blouin et al - 2005 - the ultimate form of mandatory auditor rotation - the case of former arthur andersen clients

Further, we find firms with greater performance adjusted discretionary accruals were more likely to follow their Andersen audit team to a new auditor, consistent with these firms trying

The Ultimate Form of Mandatory Auditor Rotation:

The Case of Former Arthur Andersen Clients

Jennifer Blouin University of Pennsylvania Barbara Grein Drexel University Brian Rountree Rice University This Draft: February 2005

Abstract: The collapse of Arthur Andersen provides a unique quasi-experimental setting to study the implications of mandatory auditor rotation for public firms Consistent with the extant literature on mandatory auditor rotation, we hypothesize the selection of a new auditor is a function of agency and switching costs Using a unique dataset identifying whether or not former Andersen clients followed their audit team to a new auditor, we are able to find support for both hypotheses Further, we find firms with greater performance adjusted discretionary accruals were more likely to follow their Andersen audit team to a new auditor, consistent with these firms trying to mitigate the costs of switching auditors However, tests of accruals in the subsequent year reveal the most aggressive firms who followed Andersen staff were no longer aggressive in the following year relative to the group who chose new non-Andersen auditors This is inconsistent with mandatory auditor rotation directly improving financial reporting since

we expect the non followers to exhibit the greatest degree of accrual correction However, our results must be interpreted with caution since the rotation described in the paper is quite atypical Further, whether the benefits outweigh the costs is still difficult to determine since we cannot empirically quantify these aspects

Keywords: mandatory rotation, audit quality, earnings quality, Arthur Andersen

Data Availability: Data are available from public sources

* We would like to thank Kevin Raedy, Stefanie Tate, and workshop participants at Drexel University and the University of Massachusetts at Lowell for constructive criticisms and suggestions

I I NTRODUCTION

Mandatory auditor rotation policies have been considered since at least the early 1900s Zeff (2003) documents intra-firm correspondence at E.I du Pont de Nemours & Company (Dupont) dating back to 1922 concerning the company’s policy of switching auditors every year The primary force underlying the auditor rotation policy was to insure the independence of the public accountant Similar reasoning has resurfaced after the recent business scandals (e.g Enron, WorldCom, Tyco) as part of the national debate on mandatory auditor rotation and the quality of financial statements.1

The primary tradeoff involved in the debate on mandatory auditor rotation involves agency benefits relative to switching costs Switching costs have been defined as the start-up costs incurred by both client and auditor for a new audit engagement, as well as the increased risk of audit failure in new audits (GAO 2003) Commonly cited benefits of auditor rotation are

an increase in auditor independence, which may lead to improved audit and financial statement quality The relative magnitude of the costs and benefits of switching auditors is central to this debate We use the unique setting created by the collapse of Arthur Andersen (AA) to examine these costs that are inherently captured by a firm’s selection of a new auditor Specifically, we examine which costs/benefits explain a client’s decision to follow their former AA audit team (follow firms) or to choose an entirely new audit firm (not-follow firms) We also examine the relative quality of financial reporting before and after the change in auditor for the follow and not-follow firms

Typically, a change in auditor involves two actions: dismissal/resignation of the current audit firm and the selection of a new auditor Most prior research on auditor changes has been

1 A summary of the mandatory auditor rotation debate appears in the GAO report entitled “Public Accounting Firms: Required Study on the Potential Effects of Mandatory Audit Firm Rotation.”

unable to examine the two actions separately and therefore has focused on the joint action (see for example Nichols and Smith 1983; Francis and Wilson 1988; Shu 2002 and Landsman et al 2005).2 After AA’s criminal indictment on June 15, 2002 and subsequent agreement to stop practicing in front of the SEC, all of their public clients were forced to select a new auditor.3 Therefore, our sample of former AA clients is homogeneous in the decision to dismiss their auditors, enabling us to create more direct tests of the costs involved in the selection of a new auditor than has been possible in past studies

We hypothesize the selection of a new auditor involves three primary concerns: 1) switching costs, 2) agency costs, and 3) implicit insurance provided by the auditor We hold the latter constant by considering only switches to one of the remaining Big4 audit firms (Deloitte, PriceWaterhouseCoopers, KPMG, or Ernst & Young).4 We characterize the selection of a new auditor as being either: 1) completely independent of any existing relationships with AA’s audit personnel or 2) based on the prospective employment of the AA audit team For example, in Casella Waste Systems’ Form 8-K filing on June 13, 2002, the firm reports:

As recommended by the audit committee, the Board of Directors on May 20, 2002, decided to no

longer engage its independent accountants, Arthur Andersen LLP, and engaged KPMG LLP

(“KPMG”) to serve as the Company’s independent accountants for the fiscal year ending April 30,

2003 and to audit the Company’s financial statements for the fiscal year ended April 30, 2002

The Audit Committee’s recommendation to engage KPMG was based on the assumption that

certain individuals from Arthur Andersen’s Boston, Mass office, including the team auditing the

Company, would join KPMG That event did not occur As a result, the Audit Committee

subsequently reconsidered its recommendation and, as recommended by the Audit Committee, the

Board of Directors on June 13, 2002 decided to no longer engage KPMG, and engaged

PricewaterhouseCoopers LLP (“PWC”) to serve as the Company’s independent accountant for the

4 This assumes that the relative implicit insurance provided by the remaining Big4 auditors is in fact reasonably equal This is consistent with prior literature that examined implicit insurance (i.e Menon and Williams 1994), which utilizes a BigN/non-BigN designation to test for differences in insurance values

fiscal year ending April 30, 2003 and to audit the Company’s financial statement for the fiscal

year ended April 30, 2002

As it turned out, AA’s Boston office actually became part of PWC rather than KPMG We argue that firms like Casella Waste Systems did not switch audit teams, but instead simply transferred their existing audit relationship to a new firm Since other firms clearly severed ties with their former AA audit team, we have identified an interesting quasi-experimental setting to study the cost/benefit relationship underlying the selection of a new auditor under a mandatory rotation regime

We find firms with greater agency issues and/or monitoring concerns, as measured by earnings transparency, geographic diversity and the presence of an outside blockholder, were more likely to severe ties with Andersen completely and select an entirely new auditor At the same time, using an indicator whether AA was the industry expert and performance adjusted discretionary accruals as proxies for switching costs, we find firms with greater switching costs were more likely to follow their former AA audit team to the new auditor The unique research design allows us to simultaneously determine if switching and agency costs played a role in the selection of a new auditor in a setting incrementally more powerful than previous studies using measures such as abnormal returns and duration

The final set of tests provide direct evidence concerning the hypothesis posed and tested

in Myers et al (2003) on the quality of earnings before and after mandatory auditor rotation As discussed above, we find that firms that followed AA had more aggressive performance matched discretionary accruals relative to the non-follow firms in the final year audited by AA Utilizing this discretionary accrual measure as an indicator of earnings quality, results are consistent with more aggressive firms attempting to follow AA in an effort to minimize the costs associated with said behavior However, when we model the discretionary accruals using the framework

outlined in Myers et al (2003), we find firms in the lowest quintile of accruals (i.e the most conservative) in the final year of AA continue to have lower discretionary accruals on average in the following year regardless of the follow decision This finding suggests the mandatory rotation did nothing to improve the reporting for firms in this particular tail Further, the follow firms in the highest quintile of discretionary accruals in their final year with AA exhibit reversion in the following year under a new auditor whereas the corresponding not-follow firms

do not Given followers did not fully switch firms per se, we expect the not-follow group to exhibit the greatest degree of reversion in aggressive behavior if mandatory rotation is effective

in improving financial reporting This is not the case and therefore casts some doubt that reporting quality would be greatly influenced under a mandatory rotation regime However, these results need to be interpreted with caution since this is not the typical mandatory rotation regime entertained by the literature and rule making bodies We discuss these limitations in section 4 below

The rest of the paper is organized as follows Section 2 reviews the related literature on mandatory auditor rotation and develops hypotheses Sample selection and research design are outlined in section 3 Section 4 provides results and robustness checks Section 5 concludes

II H YPOTHESIS DEVELOPMENT

The GAO’s November 2003 report on mandatory auditor rotation states that the majority

of Tier 1 public accounting firms and Fortune 1000 public companies “believe that the costs of mandatory audit firm rotation are likely to exceed the benefits.” Costs identified by the GAO include the risk of audit failure in the early years of an audit engagement, audit firm competition issues, increased initial year audit costs, auditor selection costs and support costs The report

goes on to explain that the “benefits of mandatory audit firm rotation are harder to predict and quantify …” (GAO 2003, 8) The prior literature on auditor changes has not addressed this issue because of the general lack of mandatory auditor rotation regimes.5 Instead, research has focused on auditor changes that result from the dismissal or resignation of the incumbent auditor, which is obviously quite different than mandatory rotation However, the collapse of Arthur Andersen creates the opportunity to study the costs and benefits related to mandatory auditor rotation

We acknowledge that the collapse of Andersen is not the standard mandatory auditor rotation setting Nevertheless, it is arguably the closest setting available to date with enough data

to properly address this important issue The unexpected and rapid collapse of Arthur Andersen provides us an opportunity to examine a group of firms that switched auditors for the same reason: their former audit firm was forced to stop practicing We use this mandatory rotation to examine a firm’s choice of new auditor Specifically, we examine which costs explain a client’s decision to follow their former AA audit team or to choose an entirely new audit firm Given the decision to change auditors has been uniformly mandated, prior research on auditor change and the debate on auditor rotation suggest three potential costs involved in the selection of a new auditor - switching, agency, and implicit insurance We hold the latter constant by only examining switches to the remaining Big4 auditors, allowing us to focus on switching and agency costs.6

We also utilize the setting to test the implications of a mandatory auditor rotation on the financial reporting characteristics of firms Specifically, we analyze firms’ performance adjusted discretionary accrual behavior surrounding the collapse of AA Myers et al (2003) document

5 Exceptions include Austia, Brazil, Italy and Singapore which currently have mandatory rotation policies Also, Spain and Canada had mandatory policies that were ended in 1995 and 1991 respectively (GAO 2003)

6 See footnote 4 above

more aggressive accrual behavior for firms with shorter auditor tenure They interpret their findings as being inconsistent with mandatory auditor rotation improving financial reporting However, the authors recognize that they are not analyzing mandatory auditor rotation and that their results are simply suggestive On the contrary, the current setting is a more direct form of mandatory auditor rotation and therefore has the potential to be informative for this debate

S WITCHING COSTS

We define switching costs as the start-up costs incurred by both the client and auditor for

a new audit engagement These include the (1) costs incurred by the auditor to learn about the company’s operations, systems, financial reporting practices, and accounting issues, (2) costs incurred by the client to aid the auditor in understanding its operations, and (3) costs incurred by

a client in selecting a new auditor (GAO 2003) Further, there is an increased risk of audit failure AICPA (1978), Palmrose (1986, 1991), Geiger and Raghunandan (2002) and Myers et

al (2003) all find evidence consistent with a greater likelihood of audit failure in early years of

an audit engagement

Standard value maximizing behavior suggests that firms will seek to minimize switching costs, ceteris paribus We hypothesize that companies may try to minimize the cost of switching auditors by following their AA audit team who already possess client and industry specific knowledge or more succinctly:

H1: The greater the switching costs, the more likely a former AA client will follow its

AA audit team to a new auditor, ceteris paribus. 7

7 The maintained assumption throughout is that, ceteris paribus, following AA has lower switching costs than following Education of the audit team about the operations of the firm along with obtaining comfort with the reported results is an expensive and time consuming proposition Following AA would almost certainly reduce these costs even if the audit team is not maintained because at minimum they would be available for consultation

not-A GENCY COSTS

Consistent with Jensen and Meckling (1976), we define agency costs as monitoring

expenditures by the principal, bonding expenditures by the agent, and loss in welfare

experienced by the principal due to the agent not acting in the principal’s best interest Auditing

is widely believed to be a means of reducing agency costs through the monitoring of the agent by

an independent third party auditor (Jensen and Meckling 1976 and Watts and Zimmerman 1983, among others) Further the greater the agency costs, the greater is the demand for high quality audits (DeAngelo 1981; Dopuch and Simunic 1982).8

The decision to change auditors is frequently cast in terms of mitigating agency costs and/or changes in audit quality (Nichols and Smith 1983; Francis and Wilson 1988; Johnson and Lys 1990; DeFond 1992) In our setting, it may be that agency conflicts at the firm are unchanged, while the perceived quality of the AA audit has suddenly declined The results in Chaney and Philipich (2002) and Krishnamurthy et al (2003), which document negative market reactions for Andersen clients after negative news concerning their auditor, suggest that investors may have perceived audit quality issues to be systematic at AA Further, duration analyses examining cross sectional differences in former AA clients support the notion that firms were concerned about the perceived quality of AA’s audits by illustrating clients with greater agency conflicts dismissed AA sooner (Chang et al 2003, Barton 2004) If firm management perceived audit quality issues and/or is concerned with investors’ perceptions of audit quality, then we hypothesize that:

Consistent with this notion, the GAO found that Tier 1 public accounting firms (firms with 10 or more public

company clients that were members of the AICPA’s self-regulatory program for audit quality) “generally saw more potential value in having access to the previous audit team and its audit documentation than in performing additional audit procedures and verification of the public company’s data during the initial years of the auditor’s tenure” (GAO

2003, 2133)

8 Consistent with DeAngelo (1981) and DeFond (1992), we define audit quality as the probability that an audit firm will detect and report “material breaches in the accounting system.”

H2: The greater the agency conflicts, the more likely a former AA client will not follow its AA audit team to a new auditor, ceteris paribus

It is important to note that a firm may have conflicting costs (i.e high agency and switching costs), which biases against finding any systematic relation between the decision to follow and our measures of the underlying costs

III R ESEARCH D ESIGN AND S AMPLE S ELECTION

We model the decision to follow AA personnel as a function of variables aimed at capturing the degree of switching and agency costs, along with industry fixed effects to allow for differences in mean follow rates across industries:

εγ

γγ

γγ

γγ

γγ

γγ

γα

++

++

++

++

++

++

+

RETURN LOSS

ROA

INSIDER BLOCK

LEVERAGE ACCRUAL

COMPLEX CY

TRANSPAREN SIZE

TENURE EXPERT

12 11

10

9 8

7 6

5 4

3 2

1

where all variables are measured as of the final year audited by AA and are defined as follows (Compustat data items in parentheses):

FOLLOW = 1 if the client followed AA, and 0 otherwise;

EXPERT = 1 if AA had at least 5% more clients in a particular industry and

state than the next closest competitor, and 0 otherwise;

TENURE = number of years audited by AA per Compustat;

SIZE = natural logarithm of total assets (#6);

TRANSPARENCY = decile rank of absolute value of residual from regression of annual

returns on annual earnings (#18), changes in annual earnings, both

scaled by total assets (#6) and SIZE

TotalSales LN

1

where TotalSales is company sales revenue for 2001 and Segment i

represents the sales for a specific geographic segment of the business per Compustat (Bushman et al 2002)

ACCRUAL = performance adjusted discretionary total accruals following

Kothari et al (2004);

LEVERAGE = ratio of debt (#9 + #34) to total assets (#6);

BLOCK = 1 if an outside blockholder per Spectrum holds at least 5% of the

outstanding shares, and 0 otherwise;

INSIDER = 1 if an insider per Spectrum holds at least 5% of the outstanding

shares, and 0 otherwise;

ROA = return on assets, defined as net income before extraordinary items

(#18) divided by ending total assets (#6);

RETURN = abnormal market model return for the ±1 days surrounding AA’s

indictment date, using CRSP’s value weighted index as a proxy for the market

I denotes industry as defined in Barth et al (1998)

We utilize logistic regression to isolate the determinants of auditor choice The empirical

specification of the dependent variable, FOLLOW, is a 1 when firms are categorized as following

AA, and 0 otherwise In constructing our sample, we identified firms that were audited as of fiscal year 2000 or 2001 by AA and changed auditors after November 8, 2001.9 Next, we hand collected information concerning the acquisition of AA offices by other auditors from a variety

of sources including audit firm press releases, AA client Form 8-Ks relating to the choice of a new auditor, and representatives from two of the remaining Big4 audit firms Through this process we were able to classify 561 former AA clients as either following AA personnel to a new auditor or completely severing ties with their AA audit team.10 Of these firms, 425 have the necessary financial statement information to perform our baseline tests concerning the decision

9 AA received a subpoena from the SEC as Enron’s auditor on November 8, 2001 The following highlights other key dates in Arthur Andersen’s collapse On March 15, 2002, the grand jury indictment of AA was unsealed AA signed and announced a Memorandum of Understanding with Deloitte and Touche for the sale of its tax practice on April 4, 2002, following through on plans to reduce its business to just the core audit practice The criminal trial of

AA began on May 6, 2002, the same day that AA agreed to settle a lawsuit with the Baptist Foundation of Arizona for $217 million The first of many office sale announcements, was also made on May 6, 2002 – Ernst & Young acquired the Detroit, Toledo, Ann Arbor and Grand Rapids offices of AA Finally, AA was convicted of one count

of obstructing justice on June 15, 2002 As a result of the conviction, AA agreed to cease practicing before the SEC

by August 31, 2002

10 For example, KPMG acquired AA’s Philadelphia office If an AA client whose audit opinion was signed

Philadelphia chose KPMG as their new auditor, we assume they followed their AA audit team If that same client chose Ernst & Young, we assume that they did not follow their AA audit team

to follow AA or not and represent switches that range from February 12, 2002 to August 2,

2002.11 Table 1 provides a summary of the sample selection process

Our methodology is novel as it allows us to distinguish between the switching costs and agency costs hypotheses in a systematic fashion that neither returns nor duration can necessarily replicate For instance, in an abnormal returns analysis, the researcher may be unable to disentangle switching costs, agency costs, and insurance costs since the magnitudes of the returns may be equivalent for firms facing different cost issues.12 In contrast, our research design provides the opportunity to isolate these alternatives even if the magnitudes of their influence are equivalent since, presumably, they will lead to different auditor selection decisions Although there are strengths and weaknesses to any methodology, we believe our setting provides us with a unique opportunity to study the selection of auditors from a relatively homogenous set of potential auditors

S WITCHING C OSTS

The regressors in the model are measures of switching and agency costs motivated by prior

research EXPERT, TENURE, SIZE, TRANSPARENCY, COMPLEX and ACCRUAL all relate to switching costs and, with the exception of TENURE and TRANSPARENCY, all are predicted to

have positive coefficients suggesting the greater the switching costs the more likely the firm is to

follow AA Note, SIZE, TRANSPARENCY and COMPLEX are also related to agency costs,

which we describe below in section 3.2

11 We perform robustness tests by restricting the characterization of following AA to periods in which public

documents indicated the office switch occurred prior to the firm’s announcement of the switch The results remain qualitatively and statistically unchanged

12 For instance, firm A may have had a -2% abnormal return on the indictment date because this was the market’s assessment of the costs of switching auditors Firm B may have also experienced the same return, but because of agency related issues while firm C experienced the same return due to a loss of insurance and agency costs Since these firms will presumably vary in regards to measures of switching, agency and insurance costs the ability to isolate these alternatives is hindered

The model includes a measure of industry expertise, EXPERT Expertise reduces the

start-up and switching costs for clients opting to hire those auditors If AA was the industry expert, then switching costs may be reduced by following the expert to the new audit firm, hence the

predicted positive coefficient Similarly, we predict a positive coefficient on SIZE, because the costs of changing auditors are expected to be higher for larger clients (DeAngelo 1981).13

TENURE is an auditor related variable that corresponds to switching costs, but its

direction cannot be specified For instance, DeAngelo (1981) suggests there may be a relationship specific investment between auditor and client where, in order to recover start-up costs and switching costs, the two firms are better off maintaining their relationship, at least in the early years This suggests firms with shorter TENURE will be more likely to follow AA However, firms with extended TENURE may also find it costly to switch since they have developed relations with their auditor over an extended period of time making a sign prediction ambiguous

Next, we expect switching costs to be decreasing in the financial transparency of the firm Following prior research (Easton and Harris 1991, Bushman et al 2004, Barth and Landsman 2004), we measure financial reporting transparency as the degree to which a firm’s accounting

summary measures correlate with its economic value The variable TRANSPARENCY is the

decile rank (in descending order) of the absolute value of the residual from a cross sectional

regression of annual returns on ROA, changes in earnings, SIZE and industry fixed effects

Observations in the highest decile are those with the highest transparency, while those in the lowest decile are those with the lowest transparency We predict a negative coefficient for

13 An alternative interpretation of a positive association would be that SIZE is a proxy for audit fee potential

consistent with Simunic (1980) and therefore simply represents the effort of former AA partners to maintain their most lucrative clients

TRANSPARENCY because we expect firms with greater transparency to find it easier to switch

auditors.14

Related to financial transparency is the firm’s valuation complexity Bushman et al

(2002) utilize COMPLEX as a proxy for valuation complexity in analyzing the market-wide effects from the Enron bankruptcy We consider COMPLEX as a measure of overall valuation

complexity/firm transparency based on the firm’s geographic segments, where the higher the value the less transparent or more complex and therefore more difficult to audit.15 Under the

switching cost hypothesis, we predict companies with higher values of COMPLEX would be

more likely to follow AA.16

The final measure of switching costs is ACCRUAL Bradshaw et al (2001) finds that auditor changes are less likely for high accrual firms suggesting that it is more costly for these

firms to voluntarily change auditors In the current context, these same firms may attempt to reduce the costs of switching auditors by following AA resulting in a positive prediction for the

ACCRUAL coefficient Alternatively, Defond and Subramanyan (1998) find firms changing

auditors have negative discretionary accruals on average and attribute the change to overly conservative accounting required by the incumbent auditor Firms with more negative accruals may find it less costly to change auditors thereby leading to the same positive coefficient prediction

14 Inferences are unaltered if we utilize the actual residual value rather than the decile rank

15 COMPLEX captures more than just the number of geographic segments The correlation with the number of

segments is positive and significant, but is only 0.32 Further when the number of geographic segments is added to

our cross-sectional analysis, it is not significant and does not alter the significance of COMPLEX

16 SIZE may also act as a proxy for client complexity and geographic constraints which we expect to be positively

correlated with start up costs associated with switching auditors

A GENCY C OSTS

Under our agency cost hypothesis, the greater the agency costs the greater the demand for

a credible audit and the less likely a client will follow their AA audit team to the new auditor Given the fact that sample firms were forced to switch auditors, firms with the most severe agency issues may have opted to completely severe ties with their former auditor in an effort to minimize the reputational damage related to their association with AA We consider two aspects related to agency issues – degree of conflict and monitoring by outside parties

As previously noted, SIZE, TRANSPARENCY and COMPLEX are related to both

switching and agency costs However, their predicted signs change under the agency costs hypothesis Barton (2004) uses firm size as a proxy for reputation costs from the AA collapse

He finds that larger AA clients switched to a new auditor earlier than smaller firms and argues that this result is attributable to larger firms being subject to greater reputation costs In addition

to reputation costs, SIZE may also measure the diffusion of ownership and related agency costs

If agency costs dominate the decision to switch auditors, we expect SIZE to be negatively related

to the likelihood of following the AA team

Similarly, we expect TRANSPARENCY and COMPLEX to change signs under the agency

hypothesis to positive and negative, respectively The inability to perfectly observe the actions

of managers by outside parties increases agency costs (Jensen and Meckling 1976)

TRANSPARENCY and COMPLEX capture income statement transparency and the overall firm

transparency/complexity, respectively As such, they capture the degree of difficulty outside

parties have in monitoring management Firms with lower values of TRANSPARENCY and higher values of COMPLEX are less transparent and more difficult to monitor, which leads to a

greater demand for severing ties with AA

LEVERAGE and BLOCK are alternative measures of the degree of outside monitoring that

might lead to an increased desire to completely change auditors in an effort to mitigate concerns about the quality of the audit DeFond (1992) argues that companies with greater leverage tend

to switch to higher quality audit firms because of the monitoring performed by bondholders If debt holders viewed the demise of AA as indicative of quality related problems, then we predict

the greater the LEVERAGE the less likely firms will be to follow AA We also consider the

presence of a large blockholder as indicative of monitoring concerns (see Francis and Wilson 1988) We predict that firms with outside monitoring will be less likely to follow AA in an effort to increase the credibility of their audit

INSIDER captures the degree of conflict between insiders and outsiders Jensen and

Meckling (1976) show that higher management ownership leads to greater alignment of interests with outside owners and, hence, lower agency conflicts The results in prior research related to insider ownership and auditor changes have been mixed Francis and Wilson (1988) and Palmrose (1984) find no significant relation between insider ownership and the quality of the successor auditor, while Simunic and Stein (1987) find a negative association and Eichenseher and Shields (1989) find a positive association.17 If low insider ownership (INSIDER) is

indicative of greater agency problems then we predict these firms will be less likely to follow

AA.18

In addition to industry fixed affect, the remaining variables ROA, LOSS, and RETURN

are utilized as controls Landsman et al (2005) and Schwartz and Menon (1985) find that firms

17 In related research, Barton (2004) finds that firms with smaller managerial ownership were more likely to dismiss

AA sooner

18 In unreported results, we also utilize the Kaplan and Zingales (1997) measure of the need for external financing as

a measure of the degree of conflict between insiders and outsiders, as well as equity volatility However, neither measure was ever significant, nor were any of the other inferences altered, therefore we excluded these variables to make the model more parsimonious

with poor financial performance are more likely to change auditors In our context, this suggests that poorly performing firms may be less likely to follow AA, but classifying this prediction as related to agency or switching costs is difficult Chaney and Philipich (2002) and Krishnamurthy

et al (2003) find that clients experienced negative abnormal returns on AA related event dates

and conclude the reactions are related to agency concerns We include RETURN in our analysis,

but our research design allows it to capture either switching or agency costs thereby making the prediction of its coefficient’s sign ambiguous Figure 1 summarizes our sign predictions under the two hypotheses

IV Results

DATA AND UNIVARIATE TESTS

Our sample consists of 425 former AA clients that selected one of the remaining Big4 auditors after the collapse of AA There are a total of 236 firms classified as following their AA audit team, and 189 choosing not to follow In unreported tabulations, similar breakdowns were found incorporating non-Big4 auditors, but given the relatively small reduction in sample size and the increased homogeneity of the sample we restrict our attention to the Big4 sample.19 The industry composition for the sample is illustrated in table 1, panel B

Table 2 documents descriptive statistics for the firms that did not follow (panel A) and firms that are designated as following their AA audit team (panel B) Neither following nor not-following firms appears to have performed very well in the final year audited by AA as indicated

by mean ROAs of -0.16 and -0.09 respectively, with no significant difference between the samples at conventional levels The next variable of interest is RETURN, which provides

evidence consistent with the Chaney and Philipich (2002) and Krishnamurthy et al (2003) findings that AA firms on average experienced negative abnormal returns Unreported statistics

show that both the mean and median RETURN for the not-follow sample are significantly less than zero, whereas only the median RETURN is significantly less than zero for the follow

sample This suggests that the market values of follow firms were not as influenced by the AA collapse, but tests of differences in either means or medians fail to confirm this result

The variables that are significantly different in cross sample comparisons are

TRANSPARENCY, COMPLEX, EXPERT and ACCRUAL The first two measures relate to the

transparency/complexity of the firm measuring the ability of earnings to explain returns and geographic diversity in corporate sales respectively Results from univariate tests suggest that firms that chose not to follow AA were less transparent than firms that followed AA If

TRANSPARENCY (COMPLEX) represents the learning costs of new auditors then it would be

reasonable to expect AA followers to be less (more) transparent (complex) than those that did

not follow This does not appear to be the case and presents the first evidence that agency costs played a role in the auditor choice decision in this instance

EXPERT and ACCRUAL results illustrate that firms chose to follow AA when AA was

the designated expert within their industry and region and when they had higher performance

adjusted discretionary accruals than their not-follow counterparts The EXPERT result is

indicative of clients trying to minimize switching costs by following the expert to their new

auditors The ACCRUAL results are consistent with the those in Defond and Subramanyan

(1998), who find clients switching auditors have negative discretionary accruals on average The

mean and median for the not-follow firms are significantly negative, whereas the mean and median for the follow firms are positive, but not significantly different from zero This illustrates that the not-follow firms were relatively conservative in their financial reporting and is consistent with these firms facing lower switching costs However, these are only univariate comparisons and therefore are only suggestive

Table 3 documents the pearson and spearman correlations among the variables in the regression described above In general there are a variety of significant correlations, but none that would indicate multicollinearity problems.20 Based on the results described above for table

2, it is not surprising to find significant correlations between FOLLOW and EXPERT,

TRANSPARENCY, COMPLEX and ACCRUAL All are in the same direction as the univariate

tests in table 2 and no new significant correlations are noted

Table 4 presents regression results for three different models (Model 1-Model 3) Model

1 presents our primary findings, while Models 2 and 3 provide robustness tests based on different categorizations of the dependent variable It is likely that some clients in our sample chose an auditor before knowing where their former AA audit team ended up To allow for this possibility, in Model 2 we re-coded any company that changed auditors prior to May 1, 2002 as a not-follow client This is an admittedly arbitrary date, but represents a week before the first publicly available information concerning an AA audit office takeover by another auditing firm

in our sample As a further robustness test, in Model 3 we exclude all observations that changed auditors prior to May 1, 2002

The results are consistent across the different models suggesting that we have characterized the choice of auditor with some degree of precision Furthermore, the pseudo R-

20 Although the correlations do not indicate multicollinearity issues, we estimated standard diagnostics within the regression framework anyway No causes for concern were found