather

than be dismissed from clients that pose greater risk (Krishnan and Krishnan, 1997), and that

clients associated with resignations are riskier than continuing clients (Shu, 2000; Johnstone and

11

Bedard, 2004). We therefore expect the sensitivity of auditor switches to a firms risk

characteristics to be greater for resignations than dismissals. However, there may be noise in the

classification of resignations and dismissals, which would bias against finding a difference in

coefficient estimates between the two subsamples.5

3.2. Comparison of lateral Big N auditor switches and downward auditor switches

The tests outlined in the preceding section limit auditor switches to client companies

switching between Big N auditors. We extend this analysis to consider whether client risk

characteristics distinguish between lateral and downward switches (i.e., switches to a non-Big N

auditor). Assertions in the financial press suggest that a downward switch is more likely than a

lateral switch for risky clients. To directly test this assertion, we estimate the above regression

model permitting the coefficient estimates to differ by the direction of the switch (lateral or

downward) and the type of the switch (dismissal or resignation).6 This specification permits us

to test whether the sensitivity to client risk differs for lateral Big N and downward switches. If

risky clients are more likely to be excluded from the Big N audit market, as many have

conjectured, downward switches (and, in particular, those triggered by an auditor resignation)

will be more highly associated with client risk characteristics than lateral switches.

3.3. Data

Our sample consists of auditor switches during fiscal years 1993-2001 reported on the

AuditorTrak database, as well as those occurring during fiscal years 2002-2004 on the Auditor

5 Firms are required to disclose in an 8-K filing whether the auditor resigned, declined to stand for re-election, or

was dismissed. We consider declining to stand for re-election as tantamount to a resignation, and code these few observations accordingly. We note that the two-way partition, although common in prior research, does not necessarily fully capture the underlying dynamics of the auditor change. For example, auditors may prefer to be dismissed from an engagement because of concerns that resignations could harm their ability to attract new clients. Alternatively, clients may rush to dismiss an auditor they believe is about to resign because of concerns that the resignation will be viewed negatively by market participants and perhaps even regulators. 6 Because our sample consists of all firms with an incumbent Big N auditor, the only possible outcomes are a lateral

switch to another Big N auditor, a downward switch to a non-Big N auditor, or no switch. Thus, our analysis does not include upward switches from a non-Big N auditor to a Big N auditor.

12

Analytics database, which only covers the period from 2000-present.7 We exclude companies in

the financial services sector (SIC codes 6000-6999) because of its unique operating environment

and differences in accounting classifications that make inferences difficult in subsequent

analyses. The sample period begins with the first year of available data, and in the pre-Enron

period ends in the year prior to the Enron scandal. The pre-Enron (1993-2001) sample thus

spans a period of relative stability in the audit market, with only one merger among the major

audit firms between Coopers & Lybrand and Price Waterhouse in 1998 and prior to the

dissolution of Arthur Anderson and subsequent governance reforms that together caused many

public companies and their auditors to reassess their business relationship.8 Our post-Enron

period is limited by data availability to the three fiscal years, 2002-2004, where fiscal year is

defined as on Compustat.

The databases obtain the identity of both the predecessor and successor auditors for all

switches from a search of SEC filings and other sources. Both databases also provide

information on whether the auditor resigned or was dismissed by the client, as reported in the 8-

K filing, the date of the change, and total sales revenue in the last fiscal year audited by the

predecessor auditor.

Table 1 reports the frequency of auditor switches during the pre-Enron (panel A) and

post-Enron (panel B) periods. We classify each change based on the identity of the predecessor

and successor auditor. Of the 5,369 switches in panel A, lateral switches among non-Big N

auditors occur with the greatest frequency (1,868 or 34.8%). Lateral switches among Big N

7 Source: Auditor-Trak. Copyright 2003 by Strafford Publications, Inc. All rights reserved. Used by permission.

We do not have access to AuditorTrak data post 2001, but do have access to Auditor Analytics. Both datasets are comprehensive, and we are not aware of any biases in either database that would confound comparisons of results across time periods. 8 We exclude all auditor switches after October 15, 2001 (the date Enron announced its restatement plans) from the

pre-Enron period.

13

auditors are the second most common type (1,632 or 30.4%), surpassing downward switches

from a Big N to a non-Big N auditor (1,181 or 22.0%). Finally, there are relatively few upward

switches to a Big N auditor (688 or 12.8%). A very different picture emerges, however, when

the data are weighted by the clients total sales revenue in the year prior to the change.9 These

findings reveal that the overwhelming majority of activity occurs among Big N firms,

representing 87.1% of sales-weighted auditor switches in the pre-Enron period.

The remaining columns in table 1, panel A, partition the data into auditor resignations

and client dismissals. The results are generally similar in both analyses, although lateral Big N

switches are relatively less common in the case of an auditor resignation, while downward

switches to a non-Big N auditor are relatively more common. However, in both partitions,

lateral Big N switches continue to dominate in economic importance. On a sales-weighted basis,

71.6% of auditor resignations and 90.2% of client dismissals are among Big N auditors.

The findings in table 1, panel A, provide clear evidence of the importance of lateral Big

N auditor switches relative to other types of auditor switches. Clearly, lateral Big N switches

represent the most economically significant set of auditor switches, and thus are of inherent

interest. Moreover, as discussed above, most prior research pools all types of auditor switches,

or concentrates on switches between Big N and non-Big N auditors. By focusing on lateral Big

N switches, this paper extends the literature to an important, yet mostly overlooked, segment of

auditor switches. Unless otherwise noted, the remainder of the analysis in this paper refers to

this set of lateral switches among Big N auditors.

Table 1, panel B documents similar statistics for the post-Enron period (2002-2004). The

findings here indicate lateral Big N switches have become less frequent than downward switches,

but still dominate on a sales-weighted basis (80.6%). The lower frequency of lateral Big N

9 All sales-weighted statistics reported in the paper have been adjusted for inflation.

14

switches relative to downward switches indicates the audit market has undergone some changes,

some of which are expected given the reduction in the number of Big N auditors in this period

because of the loss of Arthur Andersen. However, other changes, such as increased auditing

requirements, may also be affecting the statistics. For instance, Plitch and Wei (2004) notes a

recent escalation in auditor switches pooling across all types, which the authors attribute to

companies rotating auditors as part of an effort to strengthen corporate governance and a

reluctance on the part of large audit firms to retain smaller clients amid new and more extensive

auditing requirements. Whether these factors have led to any substantive post-Enron changes in

the risk profiles of companies switching auditors is an empirical question that we address in

section 5.

Table 2 reports descriptive statistics for lateral Big N switches by calendar year. The

findings reveal that the frequency of lateral Big N switches increased somewhat in the 1997-

2001 time frame and have since slowed in the post-Enron period.10 A similar pattern is observed

for dismissals. Resignations appear to have peaked in the 1998-2000 time frame, with the

exception of a substantial spike in 2003. The last two columns present comparison statistics for

the Compustat population of non-switch observations with a Big N auditor. These findings also

show a somewhat higher frequency of observations, particularly on a sales-weighted basis, in the

latter half of the sample period.

10 The unusually high sales-weighted switch frequency of 17.0% in 2000 is largely attributable to both Hewlett

Packard and Compaq Computer changing auditors from PricewaterhouseCoopers to Ernst & Young because of independence concerns arising from Hewlett Packards possible acquisition of Compaq and PWC Consulting. Also in that year, Verizon merged with GTE and the merged entity concurrently changed auditors to Ernst & Young. Without these four switches, all of which were considered dismissals, the sales-weighted switch frequency in 2000 is 15.0% in the pooled sample and 14.2% in the dismissals sample. Similarly, the unusually high sales-weighted switch frequency in the 1998 resignations sample is attributable to the merger of British Petroleum and Amoco and the concurrent resignation of PricewaterhouseCoopers as the combined entitys auditor. Without this change, the sales-weighted switch frequency in the 1998 resignation sample is 6.8%.

15

4. Results from the pre-Enron era

4.1. Univariate tests

Table 3 presents means and medians for the regressors appearing in the estimating

equations for the pre-Enron (1993-2001) sample. Panel A presents statistics comparing

differences in means and medians for the switch and no switch subsamples; panel B presents

analogous statistics for dismissals and resignations within the switch subsample. Because of

missing data, the regression sample contains 1,203 lateral Big N auditor switches, consisting of

1,046 client dismissals and 157 auditor resignations. The corresponding sample of no switch

observations includes all firm-years on Compustat with a Big N auditor in both the current and

prior year (i.e., years t and t 1) that did not switch auditors (whether lateral, downward, or

upward) within 2 years, resulting in 26,302 non-switch observations. We winsorize all non-

indicator variables at the 1% and 99% levels.

Panel A reveals that companies switching to another Big N auditor are more likely to

have received a going concern opinion from their incumbent Big N auditor (GC) and have a

shorter history with that incumbent (TENURE). In addition, companies switching between Big

N auditors are significantly less profitable (ROA and LOSS) and more highly levered

(LEVERAGE) than companies that do not switch Big N auditors. Finally, companies switching

between Big N auditors are less likely to have an incumbent auditor that is an expert in the

clients industry (EXPERT), are smaller (SIZE), and are more likely to have recently engaged in

merger and acquisition activity (M&A). The results in panel B indicate that among companies

that switch laterally between Big N auditors, those that do so because of an auditor resignation

are significantly less profitable, smaller, more likely to have received a going concern or other

16

modified opinion, and have a shorter track record with the incumbent than companies that

dismiss their Big N auditor.

In summary, the findings in table 3 suggest that companies switching laterally between

Big N auditors are riskier than those retaining their incumbent Big N auditor (panel A), and that

auditor resignations are associated with riskier clients than client dismissals (panel B). In

interpreting these results, we emphasize that the sample of auditor switches in our analysis is

distinctly different from prior research in that it contains only lateral Big N switches. By

implication, then, the risky clients in our sample are not excluded from the Big N audit market,

even when the incumbent Big N auditor resigns from the engagement. In the next section, we

further investigate the risk profile of companies changing laterally between Big N auditors using

the logistic regression model developed above.

4.2. Regression analysis of lateral Big N auditor switches

Table 4 presents regression summary statistics for estimations of the logistic regression

model. The first set of results, labeled Binary Logit Estimation, includes all lateral Big N

auditor switches in a binary logistic regression with the sample of companies not switching Big N

auditors as the reference category. The second set of results, labeled Multinomial Logit

Estimation, is for a single multinomial logistic regression that permits different coefficient

estimates for auditor switches identified as dismissals and resignations, with companies not

switching Big N auditors as the reference category. The final column in the table presents

significance levels for tests of coefficient differences between the dismissal and resignation

subsamples in the multinomial estimation. For parsimony, year and industry fixed-effects are not

tabulated, although some of the individual coefficients are significant.

17

Results for the sample of all lateral Big N switches reveal that many of the coefficient

estimates are significant and are consistent with audit risk increasing the probability of a lateral

Big N switch. Specifically, the coefficient estimate on GROWTH is significantly positive, which

is consistent with the findings of Stice (1991). In addition, the issuance of either a going concern

(GC) or otherwise modified audit opinion (MODOP) significantly increases the probability of a

lateral switch in Big N auditors, as does shorter tenure with the client (TENURE) and less

expertise in the clients industry (EXPERT). Finally, the control variables, SIZE and M&A, are

significant in the predicted direction, indicating that the likelihood of switching Big N auditors is

decreasing in client firm size and increasing in the incidence of recent merger or acquisition

activity. Among the audit risk measures, only the coefficient estimates on the discretionary

accruals variables are insignificant.

The results on the financial risk variables are also generally consistent with expectations

and the univariate tests in table 3. In particular, the positive and significant coefficient estimate

on LOSS indicates that loss companies are more likely to switch laterally to another Big N

auditor. The coefficient estimate on ROA, however, is insignificant, suggesting that reported

profitability is not incrementally important in the switch decision. Only when LOSS is excluded

from the estimation is the coefficient estimate on ROA significantly negative (results

untabulated). Also as expected, LEVERAGE has a significant positive effect on the probability

of switching between Big N auditors.

The remaining columns of table 4 present findings from the multinomial logit estimation

that permits coefficient estimates to differ for lateral Big N auditor switches identified by the

client as dismissals or resignations. With one exception, the findings for dismissals parallel those

of the pooled model; specifically, the issuance of a going concern audit opinion does not

18

significantly increase the probability that the incumbent will be dismissed in favor of another Big

N auditor. The results for resignations are also generally consistent with the pooled model,

although client growth, the issuance of a modified audit opinion, and auditor expertise are not

significant at traditional levels. Finally, it is not surprising that the coefficient estimate on the

control variable M&A is insignificant for resignations, as there is no reason to expect auditors to

resign from clients that have recently engaged in a merger or acquisition. The final column of

table 4 reveals that most of the differences in coefficient estimates between lateral Big N

dismissals and resignations are insignificant. However, the probability a Big N auditor will

resign rather than be dismissed from an engagement increases with the issuance of a going

concern audit opinion and decreases with auditor tenure.

Although the focus of our study is not on the distinction between resignations and

dismissals, we note that these findings are consistent with Krishnan and Krishnan (1997), which

pools all auditor switches, including downward switches to a non-Big N auditor. Krishnan and

Krishnan (1997) concludes, however, that the studys evidence supports claims that risk

avoidance by the Big N leads to the withdrawal of audit services for an important segment of the

market, even though they do not examine the direction of the auditor switch. Because our sample

consists entirely of lateral Big N auditor switches, our findings contradict this conclusion.

Instead, we show that even though Big N firms are more likely to resign from clients with certain

risk characteristics, another Big N firm is willing to audit these risky clients. Thus, although

prior studies document risk differences between clients whose auditor resigned and clients that

dismiss their auditor (Krishnan and Krishnan, 1997; Shu, 2000) or continue with their incumbent

auditor (Shu, 2000; Johnstone and Bedard, 2004), this is the first study to show that these same

risk characteristics also explain lateral switches among Big N auditors.

19

4.3. Comparison of lateral Big N and downward switches

Although the findings presented in table 4 are consistent with an increased likelihood of a

lateral switch in Big N auditors for riskier clients, the evidence does not address the related issue

of the extent to which client risk distinguishes between lateral and downward switches to a non-

Big N auditor. The assumption in prior research is that riskier clients switching from one of the

Big N firms will engage a smaller, non-Big N auditor rather than another Big N auditor.

However, as discussed above, there is limited evidence on this question and the results are

inconclusive. In this section we present evidence from a multinomial logit estimation that

permits coefficient estimates to differ for lateral and downward switches. T-tests for pairwise

coefficient differences, conducted separately for dismissals and resignations, indicate whether

client risk factors distinguish between the likelihood a client will change laterally to another Big

N auditor or move downward to a non-Big N auditor. The sample of downward switches

includes all companies switching from a Big N to a non-Big N auditor, while the sample of non-

switch observations is the same as above.

Table 5, panel A, presents summary statistics from the multinomial logit estimation, and

panel B presents p-values for tests of coefficient differences. Because the estimation sample in

table 5 includes downward switches in addition to lateral Big N switches, the coefficient

estimates for lateral Big N dismissals and resignations are not identical to the coefficient

estimates reported in table 4. However, the results are quite similar, and none of our previous

inferences regarding lateral Big N switches is altered. More importantly, the findings show that

lateral Big N and downward switches are sensitive to the same client risk characteristics. For

example, of the 8 coefficient estimates that are significant at the 0.10 level or less for lateral Big

N dismissals, 6 are also significant in the same direction for downward dismissals. Unlike lateral

20

dismissals, LEVERAGE and M&A are insignificant for downward dismissals, while a going

concern audit opinion and negative discretionary accruals (ACC + ACC*NEGACC) are

incrementally significant. The latter result is consistent with the findings of DeFond and

Subramanyan (1998) showing that companies dismiss incumbent auditors that impose

conservative accounting choices in hopes of finding a less conservative successor auditor.

The findings in table 5, panel A, also reveal that 4 of the 5 variables that are significant

for lateral Big N resignations are also significant for downward resignations. Similar to the

dismissal results, however, LEVERAGE is insignificant for downward resignations. In addition,

the likelihood of a downward resignation increases significantly for companies with poor

financial performance (ROA), low growth (GROWTH), a modified audit opinion (MODOP), and

an incumbent auditor with less expertise in the clients industry (EXPERT).

Despite the similarities between lateral Big N and downward auditor switches observable

in panel A, the coefficient estimates for downward switches are generally of greater magnitude.

Inspection of the p-values for tests of coefficient differences reported in panel B, however,

reveals that many of the coefficient differences between lateral and downward switches are

insignificant. The likelihood of a downward switch, whether by dismissal or resignation, is

decreasing in client size and growth and the tenure of the incumbent Big N auditor. In addition,

downward dismissals are more sensitive than lateral dismissals to a going concern opinion and to

positive (ACC) and negative (ACC+ACC*NEGACC) discretionary accruals. Contrary to

expectations, lateral Big N switches, both dismissals and resignations, are more sensitive to

client leverage than downward switches. Finally, untabulated findings reveal that 20% of the

downward sample had switched upward to a Big N auditor within the previous five years.

Excluding these companies from the estimation generally does not affect inferences, although the

21

coefficient estimates on GC and negative discretionary accruals (ACC+ACC*NEGACC) are no

longer significantly different.

It is important to note that most of the significant differences between the lateral and

downward samples in table 5, panel B, are related to client dismissals, not auditor resignations.

Moreover, the downward switches appear to represent small clients with going concern opinions,

and thus are arguably no longer of interest to the Big N. Untabulated statistics indicate that

downward switch companies are much smaller than lateral switch companies. Specifically, the

lower size quartile of lateral Big N switches is larger than the upper size quartile of downward

switches. Additional untabulated statistics reveal that more than 25% of downward switches had

going concern opinions in the year prior to the change, compared to only 7% of lateral Big N

switches. Many of these going concern companies likely face bankruptcy, which could preclude

their ability to afford a Big N auditor or create independence issues if there are outstanding fees

to the incumbent Big N auditor. Consequently, our evidence suggests that large, risky

companies are able to switch laterally within the Big N audit tier, while small companies that

generally pose less risk to the auditor, all else equal, switch downward to a non-Big N auditor.

4.4. Sensitivity analyses

We conduct several additional analyses to assess the robustness of our results. First, we

examine whether our results are distinct from switches due to auditor realignment or clientele

mismatch (e.g., Johnson and Lys, 1990, Shu, 2000). Specifically, following the procedure in Shu

(2000), we calculate an annual index measure for each client that captures how well that client is

matched with its current auditor, and then determine an optimal cut-off probability that predicts

whether a client is better matched with a Big N or non-Big N auditor. If an actual auditor-client

22

pairing is opposite to the prediction in the current year but not in the prior year, then the client

has become mismatched with its auditor and the likelihood of a switch is expected to increase.

In untabulated analyses, we find that the clientele mismatch variable is incrementally

positive and significant at the 0.01 level for downward switches, whether dismissals or

resignations. This finding is consistent with the results reported by Shu (2000). Importantly,

however, we find that the clientele mismatch variable is insignificant in explaining lateral Big N

auditor switches, while none of the inferences regarding our client risk variables is altered.11

Thus, we show that our results regarding the lateral movement of risky clients between Big N

auditors are distinct from prior evidence regarding clientele adjustment or auditor realignment.

Second, we examine whether our results are robust across Big N auditors by permitting

the coefficient estimates in our logistic model to differ for each Big N successor auditor.

Untabulated results reveal no significant differences in the coefficient estimates across auditors.

Thus, our results do not appear to be driven by the behavior of one or a few of the Big N

auditors.

Third, we investigate the frequency of reportable events and accounting disagreements

for clients switching laterally between Big N auditors and downwards to a non-Big N auditor.

Reportable events and accounting disagreements disclosed at the time of the switch are generally

viewed to be indicative of client risk.12 The untabulated results reveal that lateral Big N

(downward) switches are accompanied by a reportable event 7.3% (9.1%) of the time and by an

11 For completeness, in these analyses we also include the summary measure of litigation risk that is the other

primary variable of interest in Shu (2000). Except for downward resignations, this variable is not incrementally significant. 12

SEC rules require registrants to report a change in auditor by filing a Form 8-K within five days of the change. Among other disclosure requirements, the company must reveal whether in the two most recent fiscal years the auditor had advised them of any of the following reportable events: (i) internal controls necessary to develop reliable financial statements do not exist; (ii) the auditor was unwilling to rely on managements representations; (iii) the scope of the audit needs to be significantly expanded; or (iv) information has become available that materially affects the fairness or reliability of a previously issued audit report or financial statements. The company must also disclose any disagreements on accounting matters even if resolved to the auditors satisfaction.

23

accounting disagreement 4.6% (5.7%) of the time. These frequencies are not statistically

different at the 10% level. Thus, consistent with our primary results, riskier clients are no more

likely to be excluded from the Big N audit market.

5. Results from the post-Enron era

The results for the 1993-2001 period indicate that risky clients switch between Big N

auditors rather than being forced to move to lower tier auditors as the popular press suggests.

However, given the many legal and regulatory changes subsequent to Enrons collapse, the

auditing market experienced a significant number of changes including the loss of one of the Big

N auditors (Andersen), as well as restrictions on the services auditors are allowed to perform.

These changes, coupled with the realization that the risk posed by clients is likely higher than

previously thought, could have significantly affected the auditor switch market. To determine

whether this is the case, we repeat the analyses in tables 4 and 5 utilizing a sample of companies

from the post-Enron period (2002-2004). In conducting these analyses, we exclude all auditor

switches where Arthur Andersen was the predecessor auditor, as these companies were forced to

change auditors (Blouin et al., 2005), a fundamentally different situation from the auditor

switches examined in this paper and the prior literature.

In contrast to the pre-Enron findings, the results from the binary logit estimation reported

in table 6 indicate that only the control variables EXPERT, SIZE and M&A are significant in the

post-Enron period. The multinomial logistic regression that permits coefficient estimates to

differ for dismissals and resignations reveals similar findings for both types of auditor switches

with the exception of M&A which is insignificant for resignations. Tests of coefficient

differences in the last column of table 6 reveal no significant differences between lateral Big N

dismissals and resignations in the post-Enron period.

24

Table 7 compares lateral Big N and downward switches in the post-Enron period.

Although the coefficient estimates in the lateral Big N switch columns may differ from those

reported in table 6 because of the inclusion of downward switches in the estimation, all

inferences regarding post-Enron lateral Big N switches remain unchanged. Unlike the results for

the lateral Big N switches, several of the coefficient estimates for the downward switches,

whether dismissals or resignations, retain their significance in the post-Enron period.

To facilitate comparison of the findings of the pre- and post-Enron periods, table 8

reports a summary of the results from tests of coefficient differences in the pre- and post-Enron

periods. A Yes indicates the coefficients across the comparison categories (e.g., Lateral

Dismissal versus Lateral Resignation) are significantly different at or below the 10% level, while

a No indicates the coefficient differences are not significantly different. The comparison of

lateral Big N dismissals versus resignations reveals no significant coefficient differences in the

post-Enron period, compared to just two in the pre-Enron period. The results for lateral versus

downward dismissals and lateral versus downward resignations also indicate there are fewer

significant differences in the post-Enron period. However, in both instances, several of the

significant coefficient differences continue to exist in the post-Enron period. Moreover, as in the

pre-Enron period, the significant differences relate primarily to client dismissals, and appear to

represent small clients with going concern opinions.

Although the post-Enron findings should be interpreted with caution because of limited

data availability, the results reported above suggest there have been some changes in the market

for audit switches in the post-Enron era. Most importantly, lateral Big N switches, particularly

auditor resignations, have become less frequent relative to downward switches (table 1).

Although this decline in lateral Big N switches could be simply the result of a smaller number of

25

Big N auditors, we also find that audit and financial risk factors of clients are no longer

significantly associated with lateral Big N auditor switches (table 6). Taken together, these

findings provide some evidence that risky firms are less likely to switch laterally to another Big

N auditor in the post-Enron environment. There appears to be fewer post-Enron changes in

downward switches, as it is still small companies with going concern opinions that are excluded

from the Big N auditor market. As more data become available, exploration of post-Enron

auditor switches, both laterally between the remaining Big N auditors and downwards to non-Big

N auditors, is likely to provide further insights into the forces affecting auditors risk

management decisions.

6. Summary and conclusion

This study examines a comprehensive sample of lateral switches among Big N auditors to

investigate the extent to which risky clients are excluded from the Big N audit market in the pre-

Enron (1993-2001) and post-Enron (2002-2004) eras. Understanding auditors risk management

practices is of great importance to auditors, managers, regulators, and academics, particularly in

light of the accounting scandals that have recently rocked the auditing industry. We examine the

decade preceding these events to better understand characteristics of lateral switches among Big

N auditors in general and as a means of establishing baseline results for our examination of

auditor switches in the new environment.

To investigate the client risk factors associated with lateral Big N auditor switches, we

estimate a logit regression that models auditor switches as a function of a set of variables that

measure client audit and financial risk. Our results show that the probability of a lateral Big N

auditor switch is significantly increasing in both dimensions of client risk. Moreover, we find

that similar risk factors are associated with lateral Big N dismissals and resignations. Findings

26

from robustness tests reveal no systematic differences between individual Big N auditors. We

also compare the risk profile of lateral Big N auditor switches with downward switches to a non-

Big N auditor, and find that lateral and downward switches are sensitive to similar client risk

characteristics. The downward switches generally comprise much smaller companies with going

concern opinions, suggesting that the Big N are willing to accept large, risky clients that have left

another Big N firm, but are unwilling to accept clients that pose less risk because of their small

size but are also are likely to be less profitable.

The analysis of the post-Enron period indicates that downward switches have become

more frequent than lateral Big N switches. More importantly, several risk factors that were

significant determinants of lateral Big N auditor switches in the pre-Enron period are no longer

significant in the post-Enron period, consistent with a shift in the risk management practices of

the remaining Big N auditors. However, downward switches to a non-Big N auditor continue to

relate to small clients with going concern opinions.

Taken together, we provide several key new findings not documented in the prior

literature on auditor switches. By focusing on lateral Big N auditor switches, we are able to

show that although the relationship between risky clients and one Big N auditor may be

terminated, one of the other Big N firms is willing to accept the engagement. Our post-Enron

analysis, however, suggests that Big N auditors may have become more sensitive to risky clients

in recent years. As such, our study not only offers insights into prior research on auditor

switching, but also suggests opportunities for future research. Because our post-Enron analysis

is limited to a few years, additional work can be done as more data becomes available. In

addition, researchers could explore the economic forces underlying the swapping of risky clients.

27

References

Bell, T. B., Landsman, W. R., Shackelford, D.A., 2001. Auditors perceived business risk and audit fees: analysis and evidence. Journal of Accounting Research 39, 35-43.

Berton, L., 1995. Big accounting firms weed out risky clients. The Wall Street Journal, June 26, B1.

Blouin, J., Grein, B., Rountree, B. R., 2005. An analysis of forced auditor rotation: the case of former Arthur Andersen clients. Working paper, University of Pennsylvania.

Bockus, K., Gigler, F., 1998. A theory of auditor resignation. Journal of Accounting Research 36, 191-208.

Bradshaw, M. T., Richardson, S. A., Sloan, R. G., 2001. Do analysts and auditors use information in accruals? Journal of Accounting Research 39, 45-74.

Choi, J-H., Doogar, R., Ganguly, A. R., 2004. The riskiness of large audit firm client portfolios and changes in audit liability regimes: evidence from the U.S. audit market. Contemporary Accounting Research 21, 747-785.

Chow, C. W., Rice, S.J., 1982. Qualified audit opinions and auditor wwitching. The Accounting Review 57, 326-335.

Cook, J. M., Freedman, E. M. , Groves, R. J., Madonna, J. C., OMalley, S. F., Weinbach, L. A., 1992. The Liability crisis in the United States: impact on the accounting profession. Journal of Accountancy 174, 19-23.

DeAngelo, L. E., 1981. Auditor size and audit quality. Journal of Accounting and Economics 3, 183-199.

DeFond, M. L., Subramanyam, K.R., 1998. Auditor changes and discretionary accruals. Journal of Accounting and Economics 25, 35-67.

Francis, J. R., Wilson, E. R., 1988. Auditor changes: a joint test of theories relating to agency costs and auditor differentiation. The Accounting Review 63, 663-682.

Haskins, M. E., Williams, D. D., 1990. A contingent model of intra-Big Eight auditor changes. Auditing: A Journal of Practice and Theory 9, 55-74.

Heninger, W. G., 2001. The association between auditor litigation and abnormal accruals. The Accounting Review 76, 111-126.

Hindo, B., 2003. Audit clients get the heave-ho. Business Week, December 1, 7.

28

Hogan, C. E., Jeter, D. C., 1999. Industry specialization by auditors. Auditing: A Journal of Practice and Theory 8, 1-17.

Holland, K., Light, L., Galen, M., 1993. Big Six firms are firing clients. Business Week, March 1, 76-77.

Johnson, W. B., Lys, T., 1990. The market for audit services: evidence from voluntary auditor changes. Journal of Accounting and Economics 12, 281-308.

Johnstone, K. M. Client-acceptance decisions: simultaneous effects of client business risk, audit risk, and auditor business risk, and risk adaptation. Auditing: A Journal of Practice and Theory 19, 1-25.

Johnstone, K. M., Bedard, J. C., 2003. Risk management in client acceptance decisions. The Accounting Review 78, 1003-1025.

Johnstone, K. M., Bedard, J. C. 2004. Audit firm portfolio management decisions. Journal of Accounting Research 42, 659-690.

Kothari, S. P., Leone, A., Wasley, C., 2005. Performance matched discretionary accrual measures. Journal of Accounting and Economics 3, 163-207.

Krishnan, J., 1994. Auditor switching and conservatism. The Accounting Review 69, 200-215.

Krishnan, J., Krishnan, J., 1997. Litigation risk and auditor resignations. The Accounting Review 72, 539-560.

Lys, T., Watts, R. L., 1994. Lawsuits against auditors. Journal of Accounting Research 32, 65-93.

MacDonald, E., 1997. More accounting firms are dumping risky clients: Big Six worry about their reputations and chance of costly litigation. The Wall Street Journal, April 25, A2.

OKeefe, T. B., Simunic, D. A., Stein, M. T., 1994. The production of audit services: evidence from a major public accounting rirm. Journal of Accounting Research 32, 241-261.

Plitch, P., Wei, L., 2004. Auditor-client breakups rise, while disclosure often lags. The Wall Street Journal, August 3, C3.

Schwartz, K. B., Menon, K., 1985. Auditor switches by failing firms. The Accounting Review 60, 248-261.

Shu, S. Z., 2000. Auditor resignations: clientele effects and legal liability. Journal of Accounting and Economics 29, 173-205.

29

Stice, J. D.. 1991. Using financial and market information to identify pre-engagement factors associated with lawsuits against public accountants. The Accounting Review 66, 516-533.

30

Table 1 Relative Importance of Auditor Switches for Big N and non-Big N Auditors

Panel A: Auditor Switches by Type (1993-2001) Pooled Resignations Dismissals Sales Sales Sales

Direction of Change Number Freq. (%) Wtd. (%) Number Freq. (%) Wtd. (%) Number Freq. (%) Wtd. (%) Non-Big N to Big N (Up) 688 12.8 2.4 58 4.6 1.6 630 15.3 2.6 Big N to non-Big N (Down) 1,181 22.0 6.0 443 35.2 25.1 738 18.0 2.2 Lateral non-Big N 1,868 34.8 4.4 532 42.3 1.7 1,336 32.5 5.0 Lateral Big N 1,632 30.4 87.1 226 18.0 71.6 1,406 34.2 90.2 Total 5,369 100.0 100.0 1,384 100.0 100.0 5,022 100.0 100.0

Panel B: Auditor Switches by Type (2002-2004) Pooled Resignations Dismissals Sales Sales Sales

Direction of Change Number Freq. (%) Wtd. (%) Number Freq. (%) Wtd. (%) Number Freq. (%) Wtd. (%) Non-Big N to Big N (Up) 112 3.0 3.4 21 1.8 4.3 91 3.6 3.3 Big N to non-Big N (Down) 796 21.6 11.3 283 23.9 31.7 513 20.5 8.5 Lateral non-Big N 2,397 65.0 4.7 826 69.9 12.2 1,571 62.8 3.7 Lateral Big N 380 10.3 80.6 52 4.4 51.8 328 13.1 84.5 Total 3,685 100.0 100.0 1,182 100.0 100.0 2,503 100.0 100.0 This table provides descriptive statistics on auditor switches between January 1, 1993 and October 15, 2001 in Panel A, and January 1, 2002 and December 31, 2004 in Panel B (Post-Enron), except for companies in the financial service industries (SIC codes 6000-6999). Big N auditors are defined as Arthur Andersen, Deloitte & Touche, Ernst & Young, KPMG, and PricewaterhouseCoopers or its predecessor firms, Price Waterhouse and Coopers & Lybrand. All other auditors are classified as non-Big N. Switches from Arthur Andersen as a result of their collapse are excluded in Panel B. Sales in the sales-weighted calculations is for the last fiscal year audited by the predecessor auditor, per the AuditorTrak database in the 1993-2001 period and Auditor Analytics in the 2002-2004 period (supplemented by Compustat data if necessary), adjusted for inflation.

31

Table 2 Characteristics of Lateral Switches among Big N Auditors

Pooled Resignations Dismissals Compustat Population Calendar Sales Sales Sales Sales

Year Number Freq. (%) Wtd. (%) Number Freq. (%) Wtd. (%) Number Freq. (%) Wtd. (%) Freq. (%) Wtd. (%) 1993 153 7.6 2.0 10 3.6 0.5 143 8.2 2.2 7.8 6.0 1994 168 8.3 4.8 20 7.2 1.1 148 8.5 5.3 8.1 6.4 1995 177 8.8 6.4 21 7.6 2.9 156 9.0 6.8 8.7 7.2 1996 142 7.1 4.3 21 7.6 1.2 121 7.0 4.7 9.7 7.8 1997 199 9.9 7.3 24 8.6 1.3 175 10.1 8.1 9.9 8.2 1998 192 9.5 8.7 37 13.3 40.8 155 8.9 4.5 9.4 8.2 1999 197 9.8 9.0 36 12.9 10.9 161 9.3 8.8 9.3 8.7 2000 205 10.2 17.0 38 13.7 9.4 167 9.6 18.0 8.7 9.6 2001 199 9.9 8.4 19 6.8 10.9 180 10.4 8.1 8.1 9.6 2002 122 6.1 4.7 10 3.6 6.2 112 6.5 4.5 7.3 8.8 2003 159 7.9 14.9 28 10.1 11.9 131 7.6 15.3 6.9 9.7 2004 99 4.9 12.5 14 5.0 3.0 85 4.9 13.8 6.0 9.7

Total 2,012 100.0 100.0 278 100.0 100.0 1,734 100.0 100.0 100.0 100.0 This table provides descriptive statistics on auditor switches between January 1, 1993 and May 31, 2005, except for companies in the financial service industries (SIC codes 6000-6999). Big N auditors are defined as Arthur Andersen, Deloitte & Touche, Ernst & Young, KPMG, and PricewaterhouseCoopers or its predecessor firms, Price Waterhouse and Coopers & Lybrand. Except for the Compustat Population, sales in the sales-weighted calculations are for the last fiscal year audited by the predecessor auditor adjusted for inflation. Data for the Compustat Population are obtained from Compustat, and are based on all firm-years on Compustat during 1993-2004 with a Big N auditor in both the current and prior year.

32

Table 3 Descriptive Statistics on Regression Variables, 1993-2001

Panel A: Comparison of Switch and No Switch Samples Mean Median

Variable No Change Change No Change Change GROWTH 0.14 0.14 0.07 0.06 ACC 0.00* 0.01 0.00 0.00 NEGACC 0.52 0.52 1.00 1.00 GC 0.03 0.07*** 0.00 0.00*** MODOP 0.14 0.16 0.00 0.00 TENURE 6.89*** 6.08 7.00*** 6.00 ROA 0.04*** 0.13 0.03*** 0.00 LOSS 0.32 0.48*** 0.00 0.00*** LEVERAGE 0.23 0.27*** 0.20 0.23*** EXPERT 0.31*** 0.25 0.00*** 0.00 SIZE 5.21*** 4.42 5.07*** 4.27 M&A 0.31 0.36*** 0.00 0.00***

N 26,302 1,203 26,302 1,203

Panel B: Comparison of Resignations and Dismissals for the Switch Sample Mean Median

Variable Dismissal Resignation Dismissal Resignation GROWTH 0.15 0.12 0.07 0.02 ACC 0.01 0.01 0.00 0.02 NEGACC 0.52 0.52 1.00 1.00 GC 0.06 0.17*** 0.00 0.00*** MODOP 0.17** 0.11 0.00* 0.00 TENURE 6.21*** 5.22 6.00*** 4.00 ROA 0.11*** 0.23 0.01*** 0.05 LOSS 0.46 0.61*** 0.00 1.00*** LEVERAGE 0.27 0.28 0.23 0.23 EXPERT 0.26 0.22 0.00 0.00 SIZE 4.47*** 4.05 4.32** 3.98 M&A 0.36 0.34 0.00 0.00

N 1,046 157 1,046 157

33

Table 3 Continued The Switch sample consists of firm-years during 1993-2001 with a lateral switch among Big N auditors. The No Switch sample consists of firm-years during 1993-2001 with a Big N auditor in both the current and prior year that did not switch auditors (whether lateral, downward, or upward) within 2 years. GROWTH is total assets less beginning total assets, divided by beginning total assets. ACC is performance-adjusted discretionary total accruals. NEGACC equals 1 if ACC is negative, and 0 otherwise. GC equals 1 if the audit opinion is a going concern, and 0 otherwise. MODOP equals 1 if the audit opinion is modified for anything other than a going concern, and 0 otherwise. TENURE is the number of years audited by the incumbent auditor, with a maximum of 10 years. ROA is net income before extraordinary items, divided by average total assets. LOSS equals 1 if ROA < 0, and 0 otherwise. LEVERAGE is long-term debt divided by total assets. EXPERT equals 1 if the incumbent auditor has at least 5% more clients in a particular industry and state than any other auditor, and 0 otherwise. SIZE is the natural logarithm of market value of equity. M&A equals 1 if the client engaged in a merger or acquisition in the preceding two years, and 0 otherwise. All non-indicator variables are winsorized at the 1% and 99% levels.

*, **, and *** indicate variable is significantly greater than the corresponding value at the 10%, 5%, and 1% levels, respectively, using two-tailed tests.

34

Table 4 Regressions of Lateral Big N Auditor Switches on Client Risk Characteristics, 1993-2001

Model:

= + + + + +

+ + + + + +

+ + + +

it t I 1 it 1 2 it 1 3 it 1 4 it 1 it 1t I5 it 1 6 it 1 7 it 1 8 it 1 9 it 1 10 it 1

11 it 1 12 it 1 13 it 1 it

SWITCH GROWTH ACC NEGACC ACC NEGACCGC MODOP TENURE ROA LOSS LEVERAGEEXPERT SIZE M & A

Binary Logit Estimation Multinomial Logit Estimation Tests of All Switches Dismissals Resignations Differences

Variable Coeff. Est. p-value Coeff. Est. p-value Coeff. Est. p-value p-values GROWTH 0.21 0.00 0.24 0.00 0.07 0.56 0.17 ACC 0.40 0.25 0.50 0.19 0.08 0.92 0.51 NEGACC 0.03 0.74 0.04 0.59 0.09 0.69 0.57 ACC*NEGACC 0.32 0.50 0.34 0.51 0.25 0.82 0.94 GC 0.33 0.01 0.15 0.31 0.96 0.00 0.00 MODOP 0.39 0.00 0.40 0.00 0.22 0.42 0.54 TENURE 0.05 0.00 0.04 0.00 0.14 0.00 0.00 ROA 0.09 0.54 0.05 0.74 0.15 0.64 0.78 LOSS 0.38 0.00 0.36 0.00 0.57 0.01 0.35 LEVERAGE 0.46 0.00 0.44 0.00 0.62 0.05 0.60 EXPERT 0.19 0.01 0.17 0.02 0.31 0.12 0.51 SIZE 0.16 0.00 0.16 0.00 0.19 0.00 0.52 M&A 0.21 0.00 0.22 0.00 0.14 0.44 0.69

ACC + ACC*NEGACC 0.08 0.77 0.16 0.59 0.33 0.63 0.50

Switch 1,203 1,046 157 No Switch 26,302 26,302 26,302

See table 3 for variable definitions. The columns labeled Binary Logit Estimation includes all lateral Big N auditor switches for the 1993-2001 period in a binary logistic regression with the sample of companies not changing Big N auditors as the reference category (pseudo R2 = 0.05). The columns labeled Multinomial Logit Estimation are for a single multinomial logistic regression for the 1993-2001 period that permits different coefficient estimates for auditor switches identified as dismissals and resignations, with companies not changing Big N auditors as the reference category (pseudo R2 = 0.06). The Tests of Differences are for a comparison of the coefficient estimates for Dismissals and Resignations. All p-values are two-tailed.

35

Table 5 Regression of Lateral Big N and Downward Auditor Switches on Client Risk Characteristics, 1993-2001

Model:

= + + + + +

+ + + + + +

+ + + +

it t I 1 it 1 2 it 1 3 it 1 4 it 1 it 1t I5 it 1 6 it 1 7 it 1 8 it 1 9 it 1 10 it 1

11 it 1 12 it 1 13 it 1 it

SWITCH GROWTH ACC NEGACC ACC NEGACCGC MODOP TENURE ROA LOSS LEVERAGEEXPERT SIZE M & A

Panel A: Summary Statistics from Multinomial Logit Estimation Lateral Big N Switches Downward Switches Dismissals Resignations Dismissals Resignations

Variable Coeff. Est. p-value Coeff. Est. p-value Coeff. Est. p-value Coeff. Est. p-value GROWTH 0.24 0.00 0.07 0.57 0.30 0.00 0.33 0.01 ACC 0.49 0.20 0.13 0.87 0.72 0.11 0.72 0.21 NEGACC 0.04 0.60 0.10 0.64 0.04 0.76 0.12 0.55 ACC*NEGACC 0.31 0.54 0.18 0.87 1.94 0.00 1.39 0.09 GC 0.17 0.25 0.99 0.00 0.56 0.00 1.06 0.00 MODOP 0.41 0.00 0.23 0.41 0.55 0.00 0.76 0.00 TENURE 0.04 0.00 0.14 0.00 0.19 0.00 0.26 0.00 ROA 0.04 0.78 0.17 0.60 0.25 0.17 0.67 0.00 LOSS 0.36 0.00 0.55 0.01 0.42 0.00 0.65 0.00 LEVERAGE 0.45 0.00 0.64 0.04 0.11 0.56 0.19 0.46 EXPERT 0.17 0.02 0.31 0.11 0.29 0.02 0.56 0.00 SIZE 0.16 0.00 0.20 0.00 0.84 0.00 0.66 0.00 M&A 0.22 0.00 0.16 0.40 0.07 0.63 0.19 0.28

ACC + ACC*NEGACC 0.18 0.54 0.32 0.64 1.22 0.00 0.67 0.19

Switch 1,046 157 473 227 No Switch 26,302 26,302 26,302 26,302

36

Table 5 Continued

Panel B: p-values for Tests of Coefficient Differences Lateral Lateral versus Downward Lateral versus Downward

Variable Dismissals versus Resignations Dismissals Resignations GROWTH 0.16 0.00 0.02 ACC 0.48 0.03 0.55 NEGACC 0.53 1.00 0.45 ACC*NEGACC 0.92 0.00 0.25 GC 0.00 0.05 0.80 MODOP 0.54 0.39 0.12 TENURE 0.00 0.00 0.00 ROA 0.72 0.38 0.20 LOSS 0.39 0.68 0.75 LEVERAGE 0.58 0.01 0.04 EXPERT 0.49 0.40 0.35 SIZE 0.44 0.00 0.00 M&A 0.76 0.06 0.90

ACC + ACC*NEGACC 0.50 0.03 0.24 See table 3 for variable definitions. The results are from a single multinomial logistic regression for the 1993-2001 period with the sample of companies not changing Big N auditors as the reference category (pseudo R2 = 0.19). In panel B, reported p-values are for the indicated tests of differences in coefficient estimates reported in panel A. All p-values are two-tailed.

37

Table 6 Regressions of Lateral Big N Auditor Switches on Client Risk Characteristics, 2002-2004

Model:

= + + + + +

+ + + + + +

+ + + +

it t I 1 it 1 2 it 1 3 it 1 4 it 1 it 1t I5 it 1 6 it 1 7 it 1 8 it 1 9 it 1 10 it 1

11 it 1 12 it 1 13 it 1 it

SWITCH GROWTH ACC NEGACC ACC NEGACCGC MODOP TENURE ROA LOSS LEVERAGEEXPERT SIZE M & A

Binary Logit Estimation Multinomial Logit Estimation Tests of All Switches Dismissals Resignations Differences

Variable Coeff. Est. p-value Coeff. Est. p-value Coeff. Est. p-value p-values GROWTH 0.17 0.30 0.20 0.24 -0.07 0.88 0.59 ACC 0.37 0.57 0.62 0.38 -1.42 0.49 0.34 NEGACC 0.08 0.62 0.10 0.57 -0.04 0.93 0.76 ACC*NEGACC -0.03 0.98 -0.32 0.78 2.17 0.49 0.46 GC -0.36 0.37 -0.53 0.26 0.24 0.76 0.40 MODOP 0.15 0.36 0.12 0.50 0.25 0.51 0.76 TENURE -0.03 0.13 -0.02 0.32 -0.09 0.11 0.27 ROA 0.20 0.44 0.18 0.53 0.26 0.70 0.91 LOSS -0.20 0.24 -0.21 0.25 -0.15 0.72 0.90 LEVERAGE -0.13 0.67 -0.29 0.41 0.51 0.47 0.30 EXPERT -1.13 0.00 -1.07 0.00 -1.55 0.04 0.54 SIZE -0.18 0.00 -0.19 0.00 -0.15 0.08 0.73 M&A 0.34 0.02 0.40 0.01 -0.02 0.97 0.33

ACC + ACC*NEGACC 0.34 0.69 0.29 0.75 0.75 0.74 0.85

Switch 245 207 38 No Switch 10,315 10,315 10,315

See table 3 for variable definitions. The estimations use only post-Enron data (2002-2004) and exclude all auditor switches related to the collapse of Arthur Andersen. The columns labeled Binary Logit Estimation includes all lateral Big N auditor switches in a binary logistic regression with the sample of companies not changing Big N auditors as the reference category (pseudo R2 = 0.05). The columns labeled Multinomial Logit Estimation are for a single multinomial logistic regression that permits different coefficient estimates for auditor switches identified as dismissals and resignations, with companies not changing Big N auditors as the reference category (pseudo R2 = 0.05). The Tests of Differences are for a comparison of the coefficient estimates for Dismissals and Resignations. All p-values are two-tailed.

38

Table 7 Regression of Lateral Big N and Downward Auditor Switches on Client Risk Characteristics, 2002-2004

Model:

= + + + + +

+ + + + + +

+ + + +

it t I 1 it 1 2 it 1 3 it 1 4 it 1 it 1t I5 it 1 6 it 1 7 it 1 8 it 1 9 it 1 10 it 1

11 it 1 12 it 1 13 it 1 it

SWITCH GROWTH ACC NEGACC ACC NEGACCGC MODOP TENURE ROA LOSS LEVERAGEEXPERT SIZE M & A

Lateral Big N Switches Downward Switches Dismissals Resignations Dismissals Resignations

Variable Coeff. Est. p-value Coeff. Est. p-value Coeff. Est. p-value Coeff. Est. p-value GROWTH 0.20 0.24 -0.07 0.88 -0.24 0.07 -0.75 0.00 ACC 0.60 0.39 -1.33 0.51 0.18 0.70 0.98 0.09 NEGACC 0.10 0.60 -0.04 0.93 -0.19 0.23 0.11 0.60 ACC*NEGACC -0.37 0.75 2.04 0.52 -1.58 0.04 -1.25 0.21 GC -0.51 0.29 0.27 0.74 0.56 0.00 0.82 0.00 MODOP 0.13 0.48 0.25 0.52 0.37 0.01 0.23 0.26 TENURE -0.02 0.32 -0.09 0.11 0.01 0.55 0.03 0.32 ROA 0.24 0.55 0.12 0.90 -0.69 0.00 -1.10 0.00 LOSS -0.21 0.30 -0.19 0.66 -0.29 0.06 0.32 0.16 LEVERAGE -0.30 0.39 0.48 0.48 -0.42 0.06 -0.50 0.10 EXPERT -1.07 0.00 -1.54 0.04 0.02 0.90 0.00 0.98 SIZE -0.19 0.00 -0.15 0.09 -0.77 0.00 -0.58 0.00 M&A 0.40 0.01 0.00 0.99 -0.15 0.37 0.07 0.75

ACC + ACC*NEGACC 0.23 0.80 0.71 0.76 -1.40 0.01 -0.27

Switch 207 38 367 185 No Switch 10,315 10,315 10,315 10,315

See table 3 for variable definitions. The estimations use only post-Enron data (2002-2004) and exclude all auditor switches related to the collapse of Arthur Andersen. The results are from a single multinomial logistic regression with the sample of companies not changing Big N auditors as the reference category (pseudo R2 = 0.18).

39

Table 8 Summary of Tests of Coefficient Differences for the pre- and post-Enron Periods

Lateral Lateral versus Downward Lateral versus Downward Dismissals versus Resignations Dismissals Resignations

Variable Pre-Enron Post-Enron Pre-Enron Post-Enron Pre-Enron Post-Enron GROWTH No No Yes Yes Yes No ACC No No Yes No No No NEGACC No No No No No No ACC*NEGACC No No Yes No No No GC Yes No Yes Yes No No MODOP No No No No No No TENURE Yes No Yes No Yes Yes ROA No No No Yes No No LOSS No No No No No No LEVERAGE No No Yes No Yes No EXPERT No No No Yes No Yes SIZE No No Yes Yes Yes Yes M&A No No Yes Yes No No

ACC + ACC*NEGACC No No Yes No No No

See table 3 for variable definitions. A Yes indicates the coefficients across the comparison categories (e.g., Lateral Dismissal versus Lateral Resignation) are significantly different at or below the 10% level, while a No indicates the coefficient differences are not significantly different. The Pre-Enron (Post-Enron) columns refer to findings for the 1993-2001 (2002-2004) time period.