Risk Shifts in the Market for Audits:
An Examination of Changes in Risk for “Second Tier” Audit Firms
Chris E. Hogan
Michigan State University
hogan@bus.msu.edu
Roger D. Martin
University of Virginia
rdm3h@virginia.edu
December 19, 2007
__________________________
We have benefited from discussions with Jeanette Franzel and the staff at the GAO
related to this topic. We appreciate the comments of Bob Allen and workshop
participants at The University of Kansas on an earlier version of this paper.
Risk Shifts in the Market for Audits:
An Examination of Changes in Risk for “Second Tier” Audit Firms
SUMMARY: The market for audit services has been affected in recent years by
significant changes like the demise of Andersen and the implementation of the Sarbanes
Oxley Act. One impact of these market changes has been an increase in the frequency of
auditor switches, and in particular, the frequency of clients switching from a Big 4
auditor to smaller audit firms. We examine whether this switching activity has resulted
in changes in the risk characteristics of publicly-traded clients of Second Tier audit firms.
This analysis is important as regulators are concerned about audit market concentration
and would like to see the Second Tier audit firms expand their share of the publiclytraded client market. Results indicate that Second Tier firms are accepting clients with
potentially increased risk characteristics relative to their existing client base, but they also
appear to be “shedding” clients that have increased risk characteristics relative to their
existing client base. Some of the differences in risk characteristics for those departing
clients are more pronounced in the period after 2000, when we expect the most
significant changes in the audit market occurred.
Keywords: auditor switching, second tier audit firms, national audit firms, risk
characteristics
Data availability: The data used in this study is available from public sources.
Risk Shifts in the Market for Audits:
An Examination of Changes in Risk for “Second Tier” Audit Firms
INTRODUCTION
Publicly-traded companies have been increasingly willing to switch to non-Big
Four audit firms in recent years (Reilly 2006, GAO 2006, Byrnes 2005, Public
Accounting Report 2004). While this shift to smaller audit firms has led to recent
research about related audit fee changes and stock price reactions, we examine the
possible changes in overall audit client portfolio risks for smaller audit firms. In
particular we examine whether the shift in the audit market has resulted in a change in the
risk characteristics of publicly-traded clients served by the large national firms – “Second
Tier” firms – over recent years.1
Significant forces have changed the market for audit services in recent years.
Audit firms face limited resources to provide expanded (and required) assurance services
demanded by audit clients, and auditors are subject to increased regulatory and public
scrutiny for their involvement with clients with low quality financial reporting. New
restrictions on services allowed to be provided by auditors to attestation clients have also
been enacted in recent years. Audit firms are reportedly responding to changes in the
audit market by more vigorously pursuing and retaining clients with lower risks that
provide profitable returns on the firms’ limited resources. Upward fee pressures and
service provision issues (e.g., more restricted services) have also caused audit clients to
reassess their independent auditor affiliations (GAO 2006).
1
Our classification of “Second Tier” audit firms includes BDO Seidman, Crowe, Chizek and Company,
Grant Thornton, and McGladrey & Pullen. We will describe the rationale for this classification in a
subsequent section of the paper.
The resulting changes in the market for audit services lead to the possibility that
adjustments in portfolios of audit clients result in certain audit firms assuming more risk
than in the past. Smaller firms in particular might face more business risk with an
increase in the frequency of audit clients “moving down” from the Big Four firms, since
those clients moving down might be doing so because they pose relatively more audit risk
or provide lower profitability to the audit firm. From a public policy perspective, one
concern is that smaller firms might now be providing attestation services to a different –
and in particular, riskier – clientele. While regulators are concerned about audit market
concentration and are encouraging small audit firms to more actively participate in the
market for audit services for publicly-traded client firms (Cox 2005), this could lead to
eventual shocks to the capital markets if the smaller firms are ill-equipped to manage
increased risks of their client base.
We examine whether the level of audit and financial risks of clients have changed
in recent years. While recent studies have examined client switching issues among the
Big Four firms and between the Big Four firms and non-Big Four firms as a group (e.g.
Landsman et al. 2006), we specifically address whether Second Tier firms might be
affected by a re-distribution of audit clients and their associated risks. The movement of
risky clients has not necessarily been solely a shift of risky clients from the Big Four
firms to the Second Tier audit firms, however. Second Tier firms have likely evaluated
their own client portfolios in the context of the changes in the audit market, and might
well have chosen to shed some of their own risky clients to even smaller firms. Clients of
Second Tier firms might also have recognized the resource constraints faced by their
auditors and resulting fee pressures and decided to move to audit firms that can provide
2
more personalized service at acceptable fee levels. It is also possible that audit clients
who were reluctant to shift away from a Big Four auditor in prior years decided the
tumultuous conditions in the early 2000’s provided an opportunity to “move down” in
auditor size without significant scrutiny from shareholders. Thus the level of risks
associated with the client portfolios of Second Tier firms is not necessarily higher in
recent years.
We examine changes in risk for Second Tier firms by comparing audit and
financial risks of publicly-traded clients that are new to or departing from a Second Tier
firm to the continuing portfolio of publicly-traded clients in each year from 2001 to 2004.
We identify audit client portfolios for each of the Second Tier firms for these years and
identify the source (e.g., either new or continuing from the prior year) and the
continuance status (e.g., either continuing or departing before the next year) for all clients.
We report the descriptive statistics for those sources and continuance classifications to
note changes over the study period, but the direct examination of changes in risks is made
by comparing measures of audit and financial risks of clients for new, continuing and
departing clients. We also compare clients coming from Big4 firms versus smaller audit
firms, and client departing to smaller firms versus those departing to a Big4 firm to gain
further insight into the changes in the Second Tier’s portfolio of clients.
We find a significant amount of switching activity both to and away from the
Second Tier firms with new clients representing approximately 20% of their publiclytraded client portfolios each year. The majority of new clients are coming from a Big4
firm whereas the majority of departing clients subsequently engage a smaller audit firm
(or delist). As a result of these changes, auditor business risk seems to have increased for
3
Second Tier firms based on the consistent pattern of accepting larger clients during the
period while disassociating from relatively smaller clients. To the degree that larger
clients are associated with an increased risk of auditor litigation, these results imply that
the exposure of the Second Tier firms to higher business risk has increased.
Profitability (measured with ROA) for new clients was lower than for continuing
and departing clients, implying that new clients might be more likely to encounter
financial problems going forward relative to the comparison groups. New clients from
Big 4 firms were more likely to have had prior losses than continuing clients of the
Second Tier firms, but in turn the clients who departed from Second Tier firms to smaller
firms were also more likely to have had prior losses. This would seem to be evidence
that the Second Tier firms were disassociating from clients with some financial risk, or
client business risk, characteristics at the same time they were accepting new clients with
greater financial risk characteristics relative to the rest of their client portfolios.
Changes to audit risk characteristics were also not in a consistent direction.
Growth rates (measured as change in sales) were higher for new and departing clients
relative to continuing clients. Restatements and disclosure control weaknesses were more
frequent for new clients relative to continuing clients, while the same two characteristics
were less frequent for departing clients relative to continuing clients. All else equal, this
would imply that Second Tier firms were increasing the riskiness of their audit portfolios
based on these characteristics. In contrast however, when comparing matters disclosed in
8-K’s associated with auditor realignments, departing clients had higher occurrence rates
of reportable conditions and accounting concerns relative to new clients throughout the
study period.
4
Overall, our findings suggest that the Second Tier firms are rebalancing their
client portfolios over this period. As they take on larger and more risky clientele,
predominantly clients coming from the Big 4 audit firms, they also seem to be shedding
clients that are less profitable and more likely to have higher risk reporting issues such as
going concern opinions, accounting concerns and reportable conditions.
The remainder of the paper is as follows. In Section II we discuss prior research
on auditor switching and motivate why our examination of switching results for Second
Tier firms is particularly important in recent years. In Section III we describe data used
in our current analyses, and we present results in Section IV. In the final section we offer
a summary and conclusion based on our findings.
BACKGROUND AND MOTIVATION
The market for financial statement auditing services has typically been analyzed
in the context of being in a state of equilibrium, with specific auditor realignments
occurring because of changing conditions for clients and/or audit firms (e.g., Schwartz
and Menon 1985, Johnson and Lys 1990, Shu 2000, Johnstone and Bedard 2004). Client
firms initiate auditor changes as they grow and/or demand a different bundle of services
from their audit firm. Audit firms face risk-return trade-offs, and may resign from clients
where the audit fee the client is willing to pay is not sufficient to cover the potential costs
of being associated with the client.2
Landsman et al. (2006) note that even though prior research has found that audit
firms tend to resign from clients with higher litigation risk (eg. Shu 2000; Krishnan and
2
Audit firms typically increase audit effort and audit fees in the presence of increased audit risk (Bell,
Landsman and Shackelford 2001; Bedard and Johnstone 2006); however client firms may not be willing to
pay a higher fee and would instead switch auditors.
5
Krishnan 1997), clients with financial distress (Krishnan and Krishnan 1997), and clients
with higher audit risk characteristics (Johnstone and Bedard 2004) this research does not
document whether the client is able to engage a similar audit firm or is forced to move to
a smaller audit firm. To address this issue, Landsman et al. (2006) examine client firms
that switch from a Big N audit firm (where Big N refers to the varying number of top tier
accounting firms over time) and note that even though client firms that switch exhibit
higher audit and financial risk, the majority of those clients are able to engage another
Big N firm in the pre-Enron period. Clients that do move down to a smaller audit firm
are smaller and more likely to receive a going-concern audit opinion. Their findings
suggest that Big N audit firms were still willing to accept larger clients despite higher
levels of audit and financial risk during this period.
Thus, research has documented that auditor-client alignments in the pre-SarbanesOxley period were determined by client characteristics and changes in those
characteristics, and by auditors realigning their client portfolios through resignations and
the acceptance of new clients within the context of their overall portfolio. The Big N
firms were willing to accept clients with higher levels of audit and financial risk, and thus
it was not necessarily the case that riskier clients were forced to move to smaller audit
firms.
Clearly, though, the events surrounding the demise of Andersen and the passage
and implementation of the Sarbanes Oxley Act introduced industry-wide “shocks” to the
market for audit services. Audit firms had to respond to several changes that likely
affected their willingness to serve certain clients (due to risk issues) and the fees that
6
would be charged for audit services. In particular, audit market changes that affected
audit firms included:
•
Increased public and political scrutiny resulting from highly publicized audit
and corporate failures
•
Sarbanes-Oxley Act provisions, most notably the required changes to the audit
production process (including internal control attestation responsibilities)
•
Increased demand on resources given the additional attestation requirements
(i.e., internal control attestations)
•
Restriction of provision of some services to audit clients
•
Required disclosure of fees for publicly-traded clients
•
Increased level of regulation and oversight by the PCAOB
These changes forced audit firms to evaluate their client portfolios during this
time. With the increased scrutiny on the profession and the higher demands on firm
resources, firms had the choice to disassociate from clients who did not provide the
requisite combination of risk and return (i.e., fees or fee potential). These realignment
choices by the firms might have been reflected in outright resignations from clients, or
the firms could have responded less directly and publicly by proposing increased fees for
audit clients who subsequently decided to choose other auditors. Whether these
realignments were the direct result of risk assessments, resource considerations or
alternative realignment incentives (e.g., a firm might decide to provide non-audit services
instead of audit services for some clients), however, is difficult to ascertain based on
publicly-available information.
Audit clients were also affected by many of the same changes in the audit market
as they evaluated their external auditor affiliations:
•
Increased reporting requirements and liability risk for executives
7
•
New demand for internal control attestation and subsequent attestation by
independent auditors
•
Restriction of certain services from independent auditors
•
Increased focus on the role and qualifications of the audit committee
Audit clients’ realignment actions during and subsequent to these changes, as in the
discussion above for realignments resulting from audit firms’ motivations, were not
necessarily all consistent with risk-shifting or fee explanations. Clients who posed
unacceptably high risks to auditors might have realigned (or been forced to realign) as a
result of the broad changes in the audit market, but other explanations are also reasonable.
For example, clients might have realigned because they thought their ability to command
adequate attention and service from resource-constrained large firms was diminished.
Clients might also have shifted away from Big Four auditors at this time because they
thought they could do so in that environment without the historically-negative
connotation of “moving down” to a lower-tier audit firm.
One clear result of these numerous explanations for auditor realignments was
increased volatility in the audit market as auditors and clients re-assessed market
conditions and their effects. The frequency of auditor switches has increased in the
2000’s (Sullivan 2006, Audit Analytics 2006), and popular press articles attribute this
switching activity to risk management practices by audit firms (Bryan-Low 2003, Byrnes
2003, Hindo 2003) or resource constraints for large audit firms (Plitch and Wei 2004,
Taub 2004). Several academic studies examine the conditions and effects of this
switching activity.
For example, researchers have examined specific dimensions of recent switching
behavior by identifying which clients switch and whom they select as successor auditors.
8
As stated above, Landsman et al. (2006) examine Big N switches and document that for
the pre-Enron period most auditor switches from Big N auditors resulted in successor Big
N auditors since other large auditors were willing to accept those new engagements, and
although companies that select non-Big N successor auditors tended to be smaller and
have going concern audit opinions, there were not significant differences in other clientrelated risks between lateral and downward switches. In the post-Enron period (i.e.,
2002-2004), however, lateral Big N switches occur with lower frequency than in the
earlier period and risky companies are less likely to switch laterally to another Big N
auditor. Landsman et al. (2006) conclude that Big N auditors are more sensitive to risky
clients in the post-Enron period. However, it is still difficult to disentangle whether the
switches are driven by temporary resource constraints (in which case it still seems
plausible that firms would drop their riskier clients first) or simply due to increased
sensitivity to risk due to increased scrutiny by regulators and investors.
Schloetzer (2006), Rama and Read (2006) and Doogar et al. (2007) present
similar evidence of an increase in client switching from Big N to smaller auditors due to
recent audit market changes, and also generally provide evidence that Big N audit firms
tend to retain clients with lower audit risk. Most studies – those addressing periods both
pre- and post early 2000’s – tend to focus most heavily on “Big N” activity, however, and
partition all non-Big 4 firms together. Given the dominance of the Big N firms this is
reasonable in terms of understanding the biggest component of the audit market, but a
limitation is that we learn little about the specific accumulation of risks at the next level
of audit firms (i.e., the Second Tier).
9
Results from recent studies on audit fees also corroborate the conjecture that Big
4 firms might be “filtering out” riskier clients through audit fee increases. Ettredge et al.
(2006) find that clients paying higher fees after the implementation of Section 404
reporting tend to dismiss their auditors, and dismissals are associated with a higher rate of
engaging non-Big 4 successor auditors. Ho and Wang (2006) report that non-Big 4
auditors appear to charge an audit fee premium to clients switching from Big 4 auditors
to compensate for the higher audit risk associated with those clients. The combined
evidence from these studies is consistent with larger audit firms managing resource
constraints by focusing on clients that generate higher audit fees and being willing to
separate from smaller, riskier clients that “move down” from the Big 4 audit market. As
with the recent switching studies discussed above, though, these audit fee papers do not
consider the implications of risk accumulation at the next smaller level of audit firms.
The combined findings from these recent studies imply there is a higher
likelihood of downward switches in recent years and the relative riskiness of companies
switching downward has likely increased at the same time, but it is not known whether
this increased auditor realignment activity has necessarily led to an increase in the
accumulation of risky clients in Second Tier firms’ client portfolios. A logical response
by these firms, of course, is to manage risks of their own client portfolios. Second Tier
firms in particular had the opportunity to evaluate their own portfolios of clients in terms
of business risk and profitability. Based on the prior discussion of recent research results
that imply an increased rate of downward switches and an increased level of risk of those
clients switching downward, Second Tier firms could be adjusting their own portfolios by
accepting more clients that are shifting downward from Big 4 firms but in turn pushing
10
some of their own riskiest or least profitable clients to even smaller firms. In that case,
the relative risk level of the portfolios of clients served by the Second Tier firms may not
necessarily be changing significantly in recent years.
Research Question
The Government Accountability Office (“GAO”) has completed two reports that
address issues regarding consolidation and competitiveness within the auditing profession
(GAO 2003, 2006). These reports identify four national firms – Grant Thornton, BDO
Seidman, McGladrey & Pullen and Crowe, Chizek and Company – as a “next tier” of
firms (GAO 2003, p. 47; GAO 2006, p. 2). That designation is also used by Audit
Analytics in their analyses and the same four firms are subject to the annual inspections
prescribed by the Public Company Accounting Oversight Board.
The long-term financial health of these national firms is an important element in
the on-going debate about concentration of the audit market. While the health of the Big
4 draws the most attention in this debate (see, for example, American Assembly 2005),
the viability of the Second Tier is also important because of the numbers of publiclytraded clients they serve. Given their growth in recent years (see, for example, Reilly
2006), their role in the audit market is critical because they provide alternatives to Big 4
auditors (Cox 2005) and they serve a significant number of publicly-traded clients. An
example of the potentially catastrophic risk faced by these Second Tier firms is provided
by a recent lawsuit against BDO Seidman which resulted in a guilty verdict against the
firm for negligence; potential punitive damages could be as much as $510 million. BDO
reports “a judgment of that size certainly would have a severe impact on any firm” and
could lead to significant layoffs at BDO (Leone and Taub 2007).
11
We examine risk characteristics of clients of Second Tier audit firms in recent
years. In particular, we identify the publicly-traded clients served by Second Tier firms
for the years 2001 through 2004 and test whether audit and financial risks of those clients
changed by comparing (1) new clients in each year to clients continuing from the prior
year and (2) continuing clients in a given year to clients that depart to other firms before
the next year’s audit. These comparisons inform us about possible changes in the level of
risk from the portfolio of publicly-traded clients in each year for the Second Tier firms.
We also address whether changes in risk between new and continuing clients and
between continuing and departing clients are different in the years after the demise of
Andersen and the passage of the Sarbanes Oxley Act. If those events are associated with
market changes that have led to changes in the risk characteristics of the client portfolios
of Second Tier firms, we would expect to find differences across the pre- and postchanges time periods.
Similar to prior research, we rely on a variety of measures to proxy for risks faced
by audit firms. We generally consider three sources of client risk: audit risk (the risk that
the auditor will issue an unqualified audit opinion in error), client’s business risk (the risk
that the client experiences declining performance in the future), and auditor business risk
(the risk the auditor will suffer reputation or economic damage because of association
with a client) (Kinney 2000). Measures typically linked with audit risk include client
growth rates, the ratio of inventory and receivables to total assets, prior “abnormal” audit
opinions and the presence of unusual audit-related conditions (e.g., presence of control
problems or other accounting-related concerns identified in company reports). Client’s
business risk measures include financial performance measures such as return on assets,
12
leverage and the existence of losses that indicate the potential for declines in future
economic performance by the client. Auditor business risk is usually characterized as
indicators that the audit firm is more likely to be involved in litigation as a result of their
association with a particular client, so the other two client risks are expected to be related
to auditor business risk, along with factors such as client size (since a broader set of
stakeholders might be expected to be more likely to seek legal recourse in the event of
improper financial reporting or poor financial performance by a client).
We also use characteristics of the auditor realignments to consider risk
implications. For example, realignments can be the result of auditor resignations from
clients or of client dismissals of their prior auditors. Though resignations and dismissals
do not necessarily reveal all of the motivations leading to specific auditor realignments,
we use these designations to consider whether client movements are more commonly
associated with one or the other of these actions.3 We also consider sources of new audit
clients and destinations of departing audit clients to examine whether we can identify
differences within these groups that might inform us about prevailing trends during this
period that might also indicate changes in riskiness of client portfolios.
DATA
We use Compustat and Audit Analytics auditor information to identify client
portfolios for Second Tier firms. This coordination was important since we found the
3
We argue that resignations and dismissals are likely even more “noisy” during this period because of the
varying motivations discussed earlier. For example, prior research (e.g., Krishnan and Krishnan 1997)
indicates that resignations are more likely to be associated with audit firms wishing to separate from risky
clients, but during this period firms might have been more likely to simply resign due to known resource
constraints, which would not necessarily be associated with a specific client’s risk characteristics. We
leave it to future research to examine whether the nature of the dismissal vs. resignation realignments
occurred with unusual frequencies or under unusual circumstances during this period relative to prior
periods.
13
two sources to often have conflicting and erroneous data. We started by identifying
companies audited by any of the Second Tier firms in Compustat years 2000 through
2004, then compared that data to audit clients identified by Audit Analytics that had audit
reports issued by Second Tier firms for the corresponding dates. If either data source had
information that was inconsistent with the other, we verified the data accuracy by
examining source documents (e.g., specific audit opinion language and data in Audit
Analytics, public filings included in the SEC’s Edgar database, or company websites).
The number of data corrections identified was substantial – roughly 35% of the
companies identified in Compustat as being clients of a Second Tier firm during this time
period had at least one year of auditor information that needed to be corrected.
Identifying the combination of data from Compustat and Audit Analytics allows us to
find as many publicly-traded clients of the Second Tier firms as possible during this time
period. The most common data disagreement between the sources was in the year of a
switch to or from a Second Tier auditor – a critical piece of information as we classify
each client as new or continuing from the prior year and as continuing or departing before
the next year’s audit.
We identify a parsimonious set of variables used in prior auditor switching studies
to measure client’s business risk, audit risk and auditor business risk associated with a
specific client (see, for example, Landsman et al. 2006, Johnstone and Bedard 2004,
Krishnan and Krishnan 1997, Johnson and Lys 1990). We use Compustat data for
financial statement items and Audit Analytics to identify financial statement restatements
and internal control weaknesses. The specific variables examined include:
Assets – Total Assets, in millions (Data6)
14
Sales – Sales, in millions (Data12)
(AR+Inv)/Assets – ratio of Accounts Receivable and Inventory to Total Assets
((DATA2 + DATA3) / DATA6).
ROA – Return on Assets (DATA18 / DATA6).
Loss – dichotomous variable, = 1 if ROA < 0, = 0 otherwise.
Leverage – ratio of Total Liabilities to Total Assets (DATA181 / DATA6).
LtDebt_to_Assets – ratio of Long-Term Debt to Total Assets (DATA 9 / DATA6).
Change in sales (%) – percentage change in sales from prior year.
OCF – cash flows from operating activities scaled by total assets (DATA 308 /
DATA6).
Change in assets (%) – percentage change in assets from prior year.
Restate – equals 1 if the financial statements of the current year were eventually
restated (per Audit Analytics Restatement dataset), and 0 otherwise.
DCWeakness – equals 1 if the company reported a disclosure controls weakness in a
Section 302 report at some point during our sample period (data from Audit
Analytics Disclosure Controls dataset), and 0 otherwise.
Our study is largely descriptive as we do not have a satisfactory measure of the
overall “risk” of a client portfolio or a “best” way to capture or measure audit risk or
auditor business risk. We first examine descriptive data in the next section on all of the
variables listed above for new clients, continuing clients and departing clients by year to
examine shifts in these measures over our sample time period, which spans both the
demise of Arthur Andersen and the passage of the Sarbanes-Oxley Act of 2002. Then,
15
we also conduct a multivariate analysis comparing new to continuing clients, and
continuing to departing clients, using these same measures. In additional multivariate
analyses, we separately examine clients that are coming from Big 4 firms versus clients
coming from smaller audit firms, and clients departing to Big 4 firms versus clients
departing to smaller audit firms as these are likely clients with differing risk
characteristics. Finally, we directly compare new and departing clients supplementing
with data available from 8-K disclosures of auditor changes where we can examine
additional measures of audit and business risk due to the 8-K disclosure requirements that
are not available for continuing clients.
RESULTS
Second Tier Client Portfolios
Table 1 presents client counts for the Second Tier firms for 2000 through 2004. It
is important to re-iterate that we only include data for publicly-traded client firms. For
years 2000 through 2003 we report what happens to the clients for the next year. For
example, for the 520 clients identified as Second Tier clients in 2000, 94 departed before
the next year’s audit, while 426 continued with a Second Tier auditor. We do not count
moves within the Second Tier audit firms as departures or new clients.4 Similar summary
statistics are provided to describe the sources of clients for each year 2001-2004. For
example, of the 499 Second Tier clients identified in 2001, 73 were new in that year
while 426 continued from the prior year.
What is surprising is the amount of turnover. Approximately 20 percent of the
publicly-traded client portfolio represents new clients in each year (ranging from 15
4
There are 19 auditor changes within the Second Tier firms over our sample period.
16
percent in 2001 to 27 percent in 2004). The relative proportion of new clients is highest
in 2002 and 2004, which is consistent with an increase in new clients following the
demise of Andersen and the implementation of Section 404 of the Sarbanes-Oxley Act.
Sullivan (2006) reports a similar pattern of increases in 2002 and 2004. The proportion
of clients that depart in each year ranges from 18% in 2000 to 21% in 2001 and 2002.
Table 2 provides details of the sources and destinations for the new and departing
clients, respectively, identified in Table 1. In Panel A we report that 71% of new clients
had Big 4 predecessor auditors in 2001, and that rate increased in 2002 and 2003 to about
80%, and then rose again in 2004 to 95%. This trend is consistent with increasing
downward switching during the period both in terms of numbers of clients and
proportions of new clients for the Second Tier firms.
Panel B provides the destinations for clients departing from Second Tier firms.
For those firms for which we could identify the successor auditor, the most frequent
destination was smaller audit firms, although the frequency and proportion of downward
switches is not significantly different across this time period. For client firms that depart
the sample when they no longer appear in the Audit Analytics Opinion file or on
Compustat, we search Edgar for reasons why these client firms no longer file 10Ks. In
Panel B, we document the cases we identified where the departures are companies that
were acquired by or merged with another company, went private, or simply filed with the
SEC that public reporting was no longer required (due to bankruptcy or other events that
terminated the existence of the company). There are a few firms remaining each year for
which we could not identify the reason the company stopped filing.
17
Characteristics of Client Firms
Next we present comparisons of publicly-traded clients that are new in each year
versus those continuing from the prior year, and then clients departing in each year versus
those continuing to the next year. The numbers of firms in each of these analyses are
slightly less than what is presented in Tables 1 and 2 due to missing Compustat data.
Comparing new and departing clients to the base of continuing clients is important as the
acceptance and dismissal decisions are made with portfolio management in mind, which
means these clients are assessed relative to the existing client base (Johnstone and Bedard
2004). At this point, we pool all new clients regardless of whether they are coming from
a Big4 firm or a small firm and all departing clients regardless of where they are
departing to, so that we can examine the overall portfolio effect. In later tests, we
analyze the sources and destinations of the clients to further analyze the source of
changes in risk.
New Clients versus Clients Continuing from Prior Year - Univariate
Table 3 presents descriptive statistics for new clients versus those clients that
continued from the prior year, for each of the years 2001 through 2004. The data is
skewed, and thus we present both means and medians.5 The data does not suggest a clear
pattern of financial risk characteristics that differentiates new from continuing clients
during the period. For 2001 (Panel A), the only significant differences are between the
average sales of new vs. continuing clients (t-test p-value = 0.01) with new clients having
a lower level of sales and the average total assets of new vs. continuing clients (t-test p-
5
We eliminate four observations with extreme values. One observation is a departing client in 2001 with
an extreme value of change in sales. Two other observations, a continuing client in 2001 and a departing
client in 2002, have extreme values of ROA (and also leverage and OCF for one of the firms). The fourth
observation has an extreme value of leverage in 2003.
18
value = 0.09) with new clients having lower total assets. Sales is also significantly
different in the 2002 results (Panel B), along with new clients having a lower rate of
change in assets (p = 0.01 for both a t-test and a Wilcoxon two-sample test for a
difference in medians) and a marginally lower median value of ROA for new clients (p =
0.08). In 2003 (Panel C), new clients are marginally less profitable (have significantly
lower ROA and OCF based on the Wilcoxon test for differences in medians, and have a
significantly higher percentage of firms reporting a loss). In 2004 (Panel D), it appears
that the second tier audit firms are picking up larger clients, as indicated by significantly
larger median total assets and median sales values per the Wilcoxon two-sample test for a
difference in medians. This finding is consistent with the findings in Table 2 that the
Second Tier group of audit firms is picking up a large number of clients in 2004 from the
Big 4 audit firms.
The comparisons in Panels C and D suggest that new clients in these years were
more likely to have financial statement restatements and disclosure control weaknesses
relative to continuing clients, although the significance of this difference varies. The
percentage of financial statements eventually restated for new clients varies from 3% in
2004 to 10% in 2003, while for continuing clients the percentage ranges from 3% in 2001
to 5% in the other three years. For restatements, 2003 is the only year that shows a
significant difference (Wilcoxon p-value = 0.06). The percentage of new clients
reporting disclosure control weaknesses varies from 14% in 2001 to 28% in 2004, while
for continuing clients the percentage ranges from 12% to 17%. Disclosure control
weaknesses are significantly more likely for new clients in 2003 (Wilcoxon p-value =
0.08) and in 2004 (t-test and Wilcoxon p-value ≤ 0.01) relative to continuing clients.
19
Departing Clients versus Clients Continuing to the Next Year - Univariate
Table 4 presents data for clients departing in each year versus clients continuing
on to the next year. Note that this definition is different from the “continuing from prior
year clients” examined in Table 3, and thus the continuing numbers are different here.
Panels A through D all show that departing clients are significantly smaller (i.e., lower
Assets and Sales) and less profitable (i.e., ROA, LOSS and Cash Flows from Operating
Activities) than continuing clients, suggesting that at least some portion of these
departures were occurring as a result of Second Tier firms “managing” their client
portfolios. Departing clients also had higher median values of leverage in each year
compared to continuing clients, based on the Wilcoxon test. Another interesting
comparison is that the departing firms in 2003 are generally larger than the departing
firms in 2000 and 2001. Thus, as the Second Tier group of firms began to take on larger
clients from the Big 4, they also were shedding larger clients.
Interestingly, departing clients were less likely to report disclosure control
weaknesses (significant differences in 2000, 2001 and 2002 with p-values ranging from
<0.01 to 0.05) as compared to continuing clients. The only significant differences for
financial statement restatements are in 2003 and 2004 with departing clients less likely to
have financial statements that are eventually restated relative to continuing clients.
Multivariate Analyses of New versus Continuing and Continuing versus Departing
The univariate descriptive statistics in Tables 3 and 4 provide a sketch of the
relative risk characteristics for comparisons of new vs. continuing clients and continuing
vs. departing clients, respectively. A logistic regression approach will allow us to
examine these comparisons more directly. For example, combining observations across
20
years into a single regression will allow us to compare risk characteristics for new vs.
continuing clients. In addition, we separately examine clients coming from or going to a
Big4 firm and clients coming from or going to a small firm to isolate the sources of
client’s business risk, auditor’ business risk and audit risk. We select a subset of the
variables listed in Tables 3 and 4 since many of them are highly correlated. Specifically,
we estimate the following logistic regression for new versus continuing clients.
CONTINUE/NEW = b0 + b1(ln Assets) + b2((AR+Inv)/Assets) + b3(ROA)
+ b4(Loss) + b5(Leverage) + b6(Change in sales)
+ b7(OCF)+ b8(RstmtCurrent) + b9(DCWeakness)
(1)
CONTINUE/NEW = 0 for clients continuing from the prior year, and CONTINUE/NEW =
1 for clients new to a Second Tier firm in a given year.
Similarly, we estimate the following logistic regression to compare continuing
with departing clients.
CONTINUE/DEPART = b0 + b1(ln Assets) + b2((AR+Inv)/Assets) + b3(ROA)
+ b4(Loss) + b5(Leverage) + b6(Change in sales)
+ b7(OCF)+ b8(RstmtCurrent) + b9(DCWeakness)
(2)
CONTINUE/DEPART = 0 for clients continuing to the next year, and = 1 for clients
departing to a non-Second Tier firm in a given year.
Table 5 presents the results of estimating the logistic regression equation (1) for
the comparison of new vs. continuing clients. The results estimated including data for all
the years 2001-2004 and pooling all new clients together regardless of the source (Model
1 in Table 5) suggest that new clients are significantly larger in terms of total assets, have
a lower proportion of assets in receivables and inventory, have lower ROA, and have
21
higher growth (change in sales). New clients are also more likely to report disclosure
control weaknesses. These inferences are consistent with those discussed from the
univariate comparisons and suggest that new clients have at least a few indicators of
higher client business risk, auditor business risk and audit risk relative to continuing
clients.
Models (2) and (3) in Table 5 separately examine continuing clients versus new
clients coming from a Big4 firm and continuing clients versus new clients coming from a
small firm, respectively. The majority of new clients (90% overall) come from a Big4
firm. The new clients coming from a Big4 firm are the significantly larger clients,
whereas new clients coming from a small firm are not significantly different in terms of
total assets than the continuing group of clients. Both new groups of clients have a lower
proportion of assets in receivables and inventory, a higher increase in sales, and are more
likely to report disclosure control weaknesses. The new clients coming from a small firm
are also more likely to have financial statement restatements, while this is not the case for
clients coming from a Big4 firm.
The results of estimating regression equation (2) above comparing continuing
versus departing clients, presented as Model 1 in Table 6, confirm our observations from
Table 4 that departing clients on average are significantly smaller in terms of assets, are
more likely to report a loss, and have a higher increase in sales relative to clients
continuing to the following year. Departing clients are significantly less likely to report
restatements and disclosure control weaknesses relative to continuing clients (both at
p=0.01). These findings are consistent with departing clients having higher client
22
business risk characteristics but not necessarily auditor business risk since these are
smaller clients.
Models (2) and (3) in Table 6 separately examine continuing clients versus clients
departing to a Big4 firm and continuing clients versus clients departing to a small firm
and clients delisting for various reasons, respectively. The majority of the departing
clients move to a small firm (41%) or delist (49%). The clients departing to a Big4 firm
are significantly larger than the clients continuing on with the Second Tier firms, whereas
the clients departing to a small firm or delisting are significantly smaller. Other
significant differences noted in the pooled results of Model 1 are driven by the clients
departing to a small firm or delisting.
Differences pre- and post- demise of Andersen
To test for whether there is a change in the relative risk characteristics for
continuing vs. new clients during the time period, we estimate a second regression to
introduce a split in time periods. The demise of Andersen occurred during mid-2002.
The indictment of Andersen occurred on March 14, 2002, and the conviction occurred on
June 15, 2002. Andersen audit clients likely began switching auditors during or soon
after that time period, which would fall in the Compustat data year of 2002. Of the 73
new Second Tier clients in 2001 shown in Table 1, 18 came from Andersen. In addition,
clients of Big 4 audit firms might well have been involved with switches as a result of
Andersen as audit firms re-allocated resources during this time. Therefore, for an
analysis of changes in risk characteristics during our time period, we compare switches
that occurred in 2001 to switches that occurred in 2002 through 2004.
23
To estimate a logistic regression using this time split, we estimate a regression
similar to logistic regression equation (1) above but with each independent variable
interacted with POST_2001, where POST_2001=0 for observations from 2001 and
POST_2001=1 for observations from years 2002-2004. For this full model (results untabulated), none of the interaction terms are significant except for the interaction of LOSS
and POST_2001 which is positive and moderately significant (p=0.07). This suggests
that overall, the characteristics of new versus continuing clients do not significantly
change in 2002 through 2004, relative to 2001. In addition, none of the coefficients on
the independent variables without the Post2001 interactions are significant either,
suggesting the relationships observed in Model 1 in Table 5 are driven by the comparison
of new versus continuing clients in the 2002 through 2004 time period. For example, the
sum of the coefficients on LnAssets and LnAssets * POST2001 is positive and significant
indicating new clients in 2002-2004 are significantly larger relative to continuing clients.
However, in 2001, there are no significant differences between new and continuing
clients in the multivariate analysis.
Similarly, we estimate a regression with time period interactions for our
continuing versus departing comparison. Clients of Second Tier audit firms during 2001
would likely know of the shift in Andersen clients and the responses of Big 4 and Second
Tier firms prior to committing to an auditor for the 2002 fiscal year audit. Likewise,
Second Tier firms would likely analyze their resource constraints differently for 2001
clients than in previous years because of the shifts in the audit market. Therefore, we
split the time period by comparing departures after the 2000 audit report to departures
occurring after years 2001-2003. We estimate a regression similar to logistic regression
24
equation (2) above but with each independent variable interacted with POST_2000,
where POST_2000=0 for observations from 2000 and POST_2000=1 for observations
from years 2001-2004.
Results of this model (un-tabulated) again show that interaction terms are not
significant and the only significant coefficients on variables without interaction terms
include LnAssets and DC_Weakness (both negative and significant at p=0.02). The
results presented in Model 1 of Table 6 are largely driven by differences between
departing and continuing clients in 2001-2003.
Overall, the results suggest that new clients (relative to continuing clients) are
significantly larger in terms of total assets and this is driven by clients coming from Big4
firms. New clients have a lower proportion of assets in receivables and inventory, have
higher growth (change in sales) and are more likely to report disclosure control
weaknesses relative to clients continuing from the prior year; and these relationships
seem to be consistent in the 2002-2004 time period relative to 2001. Departing clients
(relative to continuing clients) are larger if they are departing to a Big4 firm but smaller if
they are departing to a small firm or delisting. Departing clients are also more likely to
report a loss, have a higher change in sales, and are less likely to report disclosure control
weaknesses if they are departing to a small firm or delisting whereas these characteristics
are not significantly different for the smaller subset of clients departing to a Big4 firm.
Direct Comparison of New versus Departing Clients
In this section, we directly compare the new clients to the departing clients,
supplementing with data available from 8-K disclosures of auditor changes. Using 8-K
25
data allows us to examine characteristics that may signal problems such as internal
control weaknesses, predecessor auditor resignations, a desire to reduce audit fees, or
accounting concerns – data that is not available for the continuing group of clients.
Relying on 8-K data restricts the size of this group for analysis, since clients changing
auditors would have been required to file 8-K’s, but clients departing for other reasons
(e.g., bankruptcy, deregistration, etc. as noted in Table 2) would not have been subject to
that requirement.
We first examine the characteristics of the subsets of new clients coming from a
Big4 firm versus those coming from a small firm, and the subsets of clients departing to a
Big4 firm versus those departing to a small firm as these subsets likely have different
firm characteristics. Table 7 presents descriptive data on these groups of new and
departing clients, pooled together across all years. For new clients, those coming from a
Big4 firm are significantly larger (p<0.01 for both tests of differences in means and
medians), have a significantly lower median change in sales (p<0.01), are less likely to
receive a going concern opinion (p<0.01), but are more likely to have mentioned “fee
reduction” as a reason for the auditor change (p<0.01 for the t-test for difference in
means). Interestingly, the resignation rate is very similar across clients coming from a
Big4 firm (27% resignation rate) and clients coming from a small audit firm (23%
resignation rate).
For the departing clients, clients departing to a small firm are significantly smaller,
are less profitable and more likely to report a loss, are more likely to have received a
going concern opinion, and are more likely to have had a financial statement restatement.
Consistent with the higher client business risk and audit risk profile of these clients,
26
Second-Tier audit firms are more likely to have resigned from the clients departing to a
small firm (i.e. the Second-Tier firms only resign from 8% of the firms departing to a
Big4 but resign from 26% of the clients departing to a small auditor). The clients
departing to a Big4 firm are relatively larger, more profitable firms that the Second-Tier
auditors would probably prefer to retain, on average.
Next, we directly compare new and departing clients to assess change in the
overall client portfolio. We estimate a logistic regression model where the dependent
variable equals 1 if the client is departing one of the Second Tier firms, and 0 if the client
is new to one of the Second Tier firms. Results are reported in Table 8. We report
results using all years pooled, and also for the pre-Sarbanes-Oxley (and Andersen demise)
time period versus the post-Sarbanes-Oxley (and Andersen demise) time period. Newer
clients are larger, as measured in total assets, as compared to departing clients, consistent
with our earlier findings and consistent with the Second Tier firms picking up clients
from the Big 4 during this time period. Interestingly, the pooled results suggest departing
clients are more profitable than new clients as measured by ROA, although this difference
is driven by the post-Sarbanes-Oxley time period (and also note that the group of firms
departing due to delistings or mergers is not included here whereas they were included in
earlier analyses that did not require 8-K data). The ratio of accounts receivable and
inventory to total assets is not significant either.6 Interestingly, the negative coefficient
on the Resign variable suggests that the Second Tier firms are less likely to have resigned
from their departing clients (as compared to the new clients they are gaining from
6
We also estimate the model including the change in sales variable; however, we do not report those
results in the paper as we lose an additional 45 observations that do not have a value for change in sales.
The coefficient on change in sales is not significant (p=0.72) and other results are qualitatively similar.
27
predominantly the Big 4); however, the coefficients are not significant in either the
pooled results or the pre- or post-Sarbanes-Oxley period.
Several of the measures capturing audit risk are more likely for the departing
clients as compared to the new clients. Going concern opinions (GC) are significantly
more likely for the departing clients in the pooled results (p=0.01), but this seems to be
driven by the post-Sarbanes-Oxley time period as the coefficient is not significant in the
pre-Sarbanes-Oxley period. Both reportable conditions (RepCond) and accounting
concerns (AcctConcerns) are more likely for the departing clients in the pooled results
(p=0.06 for both coefficients), although the coefficients are not significant in the pre- or
post-Sarbanes-Oxley periods individually. The occurrence of restatements (Restate) does
not appear to differ across new and departing clients, and there also does not seem to be a
difference in the reporting of internal control weaknesses although they are marginally
significantly more likely for new clients in the pre-Sarbanes-Oxley period only (p=0.07).
Finally, departing clients are more likely to have identified fee reductions as causes for
switching auditors during the period, particularly in the pre-Sarbanes-Oxley period. 7
Also worth noting are the variables that are not significantly different across the
new and departing clients. The incidence of reporting losses, the ratio of inventory and
receivables to total assets, the occurrence of auditor resignations from the predecessor
auditor, and financial statement restatements are not significantly different across new
and departing clients either in the pooled results or in the separate periods.
7
We conducted Chow tests across the two periods noted in Table 8, and the only significant difference
between estimated coefficients across the two periods is for the ICW variable. Thus our discussion above
that refers to significant results apparently being driven by one period or the other is based on the
observation that the estimated coefficient for a given variable is significant in one period but not the other,
but differences between the two periods are not necessarily statistically significant.
28
Overall, the results are consistent with the Second-Tier firms taking on more
auditor business risk as a result of new clients being significantly larger than departing
clients. This result is driven by the fact that the new clients are coming predominantly
from Big4 firms whereas departing clients are going predominantly to smaller audit firms.
The Second-Tier firms are shedding clients with some characteristics that are consistent
with greater levels of audit risk (more likely to have disclosed reportable conditions and
accounting concerns in the 8-K announcing the auditor change), and this is driven by the
clients departing to a smaller audit firm. However, many other measures of audit risk and
client business risk are not significantly different across new and departing clients.
DISCUSSION AND CONCLUSION
The evidence and analysis indicate a significant amount of switching activity for
the Second Tier audit firms, with approximately 20% of their publicly-traded client
portfolio being comprised of new clients each year over the 2001-2004 time period. This
period of increased realignment activity for Second Tier firms clearly provided an
opportunity for risk characteristics of Second Tier client portfolios to change during the
period, which would be important to consider as clients and regulators evaluate the
viability of this set of audit firms as providers of audits to more and more publicly traded
companies.
Client business risk characteristics did change during the period, but not in a
consistently clear upward or downward direction. Profitability (measured with ROA) for
new clients was lower than for continuing and departing clients, implying that new clients
might be more likely to encounter financial problems going forward relative to the
29
comparison groups. New clients from Big 4 firms were more likely to have had prior
losses than continuing clients of the Second Tier firms, but in turn the clients who
departed from Second Tier firms to smaller firms were also more likely to have had prior
losses. This would seem to be evidence that the Second Tier firms were disassociating
from some risky firms at the same time they were accepting new clients with riskier
characteristics than the rest of their client portfolios.
Changes to audit risk characteristics were also not in a consistent direction.
Growth rates (measured as change in sales) were higher for new and departing clients
relative to continuing clients. Restatements and disclosure control weaknesses were more
frequent for new clients relative to continuing clients, while the same two characteristics
were less frequent for departing clients relative to continuing clients. All else equal, this
would imply that Second Tier firms were increasing the riskiness of their audit portfolios
based on these characteristics. In contrast however, when comparing matters disclosed in
8-K’s associated with auditor realignments, departing clients had higher occurrence rates
of reportable conditions and accounting concerns relative to new clients throughout the
study period.
Auditor business risk, which is typically considered to be associated with client
business risk and audit risk as well as indicators that an audit firm is more likely to suffer
economic or reputational losses, seems to have increased for Second Tier firms based on
the consistent pattern of accepting larger clients during the period while disassociating
from relatively smaller clients. New clients were larger than continuing clients during the
period, with former Big 4 clients explaining that difference. Departing clients were
smaller than continuing clients overall, but for the smaller set of clients (compared to the
30
number of clients moving to smaller firms) moving “up” to Big 4 firms, the departing
clients were relatively larger. Direct comparisons of new versus departing clients show
that new clients were larger throughout the study period. To the degree that larger clients
are associated with increased risks of auditor litigation, these results imply that the
exposure of the Second Tier firms to higher business risk has increased.
Overall, our findings suggest that the Second Tier firms are clearly rebalancing
their client portfolios over this period, but there is not a marked shift in risk
characteristics that indicate either significantly more or less risk to the firms as a result.
As they take on larger and more risky clientele, predominantly clients coming from the
Big 4 audit firms, they also seem to be shedding clients that are less profitable and more
likely to have higher risk reporting issues such as accounting concerns and reportable
conditions.
31
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34
TABLE 1
New, Continuing and Departing Clients for Second Tier Audit Firms
2000
2001
2002
2003
2004
73
135
101
149
426
393
417
413
520
499
528
518
562
94
106
111
105
426
393
417
413
New in current year
Continuing from prior year
Total clients during current year
Departing before next year
Continuing to next year
New, continuing and departing clients are determined using Compustat and Audit Analytics data,
as described in the text, and include only publicly-traded client firms. New clients are defined as
having a new auditor in the corresponding year that is a Second Tier auditor. Continuing clients
are defined as those continuing with a Second Tier auditor from the prior year. Departing clients
are defined as those departing before the next fiscal year-end to a non-Second Tier auditor.
Second Tier audit firms include BDO Seidman, Crowe, Chizek and Company, Grant Thornton,
and McGladrey & Pullen. Years correspond to Compustat classifications (e.g., 2001 contains
data for companies with fiscal year-ends from June, 2001 through May, 2002).
35
TABLE 2
Further Analysis of New and Departing Clients
Panel A: Sources of new clients
Big4
Small firms
Unknown
2001
count
%
52
71%
11
15%
10
14%
73 100%
2002
count
%
108
80%
11
8%
16
12%
135 100%
2003
count
%
82
81%
12
12%
7
7%
101 100%
2004
count
%
142
95%
7
5%
0
0%
149 100%
2002
count
%
9
8%
46
42%
7
6%
14
13%
26
23%
9
8%
111 100%
2003
count
%
11
10%
47
45%
7
7%
10
9%
26
25%
4
4%
105 100%
Panel B: Destinations of departing clients
Big4
Small firms
Bankruptcy
M&A
Deregistered
Unknown
2000
count
%
14
15%
37
39%
12
13%
6
6%
14
15%
11
12%
94 100%
2001
count
%
12
11%
42
40%
13
12%
6
6%
19
18%
14
13%
106 100%
See Table 1 for a description of new and departing clients. “Big 4” refers to Deloitte and Touche,
Ernst and Young, KPMG and PricewaterhouseCoopers. “Small firms” exclude Big 4 and Second
Tier firms. “Unknown” new clients are typically cases where the client firm issued stock in an
IPO, and thus no prior filings were available to determine the auditor. “Unknown” departing
clients are cases where we cannot determine from any sources what happened to the company.
36
TABLE 3
Risk Characteristics of New Clients Relative to Existing Client Base
Panel A: 2001
New clients
(n=73)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
64.35
50.41
0.31
-0.71
0.58
0.95
0.28
12.64
-0.25
29.35
0.05
0.14
Continuing clients
(n=425)
median
27.53
28.44
0.22
-0.06
1.00
0.50
0.03
0.00
0.05
-0.06
0.00
0.00
mean
218.72
170.01
0.34
-0.67
0.61
0.92
0.24
0.30
-0.24
0.06
0.03
0.12
median
21.07
23.07
0.33
-0.06
1.00
0.56
0.07
0.00
0.01
-0.05
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.09
0.38
<0.01
0.93
0.30
0.21
0.90
0.74
0.58
0.58
0.87
0.84
0.65
0.52
0.31
0.49
0.94
0.23
0.19
0.53
0.39
0.29
0.68
0.68
Panel B: 2002
New clients
(n=135)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
126.62
86.21
0.31
-1.23
0.61
1.09
0.20
0.19
-0.39
-0.15
0.06
0.14
Continuing clients
(n=392)
median
29.31
27.20
0.30
-0.07
1.00
0.61
0.06
-0.03
0.02
-0.13
0.00
0.00
mean
304.10
205.65
0.34
-0.54
0.55
1.00
0.22
0.86
-0.17
0.23
0.05
0.14
.
(continued on next page)
37
median
26.35
29.26
0.34
-0.03
1.00
0.53
0.08
-0.00
0.04
-0.02
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.25
0.89
0.01
0.59
0.22
0.14
0.43
0.08
0.20
0.20
0.82
0.39
0.48
0.51
0.35
0.21
0.32
0.18
0.01
<0.01
0.56
0.54
0.88
0.88
Table 3 (continued)
Risk Characteristics of New Clients Relative to Existing Client Base
Panel C: 2003
New clients
(n=101)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
214.87
328.01
0.29
-0.87
0.67
0.84
0.18
12.38
-0.24
0.62
0.10
0.23
Continuing clients
(n=417)
median
29.84
33.86
0.28
-0.06
1.00
0.49
0.04
0.01
0.00
-0.02
0.00
0.00
mean
426.82
219.28
0.33
-0.22
0.54
0.81
0.20
0.23
-0.09
0.26
0.05
0.16
median
33.72
35.51
0.31
-0.01
1.00
0.54
0.07
0.03
0.04
0.03
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.39
0.91
0.65
0.48
0.14
0.13
0.14
0.01
0.02
0.02
0.89
0.55
0.72
0.10
0.17
0.14
0.18
<0.01
0.50
0.15
0.13
0.06
0.12
0.08
Panel D: 2004
New clients
(n=149)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
194.50
162.89
0.30
-0.12
0.50
0.62
0.23
0.34
-0.03
0.61
0.03
0.28
Continuing clients
(n=413)
median
85.52
90.96
0.28
0.01
0.00
0.43
0.06
0.09
0.03
0.03
0.00
0.00
mean
272.73
257.19
0.32
-0.21
0.47
0.67
0.16
0.19
-0.08
0.67
0.05
0.17
median
45.22
45.54
0.29
0.01
0.00
0.47
0.05
0.10
0.03
0.07
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.12
<0.01
0.12
<0.01
0.36
0.51
0.21
0.46
0.61
0.61
0.58
0.92
0.08
0.47
0.28
0.76
0.33
0.95
0.92
0.11
0.35
0.39
0.01
<0.01
New clients are defined as having a new auditor in the corresponding year that is a Second Tier
auditor. Continuing clients are defined as those continuing with a Second Tier auditor from the
prior year. Reported “n” is the maximum number of firms reported for any variable in a given
year; for other variables the number of firms included in the computation of means and medians
is less than “n” due to data availability constraints.
(Continued on next page)
38
TABLE 3 Continued
Variable definitions (financial statement variables are all from Compustat, and the restatement
and disclosure control weakness variables are from Audit Analytics)
Assets........................... Total Assets (in millions) (Data6).
Sales ............................ Sales (in millions) (Data12).
(AR+Inv)/Assets .......... Ratio of Accounts Receivable and Inventory to Total Assets ((Data2 +
Data3)/Data6).
ROA............................. Return on Assets (Data18/Data6).
Loss ............................. Dichotomous variable, = 1 if ROA<0, = 0 otherwise.
Leverage ...................... Ratio of Total Liabilities to Total Assets (Data18/Data6).
LtDebt_to_Assets ......... Ratio of Long-Term Debt to Total Assets (Data9/Data6).
Change in sales (%) ..... Percentage change in sales from prior year.
OCF............................. Cash flows from operating activities deflated by total assets (Data308/
Data6).
Change in assets (%).... Percentage change in assets from prior year.
Rstmt Current…………Financial statements of the current year were eventually restated
DC Weakness…………The company reported a disclosure controls weakness in a Section 302
report at some point during our sample period
39
TABLE 4
Risk Characteristics of Departing Clients Relative to Continuing Client Base
Panel A: 2000
Departing clients
(n=94)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
67.33
63.83
0.30
-1.20
0.70
1.23
0.17
2.38
-0.59
0.90
0.02
0.04
Continuing clients
(n=426)
median
11.91
12.84
0.27
-0.19
1.00
0.62
0.04
0.12
-0.08
0.04
0.00
0.00
mean
186.71
165.25
0.34
-1.82
0.59
1.06
0.20
0.53
-0.46
5.23
0.04
0.12
median
24.21
24.13
0.33
-0.04
1.00
0.54
0.05
0.07
-0.01
0.03
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.05
0.01
<0.01
0.01
0.20
0.14
0.64
<0.01
0.05
0.05
0.63
0.04
0.34
0.20
0.31
0.74
0.68
<0.01
0.23
0.77
0.43
0.49
<0.01
0.03
Panel B: 2001
Departing clients
(n=105)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
35.04
45.43
0.31
-1.06
0.76
1.15
0.23
0.71
-0.39
17.03
0.02
0.07
Continuing clients
(n=393)
median
9.84
8.39
0.26
-0.30
1.00
0.62
0.06
0.00
-0.07
-0.13
0.00
0.00
mean
240.15
181.58
0.35
-0.57
0.57
0.86
0.25
2.23
-0.19
0.25
0.04
0.14
(continued)
40
median
27.41
28.90
0.34
-0.04
1.00
0.54
0.07
0.00
0.03
-0.05
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.04
<0.01
<0.01
<0.01
0.28
0.18
0.08
<0.01
<0.01
<0.01
0.12
0.02
0.68
0.17
0.45
0.77
0.14
<0.01
0.22
0.02
0.25
0.34
0.02
0.05
TABLE 4 (Continued)
Risk Characteristics of Departing Clients Relative to Continuing Client Base
Panel C: 2002
Departing clients
(n=110)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
53.77
70.13
0.31
-2.45
0.65
2.19
0.23
2.58
-0.75
0.23
0.02
0.06
Continuing clients
(n=416)
median
11.39
15.88
0.26
-0.19
1.00
0.67
0.03
-0.03
-0.03
-0.08
0.00
0.00
mean
313.62
203.56
0.34
-0.25
0.54
0.71
0.21
0.18
-0.08
0.12
0.06
0.16
median
34.23
33.48
0.34
-0.01
1.00
0.53
0.08
-0.00
0.04
-0.04
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.07
<0.01
<0.01
<0.01
0.28
0.17
0.05
<0.01
0.04
0.04
0.02
<0.01
0.80
0.13
0.33
0.30
0.03
<0.01
0.70
0.05
0.01
0.09
<0.01
0.01
Panel D: 2003
Departing clients
(n=105)
Assets (in millions)
Sales (in millions)
(AR+Inv)/Assets
ROA
Loss
Leverage
LtDebt_to_Assets
Change in sales (%)
OCF
Change in assets (%)
Rstmt Current
DC Weakness
mean
1028.88
213.25
0.32
-1.02
0.72
1.41
0.22
11.31
-0.49
0.12
0.03
0.18
Continuing clients
(n=413)
median
20.66
24.21
0.30
-0.12
1.00
0.68
0.06
0.00
-0.02
0.00
0.00
0.00
mean
221.94
247.08
0.33
-0.17
0.52
0.67
0.19
0.22
-0.03
0.37
0.07
0.17
median
41.14
39.21
0.30
-0.01
1.00
0.49
0.06
0.04
0.04
0.03
0.00
0.00
t-test Wilcoxon
p-value
p-value
0.39
<0.01
0.81
<0.01
0.96
0.92
0.09
<0.01
<0.01
<0.01
0.13
<0.01
0.59
0.84
0.17
0.12
0.07
<0.01
0.12
0.12
0.06
0.13
0.74
0.74
Departing clients are defined as those departing in the corresponding year to a non-Second Tier
auditor. Continuing clients are defined as those continuing on with a Second Tier auditor in the
next year. Reported “n” is the maximum number of firms reported for any variable in a given
year; for other variables the number of firms included in the computation of means and medians
is less than “n” due to data availability constraints. Variable definitions are provided in Table 3.
41
TABLE 5
Logistic Regression Analyses of Characteristics of New Clients
Relative to Existing Client Base
Intercept
Ln Assets
(AR+Inv)/Assets
ROA
Loss
Leverage
Change in sales
OCF
RstmtCurrent
DCWeakness
Pseudo-R2
Model 1
Model 2
Continuing versus
All New Clients
p-val
Coeff
Continuing versus
New from Big4
Coeff
p-val
-1.778
0.116
-0.536
-0.061
0.186
-0.060
0.006
-0.015
0.199
0.506
<0.01
<0.01
0.03
0.08
0.13
0.27
0.05
0.87
0.42
<0.01
-1.963
0.141
-0.501
-0.037
0.236
-0.063
0.006
-0.024
0.045
0.425
0.03
0.03
<0.01
<0.01
0.05
0.39
0.06
0.32
0.08
0.82
0.87
<0.01
Model 3
Continuing versus
New from Small
Firms
Coeff
p-val
-2.874
-0.163
-1.446
-0.071
-0.396
-0.034
0.011
0.054
1.372
1.044
<0.01
0.13
0.05
0.13
0.27
0.70
0.03
0.70
<0.01
<0.01
0.11
In Model 1 the dependent variable equals 0 for continuing clients and 1 for all new clients (n=414
new clients and 1,571 continuing clients). In Model 2 the dependent variable equals 0 for
continuing clients and 1 for new clients coming from a Big4 firm (n=374 “new from Big4”
clients and 1,571 continuing clients). In Model 3 the dependent variable equals 0 for continuing
clients and 1 for new clients coming from a small firm (n=40 “new from a small firm” clients and
1,571 continuing clients).
Variables are defined in Table 3.
42
TABLE 6
Logistic Regression Analyses of Characteristics of Departing Clients
Relative to Existing Client Base
Model 1
Model 2
Model 3
Continuing versus
All Departing
Clients
Continuing versus
Departing to a
Big4 firm
Continuing versus
Departing to a
Small Firm or
“other”
Coeff
p-val
Coeff
Intercept
Ln Assets
(AR+Inv)/Assets
ROA
Loss
Leverage
Change in sales
OCF
RstmtCurrent
DCWeakness
Pseudo-R2
-0.848
-0.209
-0.104
0.030
0.327
0.041
0.004
-0.078
-1.117
-0.526
p-val
Coeff
<0.01
<0.01
0.68
0.12
0.01
0.24
0.05
0.34
0.01
<0.01
-3.667
0.209
-0.494
0.423
-0.284
-0.898
0.004
-0.898
--0.105
0.08
0.06
p-val
<0.01
0.03
0.50
0.11
0.43
0.12
0.31
0.12
0.82
-0.869
-0.271
0.003
0.022
0.456
0.033
0.004
-0.040
-0.931
-0.685
<0.01
<0.01
0.99
0.26
<0.01
0.36
0.05
0.62
0.04
<0.01
0.11
In Model 1 the dependent variable equals 0 for continuing clients and 1 for all departing clients
(n= 385 departing clients and 1,518 continuing clients). In Model 2 the dependent variable equals
0 for continuing clients and 1 for departing clients going to a Big4 firm (n=41 “departing to Big4”
clients and 1,571 continuing clients). In Model 3 the dependent variable equals 0 for continuing
clients and 1 for departing clients going to a small firm (n= 159 “departing to small firm” clients)
or “other” which includes firms being acquired or delisting for other reasons (n= 185 departing
for “other” reasons, and 1,518 continuing clients.
Variables are defined in Table 3.
43
TABLE 7
New and Departing Clients
Descriptive Statistics
New from
small
(n=39)
mean
(median)
New from
Big4
(n=374)
mean
(median)
LnAssets
3.82
(3.82)
***
***
Depart to
Big4
(n=39)
mean
(median)
Depart to
Small
(n=159)
mean
(median)
2.33
(3.05)
4.34
(3.87)
1.80
(2.06)
***
***
ROA
-0.36
(-0.03)
-4.46
(-0.10)
0.16
(0.01)
-1.60
(-0.41)
***
Loss
0.58
(1.00)
0.64
(1.00)
0.41
(0.00)
0.82
(1.00)
***
(AR+Inv)/Assets
0.31
(0.28)
0.29
(0.22)
0.32
(0.22)
0.32
(0.26)
ChginSales
3.45
(0.03)
23.87
(0.44)
4.49
(0.10)
2.22
(-0.01)
Resign
0.27
(0.00)
0.23
(0.00)
0.08
(0.00)
0.26
(0.00)
***
GC
0.15
(0.00)
0.36
(0.00)
0.08
(0.00)
0.43
(0.00)
***
ICW
0.15
(0.00)
0.10
(0.00)
0.18
(0.00)
0.17
(0.00)
RepCond
0.08
(0.00)
0.07
(0.00)
0.13
(0.00)
0.11
(0.00)
Restate
0.03
(0.00)
0.03
(0.00)
0.00
(0.00)
0.06
(0.00)
AcctConcerns
0.04
(0.00)
0.03
(0.00)
0.05
(0.00)
0.07
(0.00)
FeeReduction
0.04
(0.00)
0.00
(0.00)
0.03
(0.00)
0.09
(0.00)
***
***
***
***
*** ** *
, , indicates a difference significant at p<0.01, p<0.05, or p<0.10 respectively
between “new from Big4” and “new from small” or between “depart to Big4” and
“depart to small”, based on t-tests for differences in means and Wilcoxon tests for
differences in medians.
44
***
***
**
***
***
***
*
TABLE 8
New versus Departing Clients
Logistic Regression Model
Pooled 2000-2004
n=615 changes
(413 new, 198
departing)
2000-2001
n=156 changes
(60 new, 95
departing)
2002-2004
n=459 changes
(353 new, 103
departing)
Coefficient
(p-value)
0.321
(0.36)
Coefficient
(p-value)
1.129
(0.09)
Coefficient
(p-value)
-0.168
(0.71)
-0.435
(<0.01)
-0.326
(0.01)
-0.455
(<0.01)
ROA
0.061
(0.04)
0.143
(0.17)
0.054
(0.07)
Loss
0.070
(0.76)
0.403
(0.36)
0.010
(0.97)
(AR+Inv)/Assets
0.059
(0.88)
-0.034
(0.96)
-0.047
(0.93)
Resign
-0.302
(0.18)
-0.509
(0.32)
0.010
(0.97)
GC
0.572
(0.01)
0.323
(0.47)
0.622
(0.04)
ICW
-0.121
(0.76)
-1.324
(0.07)
0.361
(0.48)
RepCond
0.834
(0.06)
0.998
(0.28)
0.783
(0.16)
Restate
0.255
(0.61)
1.663
(0.19)
-0.033
(0.96)
AcctConcerns
0.830
(0.06)
0.975
(0.29)
0.573
(0.32)
FeeReduction
0.918
(0.02)
2.079
(0.06)
0.660
(0.23)
0.20
0.18
0.21
Intercept
LnAssets
Pseudo-R2
Continued on next page
45
Table 8 Continued
The dependent variable, NeworDepart equals 1 if the client firm is departing one of the
Second Tier audit firms in the current year and 0 if the client is new to the Second Tier
audit firms in the current year. LnAssets, ROA, Loss and (Ar+Inv)/Assets are taken from
Compustat, as defined in Table 3. The remaining variables are taken from 8-K
information contained in the auditor change dataset of Audit Analytics, and are defined as
follows. Resign=1 if the predecessor auditor resigned from the engagement, and 0 if the
client dismissed the auditor. GC=1 if the prior audit report contained a going concern
paragraph. ICW=1 if Audit Analytics indicates the 8-K disclosed an internal control
weakness, and 0 otherwise. RepCond=1 if Audit Analytics indicates the 8-K disclosed a
reportable condition, and 0 otherwise. Restate=1 if Audit Analytics indicates the 8-K
disclosed a previous restatement, and 0 otherwise. AcctConcerns = 1 if Audit Analytics
indicates the 8-K disclosed accounting concerns, and 0 otherwise. FeeReduction = 1 if
Audit Analytics indicates the 8-K discusses a desire to reduce fees as a reason for
switching, and 0 otherwise.
46