Pricing of Risky Initial Audit Engagements

John A. Elliott

Aloke Ghosh#

and

Elisabeth Peltier Wagner

June 2008

#Corresponding author Professor of Accountancy Stan Ross Department of Accountancy Baruch College, City University of New York Box B12-225, One Bernard Baruch Way New York, NY 10010 E-mail: Aloke_Ghosh@baruch.cuny.edu Ph. 646.312.3184; Fax: 646.312.3148 We thank Masako Darrough, Harry Davis, Paquita Davis-Friday, Rong Huang, Steve Lilien, Steven Lustgarten, Rob Pawlewicz, Joe Weintrop, and the seminar participants at the Baruch College workshop for their helpful comments.

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Pricing of Risky Initial Audit Engagements

Abstract

This study analyzes the pricing of auditors’ business risk in the first year of an audit engagement. We posit that reportable events from the prior auditor’s tenure that are disclosed in the 8-K auditor change filing provide reliable information about the level of business risk for the incoming auditor. We hypothesize that for clients perceived as risky, the incoming auditor charges a fee-premium for bearing the higher risk. Our evidence is consistent with this expectation. Using a large sample of US publicly disclosed fee data from 2000-2006, we find that audit fees are about 4% lower for firms in the first year of an audit engagement compared to continuing engagements, which is consistent with incoming auditors low-balling or fee-discounting to attract new clients. More importantly, rather than receiving a fee discount, firms that report problems in the 8-K auditor change filing pay a fee premium. Finally, fee discounting appears to be eliminated by the second year of the engagement for clients without problems while auditors of more risky clients continue to charge a fee premium for the first three years of the engagement.

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Pricing of Risky Initial Audit Engagements

I. INTRODUCTION

The pricing of audit engagements is a well-researched topic in the accounting literature.

The bulk of the audit fee literature uses variations of the Simunic (1980) model which

decomposes audit fees into two components, audit effort and the expected loss from litigation.

While several studies find a positive link between audit fees and audit effort, difficulties in

identifying good proxies for expected losses in an audit engagement have limited our ability to

understand the pricing of business risk by auditors. While a few studies suggest that business

risk is priced in particular settings, it is debatable whether the results are generalizable. Some of

the limitations include the use of proprietary data from one accounting firm (Simunic and Stein

1998, Bell et al. 2001), limited sample period (Lyon and Maher 2005, Simunic and Stein 1996,

Bell et al. 2001), and the use of non-US data (Seetharaman et al. 2002). Moreover, most of

these studies evaluate ex-post business risk while auditors are interested in an ex-ante

measure.

We study the pricing of business risk for the first year of an audit engagement because

this is when auditors are most likely to price risk explicitly and to measure the risk of the new

client objectively. One innovation of our study is that we develop new proxies for business risk

by combining several observable risk indicators for new engagements. Specifically, we identify

the problems arising during the tenure of the outgoing auditor as reported in the auditor change

filings (Section 4, Form 8-K).1 We group these problems into three broad categories: (1) audit

quality problems (i.e., audit opinion disagreements, reaudits, and scope limitations), (2) financial

reporting quality problems (i.e., internal control weaknesses, accounting disagreements, and

1Public companies must report material corporate events that shareholders should know on a

timely basis in Form 8-K. The obligation to file a current report includes any of the following broad topics: (1) business and operations, (2) financial information, (3) securities markets trading, (4) matters related to accountants and financial statements, (5) corporate governance and management, (6) regulation FD, and (7) other events.

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restatements), and (3) business-related problems (i.e., illegal acts by management, going

concern problems, and bankruptcy). Collectively, these events are expected to act as signals of

increased business risk for the incoming auditor.

Several studies find that auditors offer fee discounts on initial engagements also

frequently termed “low-balling” or “fee discounting.” DeAngelo (1981) defines low-balling as the

practice of setting fees below total current costs during the initial audit engagement. By focusing

on the pricing of the first year audits, we can test for the role of pricing of risky engagements in

the context of the practice of low-balling.

Following prior literature, our study relies on a regression framework to determine how

risk is priced in the first year of an audit engagement for a comprehensive sample of U.S. public

firms with audit fee data between 2000 and 2006. As in prior studies of audit-fees, we include

several firm characteristics that proxy for audit effort and audit risk. Consistent with prior studies,

we find that auditors discount audit fees by about 4% for first year audits compared to

continuing audits, confirming the existence of low-balling in the US audit market (Turpen 1990;

Walker and Casterella 2000; Ghosh and Lustgarten 2006, Ghosh and Pawlewicz 2008).

More importantly, we find that for high risk clients, measured by pre-existing, explicitly

disclosed financial reporting, business and audit-related problems, audit fees are significantly

higher for the first year of audit. Our results suggest that these high risk firms pay a fee

premium, rather than receive a fee discount as past studies document, for the first year of an

audit engagement. Specifically, for clients with existing problems, fees are 42% higher

compared to those without such problems. Additionally, the severity of the problems (i.e. the

number of individual problems) is positively associated with the level of the first year risk

premium.

Finally, our examination of fee pricing in the years subsequent to the auditor change

provides several key insights. The practice of fee discounting appears to be eliminated by the

second year of the engagement for clients without problems in auditor change filings. In

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contrast, auditors of clients deemed as risky for the initial engagement continue to charge a fee

premium for the first three years of the engagement. However, beyond the first three years,

fees are no longer statistically different between risky and continuing engagements.

We contribute to the audit fee literature in several ways. Although numerous prior

studies examine the practice of low-balling in the U.S., the lack of publicly available audit fee

data before 2000 led to mixed evidence. The main problems were self-selection concerns and

sample-size issues because researchers had to rely on survey responses or proprietary data to

test the pricing of audit fees in the US. Using recently available public data for a large sample of

firms, we provide evidence that low-balling exists throughout the sample period, but is

significantly reduced after the Sarbanes Oxley Act (SOX). Further, we show that only less risky

clients receive fee discounts in the initial engagement while riskier clients pay a fee premium.

We also document that the premium charged by the new auditor for risky engagements

increases with the severity of the business risk.

Although our study documents higher audit fees for new risky engagements, we are

unable to discriminate between the reasons for the fee differences. Because audit fees are a

function of both effort and the quality of the professional staff assigned to the audit, fees could

be higher either because firms assign more experienced and expensive auditors or because

greater audit effort is required to achieve a desirable level of audit quality. Future research is

likely to provide insights into the explanations for the fee differentials.

The rest of the paper is organized as follows. Section II provides a review of the audit

fee pricing literature on risk and low-balling and develops our hypotheses. Section III describes

our research design and sample. Section IV presents our results and Section V concludes the

paper.

II. HYPOTHESIS DEVELOPMENT Literature Review

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Simunic’s (1980) model describing the audit pricing process is one of the most

prominent models in the audit fee literature. He models auditors’ fee determination as a function

of costs of the internal accounting system, external audit, and expected litigation loss using the

following model:

)(),|()( θEqadEcqCE += (1)

where is the cost of the external audit, cq ),|( qadE is the present value of possible future

losses conditional on the quality of the client’s internal accounting system and the auditor’s

effort in performing the audit, and )(θE is the expected fraction of that loss for which the auditor

will be responsible. ×),|( qadE )(θE is therefore the auditor’s expected loss from litigation.2

In performing empirical tests of his theory, Simunic (1980) includes several variables that

capture dimensions of audit effort and audit risk. To control for loss exposure ),|( qadE , he

includes client’s size, complexity of operations, auditing problems with receivables and

inventories, client’s industry, and whether the client is public. For variance in the loss-sharing

ratio )(θE , he controls for the ratio of net income to total assets, the presence of a loss in the

last three years, and the existence of qualified audit opinions. Finally, to capture differences in

auditor production functions, he includes the tenure of the auditor. While he considers size and

complexity as measures of increased liability exposure, subsequent studies have associated

these variables with audit effort, another component of audit fees.

Beatty (1993) introduces three new variables to capture the liability loss component of

audit fees: delisting, bankruptcy, and lawsuit. Concentrating on firms undergoing initial public

offerings (IPOs), he finds that firms that subsequently filed for bankruptcy or suffered lawsuits

had significantly higher audit fees at the time of IPO than other firms. The results provide

2Some of the other analytical studies modeling audit fee pricing include DeAngelo (1981), Magee

and Tseng (1990), Kanodia and Mukerji (1994), Schatzberg and Sevcik (1994), and Morgan and Stocken (1998).

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important evidence that liability exposure is priced by auditors. One drawback of this research

design is that the measures for auditors’ expected liability are ex-post measures. Although an

association between audit fees and subsequent negative outcomes is consistent with risk being

priced, it does not help us understand the role of expected risk. A key challenge for the auditors

in audit fee pricing is to assess the ex-ante liability exposure in setting fees.

Bell et al. (2001) use auditor’s assessment of risk from a survey administered by a large

accounting firm to proxy for business risk. They find that audit fees are higher for high-risk

clients. These higher fees are a result of a greater number of hours worked rather than higher

per hour charges. While this measure of auditors’ business risk is among the most direct

measures of auditors’ pricing decisions, it is also an ex-post test since the survey results were

collected after the audit.

Seetharaman et al. (2002) use the U.S. legal system as a proxy for increased litigation

risk for U.K. firms cross-listing in the U.S. They perform a cross-sectional multivariate regression

analysis with audit fees as the dependent variable and a cross-listed indicator variable as the

variable of interest. They find that fees are significantly higher for U.S. cross-listed firms even

after controlling for general cross-listing effects and costs of increased disclosure. Thus,

Seetharaman et al. (2002) is one of the few studies to capture expected litigation losses using

an ex-ante measure. However, audit fee determination in a cross-listing setting is not

informative about fee variation among the population of U.S. firms.

Finally, Lyon and Maher (2005) hypothesize that the payment of bribes to foreign

government officials signifies to auditors that clients operate a “risky business.” They expect

auditors to charge a fee premium to compensate for the higher risk. Consistent with their

prediction, they find a significant relationship between audit fees and the payment of bribes with

fees estimated to be 43% higher for firms paying bribes. However, their small sample results for

firms paying bribes may not be representative of recent audit fee pricing for risky U.S. firms.

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Their focus on firms with international operations that pay bribes represents only a small sample

of the population of U.S. public firms and only one dimension of business risk.

This brief survey of the existing literature suggests that while auditors’ business risk is a

critical component of audit fees, few empirical studies, if any, document a linkage between audit

fees and an ex-ante measure of the auditors’ expected business risk. In the ensuing section, we

develop ex-ante measures of auditors’ business risk based on publicly disclosed information.

Audit Fee Pricing and Risky Initial Engagements

As in Morgan and Stocken (1998), we define auditor’s business risk as consisting of two

components, (1) client’s business risk, i.e., the risk associated with the client’s continued

survival as an independent entity, and (2) the risk of litigation costs from auditing the client’s

financial statements (AICPA 1992). Prior studies conclude that the majority of business risk

arises from the threat of litigation, but other components of auditor’s business risk include

regulatory sanctions, reputation damage, and loss of fee revenue (e.g., Houston et al. 1999).

Auditors’ litigation risk exists even when the audit is performed in accordance with GAAS

(SAS NO. 107, Footnote 2). For instance, O’Malley (1993), Chairman of Price Waterhouse,

claims that the vast majority of the claims against accountants and shareholders are

unwarranted. Lawsuits are filed against auditors even when auditors are not responsible for

shareholder losses. Other auditing studies show that auditors encounter a significant level of

claims, including weak ones that they frequently settle because doing so is less expensive than

litigating and also because auditors are often insured against lawsuits (Carcello and Palmrose

1994).

An essential feature of the auditing environment is that auditors learn about the business

risk associated with a client over the length of an engagement. Over time, auditors gain

knowledge about management’s integrity, client’s preferences over questionable accounting

reporting matters, and going concern issues. Therefore, an incumbent auditor is expected to

assess a client’s business risk more accurately than an incoming auditor (Morgan and Stocken

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1998). However, the incumbent auditor’s knowledge is unobservable and cannot be explicitly

incorporated into an empirical research design. We posit that disclosures included in the auditor

change 8-K filings provide incoming auditors with valuable information about their exposure to

business risk associated with initial engagements. Thus, the disclosures under 8-K filings could

serve as useful measures for the auditor’s perception of the client’s business risk.

The Securities Act of 1934 requires a registrant to submit a form 8-K within five business

days after a material event including the dismissal or resignation of a registrant’s independent

certifying accountant. The registrant is not required to disclose the reason for the auditor

change. However, any qualified opinion, reportable condition, or disagreement with its auditors

within the previous two years must be reported. Thus, while much of the information gained by

an incumbent auditor about the client is private, both incumbent auditors and clients are

required to disclose material information surrounding auditor changes.

Using the information included in auditor change filings, we classify the disclosures

(“potential problems”) identified by the predecessor auditor into three broad categories: (1) audit

quality problems raised by the predecessor auditor including audit opinion disagreements,

reaudits, and scope limitations, (2) problems relating to client’s financial reporting quality

including internal control weaknesses, disagreements over accounting treatment, and

restatements, and (3) business related problems that revolve around management integrity

concerns and going concern issues. Each category signals an increased level of business risk

for prospective auditors.

Auditing Quality Problems

Three events (disclosed in the 8-K filings) that signal audit risk due to lower audit quality,

are audit opinion disagreements, reaudits, and audit scope limitations. Audit opinions issued by

the incumbent auditor are not always deemed acceptable by the client. The client may feel that

a given audit opinion is either incorrect or inapplicable. If the disagreement between the auditor

and client is significant, it may be disclosed in the 8-K filing. While the disagreement may be the

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result of a poor quality audit conducted by the predecessor auditor, it may also occur when the

auditors correctly perform the audit but management refuses to accept the auditor’s conclusion.

As the result of audit opinion disagreements with the predecessor auditor, management

may ask the new auditor to issue an opinion on financial statements that were previously

audited by the outgoing auditor (also known as reaudits). Reaudits may suggest a management

preference for overly aggressive financial reporting which the previous auditor refused to allow.

Not knowing whether the dissatisfaction with previously reported financial information results

from a poor quality audit or overly aggressive reporting practices by the client, the incoming

auditor faces greater business risk on such audits.

In some cases, predecessor auditors do not render an opinion on firms’ financial

statements because they cannot verify all of the information provided in the financial

statements. In such cases, the auditor may issue a scope limitation. This may signal to the

incoming auditor that management is not forthcoming with information or that internal controls

are weak.

Prior audit opinion disagreements, reaudits, and scope limitations are all caution-signals

that the successor auditor may be unable to issue an unqualified opinion on misstated financial

statements or will do so in error. Because qualified opinions are associated with going concern

issues which increase the auditor’s litigation risk (Palmrose 1988, Louwers 1998), audit quality

issues are expected to increase the business risk for the prospective auditor in two ways. First,

prior events may recur under the new auditor, leading to potential reputation loss. Second,

lawsuits on the basis of auditor negligence are inevitable when investors suffer economic losses

and audit quality is questionable. Therefore, we hypothesize that incoming auditors will charge

fee premiums when new clients have had audit related problems with the predecessor auditor.

Financial Reporting Quality Problems

Indicators of poor financial reporting quality in 8-K filings reporting auditor changes

include internal control weaknesses, disagreements with auditors concerning accounting issues,

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and restatements. An effective internal control system helps provide reliable financial

information, but a poor internal control system increases the risk of fraud and errors. Fraud and

errors contribute to misstatements which lead to unreliable financial information, and a higher

probability of lawsuits (Lys and Watts 1994).

Disagreements between auditors and clients concerning accounting treatment and

accounting principles may also contribute to poor financial reporting quality. Disagreements

may arise when management desires more aggressive financial reporting than auditors are

willing to allow. The client may disagree with the auditors’ application of accounting principles

and pressure auditors to reevaluate their judgments. While disclosed disagreements represent

cases where the issues are known and can be evaluated by the successor auditors, they may

also suggest increased risk of other aggressive reporting by the client.

Similarly, restatements are another indication that financial information may be of poor

quality. Past restatements suggest other misstatements may arise in future financials. The

client may be prone to aggressive accounting interpretations. Collectively, internal control

weaknesses, disagreements over accounting treatment, and restatements all increase the

auditor’s liability loss exposure. Thus, we hypothesize that auditors’ business risk is higher

when clients switching auditors exhibit financial reporting problems and we expect that incoming

auditors will charge a fee premium for bearing this risk.

Business Related Problems

Some of the business problems that affect the welfare of incoming auditors include

management integrity and issues related to going concerns. Illegal acts and management

representation concerns lead to questions of management integrity. When previous auditors

report inability to rely on management representations, new auditors face high levels of

uncertainty. Additionally, illegal acts, which can range from embezzlement by company officials

to violations of the Foreign Corrupt Practices Act, have a similar effect. Illegal acts may be a

symptom of a poor ethical culture in the firm.

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Being involved with a client with poor management integrity or a history of illegal acts

significantly increases the auditor’s business risk. When illegal acts cause shareholder losses,

auditors can expect to incur real costs from lawsuits. Illegal acts may lead to perceptions of

poor audit quality even when financial statements are reliable. Lyon and Maher (2005) cite

Arthur Andersen’s demise as a result of its audits of Enron as an extreme case of auditors’

increased business risk from association with a client of questionable integrity.

Similarly, firms filing for bankruptcy or receiving going concern opinions pose a higher

business risk to auditors. One reason for increased business risk is the loss of future fee

revenue due to the dissolution of the firm. The second reason for increased business risk is a

higher probability of lawsuits. Stice (1991) hypothesizes that since management of financially

weak firms try to disguise their firm’s distress, misstatements are more likely for such clients. He

also argues that even in the absence of financial errors, investors are likely to sue auditors with

“deep pockets” to recover their losses. In a related paper, Beatty (1993) shows that audit fees at

the time of an IPO are significantly higher for firms that later declare bankruptcy. Therefore, we

hypothesize that auditors charge a fee premium to compensate for the increased business risk

due to prior going concern opinions or bankruptcy.

In summary, we investigate whether incoming auditors price business risk for initial

engagements by relying on the selected disclosures accompanying auditor change filings. We

believe that the first year of the audit engagement provides direct tests of the pricing of business

risk. The uncertainty surrounding the business risk of the unfamiliar client leads the auditor to

assess all publicly available information carefully in quantifying business risk (Morgan and

Stocken 1998).

In contrast, in continuing engagements, auditors have private information which allows

them to price risk more accurately. With a more accurate assessment of business risk, the

auditor may increase the audit effort to reduce identified risks. Another concern in continuing

engagements is reductions in auditor independence. DeAngelo (1981) provides a model which

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shows that rents to incumbent auditors lower the level of auditor independence. By focusing on

the first year, we avoid the task of having to disentangle the effects of risk and independence on

audit pricing.

III. METHODOLOGY AND DATA

Regression Models Fees and Risky Initial Engagements

Similar to the approach used in prior studies to test low-balling, we perform ordinary

least squares regressions using the natural logarithmic transformation of the level of audit fees

as the dependent variable. We include an indicator variable for the first year of an audit

engagement (Initial engagement) as an independent variable to test whether audit fees are

lower for initial engagements compared to continuing engagements. Because low-balling has

been established in the literature, we expect the coefficient on the Initial engagement indicator

variable to be negative. Specifically, we estimate the following regression

AuditFees = α0 + α1Initial engagement + α2Assets + α3Current assets + α4 Current ratio + α5Receivables ratio + α6Leverage + α7Profitability + α8Loss + α9Large auditor + α10Business segments + α11Foreign sales + α12Capital expenditures + α13R&D + ε

(2) As control variables for audit fee pricing, we include the natural logarithm of total assets

(Assets), current assets as a percentage of total assets (Current assets), ratio of current assets

to current liabilities (Current ratio), accounts receivable to total assets (Receivables ratio), sum

of total debt to total assets (Leverage), ratio of net income before extraordinary items to total

assets (Profitability), an indicator variable if net income before extraordinary items is negative in

year t or t-1 (Loss), an indicator variable for a large (Big 5/4) auditor (Large auditor), the number

of business segments reported by the client (Business segments), the portion of sales from

foreign operations (Foreign sales), capital expenditures to total assets (Capital expenditures),

and R&D expenditures to total assets (R&D). We also include fixed year effects and Fama-

French industry effects.

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Our main test supplements model (1) with a business risk proxy, which is an indicator

variable identifying the previously discussed reporting and auditing problems during the prior

audit engagement as reported in the 8-K filings that accompany auditor change news. The

problems are (1) audit opinion disagreements, (2) audit scope limitations, (3) reaudits, (4)

internal control weaknesses, (5) restatements, (6) disagreements between auditor and client

concerning accounting treatment or application of accounting principles, (7) illegal acts by

employees of the client, (8) going concern opinions, (9) unreliable management, or (10)

bankruptcy. The indicator variable Problem is set to one if a client firm has any of the above

indicated financial reporting or auditing problems.

AuditFees = α0+ α1Initial engagement + α2 Assets + α3 Current assets + α4 Receivables ratio + α5 Inventory ratio + α6 Leverage + α7 Profitability + α8 Loss + α9 Large auditor + α10 Business segments + α11 Foreign sales + α12 Capital expenditures + α13 R& D + α14 Problem + ε (3)

To capture the severity of business risk, we also create a variable Problem score which

is zero in the case no problems are disclosed and increases by one for each of the above

problems a client reports. 3

AuditFees = α0+ α1Initial engagement + α2 Assets + α3 Current assets + α4 Receivables ratio + α5 Inventory ratio + α6 Leverage + α7 Profitability + α8 Loss + α9 Large auditor + α10 Business segments + α11 Foreign sales + α12 Capital expenditures + α13 R& D + α14 Problem score + ε (4)

Fees and the Length of Risky Engagements

We also examine how the pricing of audit fees for risky initial engagements varies over

the duration of the auditor client relationship. We modify equation (3) by replacing Initial

engagement with Tenure 1 to Tenure 5 for firms that have at least one auditor switch during the

sample period. If the client reveals problems in the 8-K auditor change filing, the variable

Problem client is set to one for the entire tenure of the audit engagement. We then interact each

of the tenure variables with Problem client as follows.

3 Of the 398 firm-years with problems, 284 have only 1 problem, 94 have 2 problems, 49 have 3 problems, 28 have 4 problems, 6 have 5 problems and 2 have 6 problems. For firms with problems, the mean number of problems is 1.72.

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AuditFees = α0+ αjControl variables + α14Tenure1 + α15Tenure1*Problem client + α16Tenure2 + α17Tenure2*Problem client + α18Tenure3 + α19Tenure3* Problem client + α20Tenure4 + α21Tenure4*Problem client + α22Tenure5 + α23Tenure5*Problem client + ε

(5)

Tenure1 to Tenure5 are indicator variables each set to one when the auditor-client

relationship is equal to one to five or more years, respectively. All the other independent

variables are as defined previously. Relative to clients that did not switch auditors over the

sample period, α14 captures the extent of low-balling for initial engagements for clients without

pre-exiting problems while α14+α15 shows the effect for firms with pre-existing problems. When

auditor tenure is two years, α16 captures incremental audit fees for firms without pre-existing

problems and α16+α17 captures incremental fees for firms with pre-existing problems. Finally,

when auditor tenure is five or more years, α22 captures incremental audit fees for firms without

pre-existing problems while α22+α23 is the estimate for firms with such problems.

Data

Our auditor change data are from Audit Analytics’ Auditor Changes file and audit fee

data are from the Audit Analytics’ Audit Fees file. Data for the financial variables are from

Compustat Annual files. The audit fee data includes 19,297 observations over the years 2000

to 2006. A total of 1,934 firm-years involve auditor switches; 398 of these firm-year switches

have some type of problem disclosed in the auditor change filings while the remaining 1,934

observations do not report problems.

5. Results Descriptive Statistics

Table 1 reports the mean values of the variables used in our analyses. In Panel A, we

report the results for the full sample of initial and continuing engagements. The t-statistics for

the differences in firm characteristics between the two groups suggest that firms with new

auditors and those with incumbent auditors are dramatically different. Panel A shows that firms

in the first year with a new auditor have lower audit fee levels, are smaller, have more current

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assets relative to total assets but less current assets compared to current liabilities, have higher

receivables, are less profitable, are more likely to experience a loss, are less likely to have a

large auditor, have fewer business segments, and have less foreign operations compared to

clients with continuing audits.

In Panel B, initial engagements are separated based on whether they report at least one

problem in the 8-K auditor change filings. The preliminary results are consistent with our

expectations; the level of audit fees is significantly higher for problem clients relative to those

without problems based on univariate tests. Average audit fees for initial engagements are

$835,690 for clients disclosing some type of problem in the auditor change filings while the

number for firms without problems is $567,552. The difference between the two groups

($268,138) is statistically and economically significant. Our results suggest that auditors charge

fees that are about 47% higher for clients reporting problems relative to those without problems

In addition to being significantly smaller than problem-free clients, problem clients are

also less liquid, more leveraged, less profitable, 21% more likely to suffer a recent loss, have

fewer business segments, have more foreign operations, have less capital expenditures and

more R&D. These results suggest that clients without problems are larger and healthier than

problem-clients. By controlling for these differences in the multivariate regressions, we isolate

the difference in fees attributable to the increased business risk.

Table 2 provides details about the types of problems revealed during auditor changes.

The full sample of 1,934 firm-year switches includes 398 switches involving problem clients and

1,536 switches that do not involve problem clients. We further partition these problems into

accounting-, audit-, and business-related problems. Using a Venn diagram to display the

various types of problems in firms, we find that 19 switches have all three types of problems, 57

switches have accounting and auditing problems, 37 switches have accounting and business

problems, and one switch has auditing and business problems. For firms with only one type of

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problem, 179 have only accounting problems, 104 have only business problems, and one

contains only auditing problems.4

The auditing-related problems consist of audit opinion disagreements, audit scope

limitation problems, and financial statement reaudits. The vast majority (79%) of the auditing-

related problems are audit opinion disagreements. The accounting-related problems include

internal control issues, restatements, accounting principles or accounting treatment

disagreements, or illegal acts (embezzlements by employees, violations of FCPA, etc.). The

majority (59%) of accounting-related problems involve internal control issues. Business-related

problems include going concern opinions, unreliable management, or bankruptcy. Going

concern opinions make up most (82%) of the business-related problems.

Main Results

Fees and First Year Audits

In Table 3 we test whether auditors discount audit fees for new clients after controlling

for various known determinants of audit fees. In Panel A, we estimate a pooled regression of

audit fees on Initial engagement and several control variables. Our results suggest that audit

fees for firms switching auditors are about 4% less than those for continuing audits.5

In Panel B we perform yearly regressions to examine whether fee discounting changed

over the sample period. Consistent with the results of Ghosh and Pawlewicz (2008), we find that

the extent of low-balling changes over our sample period; it is about 14% in 2001, then falls to

about 10% in 2002 and 2003, and finally there is no evidence of low-balling over the post

4 The one firm with only an audit-related problem is China Bak Battery Inc. They report a reaudit for their fiscal year 2006 switch. Bio Key International, Inc. is the one firm-year with auditing and business problems. For fiscal year 2006 they report a disagreement with the going concern opinion the auditors issued.

5Since the dependent variable is the natural logarithmic transformation of audit fees, the economic impact of Initial engagement on audit fees is 1 ─ e-0.04.

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Sarbanes-Oxley period.6 There appears to be a slight premium (instead of a discount) in 2005.

One plausible explanation for the premium in 2005 appears to be the result of an unusually high

number of “problem” clients switching auditors (2005 has the highest percentage of such clients

among all of the years in our sample).

Table 4 adds to the base regressions in Table 3 by introducing our main variables of

interest, Problem and Problem score. We use Problem as a proxy for high business risk and

Problem score as a proxy for the severity of the risk. The results from the first regression

indicate that Initial engagement continues to be significant (α=-0.11, t-stat=-6.67). More

importantly, the coefficient on Problem is positive and significant (α=0.38, t-stat=11.64).

Because we include two indicator variables (Initial and Problem) in the same regression, the

coefficient on Initial captures incremental fees charged by auditors for initial engagements

without reporting problems compared to those for continuing engagements. The coefficient on

Problem captures incremental fees charged by auditors for initial engagements with reporting

problems compared to those for initial engagements without reporting problems. Therefore, the

sum of the coefficients on Initial and Problem capture the incremental fees charged by auditors

for initial engagements compared to those for continuing engagements.

The coefficient on Initial suggests that audit fees for initial engagements without

reportable problems are about 10% lower compared to those for continuing engagements. In

contrast, the coefficient on Problem suggests that audit fees are 46% higher for initial

engagements with reportable problems compared to initial engagements without reportable

problems. Therefore, problem clients switching auditors pay a 31% fee premium compared to

continuing audits (sum of the coefficients Initial and Problem).

6Because our study focuses on the pricing of audit fees for clients with and without problems, we

do not analyze why low-balling is eliminated over the SOX period which is discussed extensively in Ghosh and Pawlewicz (2008).

19

When we replace Problem with Problem score in the column 3 regression, the coefficient

on Problem score remains positive and significant (α=0.19, t-stat=11.75). Our results suggest

that for each reported problem, the average audit fees increase by about 21%.

Since Table 4 results are based on OLS regression from pooled data, another concern is

that the inferences may be biased because of cross-sectional dependence among observations.

Therefore, we also report the yearly results in Table 5 emphasizing the important coefficients on

initial engagement and problem. Since the year 2000 has only 6 problem clients, we do not

report yearly regressions for 2000. Consistent with the pooled results from Table 4, we find that

the coefficients on Initial engagement are negative and significant. While the decrease in low-

balling is not monotonic over time, there is a clear downward trend in low-balling.

More importantly, the coefficient on Problem is positive and significant for all six years

(Panel A of Table 5). The range of the coefficients is between 0.24 and 0.47. Our results

suggest that the premium in audit fees associated with risky clients seems to have increased for

the post-SOX period. The results are very similar in Panel B when we replace Problem with

Problem score. The coefficients are positive and significant for all six years and the range is

between 0.13 and 0.34. Overall, our results from the pooled and yearly regressions indicate that

auditors offer a fee discount to attract new clients (compared to continuing engagements) when

clients do not have pre-existing problems. In sharp contrast, clients reporting various problems

in their auditor change filings with the SEC pay a substantial premium to incoming auditors.

In Table 6 we partition problems into auditing, business, and accounting categories and

include them as separate independent variables in the first three columns. Column 1 of Table 6

shows that having an auditing-related problem increases audit fees 55% (α=0.44, t-stat=6.32)

compared to problem-free first-year audits. Column 2 indicates a 27% increase (α=0.24, t-

stat=5.11) when business-related problems are revealed and column 3 estimates a 55%

increase (α=0.44, t-stat=6.25) when accounting-related problems are disclosed. Thus, the

20

largest price increases are associated with accounting and auditing-related problems. However,

all three are statistically and economically significant.

In column 4 of Table 6, we include all three types of problems and find that when a firm

reveals multiple types of problems, the auditing-related problems increase fees by 36%,

business-related problems contribute to 38% higher fees, and accounting-related problems lead

to 21% higher fees. Since audit-related problems should have the most direct effect on the cost

of the audit, it is not surprising that its effect on fees is largest.

A few recent studies also examine the impact on audit fees for firms reporting internal

control weaknesses under Sections 302 and 404 of the Sarbanes Oxley Act (2002) (e.g., Hogan

and Wilkin 2008, Hoitash et al. 2007, Raghunandan and Rama 2006). In general these studies

find that audit fees are higher for firms reporting internal control weaknesses. Although we

include firms disclosing internal control issues in the Problem variable, ours is a much more

comprehensive dataset because we include disclosures included in the 8-K filings and not just

reports filed under Section 302 and 404 of SOX. Moreover, we concentrate on audit pricing of

initial engagements while the other studies do not distinguish between continuing and initial

engagements.

For a comparative analysis, we also include an indicator variable Internal control in

Table 4 regressions along with the other independent variables. Internal control is set to one

whenever the 8-K reports indicate problems pertaining to internal controls. In unreported results,

we find that Problem and Problem score continue to be positive and significant. For instance, in

the first regression, the coefficient on Problem is 0.19 (t-stat=3.92) and that on Problem score is

0.29 (t-stat=4.84). In both of these regressions, Internal control is also positive and significant.

Fees and Subsequent Year Audits

Thus far our emphasis has been on the pricing of audit fees for risky initial

engagements. In Table 7, we investigate how audit fees change for risky and less risky

21

engagements as the length of the auditor-client relationship lengthens.7 Similar to the results

from the prior tables, the coefficient on Tenure 1 is negative (-0.09, t-stat=-5.61) while that on

Tenure 1 X Problem client is positive (0.40, t-stat=-11.69). Our results suggest that relative to

clients that do not change auditors, audit fees for initial engagements are lower by 9% for less

risky clients but they are higher by 35% for risky clients.

Table 7 results provide some additional key insights. First, controlling for the other

factors, the practice of fee discounting appears to be eliminated by the second year (α14 is

negative and significant for year 1 but α16, α18, α20 and α22 are not.) Second, and in contrast to the

results for less risky clients, audit fees for risky clients are incrementally higher for the first three

years only (based on F-statistics and positive summed coefficients). Specifically, compared to

continuing engagements that did not switch auditors, audit fees are higher by 36%, 35%, 22%

for clients deemed as risky in the first three years of the engagements (i.e., when tenure is one,

two and three). For subsequent years, audit fees are not statistically distinguishable from

continuing engagements that did not switch auditors.

Although we control for the size of the auditor in the audit fee regressions, our analysis

does not take into account whether the fee premium charged by the auditor for risky

engagements varies by the size of the auditor. Because of litigation concerns, Big 4 (smaller)

auditors are expected to be less (more) likely to get involved in risky engagements. Further,

conditional on auditors accepting risky engagements, because of lawsuits, Big 4 auditors are

expected to be more likely to charge a higher premium than smaller auditors. Following this

intuition, Table 8 examines differences in pricing of risky clients based on auditor size.

Based on the sample of clients switching auditors, we find 58% of the clients use large

auditors while 42% use small auditors (Panel A). Further, large auditors are much less likely to

be associated with new risky engagements than small auditors; 12% (=7%/58%) of the large

7 We only create tenure indicators for firms that change auditor during our sample period. The

tenure results are therefore interpreted relative to continuing engagements of firms that never switched auditors during the sample period.

22

auditors have initial engagements deemed as risky while 29% (=12%/42%) of the small auditors

have risky initial clients. The chi-square test also indicates that there is an association between

the size of the auditor and clients with problems; small auditors are associated with a high

proportion of clients with problems.

In Panel B we report the mean audit fees for each subgroup sorted by auditor size and

the type of client. Consistent with our expectations, we find that the average audit fees for large

auditors are greater than those of small auditors for clients with and without problems (all

column and row mean fee differences are significant). Large auditors charge about $1.8 million

for new, risky clients compared to $1.1 million for others, a 64% premium. Small auditors charge

$0.53 million for new, risky clients versus $0.27 million, a 96% premium. Thus, our results

suggest that small auditors are more likely to bid aggressively for new clients when they do not

have pre-existing problems.

In Panel C we control for many of the variants between large and small auditors that also

affect audit fees. We isolate the effect of client problems on audit fee pricing by estimating the

audit fee regression for samples with large and small auditors separately. Consistent with the

Panel B results, we find that the coefficients on both Problem and Problem score are

significantly larger for the sample with large auditors than for the sample with small auditors.

Further unreported analyses suggest that problem clients tend to migrate to smaller

audit firms. The transition patterns reveal that for the overall sample, 35% of the clients using

large auditors switch to smaller auditor firm, but that number is 60% for clients with problems.

Similarly, while 30% of the clients using small audit firms typically switch to large auditor firms

(among the switching firms), for clients with problems, this percentage falls to 17. Thus, it

appears that large auditors are reluctant to accept new clients with reporting problems. While

the data in Panel B suggests that large auditors charge a lower premium for risky clients than

small audit firms, the frequency data suggest that larger firms are very selective in their

acceptance of clients that disclose problems in 8-Ks.

23

Sensitivity Analyses

Panel A of Table 1 results suggest that there are substantial differences in firm

characteristics between continuing and initial engagements. Firm characteristics are frequently

used to proxy for audit effort and audit risk. It is therefore possible that audit fee determination

between the two groups differ on dimensions other than those included in our analysis (i.e., the

omitted correlated variables problem).

Conceivably, a better benchmark for comparing the pricing of risky new engagements is

the fees charged by auditors for less risky initial engagements. Therefore, Table 9 replicates the

regressions estimated in Table 4 using a restricted sample that includes clients switching

auditors. The coefficient on Problem indicates the incremental impact on audit fees for risky

initial engagements. Our results are consistent with all the prior tables. In Regression 1 of Table

9, the coefficient on Problem is 0.38 (t-statistic=9.70) suggesting that, relative to other clients in

the first year of audit engagements, audit fees are higher by about 46% for clients reporting

problems in the auditor change filings. In Regression 2, when we replace Problem with Problem

score, the coefficient continues to be positive and significant (0.19, t-statistic=9.83). One

difference between the results reported in Tables 4 and 9 is that Leverage, Capital expenditures

and R&D are not statistically significant in Table 9 regressions when we use the reduced

sample. This result is not surprising because there are fewer firm specific differences between

clients with and without problems.

Another concern is that some of the auditor switches in our sample are the result of

Arthur Andersen’s demise.8 Because this event gave most clients no choice but to leave

Andersen, the involuntary switches in connection with Andersen’s downfall are not of interest in

this study. We have no predictions about audit pricing under such circumstances and,

8Late 2001 the SEC began investigating Arthur Andersen in connection with its audits of Enron.

On May 6, 2002 Andersen was charged with obstruction of justice for having shredded documents concerning its audits of Enron, and on June 15, 2002 Andersen was found guilty. Before the trial even began, Andersen had lost most of its clients and employees, and on August 31, 2002, surrendered its CPA license.

24

therefore, perform our analyses without Andersen clients. The results for the reduced sample

are very similar to the main results and are therefore not reported. The only major difference

between the two samples is that the low-balling effect in the table 3 regression becomes

insignificant when Andersen clients are excluded. After controlling for Problem as in the table 4

regressions, the low-balling effect reappears for the non-Andersen subsample.

7. Conclusion

We examine fee discounting in the first year of a new audit engagement. Using newly

publicly disclosed audit fee information, we are able to test a large sample of auditor changes to

provide evidence in support of the long-standing belief that auditors discount their initial

engagements. We show that the effect of this low-balling is to charge new clients about 4% less

than continuing clients, 10% less after controlling for negative 8-K disclosures. Yearly results,

however, suggest that low-balling might have been eliminated for the post-SOX period.

More importantly, using low-balling as our base case, we analyze how business risk

affects audit pricing. Using various problems reported during the auditor switch as our ex ante

proxy for auditor’s business risk, we find that when at least one problem exists, the client no

longer receives a discount, but rather pays a fee premium compared to continuing

engagements. In addition we find that each additional problem disclosed signals higher

business risk and results in an even higher fee premium.

Finally, we analyze how the pricing of audits change after the first year of the audit

engagement. Our results suggest that the practice of fee discounting associated with clients

with less business risk (no problems disclosed in the auditor change filings) vanishes after the

first year of audit. For years two to four, the audit fees of clients with less business risk are not

statistically distinguishable from those of continuing audits. In contrast, for clients deemed as

risky in the first year, auditors continue to charge a fee premium up to the third year of the

engagement but not for the subsequent years.

25

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Magee, R. P., and M. Tseng. 1990. Audit Pricing and Independence. The Accounting Review 65

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and Audit Fees. Auditing: A Journal of Practice & Theory 25: 99-114. Schatzberg, J. W., and R. Sevcik. 1994. A Multiperiod Model and Experimental Evidence of

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27

TABLE 1 Summary Statistics

Variables All firms Continuing audit

Initial engagement

Difference

Panel A: Continuing and initial audit engagements (19,297 observations) Audit fees (dollars) 1,003,596 1,049,427 618,856 430,571a Assets (million dollars) 2,001 2,096 1,202 894a Current assets 0.49 0.49 0.51 -0.02b Current ratio 2.77 2.80 2.59 0.21a Receivables ratio 0.15 0.15 0.16 -0.01a Leverage 0.23 0.22 0.24 -0.02b Profitability -0.03 -0.03 -0.07 0.04a Loss 0.46 0.45 0.54 -0.09a Large auditor 0.84 0.87 0.58 0.29a Business segments 1.42 1.43 1.33 0.10b Foreign sales 0.24 0.25 0.22 0.03a Capital expenditures 0.05 0.05 0.05 0.00 R&D 0.05 0.05 0.05 0.00

Initial engagement

No Problem

Problem Difference

Panel B: Initial engagements with and without problems (1,934 observations) Audit fees (dollars) 618,856 567,552 835,690 -268,138a Assets (million dollars) 1,202 1,360 533 827a Current assets 0.51 0.50 0.51 -0.01 Current ratio 2.59 2.67 2.22 0.45a Receivables ratio 0.16 0.16 0.16 0.00 Leverage 0.24 0.23 0.26 -0.03b Profitability -0.07 -0.05 -0.14 0.09a Loss 0.54 0.50 0.71 -0.21a Large auditor 0.58 0.63 0.36 0.27a Business segments 1.33 1.39 1.10 0.29a Foreign sales 0.22 0.22 0.25 -0.03 Capital expenditures 0.05 0.05 0.04 0.01a R&D 0.05 0.05 0.06 -0.01a Audit fees are the fees charged by the auditor for performing an audit. Assets are total assets. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Business segments are the number of business segments. Foreign sales is the portion of sales from foreign segments. Capital expenditures are capital expenditures scaled by total assets. R&D is R&D expenditures scaled by total assets. The last column is the difference between the means in columns 3 and 4. a and b denote significance at the 1% and 5% levels, respectively.

28

TABLE 2 Auditor Change and the Type of Problems

Firm-years with no problems 1,536Firm-years with at least one problem 398Firm-years with an auditor change 1,934

Auditing

Accounting

Business

1

179

104

57

1

19 37

Auditing-related problems Audit opinion 79% Reaudit previous financials 12% Scope limitation 9%

Business-related problems Going concern 82%Unreliable management 10%Bankruptcy 8%

Accounting-related problems Internal controls 59%Restatements 22%Accounting treatment 18%Illegal acts 1%

 

29

TABLE 3 Fee Discounting for Initial Engagements

Variables Panel A: Fee discounting on initial engagements (pooled results) Intercept 8.97 (141.79)a Initial engagement -0.04 (-2.51)b Assets 0.51 (151.08)a Current assets 0.38 (12.14)a Current ratio -0.04 (-20.13)a Receivables ratio 0.49 (9.57) b Leverage 0.10 (4.36)a Profitability -0.40 (-15.08)a Loss 0.13 (11.98)a Large Auditor 0.32 (23.11)a Business segments 0.04 (18.63)a Foreign Sales 0.26 (16.36)a Capital Expenditures -0.71 (-7.52)a R&D 0.27 (3.91)a Adjusted R² 76% Number of observations 19,297

Initial engagement

Panel B: Fee discounting on initial engagements (yearly results) 2001 -0.15 (-3.51)a 2002 -0.11 (-4.47)a 2003 -0.11 (-2.70)a 2004 0.03 (0.65) 2005 0.11 (2.68)a 2006 0.05 (1.15)

The dependent variable is the logarithmic transformation of Audit fees. The independent variables are defined as follows. Initial engagement is set to one for initial engagements and zero for continuing engagements. Assets are total assets reported in the balance sheet. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Business segments are the number of business segments. Foreign sales is the portion of sales from foreign operations. Capital expenditures (R&D) are capital (R&D) expenditures scaled by total assets. Year and Fama-French industry fixed effects are included. a, b, and c denote significance at the 1%, 5%, and 10% levels respectively.

30

TABLE 4 Fee Discounting and Problem Clients: Pooled Results

Variables Problem Problem score Intercept 8.96 (141.89)a 8.96 (142.02)a Initial engagement -0.11 (-6.67)a -0.09 (-6.03)a Problem 0.38 (11.64)a Problem score 0.19 (11.75)a Assets 0.50 (151.51)a 0.50 (151.45)a Current assets 0.38 (12.21)a 0.38 (12.19)a Current ratio -0.04 (-19.87)a -0.04 (-19.91)a Receivables ratio 0.50 (9.73)a 0.50 (9.70)a Leverage 0.10 (4.38)a 0.10 (4.41)a Profitability -0.39 (-14.71)a -0.40 (-14.74)a Loss 0.13 (11.60)a 0.13 (11.77)a Large Auditor 0.32 (23.02)a 0.33 (24.02)a Business segments 0.05 (18.72)a 0.05 (18.80)a Foreign sales 0.26 (16.28)a 0.26 (16.30)a Capital Expenditures -0.69 (-7.31)a -0.68 (-7.26)a R&D 0.27 (4.00)a 0.27 (4.00)a Adjusted R² 76% 76% Number of observations 19,297 19,297 The dependent variable is the logarithmic transformation of Audit fees. The independent variables are defined as follows. Problem is set to one when clients have financial reporting or auditing related problems disclosed in the auditor change 8-K filings for initial engagements, otherwise zero. Problem score counts the number of problems reported in the 8-K reports. Initial engagement is set to one for initial engagements and zero for continuing engagements. Assets are total assets reported in the balance sheet. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Business segments are the number of business segments. Foreign sales is the portion of sales from foreign operations. Capital expenditures (R&D) are capital (R&D) expenditures scaled by total assets. Year and Fama-French industry fixed effects are included. a and b denote significance at the 1% and 5% levels respectively.

31

TABLE 5 Fee Discounting and Problem Clients: Yearly Results

Year Initial engagement Problem Panel A: Initial risky engagements: Problem versus no-problem 2001 -0.15 (-3.04)a 0.32 (2.51)b 2002 -0.15 (-3.25)a 0.29 (2.73)a 2003 -0.16 (-3.80) a 0.30 (3.56) a 2004 -0.02 (-0.46) 0.24 (2.82)a 2005 -0.04 (-0.81) 0.47 (6.27)a 2006 -0.10 (-1.78) 0.42 (4.94)a Initial engagement Problem score Panel B: Initial risky engagements: Problem score 2001

-0.17 (-3.49)a

0.34 (4.20)a

2002 -0.14 (-3.04)a 0.13 (2.38)b 2003 -0.16 (-3.80)a 0.17 (4.39)a 2004 -0.01 (-0.24) 0.13 (2.86)a 2005 -0.00 (-0.02) 0.20 (5.66)a 2006 -0.08 (-1.62) 0.21 (5.73)a

The dependent variable is the logarithmic transformation of Audit fees. The independent variables are defined as follows. Problem is set to one when clients have financial reporting or auditing related problems disclosed in the auditor change 8-K filings for initial engagements, otherwise zero. Problems score counts the number of problems reported in the 8-K reports. Initial engagement is set to one for initial engagements and zero for continuing engagements. Assets are total assets reported in the balance sheet. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Business segments are the number of business segments. Foreign sales is the portion of sales from foreign operations. Capital expenditures (R&D) are capital (R&D) expenditures scaled by total assets. Panel A reports the results from a pooled regression while Panel B reports only the coefficient estimates for the Initial engagement from yearly regressions. a, and b denote significance at the 1% and 5% levels, respectively.

32

TABLE 6 Fee Discounting and the Types of Problems

Type of Problem Auditing Business Accounting Intercept 8.97 (141.89)a 8.97 (141.60)a 8.97 (141.78)a 8.96 (141.70)a Initial engagement -0.05 (-3.46)a -0.05 (-3.58)a -0.05 (-3.41)a -0.07 (-4.63)a Type of Problem Auditing 0.44 (6.32)a 0.31 (4.25)a Business 0.24 (5.11)a 0.32 (4.43)a Accounting 0.44 (6.25)a 0.19 (3.94)a Assets 0.50 (151.12)a 0.51 (151.26)a 0.51 (151.23)a 0.51 (151.33)a Current assets 0.38 (12.19)a 0.38 (12.25)a 0.37 (12.08)a 0.38 (12.22)a Current ratio -0.04 (-0.13)a -0.04 (20.01)a -0.04 (-0.03)a -0.04 (-9.97)a Receivables ratio 0.49 (9.56)a 0.49 (9.60)a 0.50 (9.69)a 0.50 (9.67)a Leverage 0.10 (4.39)a 0.10 (4.30)a 0.10 (4.38)a 0.10 (4.35)a Profitability -0.40 (-5.00)a -0.40 (-4.83)a -0.40 (-4.98)a -0.39 (-4.75)a Loss 0.13 (11.94)a 0.13 (11.90)a 0.13 (12.04)a 0.13 (11.92)a Large Auditor 0.32 (23.36)a 0.32 (23.36)a 0.32 (23.30)a 0.33 (23.61)a Business segments 0.05 (18.67)a 0.05 (18.69)a 0.05 (18.64)a 0.05 (18.72)a Foreign sales 0.26 (16.39)a 0.26 (16.27)a 0.26 (16.24)a 0.26 (16.22)a Capital expenditures -0.70 (-7.46)a -0.70 (-7.37)a -0.71 (-7.51)a -0.69 (-7.36)a R&D 0.27 (3.92)a 0.27 (3.98)a 0.27 (3.95)a 0.27 (4.00)a Adjusted R² 76% 76% 76% 76% Number of observations 19,297 19,297 19,297 19,297 The dependent variable is the logarithmic transformation of Audit fees. The independent variables are defined as follows. Auditing problem is an indicator variable equal to 1 if the auditor change filing reports a scope limitation problem, audit opinion problem, or that the new auditors will reaudit previous financial statements. Accounting problem is an indicator variable equal to 1 if the auditor change filing reports a restatement of financials, internal control weakness, accounting treatment or principles issue or illegal acts by employees of the firm. Business problem is an indicator variable equal to 1 if the auditor change filing reports a going concern opinion, unreliable management, or bankruptcy. Initial engagement is set to one for initial engagements and zero for continuing engagements. Assets are total assets. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Foreign sales is the portion of sales from foreign operations. Capital expenditures (R&D) are capital (R&D) expenditures scaled by total assets. All regressions include year and Fama-French industry fixed effects. a denotes significance at the 1% level.

TABLE 7 Fee Discounting and the Types of Problems

Variables Coefficients (t-stat) αi+αj (F-stat) Intercept 8.91 (175.25)a Assets 0.51 (177.58)a Current assets 0.39 (14.02)a Current ratio -0.04 (-23.00)a Receivables ratio 0.54 (11.62)a Leverage 0.08 (4.21)a Profitability -0.44 (-18.74)a Loss 0.10 (10.41)a Large Auditor 0.32 (24.83)a Business segments 0.05 (22.31)a Foreign sales 0.27 (19.19)a Capital expenditures -0.78 (-9.45)a R&D 0.24 (3.86)a Tenure 1 α14 -0.09 (-5.61)a Tenure 1* Problem client α15 0.40 (11.69)a α14 + α15 0.31 (96.54)a Tenure 2 α16 -0.01 (-0.39) Tenure 2* Problem client α17 0.31 (6.92)a α16 + α17 0.30 (53.13)a Tenure 3 α18 0.04 (1.96)b Tenure 3* Problem client α19 0.16 (2.90)a α18 + α19 0.20 (15.34)a Tenure 4 α20 0.03 (1.29) Tenure 4* Problem client α21 0.06 (0.83) α20 + α21 0.09 (1.78) Tenure 5+ α22 0.06 (2.00)b Tenure 5+* Problem client α23 0.04 (0.42) α22 + α23 0.10 (1.27) Adjusted R² 79% Number of observations 23,711

The dependent variable is the logarithmic transformation of Audit fees. The independent variables are defined as follows. Tenure1 to Tenure5 are indicator variables each set to one when the auditor-client relationship is equal to 1 to 5 or more years, respectively.. Problem is set to one when clients have financial reporting or auditing related problems disclosed in the auditor change 8-K filings for initial engagements, otherwise zero. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Business segments are the number of business segments. Foreign sales is the portion of sales from foreign operations. Capital expenditures (R&D) are capital (R&D) expenditures scaled by total assets. Year and Fama-French industry fixed effects are included. a and b denote significance at the 1% and 5% levels, respectively.

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TABLE 8 Fee Premium for Problem Clients by Auditor Size

Large Auditor Small Auditor Number Percentage Number Percentage Panel A: Frequency of Switching by Auditor size Clients with problems 129 7% 239 12% Clients without problems 987 51% 579 30%

1,116 58% 818 42% Chi-square statistic: Association between size of the auditor and the type of client

94.2 a

Large Auditor Small Auditor Difference

(t-statistic) Panel B: Mean Audit Fees for Clients Switching Auditors Clients with problems 1,802,315 528,563 1,273,752 (4.48)a Clients without problems 1,092,331 272,947 819,384 (8.24)a Difference (t-statistic) 709,984 (2.48)b 255,616 (4.60)a Increase 65% 94% Large Auditor Small Auditor Difference

(F-statistic) Panel C: Results from Regressions Using the Full Sample

AuditFees = α0+ αi control variables + α14 Problem + ε AuditFees = α0+ αi control variables + α14 Problem score + ε

Problem 0.47 (8.71)a 0.29 (6.61)a 0.18 (60.81)a Problem score 0.23 (8.92)a

      0.15 (6.71)a 0.08 (61.09)a Control variables included

The sample is divided into clients of Big 5/4 firms and small firms in the first year of an audit engagement. Panel A shows the number of clients that fall into each Big 5/4 and problem subgroup. The final row reports the chi-square statistic for the test of association between Big 4 and problem. Panel B shows the mean audit fees for each subgroup and t-tests for differences in the means. Panel C shows the problem (problem score) coefficient from the regressions. The regressions are performed separately for Big 4 clients (column 2) and Non-Big 4 clients (column 3). The final column shows the statistic from the Chow test for equal coefficients across the two subgroups. a and b denote significance at the 1% and 5% levels respectively.

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Table 9 Auditor Switches and the Pricing of Risk

Variables Regression 1 Regression 2 Intercept

8.85 (56.60)a

9.03 (53.70)a

Problem 0.38 (9.70)a Problem score 0.19 (9.83)a Assets 0.53 (45.57)a 0.53 (45.32)a Current assets 0.35 (3.58)a 0.36 (3.62)a Current ratio -0.04 (-5.53)a -0.04 (-5.69)a Receivables ratio 0.32 (2.06)b 0.30 (1.94)c Leverage 0.04 (0.59) 0.04 (0.58) Profitability -0.37 (-4.82)a -0.38 (-4.95)a Loss 0.15 (4.08)a 0.16 (4.32)a Large Auditor 0.19 (4.59)a 0.18 (4.51)a Foreign sales 0.24 (4.55)a 0.25 (4.73)a Business segments 0.05 (5.63)a 0.05 (5.51)a Capital expenditures -0.26 (-0.81) -0.20 (-0.63) R&D 0.23 (1.11) 0.22 (1.05) Adjusted R² 71% 71% Number of observations 1,934 1,934

This table is identical to Table 4 with a key difference, only firms with auditor switches are included in the sample. The dependent variable is the logarithmic transformation of Audit fees. The independent variables are defined as follows. Problem is set to one when clients have financial reporting or auditing related problems disclosed in the auditor change 8-K filings for initial engagements, otherwise zero. Problem score counts the number of problems reported in the 8-K reports. Current assets (Current ratio) is the ratio of current assets to total assets (current liabilities). Receivables ratio is the ratio of accounts receivable to total assets. Leverage is total debt divided by total assets. Profitability is net income before extraordinary items over total assets. Loss is an indicator variable for negative net income before extraordinary items in year t or t-1. Large auditor is an indicator variable set to one if the client is audited by a large auditor. Business segments are the number of business segments. Foreign sales is the portion of sales from foreign operations. Capital expenditures (R&D) are capital (R&D) expenditures scaled by total assets. Year and Fama-French industry fixed effects are included. a, b and c denote significance of t values at the 1%, 5%, and 10% levels respectively.