corporate governance consequences of accounting scandals: evidence … · 2018. 10. 8. ·...

Corporate Governance Consequences ofAccounting Scandals: Evidence from Top Management,CFO and Auditor Turnover

Anup Agrawal*

Culverhouse College of CommerceUniversity of Alabama, Tuscaloosa, AL 35487-0224, [email protected]

Tommy Cooper

Culverhouse College of CommerceUniversity of Alabama, Tuscaloosa, AL 35487-0224, [email protected]

Published 30 March 2016

This paper examines the consequences of accounting scandals to top management,top ¯nancial o±cers and outside auditors. We examine a sample of 518 U.S. publiccompanies that announced earnings-decreasing restatements during the 1997–2002period and an industry-size matched sample of control ¯rms. Using logistic regres-sions that control for other determinants of management turnover, we ¯nd strongevidence of greater turnover of chief executive o±cers (CEOs), top managementand chief ¯nancial o±cers (CFOs) of restating ¯rms compared to the control sample.On average, over the three-year period surrounding the year of restatement an-nouncement, CEOs and CFOs face, respectively, a 14% and 10% greater probabilityof being replaced in restating ¯rms than in control ¯rms, after controlling for otherfactors. These represent increases of about 42% and 23%, respectively, compared tothe usual turnover probabilities for CEOs and CFOs. The magnitudes of these e®ectsare even larger for restatements that are more serious, have worse e®ects on stockprices, result in negative restated earnings, are initiated by outside parties, are ac-companied by Accounting and Auditing Enforcement Releases (AAERs), or triggersecurities class action lawsuits. We ¯nd little systematic evidence that auditorturnover is higher in restating ¯rms. Our paper provides evidence of e®ective func-tioning of internal governance mechanisms following accounting scandals.

*Corresponding author.

Quarterly Journal of FinanceVol. 7, No. 1 (2016) 1650014 (41 pages)°c World Scienti¯c Publishing Company and Midwest Finance AssociationDOI: 10.1142/S2010139216500142

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http://dx.doi.org/10.1142/S2010139216500142

Keywords: Management turnover; CFO turnover; auditor turnover; accountingscandals; earnings manipulation; earnings restatements; ¯nancial restatements.

JEL classi¯cation: G34, M43, K22.

1. Introduction

The revelations of serious accounting problems around the turn of the mil-

lennium at several prominent companies such as Enron, Worldcom, Tyco and

Healthsouth were watershed events. Following these scandals, a number of

other companies admitted to having accounting problems of their own. Most

experienced large stock price declines upon announcing that misstated ¯-

nancial reports would be restated (see, e.g., Palmrose et al., 2004; Agrawal

and Chadha, 2005). A number of companies acknowledging misstatements,

including Enron and Worldcom, were forced into bankruptcy. Many were

defendants in lawsuits ¯led by investors, customers, suppliers and employees

(see, e.g., Palmrose and Scholz, 2004).

Lawmakers have responded to these scandals by adopting the Sarbanes–

Oxley Act of 2002, whose tough corporate governance rules apply to all com-

panies with stock listed in the U.S. In addition, the New York stock exchange

(NYSE), Nasdaq, and American stock exchange (AMEX) adopted new cor-

porate governance rules as part of their listing requirements. These scandals

also resulted in signi¯cant changes in the audit industry. The Arthur Andersen

partnership dissolved after its criminal indictment on charges of obstructing

the federal investigation of the Enron scandal, and several large audit ¯rms

divested their consulting businesses to eliminate potential con°icts of interest

that could undermine their credibility as auditors.

In addition to the consequences to restating companies, these scandals can

have signi¯cant consequences to top management (i.e., the chief executive

o±cer (CEO), Chairman and President) and outside directors (see, e.g., Desai

et al., 2006; Srinivasan, 2005). However, there is yet no systematic evidence on

the consequences to the two parties closest to the ¯nancial reporting process,

namely top ¯nancial managers and external auditors. This paper attempts to

¯ll this gap in the literature. In addition, we extend Desai, et al.'s evidence on

top management turnover by examining a larger sample of restatements.

Finally, we analyze sub-samples where restatements are likely to have greater

consequences. Our study focuses on two important outcomes of the func-

tioning of internal governance mechanisms, namely management and auditor

turnover, during a time of intense corporate turmoil.

A. Agrawal & T. Cooper

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Anecdotal evidence is mixed on whether an accounting scandal leads to

greater management and auditor turnover. In certain high-pro¯le cases, top

management, the chief ¯nancial o±cer (CFO) and outside auditors all lost

their positions following the scandals. For example, Enron's CEO, Je®rey

Skilling, unexpectedly resigned in August 2001, less than three months before

the company's accounting problems were publicly revealed. Enron's CFO,

Andrew Fastow, was ousted in October 2001. Kenneth Lay, who resumed the

CEO position when Skilling left, resigned in February 2002. Enron's long-time

auditor, the Big Five accounting ¯rmArthur Andersen, dissolved after criminal

indictment. Worldcom CEO, Bernard Ebbers, resigned shortly after his ¯rm's

$3.8 billion accounting fraud became public. In addition, Worldcom ¯red its

CFO, Scott Sullivan and its auditor, ArthurAndersen. Similarly, Healthsouth's

board voted unanimously to ¯re its chairman and CEO, Richard Scrushy, less

than two weeks after the company revealed a massive accounting fraud.

Healthsouth also ¯red its CFO and its auditor, Ernst and Young. These

departures received extensive media coverage. Less known are the numerous

other scandals that did not prompt any changes inmanagement or auditors. For

example, ¯rstUSA Inc., 3Com,Boston Scienti¯c, andBausch andLomb did not

replace their CEOs, CFOs or auditors after revealing accounting problems.

As these examples show, the consequences to top management, top ¯-

nancial o±cers and external auditors of ¯rms involved in accounting scandals

can be dramatically di®erent. In this paper, we provide systematic evidence

on this issue. In doing so, we seek to shed some light on competing theoretical

arguments about these consequences.

Managerial changes entail signi¯cant costs and bene¯ts for a ¯rm. One

would expect a ¯rm to replace management if the bene¯ts exceed the costs.

Agrawal et al. (1999) discuss several reasons for greater management turn-

over in ¯rms accused of fraud. These reasons also apply to accounting

scandals. First, restating ¯rms may be more inclined to replace top man-

agement and top ¯nancial o±cers in order to regain or reestablish reputa-

tional capital that is often lost when accounting scandals occur. Second,

restating ¯rms face greater risk of securities class action lawsuits from

shareholders; replacing managers can help ¯rms limit their liability exposure

following restatements. Third, top management turnover increases following

poor stock price performance (see, e.g., Warner et al., 1988). A substantial

decline in market value upon restatement announcement can also trigger

management turnover. Fourth, along similar lines, ¯rms experiencing ¯nan-

cial distress tend to have high management turnover (see, e.g., Gilson, 1989).

Corporate Governance Consequences of Accounting Scandals

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The higher incidence of delisting or bankruptcy in restating ¯rms (see,

Palmrose and Scholz, 2004) can also lead to greater management turnover.

On the other hand, there are also reasons why an earnings restatement may

not lead to greater management turnover. First, the cost of replacing a ¯red

manager's accumulated ¯rm-speci¯c human capital may be prohibitive.

Second, the level of internal controls needed to eliminate any possibility of

accounting problems may be sub-optimal for a ¯rm. Because the direct and

indirect costs (such as lost business) of such controls may be prohibitive, the

revelation of accounting problems may not prompt the board to change

managers, unless the problems are directly linked to those individuals. Third,

while restatements generally are bad news for ¯rms, some restating ¯rms may

not lose signi¯cant reputational capital because they did not have great

reputations to begin with. In such cases, the net bene¯ts from replacing man-

agers can be small. Finally, a ¯rm's internal governance mechanisms may not

be strong enough to prompt management turnover (see, e.g., Jensen, 1993). So

even though a restatement of earnings implies that management caused, ig-

nored or failed to detect material misstatements, the restatement may not lead

to greater managerial turnover.

We also examine the e®ect of an earnings restatement on subsequent

changes in the outside auditor. As in the case of top management, there are

signi¯cant costs and bene¯ts associated with replacing the auditor. Replacing

the auditor may be bene¯cial, if the change will help the ¯rm regain its

reputational capital or limit its liability exposure. But the cost of replacing

auditors can be large. First, new auditors often face steep learning curves.

Second, the audit ¯rm also may be providing other services to the company

such as tax, computer systems or management consulting, which may have

synergies with auditing. These synergies are lost if the ¯rm replaces the

auditor. Third, the company may face a limited choice of audit ¯rms that

specialize in its industry, have the necessary scale and have o±ces near its

headquarters. Signi¯cant replacement costs may explain why auditor turn-

over is rare.

We examine a sample of 518 U.S. public companies that announced

earnings-decreasing restatements during the 1997–2002 period and an in-

dustry-size matched sample of control ¯rms. We focus on restatements an-

nounced pre-SOX. Post-SOX, a large number of companies restated to \clean

house"; consequently, these cases tend to be less serious, as evidenced by

negligible average stock price reactions to their announcements (see,

e.g., Agrawal and Cooper, 2010). We ¯nd strong evidence that restating ¯rms

have greater turnover of CEOs, top management and CFOs than control


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¯rms. The magnitudes of these e®ects are quite large. During the three-year

period (�1, þ1), restating (control) CEOs, CFOs and top managementexperience turnover rates of 53% (34%), 65% (43%), and 85% (59%), re-

spectively, where 0 is the year of restatement announcement. Using logistic

regressions that control for other determinants of management turnover over

the years (�1, þ1), CEOs, CFOs and top management of restating ¯rms facea 14%, 10% and 9% greater probability, respectively, of being replaced than

those of control ¯rms. Compared to the usual turnover probabilities in non-

restating ¯rms over this window, these represent increases of about 42%, 23%

and 20%, respectively. The magnitudes of these e®ects are even larger for

restatements that are more serious, have worse e®ects on stock prices, result

in negative restated earnings, are initiated by outside parties, are accompa-

nied by Accounting and Auditing Enforcement Releases (AAERs), or trigger

securities class action lawsuits. We ¯nd little systematic evidence that

auditor turnover is higher in restating ¯rms.

Our paper complements the literature on the consequences to managers of

enforcement actions by the U.S. Securities and Exchange Commission (SEC)

or Department of Justice (DOJ) for earnings manipulation or ¯nancial mis-

representation (see, e.g., Beneish, 1999; Karpo® et al., 2008a). As discussed

by Agrawal and Chadha (2005), most earnings misstatements di®er from

cases where regulators issue enforcement actions. Sta® and resource con-

straints prevent regulators from pursuing all cases of earnings manipulation.

To have the greatest deterrent e®ect, regulators target egregious violators

and cases likely to generate greater media coverage (see, e.g., Feroz et al.,

1991; Dechow et al., 1996; Agrawal and Chadha, 2005). While less serious

than cases warranting enforcement actions, earnings misstatements permit

larger sample sizes and avoid issues of selection by regulators. Related studies

examine the consequences to managers and directors of corporate fraud

accusations and securities class action lawsuits (see, e.g., Agrawal et al., 1999;

Niehaus and Roth, 1999; Helland, 2006; Fich and Shivdasani, 2007). Our

study also contributes to the broader literature on managerial disciplining

surrounding other times of major corporate turmoil such as bankruptcy and

corporate control events.1

1See, e.g., Gilson (1989) for bankruptcies, Martin and McConnell (1991) and Agrawal andWalkling (1994) for takeovers, DeAngelo and DeAngelo (1989) for proxy contests, and Kleinand Rosenfeld (1988) for greenmail. Related work analyzes the interaction between internaland external governance mechanisms (see, e.g., Agrawal and Knoeber, 1996; Hadlock andLumer, 1997; Mikkelson and Partch, 1997; Huson et al., 2001).


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The remainder of this paper is organized as follows. Section 2 brie°y

reviews the literature on the causes and consequences of accounting manip-

ulation, corporate fraud and other crimes. Section 3 describes our sample

and data. Section 4 presents our empirical results for the full sample, and

Section 5 reports the results for a number of sub-samples where the re-

statement may have greater e®ects. Section 6 concludes.

2. Prior Studies on the Causes and Consequences of Accounting

Manipulation and Corporate Fraud

Previous studies have examined the causes and consequences of three types of

accounting manipulations. In decreasing degrees of seriousness, these are

cases of earnings manipulation where the SEC brings enforcement action,

restatements to correct ¯nancial misstatements, and earnings management.2

Other studies have investigated a variety of corporate frauds and crimes. We

brie°y review the literature on the causes and consequences of these four

types of infractions.

2.1. Causes

2.1.1. SEC accounting enforcement actions

A seminal paper by Dechow et al. (1996) examines the motives and causes of

earnings manipulation that resulted in SEC enforcement actions. The SEC

announces these actions via AAERs. Dechow et al. ¯nd that ¯rms with weak

corporate governance are more likely to manipulate earnings to lower the cost

of external ¯nancing. Beasley (1996) also ¯nds evidence of governance

weaknesses in ¯rms subject to SEC enforcement. Beneish (1999) ¯nds evi-

dence of another motive for earnings manipulation in these ¯rms, namely

managers' desire to sell overpriced stock and option holdings. While Erickson

et al. (2006) ¯nd no consistent evidence that the likelihood of fraud in these

¯rms is related to managers' equity incentives, Johnson et al. (2009) ¯nd that

this likelihood is positively related to the size of managers' stockholdings.

2.1.2. Financial misstatements

Agrawal and Chadha (2005) ¯nd that the probability of restating earnings is

lower when boards and audit committees have ¯nancial expertise. Burns and

2See Agrawal and Chadha (2005: 373–374) for a discussion of their relative seriousness.


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Kedia (2006) ¯nd that ¯rms whose CEOs have large option holdings are more

likely to misreport. Top executives also engage in abnormally large amounts

of stock sales and option exercises during misstated periods (see, Agrawal and

Cooper, 2015; Burns and Kedia, 2008). Kedia and Philippon (2009) show

theoretically and empirically that ¯rms hire and invest excessively during

misreported periods to exaggerate their growth prospects.

2.1.3. Earnings management

Prior research ¯nds more earnings management at ¯rms with less indepen-

dent boards and audit committees (see, Klein, 2002) and in ¯rms where CEO

compensation is more closely tied to the value of stock and option holdings

(see, Bergstresser and Philippon, 2006). The latter paper also ¯nds that

during periods of high accruals, CEOs exercise unusually large amounts of

stock options, and CEOs and other insiders sell large amounts of stock.

2.1.4. Corporate fraud and other crimes

Alexander and Cohen (1999) examine a sample of 78 public companies in-

volved in corporate crimes such as contract breaches, bribes, kickbacks and

regulatory violations. They ¯nd lower incidence of crime among ¯rms where

management owns more equity. Niehaus and Roth (1999) ¯nd no evidence of

abnormal stock sales by o±cers and directors in a sample of ¯rms that settle

securities class action lawsuits. Povel et al. (2007) explain theoretically why

corporate frauds increase in good times, peak toward the end of a boom and

are revealed in the ensuing bust.

2.2. Consequences

2.2.1. SEC and DOJ enforcement actions

Dechow et al. (1996) ¯nd that ¯rms subject to SEC AAERs (see, Sec. 2.1.1)

for manipulating earnings experience signi¯cant increases in their costs of

capital. Beneish (1999) ¯nds no evidence of abnormal management turnover

in these ¯rms. Chen et al. (2005) present univariate evidence of greater CEO

and auditor turnover surrounding enforcement actions for securities fraud in

China. Karpo® et al. (2008a) examine the consequences of ¯nancial misrep-

resentation to managers of ¯rms subject to SEC and DOJ enforcement

actions under the Securities Exchange Act of 1934, as amended by the For-

eign Corrupt Practices Act of 1977. They ¯nd that about 93% of the man-

agers identi¯ed by regulators as culpable lose their jobs during the violation


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or enforcement periods; about 28% of them face criminal prosecutions and

31% are barred from serving as o±cer or director of a public company.3

Karpo® et al. (2008b) ¯nd that the reputational penalties to companies (i.e.,

the drop in market capitalization) for ¯nancial misrepresentation far exceed

the legal penalties (both private and regulatory).

2.2.2. Financial misstatements

Desai et al. (2006) examine a sample of 146 ¯rms that announce earnings

restatements during 1997–1998. They ¯nd that the top management (CEO,

Chairman and President) of these ¯rms experiences abnormally large turn-

over and diminished job prospects following restatements. Srinivasan (2005)

¯nds that outside directors of restating ¯rms experience abnormally large

turnover and loss of other board seats. This e®ect is greater for audit com-

mittee members and for more severe restatements.

Collins et al. (2009) analyze involuntary CFO turnover following an-

nouncements of earnings-decreasing restatements made by 167 ¯rms during

1997–1999 (pre-SOX sample) and 196 ¯rms during 2002–2003 (post-SOX

sample). They ¯nd that for both pre- and post-SOX restatements, the CFO

turnover rates in restating ¯rms are higher than those in control samples.

While the increase in the probability of CFO turnover is similar pre- versus

post-SOX, CFOs of restating ¯rms are penalized more severely in the labor

market post-SOX.

Leonne and Liu (2010) study CEO and CFO turnover in a sample of 96

¯rms that reveal accounting irregularities within eight years of their initial

public o®erings (IPOs), and in a control sample. They ¯nd that after newly

public ¯rms reveal accounting irregularities, the probability of CEO (CFO)

3Karpo® et al. assume that regulators know the identities of the individual perpetrators ofeach fraud and argue that event-based studies of executive turnover commit type I and typeII errors. While examining the consequences to managers charged by regulators is obviouslyof interest, the identi¯cation of individual perpetrators by regulators is not foolproof. TheSEC and DOJ have signi¯cant leverage during a formal investigation; they can threaten tocharge the entire company, a step that would seriously hurt the company's viability. Giventheir repeated dealings with regulators, companies have strong incentives to cooperateduring an investigation. A company can help railroad select perpetrators to satisfy reg-ulators and bring quick resolution to an investigation. Often, in an attempt to reduce thelegal-defense resources of identi¯ed perpetrators, regulators demand that the individuals be¯red (see, e.g., Wall Street Journal, 2007). Even if regulators identify the wrong individualsas perpetrators, the company is likely to terminate these individuals because they havebecome \damaged goods".


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turnover is lower (higher), on average, when CEOs are founders. Within their

sample of newly public ¯rms that reveal accounting irregularities, they ¯nd

an average turnover rate for founder (non-founder) CEOs of 29% (49%).

Huang and Scholz (2012) study auditor resignations during the period 2003–

2007. They ¯nd that the frequency of auditor resignations is 19% in their

sample of restating ¯rms compared to 1% in a sample of matched control ¯rms.

For a sample of 177 Canadian ¯rms that announce restatements during

the period 1997–2006, Kryzanowski and Zhang (2013) ¯nd that CEO, CFO,

top executive and auditor turnover rates subsequent to restatement

announcements are signi¯cantly higher in the sample of restating ¯rms than

in a control sample.

We add to the evidence on top management, CFO and auditor turnover by

examining a larger sample of restatements that are likely more serious. We

also examine a number of sub-samples where the restatements are likely to

have greater e®ects.

2.2.3. Earnings management

Bradshaw et al. (2001) ¯nd no evidence of greater turnover of auditors fol-

lowing higher levels of accruals. Hazarika et al. (2012) study CEO turnover

following earnings management during 1992–2004. They ¯nd that the

probability of forced CEO turnover is positively related to a ¯rm's absolute

performance-adjusted discretionary accruals in the previous year. This ¯nd-

ing persists when they control for restatements and enforcement actions.

2.2.4. Corporate fraud and other crimes

Agrawal et al. (1999) examine a sample of ¯rms facing a variety of fraud

accusations from investors, customers, suppliers, employees or governments,

regulatory violations, and 12 cases of ¯nancial reporting fraud. They ¯nd

greater turnover of inside directors, but little systematic evidence of greater

turnover of top managers and outside directors, following fraud revelations.

Niehaus and Roth (1999) ¯nd abnormally high CEO turnover in a sample of

¯rms that settle securities class action lawsuits, especially in suits with more

merit. Helland (2006) ¯nds that directors of ¯rms facing such lawsuits do

not su®er a net loss of their board seats, except for cases in the top quartile

of settlements or where the SEC initiates a case. Fich and Shivdasani (2007)

¯nd no evidence of abnormal turnover of outside directors in ¯rms facing such

lawsuits, but ¯nd a signi¯cant decline in their other board seats.


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3. Sample and Data

Section 3.1 details our sample selection procedure and describes the sample of

restating ¯rms. Section 3.2 deals with the selection of our control sample and

compares the restating and control samples. Section 3.3 describes the stock

price reaction to the restatement announcements, and Sec. 3.4 examines the

operating performance of the two samples.

3.1. Sample of restating ¯rms

Our sample of restating ¯rms is obtained from the United States General

Accounting O±ce (GAO, 2002), which lists 919 restatements of ¯nancial

statements announced by 832 publicly traded ¯rms during the period Jan-

uary 1, 1997 to June 30, 2002. These restatements correct prior misstate-

ments, i.e., violations of generally accepted accounting principles (GAAP).

Most of the restatements correct quarterly or annual ¯nancial statements

¯led with the SEC.4 The GAO database excludes routine or technical

restatements prompted by mergers and acquisitions, discontinued operations,

stock splits, accounting rule changes, and changes in accounting method. We

consider the seriousness of restatements in our sample in Sec. 5.1 below.

Table 1 summarizes our sample selection procedure. Starting with the

919 restatements in the GAO database, we omit 87 cases of repeat restate-

ments by sample ¯rms.5 In order to obtain a control sample and to construct

several control variables (see, Sec. 3.2 and 4.2 below), we require that a

restating ¯rm be listed on the Center for Research in Security Prices (CRSP)

database of the University of Chicago starting at least nine months before the

restatement announcement. We also require sample ¯rms to have at least

two-thirds of the daily stock returns available over the one-year period prior

to the announcement date. A total of 88 (¼ 47þ 13þ 5þ 23) ¯rms do notsatisfy these requirements. We omit an additional 62 cases where the

restating ¯rm is a real estate investment trust, exchange-traded fund, or is

incorporated outside of the U.S. We also omit two cases where our review of

4Fifteen cases in our sample are restatements of earnings releases and do not result in re-statement of quarterly or annual ¯nancial statements. Omitting these cases does not changeany of our results.5Our ¯nal sample of 518 restating ¯rms includes 50 ¯rms that announced multiple restate-ments during the sample period. Second and subsequent restatements by these 50 ¯rms are notincluded in our sample. Furthermore, our results are qualitatively similar when we omit these50 repeat violators from the sample.


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news reports and SEC ¯lings indicates that a misstatement did not occur.

Finally, we omit 162 cases where the restatement did not decrease net income

because auditors and investors appear to view such restatements as less se-

rious (see, e.g., Agrawal and Chadha, 2005).6 Our ¯nal sample consists of 518

¯rms that announce earnings-decreasing restatements.7,8 For each restate-

ment in our sample, we collect data on the original earnings, restated earn-

ings, and the quarters restated by reading news reports and the original and

Table 1. Sample selection.

Total Number of Restatements in GAO Database Number of FirmsExclude: 919

Repeat restatements 87Firms not listed on CRSP 47Firms delisted from CRSP more than one year before the

restatement announcement13

Firms with incomplete CRSP coverage 5Firms whose listing on CRSP began less than nine months

before the restatement announcement23

Real estate investment trusts, exchange traded funds and¯rms incorporated outside of the U.S.

62

Cases where a misstatement did not occur 2Firms whose restatements did not decrease net income 162Number of restating ¯rms in the ¯nal sample 518

Note: The table shows sample selection out of the 919 restatements listed inFinancial Statement Restatements: Trends, Market Impacts, RegulatoryResponses, and Remaining Challenges (Washington, D.C.: GAO-03-138), adatabase of restatements, announced during the period January 1, 1997 to June30, 2002, to correct GAAP violations.

6Consistent with this idea, the stock price reaction to such announcements, although statis-tically signi¯cant, is much smaller than to earnings-decreasing restatements. Over the windowof days (�1, þ1) around the announcement, the average cumulative abnormal return (CAR)for the two samples is �3.3% and �10.3%, respectively; the corresponding values over the(–20, þ1) window are �6.6% and �17.7%. Nevertheless, for completeness, we separatelyanalyze the sample of non-earnings-decreasing restatements. We ¯nd marginally signi¯cantevidence of greater CEO turnover in these ¯rms, but no evidence of greater turnover amongtop management, CFOs, top ¯nancial managers, or outside auditors. To save space, we do notpresent these results in a table.7Our sample includes 16 ¯rms that dissolved or terminated their registration with the SECafter the announcement but before any restatement.8In a few instances, a ¯rm listed in the GAO database restated its ¯nancial statements becausethe ¯nancial statements of a newly acquired subsidiary were misstated for ¯scal years orquarters ending prior to the acquisition date. In such cases, we replace the acquiring ¯rm withthe subsidiary.


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amending 10-Qs and 10-Ks ¯led with the SEC.9,10 We obtain news reports

from the ProQuest newspapers database, Lexis–Nexis news wires database,

and press releases attached to 8-Ks ¯led with the SEC. Finally, we obtain

stock prices and returns from CRSP and ¯nancial data from Compustat.

Table 2 describes our sample of 518 restating ¯rms. Panel A summarizes

the distribution of our sample by the identity of the initiator and by the

nature of accounts restated. About 79% of the restatements in our sample are

initiated by the company itself,11 and about 7% by the outside auditor. Most

of the remaining restatements are initiated by the SEC. About 63% of the

cases involve only core accounts, about 16% involve only non-core accounts,

and the remaining cases involve both.12

Panel B provides descriptive statistics of ¯rm age and the magnitude of the

change in earnings due to restatement. The median ¯rm has been listed on

CRSP (i.e., on NYSE, AMEX or Nasdaq) for about 6.5 years. The median

change in earnings13 is about �33%. The mean change is much larger, about�234%. The median ¯rm restated four quarters of earnings, and the medianlength of the misstated period is 586 days.

Panel C of Table 2 shows the distribution of the number of quarters

restated. About 20% of the sample ¯rms restate a single quarter's ¯nancial

statements (not tabulated). About 55% of the ¯rms restate four or fewer

quarters, 19% restate ¯ve to eight quarters and the remaining 26% restate

nine or more quarters. Approximately 3% of the sample ¯rms restate more

than 20 quarters.

9In several instances, news reports and SEC ¯lings indicate that the restatement was an-nounced before the announcement date listed in the GAO database. Because we use the earlierannouncement date in such cases, eight ¯rms in our sample have announcement dates prior toJanuary 1, 1997, the beginning date of the GAO database.10 In determining the beginning date of the misstated period, we take into account anyadjustments made to retained earnings for prior periods. In addition, if a ¯rm restates its¯nancials for, say, the ¯scal year ending December 2000, but the amended 10-K indicates thatthe restatement relates only to the last two quarters of the year, we de¯ne the beginning dateof the misstatement as July 1, 2000.11Following Palmrose et al. (2004), this category includes cases where the identity of theinitiator is not identi¯ed in the GAO database.12We classify as core restatements cases involving routine accounts such as sales revenue, costof sales, selling, general and administrative expenses, accounts receivable, inventory, accountspayable, and certain accrued liabilities (e.g., accrued workers' compensation expense). Weclassify cases involving non-routine accounts and one-time or special items as non-corerestatements. For restatements that a®ect income statement accounts, our de¯nition of corerestatements is very similar to that of Palmrose et al. (2004).13Change in earnings is de¯ned as (Restated earnings-Original earnings) / jOriginal earnings j.


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Tab

le2.

Frequency

distribution

anddescriptivestatistics

ofrestating¯rm

s.

Pan

elA.Frequency

distribution

a

Number

ofRestatements

Initiatedby

Total

Auditor

Com

pan

yb

Regulators

Multiple

parties

Accou

nts

Restated

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Core

325

62.7

2463

.225

061

.143

72.9

866

.7Non

-core

8516

.46

15.8

7017

.17

11.9

216

.7Mixed

108

20.8

821

.189

21.8

915

.32

16.7

Total

518

100.0

3810

0.0

409

100.0

5910

0.0

1210

0.0

Pan

elB.Descriptivestatistics

Mean

Median

Sam

ple

Size

Firm

agesince

CRSPlisting(years)

10.7

6.5

518

Original

earnings

c($million

)103.3

2.0

518

Restatedearnings

c($million

)�5

7.1

�1.0

502

Chan

gein

earnings

d(%

)�2

34.1

�32.7

502

Number

ofquarters

restated

6.3

451

8Lengthof

misstated

period(day

s)73

458

651

8


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Pan

elC.Distribution

ofnumber

ofquarters

restated

c

Number

ofRestatements

Initiatedby

Total

Auditor

Com

pan

yb

Regulators

Multiple

Parties

Number

ofQuarters

Restated

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

1–4

286

55.2

1744

.722

354

.540

67.8

650

.05–8

9618

.511

28.9

7418

.110

16.9

18.3

9–12

5811

.24

10.5

4711

.53

5.1

433

.313–16

417.9

25.3

358.6

35.1

18.3

17–20

224.2

37.9

174.2

23.4

00.0

>20

152.9

12.6

133.2

11.7

00.0

Total

518

100.0

3810

0.0

409

100.0

5910

0.0

1210

0.0

Pan

elD.Industry

distribution

f

Sam

ple

CRSPPop

ulation

Industry

(SIC

2Cod

es)

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Agriculture

(01–09

)0

015

0Mining(10–14

)10

215

43

Con

struction(15–19

)3

154

1Foo

dan

dtobacco

(20–21

)9

210

02

Textilesan

dap

parel

(22–23

)7

145

1Lumber,furniture,pap

eran

dprint(24–27

)12

214

03

Chem

icals(28)

357

365

7Petroleum,rubber,an

dplastics(29–30

)6

170

1Leather,ston

e,glass(31–32

)6

142

1

Tab

le2.

(Continued

)A. Agrawal & T. Cooper

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Tab

le2.

(Continued

)

Pan

elD.Industry

distribution

f

Sam

ple

CRSPPop

ulation

Industry

(SIC

2Cod

es)

Number

ofFirms

%of

Total

Number

ofFirms

%of

Total

Primaryan

dfabricatedmetals(33–34

)9

211

62

Machinery(35–36

)78

1567

713

Transportequipment(37)

92

832

Instruments

andmiscellan

eousman

ufacturing(38–39

)31

635

97

Transport,communications,utilities

(40–49

)40

837

97

Wholesaletrad

e(50–51

)24

420

34

Retailtrad

e(52–59

)37

733

06

Finan

ce,insurance,real

estate

(60–69

)61

1210

3320

Hotelsan

dpersonal

services

(70–71

)3

126

0Services

(72–89

)13

826

1043

20Publicad

ministrationan

dothers(90–99

)0

01

0Total

518

100

5235

100

Pan

elE.Tim

edistribution

Sam

ple

Yearof

RestatementAnnou

ncement

Number

ofFirms

%of

Total

1996

h7

1

1997

5110

1998

6112

1999

9218

2000

127

2520

0111

722

2002

6312

Total

518

100


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Note:Pan

elsA

through

Eshow

thefrequency

distribution

,descriptive

statistics,distribution

ofthenumber

ofquarters

restated,industry

dis-

tribution

,an

dtimedistribution

ofthesample,respectively.Thesample

consistsof

publicly

trad

edU.S.compan

iesthat

annou

nced

earnings-

decreasing¯nan

cial

statem

entrestatem

ents

duringtheperiodJan

uary1,

1997

toJune30

,20

02.Thelist

ofrestating¯rm

swas

obtained

from

FinancialStatemen

tRestatemen

ts:Trends,

market

impacts,

regulatory

responsesandremainingChallenges(W

ashington

,D.C.:GAO-03-13

8).

aThe

Pearson

correlation

coe±

cient

between

the

type

ofaccounts

restated

andtheidentity

oftheinitiatoris�0

.044

57,whichisindistin-

guishab

lefrom

zero

inatw

o-tailed

t-test

forstatisticalsign

i¯cance.W

etest

whether

thefrequency

ofrestatem

ents

involvingcore

accounts

ishom

ogeneousacross

thefourgrou

psof

initiators;thep-valueof

thechi-

squared

test

statisticis0.79

0.bIncludes

245caseswheretheinitiatorwas

not

identi¯ed

intheGAO

datab

ase.

cThesum

ofnet

incomeforallquarters

a®ectedbytherestatem

ent.

dDe¯ned

as(restatedearnings

–original

earnings)/

jOriginal

earningsj.

eThePearson

correlation

coe±

cientbetween

thenumber

ofquarters

restated

andtheidentity

oftheinitiatoris

�0.086

57,whichis

statisti-

callysign

i¯cantat

the5%

level

inatw

o-tailed

t-test.W

etest

whether

thefrequency

of¯rm

srestatingfouror

fewer

quarters

ishom

ogeneous

across

thefourgrou

psof

initiators;thep-valueof

thechi-squared

test

statisticis0.12

9.fThez-statisticfrom

theW

ilcoxon

sign

ed-ran

ktest

fordi®erencesin

distribution

shas

ap-valueof

0.95

5in

atw

o-tailed

test.

gIndustry

distribution

ofactiveCRSP¯rm

sas

ofDecem

ber

31,20

02.

hThese¯rm

san

nou

ncedrestatem

ents

in19

96(reportedas

1997

inthe

GAO

datab

ase).

Tab

le2.

(Continued


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Panel D shows the industry distribution of the sample based on the ¯rst

two digits of a ¯rm's primary SIC code, using Song and Walkling's (1993)

industry classi¯cation. For comparison, we also show the corresponding

distribution for the active CRSP population as of December 31, 2002. Of our

sample of 518 restating ¯rms (CRSP population), 26% (20%) are in services;

15% (13%) in machinery; 12% (20%) in ¯nance, insurance and real estate; 8%

(7%) in transport, communications and utilities; 7% (7%) in chemical in-

dustry; and 7% (6%) in retail trade. The remaining 25% (27%) of the ¯rms

are distributed over 12 (14) di®erent industries.

Panel E of Table 2 shows the distribution of the sample by the year of

restatement announcement. There is a sharp increase in the number of

restatements announced starting in 1999. The data for 2002 is for the ¯rst

half of the year. About 41% of the restatements in the sample were an-

nounced during 1996–1999, and the remaining 59% were announced during

2000–2002.

3.2. Control sample

We compare management and auditor turnover in restating ¯rms to that in a

control group. The restating and control ¯rms are matched by size and in-

dustry one year before the announcement date.14 We match each restating

¯rm with a control ¯rm that has the same two-digit primary SIC industry

code, is the closest in size, and did not announce a restatement during the

period January 1, 1995 to June 30, 2002. Size is de¯ned as the market cap-

italization of common stockholders' equity and equals the number of common

shares outstanding times the closing share price reported by CRSP on the

matching date.15 The pool of potential matching control ¯rms excludes ¯rms

incorporated outside of the U.S. Each control ¯rm is matched to a single

restating ¯rm.

Panel A of Table 3 shows characteristics of our samples of restating and

control ¯rms. All dollar values reported in the paper are in in°ation-adjusted

2005 dollars. All variables in Table 3 are measured for the last ¯scal year

ending before the restatement announcement date. The typical restating ¯rm

in our sample is relatively small compared to the typical ¯rm traded on the

14Some restating ¯rms were not listed in CRSP one year prior to the announcement date. Forthese ¯rms, the matching date is the restating ¯rm's ¯rst trading day in CRSP. We excluderestating ¯rms whose beginning date in CRSP is less than nine months before the an-nouncement date.15All publicly traded common share classes are included when calculating market capitali-zation.


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major U.S. stock markets. For the sample of restating (control) ¯rms, the

median values of total assets, net sales and number of employees are about

$236 million ($243 million), $153 million ($173 million) and 900 (1,000)

people, respectively.

The two groups of ¯rms appear to have similar growth opportunities, as

measured by the ratio of ¯rm value to total assets and the ¯ve-year sales

growth rate.16 The two groups also have similar ¯nancial leverage ratios. For

example, the median ratio of long-term debt to ¯rm value for each group is

about 7%.

Panel B of Table 3 shows certain board characteristics observed one year

before the year of announcement using the S&P Register of Corporations,

Directors and Executives. The median board consists of seven members,

about 71% of whom are outsiders in each group of ¯rms. About 65% (62%) of

the CEOs of restating (control) ¯rms chair the board.

3.3. Stock price reaction

We next examine the stock price reaction to restatement announcements. We

compute the abnormal return for stock i on day t as:

eit ¼ rit � rmt; ð1Þwhere ri and rm are the stock returns for ¯rm i and the market, respectively.

The market return is de¯ned as the return on the CRSP (i.e., NYSE, AMEX

and Nasdaq) equal-weighted stock index. The cumulative abnormal return

(CAR) for ¯rm i over days (t1, t2Þ is measured as:

CARit1;t2 ¼Xt2

t¼t1eit : ð2Þ

Table 4 shows the mean and median values of CARs for our full sample of

restating ¯rms and for a number of sub-samples over ¯ve windows covering

trading days (�1;þ1), (�5;þ1), (�5;þ5), (�20;þ1) and (�20;þ20) aroundthe announcement date (day 0). Restatement announcements have large

e®ects on stock prices. The mean CAR for restating ¯rms ranges from

�10.3% over days (�1;þ1) to as much as �20:9% over days (�20;þ20).Mean and median CARs for all ¯ve windows are signi¯cantly di®erent from

zero at the 1% level. The announcement e®ects are even more negative for the

sub-samples of more serious restatements (discussed in Sec. 5.1 below), cases

16Firm value is de¯ned as the book value of total assets minus the book value of equity plus themarket value of equity.


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where the restated earnings are negative, cases where the restatement leads

to a large drop in reported earnings (large restatements) and cases with more

restated quarters. For comparison, the abnormal returns for non-restating

¯rms (not shown in the table) are small and statistically insigni¯cant over all

¯ve windows.

Table 3. Descriptive statistics of restating and control ¯rms.

Mean MedianSample

Restate Control p-valuea Restate Control p-valueb Size

Panel A. Firm Characteristicsc

Firm size

Total assets ($million) 2796 2213 0.111 236 243 0.001 413

Net sales ($million) 2123 1539 0.048 153 173 0.132 413

Market value of equity ($million) 2885 3187 0.599 207 232 0.500 413

Firm valued ($million) 4798 4740 0.932 391 409 0.022 413

Number of employees ('000) 7.7 6.4 0.137 0.9 1.0 0.072 390

Growth

Firm value/total assets 2.26 2.43 0.322 1.41 1.48 0.068 413

Sales growthe 20.42 17.63 0.231 13.30 11.65 0.139 231

Financial leverage

Long-term debt/total assets 0.18 0.18 0.599 0.12 0.13 0.933 413

Total debt/total assets f 0.25 0.24 0.392 0.22 0.21 0.176 413

Long-term debt/¯rm value 0.14 0.13 0.432 0.07 0.07 0.375 413

Total debt/¯rm value 0.20 0.17 0.033 0.14 0.12 0.057 413

Panel B: Board Characteristicsg

Board size 7.1 7.3 0.174 7 7 0.123 518

% of outsiders on board 67.4 67.6 0.840 71.4 71.4 0.946 518

Bossh 0.65 0.62 0.250 1 1 0.250 518

Note: This table shows the mean and median values for matched samples of restating andcontrol ¯rms and tests for di®erences between the two groups. The restatement sampleconsists of 518 publicly traded U.S. ¯rms that announced earnings-decreasing restatementsduring the period January 1, 1997 to June 30, 2002, as identi¯ed by the GAO Report. Eachrestating ¯rm is matched with a control ¯rm that has the closest size (market capitalizationone year before the restatement is announced) from among all ¯rms in its industry that didnot announce, during the period January 1, 1995 to June 30, 2002, ¯nancial restatements tocorrect GAAP violations. All dollar values have been adjusted for in°ation and converted to2005 dollars.aFor the matched-pairs t-test (two-tailed).bFor the Wilcoxon signed-ranks test (two-tailed).cObserved for the last ¯scal year ending before the announcement date.dFirm value ¼ Book value of total assets – Book value of equity þ Market value of equity.eSales growth ¼ [Sales(�1) / Sales (�6)]1=5 � 1.fTotal debt equals long-term debt plus debt in current liabilities.gAs of one year before the year of announcement using the S&P Register.hEquals one if a ¯rm's CEO chairs the board; it equals zero otherwise.


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Tab

le4.

Stock

price

reaction

torestatem

entan

nou

ncements.

Day

sAroundAnnou

ncement

Means

Day

sAroundAnnou

ncement

Medians

(�1;þ

1)(�

5;þ

1)(�

5;þ

5)(�

20;þ

1)(�

20;þ

20)

(�1;þ

1)(�

5;þ

1)(�

5;þ

5)(�

20;þ

1)(�

20;þ

20)

Sam

ple

Size

Fullsample

�10:3

a�1

2:7

a�1

2:7

a�1

7:7

a�2

0:9

a�4

:9a

�6:1

a�6

:2a

�10:5

a�1

2:9

a419

Moreseriou

scases

�13:7

a�1

6:9

a�1

7:7

a�2

3:5

a�2

8:4

a�8

:8a

�9:6

a�1

0:2

a�1

7:6

a�2

2:3

a263

Positiverestated

earnings

�7:1

a�8

:5a

�9:2

a�1

2:2

a�1

5:3

a�3

:4a

�4:5

a�4

:0a

�8:3

a�1

0:0

a197

Negativerestated

earnings

�13:1

a�1

6:4

a�1

5:9

a�2

2:6

a�2

6:0

a�6

:1a

�8:2

a�9

:7a

�14:2

a�1

8:5

a222

Large

restatem

ents

�14:5

a�1

8:5

a�1

7:7

a�2

3:2

a�2

6:8

a�7

:4a

�9:9

a�1

1:5

a�1

8:5

a�1

9:6

a166

Smallrestatem

ents

�9:0

a�1

0:2

a�8

:7a

�14:1

a�1

4:3

a�4

:6a

�4:9

a�4

:4a

�9:8

a�1

1:5

a169

�4restated

quarters

�8:3

a�9

:7a

�8:8

a�1

2:4

a�1

5:0

a�3

:9a

�5:5

a�4

:8a

�7:5

a�9

:1a

235

>4restated

quarters

�12:8

a�1

6:4

a�1

7:7

a�2

4:6

a�2

8:4

a�6

:2a

�7:7

a�9

:5a

�16:0

a�2

0:8

a184

Highan

nou

ncementreturns

0.2

3:3

a8.7a

�2:6

�0:6

0.4

3.5a

5.6a

0.0

1.8

168

Low

annou

ncementreturns

�23:8

a�3

1:4

a�3

7:1

a�3

7:7

a�4

5:8

a�1

9:4

a�2

6:9

a�2

8:2

a�3

3:4

a�3

7:2

a168

Large

¯rm

s�1

0:4

a�1

2:3

a�1

2:9

a�1

7:7

a�2

1:0

a�5

:0a

�5:7

a�8

:1a

�10:5

a�1

2:4

a184

Small¯rm

s�9

:8a

�12:9

a�1

2:1

a�1

7:2

a�2

0:8

a�5

:1a

�6:9

a�6

:6a

�11:2

a�1

2:3

a151

Initiatedbythecompan

y�1

1:0

a�1

3:6

a�1

3:1

a�1

8:0

a�2

0:6

a�4

:4a

�6:1

a�5

:7a

�10:6

a�1

2:0

a332

Initiatedbyothers

�7:7

a�9

:1a

�11:3

a�1

6:9

a�2

1:9

a�5

:7a

�5:7

a�6

:8a

�10:4

a�1

7:6

a87

Lesscomplex¯rm

s�1

0:9

a�1

3:0

a�1

2:8

a�1

7:7

a�1

9:7

a�5

:2a

�6:7

a�6

:1a

�12:3

a�1

2:5

a176

Morecomplex¯rm

s�1

0:5

a�1

3:3

a�1

3:4

a�1

7:7

a�2

0:8

a�4

:3a

�6:0

a�6

:6a

�10:2

a�1

2:5

a177

Annou

ncedbeforetech

bubble

�9:5

a�1

4:2

a�1

7:8

a�2

0:7

a�2

1:8

a�4

:0a

�6:6

a�5

:3a

�10:8

a�1

2:0

a50

Annou

ncedduringtech

bubble

�14:0

a�1

6:6

a�1

6:2

a�2

3:7

a�2

5:3

a�6

:5a

�9:6

a�1

1:1

a�1

8:7

a�1

8:3

a150

Annou

ncedafter

tech

bubble

�7:9

a�9

:6a

�9:2

a�1

2:9

a�1

7:6

a�3

:8a

�4:8

a�4

:0a

�8:1

a�1

0:0

a219

Note:Thistable

show

sthemeanan

dmedianCARsof

restating¯rm

sov

er¯vewindow

ssurrou

ndingthean

nou

ncementdate.

For

each

¯rm

,the

abnormal

return

fortrad

ingday

tiscomputedbysubtractingthereturn

ontheequal-w

eigh

tedCRSP(i.e.,NYSE,Nasdaq

andAMEX)index

from

thereturn

onastockon

day

t.Bothreturnsincludedividends.

Meanan

dmedianvalues

arereportedas

percentages.

Thesub-sam

ple

ofmore

seriou

scasesexcludes

restatem

ents

that

aretriggeredbySAB10

1or

certainEIT

Fconsensuses,correctearnings

releases,or

involveon

lynon-core

accounts.Large(small)

andhigh(low)referto

thetop(bottom)40

%of

thefullsamplewhen

ranked

accordingto

thesub-sam

plecharacteristicof

interest.Restatementsize

istheab

solute

percentage

chan

gein

reportedearnings.W

euse

theCAR(�

5;þ5

)relativeto

thean

nou

ncementdate

toclassify

¯rm

sinto

thehighan

dlowan

nou

ncement-return

sub-sam

ples.Firm

size

isthemarket

valueof

equityat

thelast

¯scal

year-endbefore

the

annou

ncementdate.

Initiators

ofrestatem

ents

areidenti¯ed

usingtheGAO

datab

ase.

FollowingColes,Dan

ielan

dNav

een(200

8),weuse

factor

analysisto

measure

¯rm

complexity;thefactorsarenumber

ofbusinesssegm

ents,thenaturalloga

rithm

ofsales,an

dleverag

e,de¯ned

astotaldebt

(lon

g-term

debtplusdebtin

currentliab

ilities)

divided

bytotalassets.After

multiplyingeach

estimated

factor

load

ingbythenormalized

valueof

thecorrespon

dingfactor

observed

fora¯rm

,wesum

theproductsto

obtain

the¯rm

'sfactor

score.

More(less)

complex¯rm

shav

efactorscores

abov

e(below

)themedian.The\techbubble"istheperiodJan

uary1,

1998

toMarch

10,20

00.

aDenotes

sign

i¯cantlydi®erentfrom

zero

atthe1%

level

intw

o-tailed

tests.


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3.4. Operating performance

We next examine the operating performance of our samples of restating and

control ¯rms over the years (�3;þ3), where 0 is the ¯scal year that endsclosest to the restatement announcement date. We use two measures: oper-

ating performance to assets (OPA) and operating performance to sales

(OPS). OPA (OPS) equals operating income before depreciation as a per-

centage of a ¯rm's total assets (net sales). We compute average OPA or OPS

values over multiple years by summing a ¯rm's ratios over the relevant years

and averaging these sums across ¯rms. Table 5 shows that the median OPA

and OPS for the two groups of ¯rms are statistically indistinguishable in year

�3. Starting in year �2 (–1), the OPA (OPS) for the median restating ¯rm islower than that for its control ¯rm.17 This pattern persists until year þ2.

Table 5. Operating performance of restating and control ¯rms.

OPA OPS

Year(s) Restate Control p-Value Sample Size Restate Control p-Value Sample Size

�3 9.9 11.1 0.143 441 10.9 11.7 0.475 418�2 9.4 11.4 0.014 472 11.1 11.8 0.275 463�1 7.1 11.2 0.000 433 8.5 12.6 0.005 4260 4.5 9.7 0.000 341 6.6 11.2 0.001 337þ1 5.0 9.4 0.000 276 6.6 11.0 0.000 273þ2 5.8 10.2 0.007 225 7.3 10.7 0.003 221þ3 7.5 9.0 0.136 169 8.9 10.7 0.207 162(�3,�1) 27.9 34.1 0.041 384 30.3 35.3 0.244 364(0,þ1) 7.3 21.5 0.000 267 13.3 23.6 0.000 262(þ2,þ3) 13.5 19.1 0.143 164 17.5 19.8 0.475 158Note: The table shows the median operating performance for matched samples of restating andcontrol ¯rms and tests for di®erences between the two groups. The restatement sample con-sists of 518 publicly traded U.S. ¯rms that announced earnings-decreasing restatements duringthe period January 1, 1997 to June 30, 2002, as identi¯ed by the GAO Report. Each restating¯rm is matched with a control ¯rm that has the same two-digit SIC code and closest marketvalue of equity one year before the restating ¯rm's announcement date. The control ¯rms didnot announce restatements during the period January 1, 1995 to June 30, 2002. A sample¯rm's OPA (OPS) equals operating income before depreciation as a percentage of the ¯rm'stotal assets (net sales). OPA and OPS are calculated for seven ¯scal years beginning three¯scal years before the announcement year and ending three ¯scal years subsequent to theannouncement year. Each ¯rm's OPA or OPS percentages are summed over the applicableyears to calculate median values for multiple-year periods. P-values are for matched-pairst-tests (two-tailed) for di®erences in means or Wilcoxon signed-ranks tests (two-tailed) fordi®erences in medians.

17Young technology ¯rms with sizeable losses and minimal revenues cause mean OPS valuesto be very negative in some years.


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For example, the median OPA in year 0 for restating (control) ¯rms is 4.5%

(9.7%). These di®erences are both statistically and economically signi¯cant.

4. Management and Auditor Turnover: Full Sample Results

We discuss univariate results on management and auditor turnover in

Sec. 4.1, correlations between the variables in Sec. 4.2, and results of the

logistic regressions in Sec. 4.3.

4.1. Univariate results

Table 6 presents mean turnover rates and the percentage of ¯rms with turn-

over of management and outside auditor. The ¯rst two columns show mean

turnover rates for CEOs in matched samples of restating (R) and control (C)

¯rms. The next two columns report two-tailed p-values from matched pairs

t-tests for di®erences in means andWilcoxon signed-ranks tests for di®erences

in medians. Column 5 shows sample size. The next four sets of ¯ve columns

each show corresponding values for top management (CEO, Chairman, and

President), CFO, top ¯nancial o±cers (CFO, Controller and Treasurer), and

outside auditor. For a given year, turnover for a ¯rm equals 1 if the group of

o±cers or auditor listed in the S&P Register di®ers from the previous year's

listing; it equals 0 otherwise.18 The table shows turnover for years �1 to þ2,where 0 is the year of announcement. Turnover values for individual years are

summed to compute turnover for multi-year periods. P-values are computed

from two-tailed matched pairs t-tests for di®erences in means and Wilcoxon

signed-ranks tests for di®erences in medians.

Table 6 shows signi¯cantly greater turnover of CEOs, top management

and CFOs of restating ¯rms relative to control ¯rms in each of years 0

through þ2 and for all ¯ve multi-year periods. The magnitudes of thesedi®erences are substantial. For example, in year 0, the CEO (CFO) turnover

in restating ¯rms is 20% (27%); the corresponding rate for control ¯rms is

only 9% (11%). Over the window of years (�1;þ1), the CEO (CFO) turnoverrate in restating ¯rms is 53% (65%), while the rate for control ¯rms is only

34% (43%). There is also evidence of abnormally large turnover for the group

of top ¯nancial o±cers in restating ¯rms in years þ1, (0;þ1) and (þ1;þ2).

18In cases where a ¯rm listed in the S&P Register in the prior year is not listed in the currentyear, we attempt to identify the reason for the non-listing (e.g., name change, merger, pri-vatization, or bankruptcy) using the listings under \additional companies formerly included"in the S&P Register and by consulting the Directory of Obsolete Securities.


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Tab

le6.

Man

agem

entan

dau

ditor

turnov

erin

restatingan

dcontrol

¯rm

s.

Years

Around

CEO

Top

Man

agem

ent

CFO

Annou

ncement

Year(0)

RC

p-V

alue

oft-Test

Wilcoxon

p-V

alue

Sam

ple

Size

RC

p-V

alue

oft-Test

Wilcoxon

p-V

alue

Sam

ple

Size

RC

p-V

alue

oft-Test

Wilcoxon

p-V

alue

Sample

Size

�10.12

0.11

0.48

20.48

551

40.20

0.19

0.61

80.61

550

90.15

0.12

0.28

20.28

3491

00.20

0.09

0.00

00.00

047

90.30

0.17

0.00

00.00

047

60.27

0.11

0.00

00.00

0465

þ10.21

0.14

0.00

70.00

641

10.37

0.25

0.00

40.00

440

80.27

0.19

0.00

60.00

5391

þ20.21

0.10

0.00

00.00

034

50.33

0.21

0.00

40.00

334

20.21

0.12

0.00

50.00

5322

(�1,0)

0.33

0.20

0.00

00.00

047

50.50

0.35

0.00

10.00

147

10.42

0.22

0.00

00.00

0454

(þ1;þ2

)0.44

0.23

0.00

00.00

034

50.72

0.45

0.00

00.00

034

10.50

0.31

0.00

00.00

0320

(0,þ

1)0.41

0.23

0.00

00.00

041

10.66

0.42

0.00

00.00

040

80.53

0.31

0.00

00.00

0390

(�1,þ1

)0.53

0.34

0.00

00.00

040

70.85

0.59

0.00

00.00

040

40.65

0.43

0.00

00.00

0380

(�1,þ2

)0.75

0.43

0.00

00.00

034

21.20

0.80

0.00

00.00

033

80.87

0.54

0.00

00.00

0311


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se o

nly.

Years

Around

Top

Finan

cial

O±cers

Auditor

Annou

ncement

p-V

alue

Wilcoxon

Sam

ple

p-V

alue

Wilcoxon

Sam

ple

Year(0)

RC

oft-Test

p-V

alue

Size

RC

oft-Test

p-V

alue

Size

�10.20

0.22

0.77

00.73

311

40.06

0.04

0.19

00.19

250

70

0.31

0.20

0.14

40.17

011

80.10

0.07

0.12

80.12

947

9þ1

0.37

0.19

0.00

70.00

713

40.13

0.08

0.03

20.03

240

3þ2

0.22

0.20

0.88

70.89

493

0.10

0.07

0.18

00.18

333

3(�

1,0)

0.56

0.48

0.53

80.59

884

0.16

0.11

0.04

80.04

846

8(þ

1,þ2

)0.77

0.49

0.08

00.03

465

0.21

0.16

0.09

40.09

433

2(0,þ

1)0.81

0.49

0.00

90.01

275

0.22

0.16

0.03

40.03

340

3(�

1,þ1

)1.09

0.77

0.05

80.05

864

0.28

0.20

0.02

00.02

139

2(�

1,þ2

)1.40

1.02

0.14

30.08

647

0.36

0.27

0.03

80.03

932

5

Note:Thetableshow

smeanturnov

erratesformatched

samplesof

restating(R

)an

dcontrol

(C)¯rm

san

dtestsfordi®erencesbetweenthemeansan

dmediansof

thetw

ogrou

ps.Thesample

ofrestating

¯rm

sconsistsof

518publiclytrad

edU.S.¯rm

sthat

annou

nced

earnings-decreasingrestatem

ents

duringtheperiodJan

uary1,

1997

toJune30

,20

02.Eachrestating¯rm

ismatched

withacontrol

¯rm

that

has

thesametw

o-digitSIC

codean

dclosestmarket

valueof

equityon

eyearbeforetherestating

¯rm

'san

nou

ncementdate.Thecontrol

¯rm

sdid

not

annou

nce

restatem

ents

duringtheperiodJan

uary

1,19

95to

June30

,20

02.For

each

¯rm

,weob

serveturnov

erfor¯vegrou

ps:CEO,topman

agem

ent

(CEO,Chairm

an,an

dPresident),CFO,top

¯nan

cial

o±cers

(CFO,Con

troller,

Treasurer),an

dou

tsideau

ditor.For

agiven

year,a¯rm

'sturnov

erequalson

eifthegrou

pof

o±cers

orau

ditor

listed

intheS&PRegisterofCorporations,Directors

andExecutivesdi®ersfrom

thepreviousyear'slisting;

itequalszero

otherwise.

Turnov

eris

show

nforyears

�1to

þ2,where0is

theyearof

annou

ncement.

Turnov

ervalues

forindividual

years

aresummed

tocompute

turnov

erformultiple-yearperiods.

P-values

arefrom

two-tailed

matched-pairs

t-testsfordi®erencesin

meansan

dW

ilcoxon

sign

edrank

testsfordi®erencesin

medians.

Tab

le6.

(Continued


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The table also shows abnormally large turnover rates for the outside auditors

of restating ¯rms in year þ1 and in several multi-year periods.

4.2. Correlations

We next examine Pearson correlation coe±cients (not tabulated for brevity)

for management and auditor turnover and explanatory variables. RESTATE

is a dummy variable equal to 1 if the ¯rm is a restating ¯rm; it equals 0

otherwise. LSALES is the natural logarithm of net sales. V/A equals ¯rm

value divided by total assets. D/A equals total debt divided by total assets.

OUTSIDER equals the number of outside directors divided by board size.

BOSS equals 1 if the CEO chairs the board; it equals 0 otherwise. Data

availability reduces the sample size to 600 ¯rms (i.e., 300 matched pairs).

We ¯nd several noteworthy relations. First, consistent with the univariate

results in Table 6, the turnover of CEOs, top management and CFOs over

several time windows is positively related to the RESTATE variable. Second,

CEO and top management turnover are lower when the CEO chairs the

board. This is not surprising, given that a CEO-Chairman wields more power.

Third, the turnover of CFOs is positively related to the turnover of both

CEOs and auditors. The positive correlation between CFO and CEO turn-

over is consistent with Mian (2001). The positive correlation between the

turnover of CFOs and auditors suggests that their fortunes are linked in the

aftermath of a restatement. Fourth, larger ¯rms (LSALES) have higher debt

ratios (D/A), consistent with higher debt capacity and greater access to

public debt markets. Finally, larger ¯rms have larger boards, with a higher

proportion of outside directors. The positive relation between ¯rm size and

board size is consistent with the notion that larger ¯rms are more complex

and so need more expertise on the board, requiring more board members (see,

e.g., Agrawal and Knoeber, 1996). The positive relation between ¯rm size and

the proportion of outsiders on the board is consistent with the greater pres-

sure during our sample period on large public ¯rms to have more independent

boards (see, e.g., NYSE and Nasdaq, 1999). All of these relations are sta-

tistically signi¯cant at the 5% level in two-tailed tests.

4.3. Cross-sectional regressions

We next examine whether management and auditor turnover following the

revelation of accounting problems is higher than control ¯rms, after con-

trolling for other determinants of the level of turnover. We discuss the


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Tab

le7.

Log

isticregression

s.

DependentVariable:Turnov

er

CEO

Top

Man

agem

ent

CFO

Top

Finan

cial

O±cers

Auditor

IndependentVariable

dy/dx

zdy/dx

zdy/dx

zdy/dx

zdy/dx

z

Pan

elA:(�

1;þ

1)

RESTATE

0.137

3.40

a0.092

2.13

b0.095

2.26

b0.109

0.89

0.048

1.42

OUTSID

ER

0.024

1.97

b0.031

2.35

b�0

.001

�0.05

0.035

1.02

�0.019

�1.97b

BDSIZE

�0.065

�0.81

�0.176

�2.01b

�0.009

�0.11

0.119

0.60

0.095

1.50

BOSS

�2.035

�4.94a

�0.711

�1.40

0.267

0.62

0.521

0.44

0.456

1.33

NUMTOPMGR

2.710

5.67

a

NUMTOPFIN

MGR

0.464

0.53

CAR(�

5,þ5

)�0

.019

�2.00b

�0.027

�2.46b

�0.010

�0.97

0.053

1.95

c�0

.014

�1.87c

LSALES

0.188

1.42

0.351

2.42

b0.365

2.64

a0.183

0.52

�0.133

�1.21

V/A

�0.067

�0.71

�0.053

�0.56

�0.026

�0.26

0.110

0.55

�0.036

�0.35

OPA

�0.028

�2.60a

�0.029

�2.30b

�0.018

�1.50

�0.054

�1.10

�0.004

�0.74

D/A

�0.658

�0.55

�0.857

�0.67

�0.524

�0.44

1.814

0.49

1.312

1.29

LAGE

�0.040

�0.18

�0.169

�0.75

�0.507

�2.29b

�0.327

�0.54

0.092

0.50

Con

stan

t�0

.92

�1.86c

�2.40

�3.84a

�0.22

�0.46

�1.52

�1.08

�1.20

�2.09b

Number

ofob

servations

666

658

630

100

648

p-valued

0.0000

0.0000

0.0166

0.5931

0.1060

PseudoR-squared

0.0615

0.0939

0.0267

0.0812

0.0223

%"i

nturnov

erprobab

ilitye

41.9

20.4

23.4

19.7

24.2

Pan

elB:Allsample

periods


er

Sam

ple

PeriodRelative

CEO

Top

Man

agem

ent

CFO

Top

Finan

cial

O±cers

Auditor

toAnnou

ncementYear0

dy/dx

z%

"inprob.e

dy/dx

z%"i

nprob.e

dy/dx

z%

"inprob.e

dy/dx

z%"i

nprob.e

dy/dx

z%"i

nprob.e

(�1,

0)0.108

3.27

a59.2

0.089

2.34

b32.4

0.110

3.13

a48.7

�0.069

�0.67

�16.9

0.025

1.02

23.0

(þ1;þ

2)0.129

3.24

a54.3

0.094

2.14

b26.4

0.125

2.91

a41.1

0.231

1.92

c73.2

0.023

0.69

13.5

(0;þ

1)0.137

3.72

a57.6

0.106

2.59

a31.0

0.121

3.02

a39.4

0.193

1.64

47.2

0.045

1.45

28.0


1650014-26

Qua

rt. J

. of

Fin.

Dow

nloa

ded

from

ww

w.w

orld

scie

ntif

ic.c

omby

UN

IVE

RSI

TY

OF

AL

AB

AM

A o

n 02

/03/

17. F

or p

erso

nal u

se o

nly.

Tab

le7.

(Continued

)

Pan

elB:Allsample

periods


er

Sam

ple

PeriodRelative

CEO

Top

Man

agem

ent

CFO

Top

Finan

cial

O±cers

Auditor

toAnnou

ncementYear0

dy/dx

z%

"inprob.e

dy/dx

z%"i

nprob.e

dy/dx

z%

"inprob.e

dy/dx

z%"i

nprob.e

dy/dx

z%"i

nprob.e

(�1,þ1

)0.137

3.40

a41.9

0.092

2.13

b20.4

0.095

2.26

b23.4

0.109

0.89

19.7

0.048

1.42

24.2

(�1,þ2

)0.158

3.60

a38.0

0.081

1.82

c14.0

0.127

2.84

a25.8

0.131

0.95

19.9

0.037

0.94

14.1

Note:Thetableshow

smarginal

e®ects

(dy/d

x)an

dtheirz-statistics

from

logisticregression

sof

turnov

eron

several

explanatoryvariables.The

sample

consistsof

publiclytrad

edU.S.¯rm

sthat

annou

nce

earnings-decreasingrestatem

ents

during19

97–20

02,an

dindustry-sizematched

control

¯rm

sthat

donot

annou

nce

restatem

ents

duringthisperiod.Pan

elA

show

sregression

resultsforthesampleperiod(�

1;þ1

),where0is

theyearof

therestatem

entan

nou

ncement.

Pan

elB

show

sregression

resultsforallsample

periods:

(�1;0),(þ

1;þ2

),(0;þ

1),(�

1;þ1

)and

(�1;þ2

).Tosavespace,

Pan

elB

only

reports

themarginal

e®ects

(dy/d

x)of

RESTATE,theirz-statistics,an

dthepercentage

increasesin

turnov

erprobab

ilitydueto

restatem

ent.TURNOVERequalson

eiftherewerean

yo±

ceror

auditor

chan

gesduringthesampleperiodaccording

totheS&PRegisterofCorporations,

Directors

andExecutives;itequalszero

otherwise.

RESTATEisabinaryvariable

that

equalsonefora

restating¯rm

;itequalszero

otherwise.Boa

rddataareob

tained

from

theS&PRegisterfortheyearbeforethean

nou

ncementyear.OUTSID

ER

equalsthenumber

ofou

tsidedirectors

divided

byBDSIZE,thenumber

ofdirectors

ontheboa

rd.BOSSequalson

eiftheCEO

chairs

theboard;

itequalszero

otherwise.

NUMTOPMGR

equalsthenumber

ofpersonsholdingthetitles

CEO,Chairm

anof

theboa

rd,President,

orchief

operatingo±

cer(C

OO)in

theyearbeforethebeginningof

theturnov

erperiod.NUMTOPFIN

MGR

equalsthenumber

ofpersonsin

theyear

beforethebeginningof

theturnov

erperiodthat

holdthetitles

CFO,Con

troller,Treasurer,or

vicepresident(V

P)of

¯nan

ce,includingexecutive

orseniorVPsof

¯nan

ce.C

AR(�

5;þ5

)istheCARov

erday

s(�

5;þ5

),whereday

0isthean

nou

ncementday

.Finan

cialdataareob

served

forthe

last

¯scal

yearendingbeforethean

nou

ncementyear.LSALESisthenaturalloga

rithm

ofnet

sales.OPA,V/A

andD/A

areop

eratingincome

beforedepreciation,¯rm

valuean

dtotaldebt,respectively,divided

bytotalyear-endassets.Firm

valueequalstotalassets

minusthebookvalue

ofequityplusthemarket

valueofequity.Total

debtequalslong-term

debtplusdebtin

currentliab

ilities.LAGEisthenaturalloga

rithm

ofone

plus¯rm

age.W

ede¯ne¯rm

ageas

thenumber

ofmon

thsfrom

a¯rm

'sstartdatein

CRSPto

thean

nou

ncementdateof

the¯rm

'srestatement.

Alldollarvalues

hav

ebeenad

justed

forin°ationan

dconvertedto

2005

dollars.Reportedmarginal

e®ects

hav

ebeenmultiplied

by10forall

explanatoryvariablesexceptRESTATE.Teststatistics

arecomputedusingarobust

variance

estimator.

a;b;cDenotestatisticalsign

i¯cance

atthe1%

,5%

and10

%levels,respectively,in

two-tailed

tests.

dOfthechi-squared

test.

eThepercentage

increase

inthe

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