Market Reaction to Events Surrounding the Sarbanes-Oxley Act of 2002:
Impact as a Function of Extent of Earnings Management and Effectiveness of
Audit Committees
Haidan Li
Assistant Professor of Accounting
Tippie College of Business
University of Iowa
Morton Pincus*
Carlson-KPMG Professor of Accounting
Tippie College of Business
University of Iowa
and
Sonja Olhoft Rego
Assistant Professor of Accounting
Tippie College of Business
University of Iowa
First Draft: November 10, 2003
* Corresponding Author: 108 PBB, University of Iowa, Iowa City, IA 52242-1000
319-335-0910 morton-pincus@uiowa.edu
We thank Steve Zeff for his comments.
Market Reaction to Events Surrounding the Sarbanes-Oxley Act of 2002:
Impact as a Function of Extent of Earnings Management and Effectiveness of
Audit Committees
Abstract: A primary purpose of the Sarbanes-Oxley Act of 2002 is to improve the accuracy and
reliability of corporate financial reports. However, questions have been raised as to the extent of
substantive reform in, and thus the impact of, the Act. We investigate this by developing an
event history of Sarbanes-Oxley and then conducting an event study to infer the likely impact of
the Act as reflected in shareholder wealth effects. We find that firms that manage earnings
downward are more likely to be impacted by Sarbanes-Oxley than firms that manage income
upwards. If income-increasing firms were the type of firms the Act primarily sought to
constrain, then our results suggest that the capital market does not anticipate the Act will bring
about the expected benefits of improved accuracy and reliability of financial reports for such
firms.
Market Reaction to Events Surrounding the Sarbanes-Oxley Act of 2002:
Impact as a Function of Extent of Earnings Management and Effectiveness of
Audit Committees
1. Overview
Declaring that “The era of low standards and false profits is over” (Bumiller [July 31,
2002]), President Bush signed the Sarbanes-Oxley Act into law July 30, 2002, describing it as
incorporating the “most far-reaching reforms of American business practices” since the Great
depression (Hill [July 31, 2002]). Congress had passed the Act with unexpected swiftness,
spurred by the seemingly ever-growing list of corporate scandals at the time, including Enron,
Arthur Andersen, Adelphia, Tyco, and WorldCom.1 The Act was seen as addressing systemic
and structural weaknesses affecting the capital markets that had been revealed by repeated
failures of audit effectiveness and corporate financial (as well as broker-dealer) responsibilities
(Hamilton and Trautmann [2002, ¶2001]). The preamble of the Act states its purpose: “To
protect investors by improving the accuracy and reliability of corporate disclosures made
pursuant to the securities laws, and for other purposes” (Hamilton and Trautmann [2002, 87]).
The major accounting and auditing provisions in Sarbanes-Oxley require the
establishment of the Public Company Accounting Oversight Board, require independent audit
committee members, prohibit accounting firms from performing certain non-audit services for an
audit client, require rotation of audit partners every five years, require CEO and CFO
certification of financial statements, and impose criminal penalties for knowingly certifying
financial reports that fail to comport with the requirements of the Act. Sarbanes-Oxley further
“The stock market awakened in 2002 to discover that it no longer had numbers it could trust” (Bratton [2003, 1];
Morgenson [2002]).
1
1
states that financial statements filed with the Securities and Exchange Commission (S.E.C.) will
be reviewed by the S.E.C. at least once every three years.
In this paper we estimate the shareholder wealth effects associated with the SarbanesOxley Act of 2002 to infer the capital market’s assessment of the expected impact of the Act. 2 In
particular, we compare stock price effects (1) of firms that likely managed their reported
earnings prior to passage of Sarbanes-Oxley with firms that were not earnings managers, and (2)
of firms that had effective audit committees versus those that did not. We focus on earnings
management and audit committee effectiveness (specifically, the independence of audit
committee members) since Sarbanes-Oxley seeks to strengthen the role of audit committees with
regard to external financial reporting and to reduce earnings management. Our research is
important because it provides evidence of the expected impact of the Act, and thus the results
should be of interest to legislators and regulators, as well as researchers, in assessing the
expected net benefits achieved or costs imposed by the legislation.
Several legal commentaries have analyzed the expected effectiveness of Sarbanes-Oxley.
For example, Cunningham [2003], Perino [2002], and Ribstein [2002] discuss the main
provisions of the Act, and each author argues that the new criminal liability provisions
criminalize very little conduct that was not already criminal under existing statutes, and that the
legislation contains more rhetoric than corporate reform. Perino [2002, 2-3] asserts that “as the
political firestorm increased and the Dow Jones Average plunged, there was clearly a sense in
Washington that Congress had to do something (anything) and do it fast.”3
2
See Bhagat and Romano [2002] for a recent review of the application of the event study methodology to corporate
law and corporate governance issues.
3
Also see Gordon [2003] and Bainbridge and Johnson [2003]. Bhattacharya et al. [2002] empirically examine a
provision of Sarbanes-Oxley the S.E.C. had earlier required, specifically, that CEOs and CFOs certify their
companies’ financial statements, to investigate whether the deadline for CEO/CFO certifications was ‘an event’ date
for certifiers and non-certifiers alike. They find that abnormal stock returns of firms for which the CEO and CFO
were unable to certify the financial representations of their firms were not statistically different from those of
2
In contrast, Brickey [2003] argues that Sarbanes-Oxley expands statutory prohibitions
against fraud and obstruction of justice, increases criminal penalties, and strengthens sentencing
guidelines. In addition, during the legislative process and also after passage of the Act in
connection with the appointment of the chair of the new accounting oversight board, news
reports indicate considerable opposition to the Act’s reforms by the American Institute of
Certified Public Accountants and four of the Big 5 public accounting firms (Review and Outlook
[2002]; Schroeder [October 25, 2002]). Because lobbying is a costly activity, it is reasonable to
assume that affected parties will lobby only when they perceive that the expected benefits of
changing proposed legislation or regulations make it worth their while to incur the costs of
lobbying. The lobbying surrounding Sarbanes-Oxley suggests that the legislation and its
implementation were seen by at least some affected parties as likely having a significant impact.
If Sarbanes-Oxley contains substantive reforms to constrain earnings management
activities and to enhance audit committee effectiveness, then it should impact certain firms
differently from others. In particular, we expect that firms that manage earnings (relative to nonearnings managing firms) and firms with ineffective audit committees (versus those with
effective audit committees) will be affected more by the Act, and these differences should be
reflected in differing share price effects to critical events surrounding the Act.
Shareholder wealth effects induced by the events surrounding Sarbanes-Oxley will reflect
a netting of the expected benefits and costs of the Act. Consider, for example, companies that
managed earnings. (A similar discussion applies to firms that had ineffective audit committees.)
If the Act enhances the accuracy and reliability of financial reports, then we expect the financial
reports of firms that were earnings managers will show a greater improvement in the accuracy
and reliability of their financial information vis-à-vis the financial reports of non-earnings
‘certifying’ firms, and conclude the CEO/CFO certification requirement did not alter the market’s ability to
differentiate between these two types of firms.
3
managing firms. If capital market participants had previously identified firms that likely were
earnings managers and discounted their share prices as a result, and if Sarbanes-Oxley was
expected to improve the accuracy and reliability of information in such firms’ financial reports,
then we would expect positive share price reactions for these firms to events that (1) increased
the probability of passage of the legislation and/or (2) increased the extent of financial reporting
reforms contained in the new law; i.e., these would be good news events.
On the other hand, firms that previously had been earnings managers would have to bear
greater costs of implementing the reforms than firms whose financial reports reflected little
earning management. Earnings managers would have to change their accounting policies and
reporting strategies from what presumably had been optimal for them prior to Sarbanes-Oxley,
and thus they would incur financial reporting costs. These costs would include out-of-pocket
costs from changing accounting and reporting policies, plus opportunity costs from changing
decisions and activities under the new accounting and reporting policies from what they would
have been under the previous policies. Hence, if Sarbanes-Oxley constrained managers’ ability
to manage earnings, then these firms would incur greater contracting or political costs to the
extent, for example, that managers could no longer manage earnings to increase slack in debt
covenant provisions, or to achieve desired compensation levels, or to lower income to minimize
the likelihood of governmental expropriation. Moreover, constraints imposed by the Act could
restrict managers’ ability to communicate private information to investors through earnings. We
expect the total of all such costs to be greater for earnings managers vis-à-vis non-earnings
managers, and that events that increased the probability of passage of the Act and/or increased
the Act’s scope of reform could generate negative share price effects for earnings managers.
While we expect the shareholder wealth effects to differ for earnings managers compared
to non-earnings managing firms, and also for firms with ineffective audit committees relative to
4
firms with effective audit committees, it is difficult to know a priori the relative magnitude of
the benefits and costs of Sarbanes Oxley, and thus what the net shareholder wealth effects will
be. First, it is unlikely that shareholders of firms that managed earnings, or of firms with
ineffective audit committees, will garner all of the benefits of the enhanced information quality
that could be expected from implementation of the Act. Non-shareholders would also reap the
benefits of more accurate and reliable information due to the public goods nature of publicly
reported information. Second, it is unclear whether shareholders of firms that managed earnings
or had ineffective audit committees will bear the total costs imposed by the Act. Depending on a
firm’s power in various markets, some portion of the costs might be borne by employees through
lower compensation, by vendors through lower prices, or by customers through higher prices.4
Finally, it is likely that Sarbanes-Oxley will impose costs on all firms (Henry and Borrus
[2003], for example, to implement the internal reviews needed to gain the external certification
of internal controls mandated by Section 404 of the Act. Thus, it is unclear whether the
additional costs that we expect the Act to impose on earnings managers and firms with
ineffective audit committees will be viewed in expectation by the capital market as significantly
greater in magnitude than the costs the average firm will bear, and thus whether we can detect
differences in share price changes when comparing earnings managers with non-earnings
managers and firms with ineffective versus effective audit committees.
Table 1 summarizes the above discussion of shareholder wealth effects. We expect the
same kinds of benefits and costs to be netted for firms that are earnings managers versus nonearnings managers and for firms with ineffective versus effective audit committees, with one
exception. When audit committees become more effective, it is not necessarily the case that
4
Further complicating any prediction of the net effects is that legislative outcomes are endogenous. As previously
noted, parties facing expected costs (or benefits) from the passage of pending legislation or regulations have
incentives to engage in lobbying activities to affect the legislative or regulatory outcomes (Ball [1972]; [1980]).
5
managers become less able to communicate private information to investors though earnings,
which contrasts to what is more likely to occur when firms are constrained in their ability to
manage earnings.
Our results indicate that events surrounding the Sarbanes-Oxley legislation affected
downward-earnings managers (denoted Low EM firms) differently than firms having
performance-adjusted abnormal accruals of approximately zero (denoted Medium EM firms),
even after controlling for firm characteristics such as size and book-to-market. Specifically, Low
EM firms initially experienced significantly greater abnormal returns than the Medium EM
sample, with the significant differences in abnormal returns spanning a set of events that began
with the initial revelations of fraud at WorldCom. That event was seen as a turning point in the
Sarbanes-Oxley legislative process, as it gave momentum to supporters of substantial accounting
reform and seemingly represented the beginning of a sharp climb in the probability that reform
legislation would become law. This result is consistent with the capital market expecting that
firms that were income-decreasing earnings managers would benefit from the passage of
earnings management reform legislation. There is only limited evidence that High EM firms
(i.e., those with large positive performance-adjusted abnormal accruals) had larger abnormal
returns than Medium EM firms in this period, which is thus inconsistent with the capital market
expecting significant benefits of improved accuracy and reliability of reported financial
statement information for firms that were income-increasing earnings managers.
Both Low and High EM firms subsequently experienced significantly lower abnormal
returns than Medium EM firms at the time the bill was signed into law or immediately thereafter.
This evidence of negative abnormal returns comes after it became public knowledge that the law
contained the more substantive of the range of reforms that Congress had been considering, and
is thus consistent with the capital market expecting that the reforms contained in the final version
6
of the Act would impose greater costs on both income-increasing and income-decreasing
earnings managers that had been anticipated. We find mixed results overall in our analysis of the
audit committee effectiveness provisions of the Act.
The results suggest that firms that manage earnings downward are more likely to be
impacted by Sarbanes-Oxley than firms that manage income upwards. To the extent that
Congress intended the Act to curb aggressive financial reporting by income-increasing earnings
managers, then our results suggest that the market does not anticipate Sarbanes-Oxley as
bringing about the expected benefits of improved accuracy and reliability in the financial reports
of such firms.
We organize the remainder of this paper as follows. In the next section we develop an
event history of Sarbanes-Oxley. Section 3 describes our seemingly unrelated regression
methodology and results, and Section 4 describes our Sefcik-Thompson methodology and
results. We conclude in Section 5.
2. Event History of the Sarbanes-Oxley Act of 2002
In this section we identify the critical events surrounding passage of the Sarbanes-Oxley
Act of 2002, which we summarize in Table 2. We base the event history on a legislative history
of the Sarbanes-Oxley Act (Hamilton and Trautmann [2002]), the Library of Congress’s Bill
Summary & Status for the 107th Congress, articles in The Wall Street Journal and The New York
Times (obtained using the Factiva and Lexis-Nexis data bases), and various other sources.
In response to what he called the “Enron situation,” S.E.C. Chairman Harvey Pitt issued a
public statement January 17, 2002 calling for improvements in disclosure and financial reporting
to produce a better regulatory system. The main component of his proposal was the creation of a
public accounting regulatory body that would not be dominated by the accounting industry.
7
A February 2002 news report indicated that, unexpectedly, legislation emanating from
Rep. Michael Oxley’s Financial Services Committee would soon be introduced in the House of
Representatives (Schroeder [February 12, 2003]), and in fact the “Corporate and Auditing
Accountability, Responsibility, and Transparency Act of 2002” (H.R. 3763) was introduced
February 14, 2002 (Oppel [2002]; Schroeder [April 14, 2003]). H.R. 3763 was seen as
strengthening auditor independence and included a call for a public accounting regulatory board,
similar to Chairman Pitt’s proposal. In the Senate, Sen. Christopher Dodd introduced Senate bill
S. 2004 on March 8th. It, too, was aimed at improvements in financial reporting and included an
independent oversight board for auditors, and it also sought to enhance the accounting standard
setting process and increase the resources provided to the S.E.C.5
In April 2002, The Wall Street Journal reported (Business and Finance [April 22nd,
2002]) that Paul Volcker, the former Federal Reserve Chairman who had been appointed to head
an internal oversight board at Arthur Andersen with broad authority to mandate changes in its
business practices, was likely to abandon his efforts to institute significant reforms at Andersen.
The reforms that had been considered would have turned Andersen into a strictly auditing firm,
and were seen by some as a new model for the auditing profession. It was reported that the other
Big 5 accounting firms along with the AICPA opposed such extensive reforms (Volcker [May
21, 2002]; Review and Outlook [April 23, 2002]). Dropping the proposed changes at Andersen
may have been seen as a loss of whatever momentum existed in the push for substantive change
within the profession, and perhaps more generally as a loss in momentum for reform legislation.
However, at almost the same time (April 22nd), the House Financial Services Committee
issued a report on H.R. 3763, stating that the bill would improve the accuracy and reliability of
5
In the wake of the Enron collapse, a number of bills had been proposed in the Senate, mostly by Democrats, that
reflected a backing away from deregulation of the financial community (Schroeder and Bryan-Low [January 29,
2002]). Our review indicates that Sen. Dodd’s bill was the first Senate bill that reflected potentially significant
changes regarding the quality of financial reporting (Library of Congress [2002]).
8
financial disclosures made pursuant to the securities laws (Hamilton and Trautmann [2002]).
The House considered H.R. 3763 on April 24th and passed it on a 334 to 90 vote. The Wall
Street Journal described the bill as a “moderate” overhaul of accounting oversight and corporate
financial reporting (Schroeder [April 25, 2002]), while The New York Times quoted Democratic
leaders who attacked the bill as “toothless” (Oppel [April 25, 2002]). On April 25th, the Senate
Judiciary Committee approved proposed legislation that would create felony charges for
securities fraud and for shredding or mishandling documents (Anderson [April 26, 2002]).
No further action occurred with regard to reform proposals that had been introduced in
the Senate. However, the WSJ reported in mid-June that Sen. Paul Sarbanes, who chaired the
Senate Banking Committee, had made significant progress toward developing a consensus
proposal for major overhaul of accounting practices (Hitt [June 11, 2002]), and a Banking
Committee Press Release [June 12, 2002] announced that the Committee would meet to mark-up
the “Public Company Accounting Reform and Investor Protection Act of 2002” (S. 2673) on
June 18th. Still, it was expected there would be a strictly party line vote on the so-called
“Sarbanes bill” in the Banking Committee, followed by a filibuster against the bill on the Senate
floor. Moreover, even if the legislation overcame these hurdles in the Senate, it would have to be
reconciled with the less-stringent House bill. Sen. Sarbanes had apparently lined up support
primarily among Democrats, but had made little progress in gaining support from Sen. Phil
Gramm, the senior Republican on the Banking Committee (Murray [June 11, 2002]). Without
key Republican support, the Sarbanes bill was seen as having little chance of passing in the
narrowly divided Senate in 2002.
On Saturday, June 15th, a jury convicted the firm of Arthur Andersen of obstructing the
S.E.C.’s investigation of Enron’s collapse. This decision was seen as adding to the drive for
legislative reform of accounting (Weil et al. June 17, 2002).
9
The Senate Banking Committee met June 18th, as scheduled, and in what was described
as “a bipartisan rebuke to the scandal-plagued accounting industry,” the Committee on a 17 to 4
vote approved legislation that would create an accounting oversight board, limit audit firms’
consulting work, and discipline wayward auditors (Schroeder and Hamburger [July 19, 2002]).6
The news report also stated that the Committee’s action made “it virtually certain” that public
accounting would face new regulatory scrutiny by year-end. Sen. Sarbanes introduced S. 2673
in the Senate June 25th.
On June 26th, revelations of extensive fraud at WorldCom were reported, and this seems
to have changed the political environment overnight (Oppel and Lebaton [June 27, 2002];
Hamburger et al. [June 27, 2002]).7 While the financial reporting aspects of the Enron debacle
might have been seen as reflecting complex transactions and arcane accounting rules, WorldCom
appeared quite simply to be out-and-out fraud; expenses totaling $3.8 billion allegedly had been
reported as capital expenditures (Sandberg et al. [June 26, 2002]). President Bush called the
disclosures “outrageous” and vowed to hold people accountable for accounting scandals
(Dreazen [June 27, 2002]; Romero [June 27, 2002]). Within hours of the President’s comments,
the S.E.C. filed a civil lawsuit against WorldCom alleging a fraudulent scheme to overstate
earnings (Dreazen [June 27, 2002]).8
The Senate Banking Committee issued its report on the Sarbanes bill July 3rd, and the
entire Senate considered S. 2673 beginning July 8th, with news reports saying that passage was
virtually assured (Freeman [July 8, 2002]; Murray and McKinnon [July 11, 2002]). On July 9th,
President Bush went to Wall Street and spoke in support of securities law reform. Some viewed
6
Note the lack of audit committee reforms in this legislation.
Unfavorable reports about WorldCom’s operations and accounting issues had previously been in the news. For
example, WorldCom took action against employees in an order-booking scandal (WSJ [February 15, 2002]), and
sought to reassure investors after reporting first-quarter declines in earnings and revenue (Business Digest [April 26,
2002]).
8
The S.E.C. had already been investigating WorldCom (Young [June 25, 2002]).
7
10
his proposals as simply tinkering with things the S.E.C. had already done or proposed (Kulish
[July 10, 2002]; NYT [July 10, 2002]), while others argued the President had admitted that
financial reporting, corporate governance, and Wall Street practices had been corrupted and were
in need of repair, and that the President now supported a long list of reforms (Business Week
Editorial [July 22, 2002]).9
The Senate unanimously passed S. 2673 on a vote of 97 to zero July 15th.10 On the same
day, the “Corporate Fraud Accountability Act of 2002” (H.R. 5118) was introduced in the
House. It required certification of financial statements by top executives and imposed criminal
penalties for misrepresentation of financial reports that exceeded those in S. 2673 (Murray [July
17, 2002]). The Republican-controlled House passed H.R. 5118 on a 391 to 28 vote July 16th. A
news report described the vote as a “deft move” by House Republican leaders in that Republican
members could now return to their districts during Congress’s August break and brag they had
gone further than the Democratic-controlled Senate in punishing “corporate crooks” (Murray
[July 17, 2002]). Also on July 16th, the Senate Appropriations Committee approved a record
$750 million budget for the S.E.C., which was only slightly less than the funding amount
included in the Sarbanes bill. In addition, President Bush demanded that a final bill be passed
before Congress left for the August recess. This was said to undercut efforts by some Senate
Republicans to stall in the hope of modifying the legislation, but it was also reported as being
positively received by rank-and-file Republicans worried that any delay would hurt them in the
upcoming November elections (Murray [July 17, 2002]; [July 18, 2002]).
On July 21st, in the face of a sever cash squeeze, WorldCom filed for bankruptcy
(Sandberg et al. [July 19, 2002]; Young et al. [July 22, 2002]).
Stock prices in general dropped after Mr. Bush’s speech (Browning [July 10, 2002]).
Some felt that S. 2673 failed to eliminate the overwhelming incentive that external auditors have to please their
clients (Lee [July 10, 2002]), and it did not include action on stock options (Murray [July 16, 2002]).
9
10
11
A House-Senate Conference Committee, formed to reconcile the House and Senate bills,
issued its report July 24th. Prior to the issuance of the Conference Committee’s report, there had
been discussions in the press about various aspects of the House and Senate bills the Conference
was considering, but we find no articles that reflect leaks from the Conference Committee as to
what provisions a final bill would contain (Editorial [July 22, 2002]; Walczak et al. [July 22,
2002]; Coyle [July 24, 2002]; Farrell [July 25, 2002]). The actual provisions of the Conference
Committee’s bill, now referred to as the “Sarbanes-Oxley Act of 2002,” largely reflected the
more extensive reforms included in the Sarbanes bill (Hamilton and Trautmann [2002]; Oppel
[July 25, 2002]), however some changes had been made. These changes increased S.E.C. control
of the new Public Company Accounting Oversight Board (PCAOB). The Conference’s bill also
included the House’s tougher punishments of executives, although these criminal penalties
would now apply only to chief executive and chief financial officers; non-executive board chairs
were excluded (Economist.com [July 25, 2002]; Oppel [July 25, 2002]). The Conference
Committee’s bill passed both houses of Congress overwhelmingly July 25th, 423-3 in the House
and 99-0 in the Senate (Boston Globe [July 26, 2002]), and President Bush signed the bill into
law (Public Law 107-204) July 30th.
Several events occurred subsequent to the passage of Sarbanes-Oxley that potentially
shed light on the law’s implementation and thus its likely impact; hence, we discuss these events
as well. On August 8th, WorldCom announced that its earnings restatement had jumped to $7.2
billion (Sandberg and Pullian [August 9, 2002]). This event potentially reinforced the pressure
on the S.E.C. to rigorously implement Sarbanes-Oxley when issuing regulations.
August 14th at 5:00pm was the due date for nearly 1,000 large companies to file CEO and
CFO certifications of their companies’ financial statements with the S.E.C. We include this
12
event in light of the Bhattacharya et al. (2002) paper and under the assumption that noncertifying companies are likely earnings managers and/or have ineffective audit committees.
In October, in the midst of a budget battle between Congress and the President, the
administration sought to cap the S.E.C.’s budget at $568 million, which was substantially lower
than the $776 million authorized in Sarbanes-Oxley (Lebaton [October 19, 2002]; Schroeder
[October 21, 2002]). S.E.C. Chairman Harvey Pitt acknowledged that the lower funding level
would not allow the agency to undertake important initiatives associated with policing public
companies and Wall Street.
Finally, there was a series of events related to the appointment of the chair of the
PCAOB. The S.E.C. voted 3-2 on October 25th to appoint former C.I.A. and F.B.I. director and
federal judge William Webster as PCAOB chair. Mr. Webster’s appointment was controversial
and reflected a public, partisan fight between Chairman Pitt and S.E.C. Commissioner Harvey
Goldschmid, a Democrat (Schroeder [October 25, 2002]; [October 28, 2002]). Much of the
accounting industry opposed the other leading candidate, John Biggs, who was seen as a reformoriented candidate because of auditing policies he had adopted as CEO of TIAA-CREF (e.g.,
rotating audit firms and banning audit firms from providing consulting services). A week after
Mr. Webster was appointed, news broke that Chairman Pitt had failed to inform the other S.E.C.
commissioners prior to the vote for the PCAOB chair of some seemingly pertinent information;
specifically, that Mr. Webster had recently headed the audit committee of a company that was
being investigated for possible fraud (Lebaton [October 31, 2002]). Chairman Pitt, facing probes
of his handling of the Webster nomination and widespread calls for his resignation, resigned as
S.E.C. chairman November 5th (Schroeder et al. [November 5, 2002]; Cummings et al.
[November 6, 2002]).
13
There was no indication that Mr. Webster was linked to the alleged fraud at the company
whose audit committee he had chaired. However, the auditor of that company accused Mr.
Webster of “false and misleading statements” concerning what he knew about the financial
problems of the company (Business Digest [November 5, 2002]; Lebaton [November 8,
2002]).11 A November 12th article reported Mr. Webster would resign as PCAOB chairman
(Wilke [November 12, 2002]), and this occurred during trading hours that day (Schroeder
[November 13, 2002]).
Table 2 lists the events we have identified as being potentially critical points surrounding
Sarbanes-Oxley. That is, they are the events that could have affected the probability that
Sarbanes-Oxley would become law and/or the extent of reform in the Act if it became law.12
Because we cannot directly observe aggregate capital market expectations prior to each
individual event, or know with certainty when the market learned about an event, we use event
windows that begin one trading day prior to the occurrence of an event (or group of events) and
end one trading day following the event or group of events.13
The event history suggests that the probability that reform legislation would become law
likely increased sharply beginning with reports of massive fraud at WorldCom. News reports
claim this and comments by President Bush and actions by the S.E.C. immediately following the
This news appeared as a short item in the NYT “Business Digest” on Tuesday, November 5th, but curiously full
news reports did not appear in the NYT or WSJ until Friday, November 8th.
12
Assume a prior probability (pr) that legislation reforming financial reporting and audit committee governance
would become law, and a prior assessment of the expected impact (i.e., the magnitude effect, M) of the legislation
should it become law. Then market reaction to a given event surrounding Sarbanes-Oxley will equal the sum of the
following three components: (1) the change in the prior probability that reform legislation will become law ( pr)
times the prior assessment of the magnitude effect of the law; (2) the change in the prior assessment of the
magnitude effect of the law (M) times the prior probability of reform legislation becoming law; and (3) the change
in the prior probability that reform legislation would become law times the change in the prior assessment of the
magnitude effect of the law. That is, the market reaction to an event equals (pr)M + pr(M) + (pr)(M).
13
An exception is the Andersen trial outcome, which we assume was not known prior to the day the jury rendered
its verdict. Also note in Table 2: (1) event D9 begins Mon., July 8 rather than Fri., July 5 because July 5 is the last
day in event D8; (2) event D10 begins Mon., July 15 rather than Fri., July 12 because July 12 is the last day in event
D9; and (3) event D20 ends Tue., November 12 (rather than November 13) because it was reported in the press that
Mr. Webster would resign November 12 and he did so during trading hours.
11
14
WorldCom fraud announcement are consistent with a changed political environment favoring
reform legislation.14 Once the likelihood of passage of reform legislation became a virtual
certainty, which likely occurred by the time the Senate passed the Sarbanes bill and a new House
bill had been introduced, it then seemingly became a question of how extensive the reform
provisions of the final legislation would be. The issuance of the House-Senate Conference
Committee’s report represents the first indication that the more demanding reform provisions of
the Senate’s Sarbanes bill, along with the House’s stronger criminal penalties, would form the
core of the Act. Hence, we expect significant market reactions associated with the news about
fraudulent reporting at WorldCom and the immediately following events, since these events
appear to indicate a significant increase in the probability that reform legislation would be
passed. We also expect significant market reactions beginning with the issuance of the
Conference Committee’s report when capital market participants learned that the final bill would
generally reflect the more demanding provisions that had been considered.
3. Portfolio Approach using Seemingly Unrelated Regressions (SUR) model
3.1 EMPIRICAL METHODOLOGY
In this section, we discuss our empirical design and the results based on SUR. We first
estimate the average stock price reaction of our sample firms to events surrounding SarbanesOxley, and then examine whether the stock price response to each of the events is associated
with a firm’s earnings management activities or with the effectiveness of a firm’s audit
committee prior to passage of the legislation.
As in Ali and Kallapur (2001), we use the following time-series model that estimates the
average abnormal returns of sample firms over each event window:
14
We discussed critical events in the Sarbanes-Oxley legislative process with former S.E.C. Chief Accountant Lynn
Turner. He indicated that much of the content that was included in the Sarbanes bill had been discussed for a long
while, but had lacked support in Congress. However, news of massive fraud at WorldCom changed the political
environment for reform. Also see Economist.com [July 25, 2002] and Oppel [July 25, 2002].
15
20
Rt   0  1 Rmt    i Di  et ,
(1)
i 1
where: Rt = average daily return of sample firms on date t
Rmt = equal-weighted market index return on date t
Di = dummy variable for the ith event which takes a value of 1 for the three-day window
surrounding event i, and 0 otherwise. We examine 20 events as specified in table 2, so i
= 1, 2, … 20.
We estimate equation (1) using the 252 trading days return data in 2002. The coefficient
on each event dummy variable, i, represents an estimate of abnormal stock return related to
event i for an equal-weighted portfolio consisting of the entire sample firms. Equation (1)
measures the overall impact of the Sarbanes-Oxley Act on all sample firms in each event
window, but does not provide evidence regarding whether the impact of the Act is a function of
the extent of earnings management and/or the effectiveness of audit committees. To address this
issue, we employ two approaches, the portfolio approach estimated using seemingly unrelated
regressions (SUR), and the approach presented in Sefcik and Thompson (1986), which we
discuss in Section 4.
To test our prediction that the Sarbanes-Oxley legislation affects firms that manage
earnings differently than firms that do not manage earnings, we sort firms based on the earnings
management measure for year 2001 (as discussed below, we use performance-matched modified
Jones model abnormal accruals, or PMMJ), and place firms into the High (i.e., top one-third of
PMMJ distribution), Medium (i.e., middle one-third of PMMJ distribution), or Low (i.e., bottom
one-third of PMMJ distribution) earnings management (EM) portfolios. For each portfolio we
compute the equal-weighted daily returns for each of the 252 trading days in 2002. We then
estimate the following system of equations using SUR:
16
20
RtHEM   0HEM  1HEM Rmt    iHEM Di  etHEM ,
i 1
20
RtMEM   0MEM  1MEM Rmt    iMEM Di  etMEM ,
(2)
i 1
20
RtLEM   0LEM  1LEM Rmt    iLEM Di  etLEM ,
i 1
where RtHEM , RtMEM and RtLEM are the average daily returns on date t (t = 1, 2, … 252) for the
High, Medium, and Low EM portfolios, respectively; and Rmt and Di are as defined in equation
(1). The error terms ( etHEM , etMEM , and etLEM ) are assumed to be independent over time for
each portfolio, but may be contemporaneously correlated across portfolios. We expect such
contemporaneous correlation in our setting because event time and calendar time are the same
for all sample firms. The SUR approach takes into account the contemporaneous correlation and
allows the comparison among the coefficients  iHEM ,  iMEM and  iLEM . The coefficients on
event dummy variable Di capture the impact of Sarbanes-Oxley on the High, Medium and Low
EM portfolios on event date i. The Medium EM portfolio is considered the benchmark portfolio
since it is composed of firms with abnormal accruals that are close to zero (see Table 3 for
descriptive statistics). The High (Low) EM portfolio is composed of firms with relatively large
positive (negative) abnormal accruals, firms that likely manage earnings upwards (downwards).
Therefore, comparing  iHEM to  iMEM and  iLEM to  iMEM tests whether Sarbanes-Oxley
affected earnings managers differently than non-earnings managers, and whether the legislation
affected income-increasing earnings managers (i.e., High EM firms) differently than incomedecreasing earnings managers (i.e., Low EM firms).
We next examine whether the stock price effects of Sarbanes-Oxley are related to the
effectiveness of a firm’s audit committee. We focus on independence of the audit committee
17
because the Sarbanes-Oxley Act specifically requires independent audit committee members
(Section 301). We partition firms into two portfolios based on audit committee independence: a
firm is assigned to the High (Low) portfolio if its audit committee is comprised of 100 percent
(less than 100 percent) independent directors at the beginning of 2002.15 Similar to the analysis
for earnings management, we compute the equal-weighted daily stock returns of each portfolio,
and estimate the following models using SUR:
20
RtHACI   0HACI   1HACI Rmt    iHACI Di  etHACI ,
(3)
i 1
20
RtLACI   0LACI   1LACI Rmt    iLACI Di  etLACI ,
i 1
where RtHACI and RtLACI are the average daily returns on date t for the High and Low audit
committee independence (ACI) portfolios, respectively; and Rmt and Di are as defined in equation
(1). The coefficient  iHACI (  iLACI ) measures the abnormal price response of firms in the High
(Low) audit committee independence portfolio to event i. To examine whether Sarbanes-Oxley
affected firms with independent audit committees differently than firms with less independent
audit committees, we test for differences between  iHACI and  iLACI for each event i.
3.2 MEASURE OF EARNINGS MANAGEMENT
Prior accounting research has used several different variables to detect and measure
earnings management, including total accruals (Healy [1985]), Jones model abnormal accruals
(Jones [1991]), modified Jones model abnormal accruals (Dechow et al. [1995]), forwardlooking model abnormal accruals (Dechow et al. [2003]), and deferred tax expense (Phillips et
al. [2003]). We employ performance-matched modified Jones (PMMJ) model abnormal accruals
in light of the results in Kothari et al. [2002] which show that performance-matched abnormal
15
70 percent of the firms in our audit committee sample have audit committees composed of 100 percent
independent members.
18
accrual measures have smaller error rates than Jones model and modified Jones model abnormal
accruals.16 Performance matching, based on industry membership and return on assets, is
designed to control for the effect of performance on measured abnormal accruals.
To compute the PMMJ abnormal accrual metric, we first compute total accruals using
data from the statement of cash flows, consistent with Hribar and Collins [2002]:
TAccit = EBEIit - (CFOit - EIDOit),
(4)
where: TAccit = firm i’s total accruals in year t
EBEIit = firm i’s income before extraordinary items (Compustat #123) in year t
CFOit = firm i’s cash flows from operations (Compustat #308) in year t
EIDOit = firm i’s extraordinary items and discontinued operations from the statement of
cash flows (Compustat #124) in year t.
We then estimate the following equation to compute modified Jones model abnormal accruals:
TAccit = (1/ Assetsi,t-1) + 1 (Salesit - ARit) + 2 PPEit + it ,
(5)
where: Assetsi,t-1 = firm i’s total assets (Compustat #6) in year t-1
Salesit = change in firm i’s sales (Compustat #12) from year t-1 to t
ARit = change in firm i’s accounts receivable from operating activities (Compustat
#302) from year t-1 to t
PPEit = firm i’s gross property, plant, and equipment (Compustat #7) in year t.
We scale all variables by beginning-of-year total assets (Compustat #6), and include the change
in accounts receivable in the estimation of normal accruals because not doing so produces values
of abnormal accruals that are not centered on zero (Francis et al. [2003]).17
16
In addition, in untabulated results, a principal component analysis of multiple earnings management measures
(total accruals, modified Jones model abnormal accruals, performance-matched total accruals, PMMJ abnormal
accruals, and deferred tax expense) reveals that the principal component that explains 68 percent of the variance
between these variables has PMMJ abnormal accruals as its largest component.
19
We define the normal accrual (NAMJit) and abnormal accrual (AAMJit) metrics from the
modified Jones model as:
NAMJit = 0 (1/Assetsit-1) + 1 (Salesit - ARit) + 2 PPEit
(6)
AAMJit = TAccit - NAMJit.
(7)
The performance-adjusted abnormal accrual metric matches each firm’s abnormal accrual metric
based on industry membership and the current year performance. Specifically, we partition our
sample into deciles by ranking firms within two-digit SIC industries by the current year’s return
on assets (ROAit), defined as net income before extraordinary items (Compustat #18) divided by
beginning of year total assets (Compustat #6). We calculate PMMJit as the difference between
firm i’s year t modified Jones model abnormal accrual metric (AAMJit) and the median metric for
its joint industry and ROAit decile, where the median calculation excludes firm i.
3.3 SAMPLE SELECTION AND DESCRIPTIVE STATISTICS
We analyze data from two sets of samples: the earnings management (EM) sample and
the audit committee independence (ACI) sample. For the EM sample, we start with all
companies in Standard & Poor’s 2002 Compustat Industrial and Research files that have data
necessary to compute performance-matched modified Jones model abnormal accruals, the
natural log of market value of equity (SIZE), and the book-to-market ratio (BM) for year 2001.18
Since all events related to Sarbanes-Oxley were in 2002 (see Table 2), we require that firms have
daily stock returns available for all trading days in 2002 from the Center for Research in Security
Prices (CRSP) database. A total of 3,713 firms meet these criteria for the EM sample.
17
Like Francis et al. [2003], we analyze a broad sample of firms, and there is no basis a priori for classifying
subsets of these firms as earnings managers or non-earnings managers prior to estimating our earnings management
variable. Hence, we compute performance-matched abnormal accruals following Francis et al. [2003], who modify
the methodology in Kothari et al. [2002] by including ARit in the estimation of equation (5), which allows for the
possibility that ARit may be non-zero for normal accruals.
18
When computing abnormal accruals, we require a minimum of 20 observations in each two-digit SIC industry.
We eliminate observations with abnormal accruals (scaled by total assets) greater than 1 or less than -1.
20
For the ACI sample, we obtain audit committee independence data from the Investor
Responsibility Research Center (IRRC) database. The IRRC collects corporate governance data
for the S&P 1500 companies. We begin with 1,374 observations available in the IRRC database
for year 2001, and require firms to have 2002 daily return data in CRSP. The final ACI sample
consists of 1,280 observations.
Table 3 presents the descriptive statistics for the EM sample. Panel A contains the
statistics for the entire EM sample, while Panels B, C, and D contain the statistics for the High,
Medium, and Low EM sub-samples, respectively. By design, these panels reveal that the mean
(median) PMMJ accrual metric for the High EM sub-sample is 0.099 (0.078), the mean (median)
PMMJ accrual metric for the Medium EM sub-sample is -0.001 (-0.002), and the mean (median)
PMMJ accrual metric for the Low EM sub-sample is -0.108 (-0.08). Also of interest, the mean
and median return on assets (ROA) for the Medium EM sub-sample (-0.030 and 0.021,
respectively) are larger than the mean and median of the High EM (-0.124 and 0.006,
respectively) and Low EM (-0.184 and 0.002, respectively) sub-samples. While the Medium and
Low EM sub-samples are similar in SIZE (mean SIZE = 5.937 and 5.861, respectively), the High
EM sub-sample contains somewhat smaller firms (mean SIZE = 5.111). Finally, the High and
Medium EM sub-samples have similar book-to-market ratios (mean BM = 0.743 and 0.738,
respectively), while the Low EM sub-sample has a somewhat smaller mean (BM = 0.665). Thus,
the Medium EM sub-sample contains more profitable firms, the High EM sub-sample contains
smaller firms, and the Low EM sub-sample contains firms with lower book-to-market ratios.
Table 4 reports descriptive statistics for the ACI sample. Panel A contains the statistics
for the entire sample, while Panels B and C contain the statistics for the High and Low ACI subsamples, respectively. By design, the mean and median audit committee independence rate
(AUIND) are both 100 percent for the High ACI sub-sample, while the mean (median) AUIND
21
for the Low ACI sub-sample is 0.648 (0.667). While High ACI firms have a mean (median)
ROA of 0.008 (0.030), Low ACI s firms have a somewhat larger mean (median) ROA of 0.011
(0.035). Panels B and C also show that Low ACI firms are slightly larger than High ACI firms
(mean SIZE of Low ACI sub-sample = 7.679 versus 7.478 for the High ACI sub-sample), and
Low ACI firms have somewhat lower book-to-market ratios (mean BM of Low ACI sub-sample
= 0.521 versus 0.538 for the High ACI sub-sample). Thus, relative to the High ACI sub-sample,
the Low ACI sub-sample contains firms that are somewhat larger, more profitable, and have
lower book-to-market ratios.
Comparisons of Tables 3 and 4 reveal that our EM sample is substantially different from
our ACI sample. In particular, the EM sample, which was drawn from the Compustat
population, contains smaller (mean SIZE = 5.636), less profitable firms (mean ROA = -0.113)
with higher book-to-market ratios (mean BM = 0.715) than the ACI sample, which was drawn
from the S&P 1500. Table 4 reports a mean SIZE of 7.538, a mean ROA of 0.009, and a mean
BM of 0.533 for the ACI sample. These different sample compositions may cause discrepancies
in results across the EM and ACI samples.
Table 5 contains descriptive statistics (Panel A) and Pearson and Spearman correlations
(Panel B) for the merged EM and ACI samples. (The results reported later in Table 9 require a
merged EM and ACI sample.) The descriptive statistics show that the merged sample is similar
to the ACI sample in terms of mean SIZE, ROA, and BM. The merged sample also has slightly
negative mean PMMJ (-0.012) and a large mean AUIND (0.895).
The correlations in Panel B reinforce our conclusions from Tables 3 and 4. In particular,
there is a significantly positive Pearson correlation between PMMJ and ROA (Pearson
correlation = 0.195), significantly negative Pearson and Spearman correlations between PMMJ
and SIZE (Pearson correlation = -0.093), and significantly positive Pearson and Spearman
22
correlations between PMMJ and BM (Pearson correlation = 0.133). Thus, firms with more
positive PMMJ (i.e., High EM firms) tend to be smaller, more profitable firms with higher bookto-market ratios than Low EM firms. Also, consistent with the results in Table 4, there is a
significantly negative Spearman correlation between AUIND and ROA (Spearman correlation =
-0.062), a significantly negative Spearman correlation between AUIND and SIZE (Spearman
correlation = -0.054), and significantly positive Spearman and Pearson correlations between
AUIND and BM (Spearman correlation = 0.053). Thus, firms with more independent audit
committees (i.e., High ACI firms) are smaller, less profitable firms with higher book-to-market
ratios than firms with less independent audit committees. Finally, our proxy for earnings
management (PMMJ) is not correlated with our proxy for audit committee independence
(AUIND), suggesting that these are two different constructs.
3.4 EMPIRICAL RESULTS
3.41 EARNINGS MANAGEMENT ANALYSIS
We predict that if the Sarbanes-Oxley Act contains substantive reforms for financial
reporting and audit committee effectiveness, then it should impact firms that manage earnings
and firms with ineffective audit committees differently than other firms. Table 6 presents results
for equation (2), which regresses the High, Medium, and Low EM portfolio returns on the equalweighted market return and dummy variables for each event. If Sarbanes-Oxley reflects
substantive reforms with regard to earnings management, then we should find significant
differences between the coefficients on the event dummy variables between the High and
Medium EM portfolios and between the Low and Medium EM portfolios. In particular, a
positive (negative) difference would indicate that the High or Low EM group experienced higher
(lower) abnormal returns on the event date compared to the Medium EM group.
23
First, the ALL column in Table 6 presents OLS results for the EM sample as a single
portfolio, without the High, Medium, and Low partitioning. This analysis examines whether the
average firm in the EM sample experienced significant abnormal returns on certain event dates.
The results show that the average firm experienced significant abnormal returns on the following
event dates: the initial WorldCom fraud announcement (D7), the WorldCom bankruptcy filing
(D11), when President Bush signed the Sarbanes-Oxley bill into law (D13), when WorldCom
restated the amount of financial fraud to $7.2 billion (D14), the reduction of the SEC budget
(D16), and when Webster resigned as PCAOB chair (D20). While the average firm’s stock price
reacted positively to events D7, D11, and D16, its stock price reacted negatively to events D13, D14,
D20. Thus, Bush’s signing of the Sarbanes-Oxley Act, the additional WorldCom restatement,
and Webster’s resignation were bad news events for the average EM sample firm.
The next three columns in Table 6 show the estimated coefficients for the High, Medium,
and Low EM sub-samples separately, based on the estimation of the three portfolio regressions
using SUR. These columns reveal that the High EM group experienced significantly negative
abnormal returns during the additional WorldCom restatement (D14) and significantly positive
abnormal returns when Pitt resigned as S.E.C. chairman (D19). The Medium EM group
experienced significantly negative abnormal returns during Bush’s Wall Street speech (D9),
during Webster’s appointment as PCAOB chair (D17), and when Webster resigned as PCAOB
chair (D20), and significantly positive abnormal returns during the reduction of the SEC budget
(D16). In contrast, the Low EM group experienced significantly positive abnormal returns during
the initial WorldCom fraud announcement (D7), during passage of the Sarbanes bill in the Senate
and the revised Oxley bill in the House (D10), and during the WorldCom bankruptcy filing (D11),
and significantly negative abnormal returns when President Bush signed the Sarbanes-Oxley bill
into law (D13) and when Webster resigned as PCAOB chair (D20).
24
We interpret these results as follows: First, the additional WorldCom restatement (D14)
negatively affected firms with large positive abnormal accruals (i.e., the High EM group).
Second, because the High EM sample experienced positive abnormal returns on Pitt’s
resignation (D19), the market viewed this resignation as a good news event for upward earnings
managers. Third, because the Low EM group experienced significantly positive abnormal
returns surrounding the initial WorldCom fraud announcement (D7) and the WorldCom
bankruptcy filing (D11), the market viewed these events as benefiting downward earnings
managers. More importantly, while the market viewed passage of the Sarbanes bill in the Senate
and the revised Oxley bill in the House (D10) positively for the Low EM group, it viewed the
President’s signing of the final bill into law (D13) negatively for the same group of firms. We
attribute this reversal to the fact that the final Sarbanes-Oxley Act, whose exact contents were
unknown until the release of the Conference Committee Report, for the most part contained the
harshest provisions available from both the Sarbanes and Oxley bills coming out of the House
and the Senate. Thus, the market reaction when President Bush signed the bill into law suggests
the expectation that the Sarbanes-Oxley Act would affect the financial reporting of even the Low
EM group.
The last two columns of Table 6 present the F-values for tests of significant differences
between the High and Medium EM groups and between the Low and Medium EM groups. The
“HIGH-MED EM” column indicates that the High and Medium EM groups experienced
significantly different abnormal returns only during Pitt’s resignation (D19) and Webster’s
resignation (D20). In fact, the market viewed these events as benefiting High EM firms. In
contrast, the “LOW-MED EM” column indicates that the Low EM group, relative to Medium
EM firms, experienced higher abnormal returns during the initial WorldCom fraud
announcement (D7), during Bush’s Wall Street speech (D9), and during passage of the Sarbanes
25
and Oxley bills in the Senate and House, respectively (D10). However, these relatively higher
abnormal returns were at least partially reversed when President Bush signed the Sarbanes-Oxley
bill into law (D13). These results are consistent with our earlier discussion that the Low EM
group was seen to benefit from Sarbanes-Oxley until President Bush signed the Act into law.
3.42 AUDIT COMMITTEE INDEPENDENCE ANALYSIS
Table 7 presents results for equation (3), which regresses the High and Low ACI
portfolio returns on the equal-weighted market return and dummy variables for each event
period. If Sarbanes-Oxley made substantive changes with regard to the effectiveness of audit
committees, then we should find significant differences between the coefficients on the event
dummy variables between the High and Low ACI portfolios. In particular, a positive (negative)
difference would indicate that the High ACI group experienced higher (lower) abnormal returns
on the event date compared to the Low ACI group.
First, the ALL column in Table 7 presents the results for the entire ACI sample, without
High and Low ACI partitioning. The results show that the average firm in the ACI sample
experienced significant abnormal returns on the following event dates: the issuance of the
Conference Report (D12), Webster’s appointment as PCAOB chair (D17), Pitt’s resignation as
S.E.C. chair (D19), and Webster’s resignation as PCAOB chair (D20). While the average firm’s
stock price reacted positively to event D12, the reaction was negative to events D17, D19, and D20.
Thus, Webster’s appointment as PCAOB chair, Pitt’s resignation as S.E.C. chair, and Webster’s
resignation as PCAOB chair were bad news events for the average ACI sample firm. The results
for the entire ACI sample in Table 7 differ from those for the entire EM sample in Table 6. The
different sample compositions (as shown in Tables 3 and 4) may explain these different results.
In particular, Tables 3 and 4 indicate that the EM sample is composed of smaller, less profitable
firms with higher book-to-market ratios vis-à-vis the ACI sample.
26
The next two columns in Table 7 show the estimated coefficients for the High and Low
ACI sub-samples separately. These columns reveal that the High ACI group experienced
significantly positive abnormal returns when the Conference Committee Report was issued (D12)
and around the CEO/CFO certification deadline (D15), and significantly negative abnormal
returns during Webster’s appointment as PCAOB chair (D17), during Pitt’s resignation as S.E.C.
chair (D19), and during Webster’s resignation as PCAOB chair (D20). The Low ACI group
exhibits abnormal returns similar to those of the High ACI group. However, the average firm in
the Low ACI portfolio did not experience significant abnormal returns during event D15, but it
did experience significantly positive abnormal returns during the Andersen conviction (D6).
Overall, these results suggest there are few differences in abnormal returns between the High and
Low ACI portfolios.
This conclusion is supported by the results in the “HIGH-LOW ACI” column, which
presents the F-values for tests of significant differences between the High and Low ACI
portfolios. This column shows significant differences in abnormal returns between the High and
Low ACI groups for just three events. In particular, the average firm in the High ACI portfolio
experienced significantly lower abnormal returns than the average firm in the Low ACI portfolio
during early progress on the Sarbanes bill (D5) and significantly higher abnormal returns during
the WorldCom bankruptcy announcement (D11) and during Pitt’s resignation (D19). We interpret
these results as indicating that firms with less than 100 percent independent audit committees
benefited from early versions of the Sarbanes bill (which did not specifically address audit
committee composition) and bore costs related to the WorldCom bankruptcy announcement and
Pitt’s resignation. In summary, the SUR analysis does not reveal many instances where events
surrounding Sarbanes-Oxley affected High and Low ACI firms differently. These results
27
suggest that the market did not foresee the legislation imposing costs and benefits differentially
across these two different ACI groups of firms.
4. Sefcik and Thompson (1986) Approach
4.1 EMPIRICAL METHODOLOGY
One advantage of the portfolio approach with SUR estimation is that it does not impose a
linear relation between price response and the measures of earnings management and/or audit
committee independence. However, this method involves formation of portfolios on a somewhat
ad hoc basis and does not control for other factors that might affect stock returns. An alternative
approach would be to use regression analysis to estimate the cross-sectional relation between
abnormal returns and the level of earnings management and/or audit committee independence.
One possible estimation procedure involves estimating abnormal returns for each firm over an
event period and then regressing abnormal returns on firm-specific characteristics:19
ARij   i  1i PMMJ j   2i SIZE j   3i BM j  e j ,
(8)
where ARij is abnormal return for firm j on event i, PMMJj is performance-matched modified
Jones model abnormal accruals for firm j in 2001, SIZEj is natural logarithm of market value of
equity, and BMj is the book-to-market ratio. Note that PMMJ would be a continuous variable in
equation (8), in contrast to our use of it to partition the EM sample into three groups in the SUR
analysis. Both SIZEj and BMj would be measured at the beginning of 2002 for firm j. We would
include SIZEj and BMj in the model to control for their effect on returns. The regression would
be run separately for each event, so there would be 20 regressions since we identify 20 events
related to Sarbanes-Oxley.
19
This discussion of the estimation procedure is focused on the estimation of the relation between abnormal returns
and earnings management. A similar procedure will be used to estimate the relation between abnormal returns and
audit committee independence.
28
However, the OLS regression of equation (8) would give biased standard errors of the
coefficient estimates if there is cross-sectional correlation and/or heteroscedasticity in the
residuals across firms. As noted above, cross-sectional correlation is particularly likely in our
setting because each event surrounding Sarbanes-Oxley affects all firms on the same date. To
address these problems we instead adopt the estimation procedure proposed by Sefcik and
Thompson (1986). Their methodology accounts for cross-sectional correlation and
heteroscedasticity, and produces unbiased estimates of both the coefficients and their standard
errors.20 The first step is to form P portfolios, where P is one plus the number of explanatory
variables in equation (8) (so P = 4). The returns on the portfolios on day t are computed as:
Rtp  W p' Rt ,
(9)
where Rtp is return for portfolio p on day t, Rt is an N x 1 vector of individual firms’ returns on
day t (N is total number of firms), and W p' is a 1 x N vector of weights for portfolio p.21 The
weight vectors are from the following matrix:
W1' 
 
 '
W2 
W     ( X ' X ) 1 X ' ,
'
W3 
 
W ' 
 4
(10)
where X is an N x P matrix and can be written as:
X  [1 PMMJ SIZE BM ] .
(11)
In X, 1 represents a column of ones and PMMJ, SIZE, and BM represent columns of firm-specific
characteristics. Each of the four rows in matrix W represents a set of weights that are used in
20
One advantage of the Sefcik and Thompson methodology over the Feasible Generalized Least Squares estimation
is that is does not require direct computation of the sample covariance matrix of residuals.
21
Equation (9) is computed for each portfolio on each trading day, so all portfolios have a time-series of daily
returns in 2002.
29
equation (9) to compute portfolio returns. To summarize, we create four portfolios, the first
being the intercept portfolio and the other three having returns that are influenced by only one
firm characteristic (PMMJ, SIZE, and BM, respectively).22
We then run the following regression for each portfolio using OLS:
20
Rtp   0p   1p Rmt    i p Di  etp ,
(12)
i 1
where all variables have previously been defined. According to Sefcik and Thompson [1986],
the coefficient estimates from equation (12) (four regressions for four portfolios, each producing
20 coefficient estimates) would be the same as those estimated from equation (8) (20 regressions
for 20 events, each producing four coefficient estimates), but their approach accounts for crosssectional correlation and heteroscedasticity, and produces unbiased estimates of both the
coefficients and their standard errors.
To investigate the relation between abnormal returns and the extent of earnings
management, we perform the Sefcik and Thompson procedure separately for two samples, one
consisting of firms in the High and Medium EM portfolios, and the other consisting of firms in
the Low and Medium EM portfolios (see the previous discussion for definitions). With separate
regressions we allow the relation between abnormal returns and earnings management to differ
between income-increasing earnings managers (i.e., High EM firms) and income-decreasing
earnings managers (i.e., Low EM firms).
We use a similar procedure to investigate the relation between abnormal returns and audit
committee independence with the matrix X defined as X  [1 AUIND SIZE BM ] , where AUIND
is a column of individual firms’ audit committee independence measure (i.e., a continuous
variable). We also examine the relation between abnormal returns and both earnings
22
See Sefcik and Thompson (1986) for additional discussion.
30
management and audit committee independence using the Sefcik and Thompson procedure with
X defined as [1 PMMJ AUIND SIZE BM ] .
4.2 EMPIRICAL RESULTS
4.21 EARNINGS MANAGEMENT ANALYSIS
Table 8 presents results for the Sefcik-Thompson regressions. In particular, the first
column tests the relation between abnormal returns and PMMJj for the sample that is comprised
of just High and Medium EM firms (the High / Medium EM sample); the second column tests
the relation between abnormal returns and PMMJj for the Low / Medium EM sample; and the
third column tests the relation between abnormal returns and AUINDj for the audit committee
independence sample.
The results in column (1) indicate that for the High / Medium EM sample, a firm with a
higher PMMJj experienced higher abnormal returns during issuance of the Committee Report
(D8), and lower abnormal returns during the additional WorldCom restatement (D14), and around
the CEO / CFO certification deadline (D15), holding firm size and book-to-market constant.
These results are not consistent with the SUR analysis, which indicated significant differences in
abnormal returns between the High and Medium EM portfolios for events D19 and D20.
The results in column (2) indicate that for the Low / Medium EM sample, a firm with a
lower PMMJj (relative to near-zero PMMJj) experienced significantly higher abnormal returns
beginning with the WorldCom fraud revelations (D7) and continuing through the issuance of the
Committee Report on the Sarbanes bill (D8), President Bush’s Wall Street speech (D9), passage
of the Sarbanes bill in the Senate and the revised Oxley bill in the House (D10), and WorldCom’s
bankruptcy filing (D11).23 In contrast, a firm with a lower PMMJj experienced significantly
23
As noted, the Sefcik-Thompson analysis treats the earnings management variable, PMMJ, as a continuous
variable without partitioning the sample into Low, Medium, and High EM firms; thus, Low EM firms have lower
PMMJ than Medium EM firms, by definition. For exposition purposes, we multiplied our PMMJ variable by (-1) in
31
lower abnormal returns for D13 and D14, when Bush signed the Sarbanes-Oxley bill into law and
when the additional WorldCom restatement was announced. Finally, a lower PMMJj is
associated with higher abnormal returns during Chairman Pitt’s resignation from the S.E.C.
(D19). (The SUR analysis found similar reactions for D7, D9, D10, and D13.) Thus, after
controlling for firm size and book-to-market, the Sefcik-Thompson analysis also suggests that
relative to near-zero PMMJj firms, the market initially viewed the Sarbanes-Oxley legislation as
more positive news for firms with lower PMMJj until President Bush signed the bill into law, at
which time the relation is reversed. This pattern of event date shareholder wealth effects is
generally consistent with our expectations based on the event history of the likely most critical
events. Somewhat surprisingly, the results suggest that the market anticipates Sarbanes-Oxley as
affecting Low EM firms more than High EM firms.
4.22 AUDIT COMMITTEE INDEPENDENCE ANALYSIS
Column (3) in Table 8 presents results for the Sefcik-Thompson analysis of audit
committee independence. That column reveals that higher audit committee independence is
associated with significantly lower abnormal returns around the Andersen conviction (D6) and
during passage of the Sarbanes and Oxley bills in the House and the Senate (D10), and
significantly higher abnormal returns when Bush signed the bill into law (D13), during the
WorldCom additional restatement (D14), and during the S.E.C. budget reduction announcement
(D16). These results are not consistent with the SUR analysis, which indicated significant
differences in abnormal returns between the High and Low ACI portfolios for the D5, D11, and
D19 event dates. The results could be different due to different estimation techniques (i.e., SUR
vs. Sefcik-Thompson), or due to the lack of control variables (i.e., SIZE and BM) in the SUR
analysis.
the Sefcik-Thompson analysis of Low-Medium EM firms to make the results in Tables 8 and 9 directly comparable
in sign to the Low-Medium EM results using SUR in Table 6.
32
4.23 COMBINED EM AND ACI ANALYSIS
In light of the near-zero correlation between the EM and audit committee effectiveness
variables (i.e., PMMJ and AUIND), and given that Sarbanes-Oxley is aimed at both (i.e., at
constraining earnings management and enhancing audit committee effectiveness), we re-do the
Sefcik-Thompson analysis by including both variables in the same model. Table 9 contains
results for the Sefcik-Thompson regressions that include both a PMMJ portfolio and a AUIND
portfolio, where the analysis is performed separately for High / Medium EM firms (Panel A) and
Low / Medium EM firms (Panel B). Similar to Tables 6 and 8, these separate analyses allow for
different relations between High / Medium EM sample and Low / Medium EM firms.
Column (1) in Panel A contains results for the PMMJ portfolio based on the High /
Medium sample, and indicates that a firm with a higher PMMJj experienced significantly higher
abnormal returns when the Committee Report on the Sarbanes bill was issued (D8) and
significantly lower abnormal returns when President Bush signed Sarbanes-Oxley into law (D13).
While the results for D8 are similar to those shown in Table 8, D13 did not have a significantly
negative coefficient in Table 8, while D14 and D15 did. The difference in results could be driven
by different sample compositions or by the fact that the analysis in Table 9 controls for AUIND,
while that in Table 8 does not.
Column (2) in Panel A contains results for the AUIND portfolio and indicates that a firm
with a higher AUINDj experienced lower abnormal returns during the Andersen conviction (D6)
and during the Webster fraud announcement (D18). While the results for D6 are similar to those
in Table 8, Table 8 also finds significant coefficients for D10, D13, D14, and D16 while Table 9
(Panel A) does not.
33
Panel B presents results for the PMMJ and AUIND portfolios, where the sample is
comprised of just Low and Medium EM firms. Column (1) indicates that a firm with a lower
PMMJj experienced (relative to near-zero PMMJj) higher abnormal returns when the Committee
Report on the Sarbanes bill was issued (D8), during Bush’s Wall Street speech (D9), when
WorldCom filed for bankruptcy (D11), and during the CEO / CFO certification deadline (D15). In
contrast, a firm with a lower PMMJj experienced lower abnormal returns when President Bush
signed Sarbanes-Oxley into law (D13). With the exception of D15’s significance, these results are
consistent with those in Table 8, and somewhat consistent with those in Table 6. Thus, our
results consistently indicate that the market viewed the Sarbanes-Oxley legislation as a good
news event for Low EM firms (relative to Medium EM firms) until President Bush signed the
bill into law.
Finally, Column (2) presents results for the AUIND portfolio and indicates that a firm
with a higher AUINDj experienced higher abnormal returns when the Conference Report was
issued (D12) and when the S.E.C. budget reduction was announced (D16). While the results for
D16 are similar to those in Table 8, Table 8 also finds significant coefficients for D6, D10, D13,
and D14 while Table 9 (Panel B) does not. In addition, the Table 9 results for the AUIND
portfolio are completely different from those in Table 7 for the ACI sample SUR analysis. Due
to the inconsistency of the audit committee independence results across Tables 7, 8, and 9, we
cannot draw any conclusions regarding the relation between audit committee independence and
the impact of the Sarbanes-Oxley legislation on stock returns during our event dates.
5. Concluding Remarks
We conduct an event study to infer the capital market’s assessment of the expected
impact of the Sarbanes-Oxley Act of 2002. We focus on earnings management and audit
committee effectiveness (specifically, the independence of audit committee members) since
34
Sarbanes-Oxley purports to reduce earnings management and strengthen the role of audit
committees with regard to financial reporting.
We find that events surrounding Sarbanes-Oxley affected downward-earnings managers
(i.e., Low EM firms) differently than firms that likely were not engaged in earnings management
(i.e., Medium EM firms), even after controlling for firm size and book-to-market. Low EM
firms experienced significantly greater abnormal returns during a series of events that began with
the initial fraud revelations at WorldCom. That event appears to have been a turning point in the
legislative process. Higher abnormal returns for Low EM firms in this period are consistent with
the market anticipating that downward-earnings managers would benefit from passage of
legislation reforming earnings management practices. In contrast, there is only limited evidence
that High EM firms (i.e., those with large positive performance-adjusted abnormal accruals) had
larger abnormal returns than Medium EM firms in this period, which is thus inconsistent with the
market expecting significant benefits of improved accuracy and reliability of financial statements
for firms that were income-increasing earnings managers.
Both Low and High EM firms experienced significantly lower abnormal returns than
Medium EM firms when the bill was signed into law or immediately thereafter. This market
reaction came after it was publicly known that the Act contained the more demanding reforms
that Congress had been considering, and is consistent with the market expecting that SarbanesOxley would impose greater costs on earnings managers that had been anticipated. Our analysis
of the impact of the Act’s audit committee effectiveness provisions was inconclusive.
The results suggest firms that manage earnings downward are more likely to be impacted
by Sarbanes-Oxley than firms that manage income upwards. While income-decreasing earnings
managers could be firms facing high political costs, it seems unlikely that such firms were the
primary intended “target” of the earnings management provisions of the Act. It is more likely
35
that Congress intended the Act to curb aggressive financial reporting by income-increasing
earnings managers. If that is correct, then our results suggest that the capital market does not
anticipate that the Act will have the intended effect of bringing forth the benefits of improved
accuracy and reliability of financial reports of the income-increasing earnings managers.
36
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41
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42
TABLE 1
Netting of Benefits and Costs of Sarbanes-Oxley
Reflected in Share Price Changes to Events Surrounding the Sarbanes-Oxley Act:
For Firms that Managed Earnings Versus Non-earnings Managers
and for Firms with Ineffective versus Effective Audit Committees
Earnings Managers
and
Ineffective Audit
Committees
Non-Earnings
Managers
and
Effective Audit
Committees
Benefits:
Unobserved
Costs:
Unobserved
Benefits - Costs = Net effects:
Observed
B1
C1
Is (B1 – C1) > 0 or = 0 or < 0?
This can be directly tested.
B2
(B2 – C2) is likely to be < 0
if B2 = 0
C21
If no benefits
then B2 = 0.
This can be directly tested.
Is B1 > B2?
Is C1 > C2?
This cannot be
directly tested.
This cannot be
directly tested.
Is (B1 – C1) – (B2 – C2)
> 0 or = 0 or < 0?
This can be directly tested.
1
When audit committees become more effective, we do not expect that managers necessarily will be less able to
communicate private information to investors though accounting choices reflected in earnings, in contrast to what
we expect if firms become non-earnings managers.
Note: B1 (B2) denotes benefits, if any, from Sarbanes-Oxley for earnings managers (non-earnings managers) and
for firms with effective (ineffective) audit committees, and C1 (C2) denotes costs, if any, imposed by the Act on
earnings managers (non-earnings managers) and firms with effective (ineffective) audit committees.
43
TABLE 2
Description of Critical Events in the Legislative Process
Dummy
Variables
D1
Events
1/17/02 – S.E.C. Chairman Harvey Pitt proposes
oversight board
Event Windows
1/16, 17 (Thu), 18
D2
2/12/02 – Legislation to be introduced in the House
2/14/02 – Introduction of H.R. 3763 in the House
2/11, 12 (Tue), 13, 14 (Thu), 15
D3
3/8/02 – Introduction of S. 2004 in the Senate
3/7, 8 (Fri), 11
D4
4/22/02 – Volcker to abandon reforms at Andersen
4/22/02 – Committee report issued on H.R. 3763
4/24/02 – House considers and passes H.R. 3763
4/25/02 – Senate Judiciary approves legislation
4/19, 22 (Mon), 23, 24 (Wed),
25 (Thu), 26
D5
6/11/02 – Progress reported on Senate legislation
6/12/02 – “Mark-up” of Sarbanes bill to occur
6/10, 11 (Tue), 12 (Wed), 13
D6
6/15/02 – Andersen convicted
6/18/02 – Senate Banking Committee supports major
reform legislation
6/17 (Mon), 18 (Tue), 19
[no trading Sat 6/15]
D7
6/25/02 – Introduction of S. 2673 in Senate
6/26/02 – WorldCom fraud announcement
6/26/02 – SEC files suit against WorldCom
6/24, 25 (Tue), 26 (Wed), 27
D8
7/3/02 – Committee Report on S. 2673
D9
7/8/02 to 7/12/02 – Senate considers S. 2673
7/9/02 – Bush’s Wall Street speech
7/2, 3 (Wed), 5
[no trading 7/4]
7/8 (Mon), 9 (Tue), 10 (Wed),
11 (Thu), 12 (Fri)
D10
7/15/02 – Senate passes S. 2673
7/15/02 – Introduction of H.R. 5118
7/16/02 – Passage of H.R. 5118
7/16/02 – Senate Appropriations Committee increases
S.E.C. budget
7/16/02 – Bush wants bill before August break
15 (Mon), 16 (Tue), 17
D11
7/19/02 – WorldCom to file for bankruptcy
D12
7/24/02 – Issuance of Conference Report
7/25/02 – House, Senate pass Conference Report
7/18, 19 (Fri), 22
[no trading Sun 6/21]
7/23, 24 (Wed), 25 (Thu), 26
D13
7/30/02 – President signs bill into law
44
7/29, 30 (Tue), 31
Dummy
Variables
D14
Events
8/8/02 – Additional WorldCom financial
restatement to $7.2 billion
Event Windows
8/7, 8 (Thu), 9
D15
8/15/02 CEO/CFO certifications due at S.E.C.
8/14, 15 (Thu), 16
D16
10/18/02 – Reduction of SEC budget announced
10/17, 18 (Fri), 21
D17
10/25/2002 – Appointment of William Webster as
chair of the PCAOB
10/24, 25 (Fri), 28
D18
10/30/2002 – Announcement of fraud investigation
of company whose audit committee
Webster had chaired
10/29, 30 (Wed), 31
D19
11/5/02 – Auditor accuses Webster of false
statements
11/5/02 – Pitt resigns as S.E.C. chair
11/4, 5 (Tue), 6
D20
11/8/02 – Full news reports claiming misleading
statements by Webster
11/12/02 – Webster resigns as PCAOB chair
11/7, 8 (Fri), 11, 12 (Tue)
In general, each event window includes one trading day before the first news report and one trading day after the last
news report. One exception is D6 which included the Andersen trial outcome. We assume this was not known prior
to Sat. June 15, the day the jury rendered its verdict. Also note: (1) D9 begins with Mon., July 8 rather than Fri.,
July 5 because July 5 is the last day included in event dum8; (2) D10 begins with Mon., July 15 rather than Fri., July
12 because July 12 is the last day included in event dum9; and (3) event D20 ends Tue., November 12 rather than
November 13 because it was reported Mr. Webster would resign on November 12 and he did so during trading
hours.
45
TABLE 3
Descriptive Statistics for the Earnings Management (EM) Sample
Panel A: Entire EM Sample (N = 3,713)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
PMMJ
-0.003
0.107
-0.518
-0.051
-0.002
0.049
0.876
ROA
-0.113
0.460
-11.657
-0.099
0.011
0.053
0.560
SIZE
5.636
2.047
1.617
4.074
5.604
7.002
12.881
BM
0.715
0.623
0.044
0.299
0.532
0.916
4.321
Panel B: High EM Sample (N = 1,238)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
PMMJ
0.099
0.075
0.030
0.049
0.078
0.121
0.876
ROA
-0.124
0.399
-5.422
-0.153
0.006
0.053
0.560
SIZE
5.111
1.981
1.617
3.556
4.901
6.499
11.555
BM
0.743
0.638
0.044
0.304
0.566
0.959
4.260
Panel C: Medium EM Sample (N = 1,238)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
PMMJ
-0.001
0.017
-0.031
-0.016
-0.002
0.013
0.030
ROA
-0.030
0.223
-2.870
-0.028
0.021
0.054
0.443
SIZE
5.937
2.058
1.623
4.431
5.941
7.249
12.430
BM
0.738
0.634
0.046
0.333
0.564
0.904
4.321
Panel D: Low EM Sample (N = 1,237)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
PMMJ
-0.108
0.082
-0.518
-0.134
-0.080
-0.051
-0.031
ROA
-0.184
0.643
-11.657
-0.177
0.002
0.051
0.400
SIZE
5.861
2.000
1.639
4.348
5.826
7.173
12.881
BM
0.665
0.593
0.044
0.260
0.474
0.853
3.901
46
TABLE 3 - Continued
Variable Definitions:
PMMJ – Performance-matched modified Jones model abnormal accruals, computed as firm i’s modified Jones
model abnormal accrual less the median metric for its joint industry and ROA decile, where the median
calculation excludes firm i. Firm i’s modified Jones model abnormal accrual is the residual value from the
following regression: TAccit = (1/ Assetsi,t-1) + 1 (Salesit - ARit) + 2 PPEit + it ; where TAccit = firm
i’s total accruals in year t = EBEIit - (CFOit - EIDOit); EBEIit = firm i’s income before extraordinary items
(Compustat #123) in year t; CFOit = firm i’s cash flows from operations (Compustat #308) in year t; EIDOit
= firm i’s extraordinary items and discontinued operations from the statement of cash flows (Compustat
#124) in year t; Assetsi,t-1 = firm i’s total assets (Compustat #6) in year t-1; Salesit = change in firm i’s
sales (Compustat #12) from year t-1 to t; ARit = change in firm i’s accounts receivable from operating
activities (Compustat #302) from year t-1 to t; and PPEit = firm i’s gross property, plant, and equipment
(Compustat #7) in year t.
ROA – Return on assets, computed as income before extraordinary items at time t (Compustat #18), scaled by total
assets at time t-1 (Compustat #6).
SIZE – Natural log of market value of equity, computed as (Compustat #25 x #199).
BM – Book-to-market ratio, computed as total book value of equity (Compustat #60) divided by market value of
equity (Compustat #25 x #199).
47
TABLE 4
Descriptive Statistics for the Audit Committee Independence (ACI) Sample
Panel A: Entire ACI Sample (N = 1,280)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
AUIND
0.896
0.183
0
0.800
1.000
1.000
1.000
ROA
0.009
0.210
-4.583
0.003
0.031
0.066
0.578
SIZE
7.538
1.593
2.839
6.445
7.376
8.550
12.894
BM
0.533
0.409
0.004
0.277
0.455
0.670
3.680
Panel B: High ACI Sample (N = 900)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
AUIND
1.000
0
1.000
1.000
1.000
1.000
1.000
ROA
0.008
0.226
-4.583
0.001
0.030
0.066
0.578
SIZE
7.478
1.537
3.040
6.452
7.340
8.429
12.497
BM
0.538
0.414
0.004
0.282
0.462
0.680
3.680
Panel C: Low ACI Sample (N = 380)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
AUIND
0.648
0.159
0
0.613
0.667
0.750
0.889
ROA
0.011
0.168
-1.845
0.006
0.035
0.069
0.271
SIZE
7.679
1.713
2.839
6.438
7.591
8.859
12.894
BM
0.521
0.399
0.010
0.257
0.435
0.651
3.588
Variable Definitions:
AUIND – The ratio of independent audit committee members to total audit committee members (IRRC data).
ROA – Return on assets, computed as income before extraordinary items at time t (Compustat #18), scaled by total
assets at time t-1 (Compustat #6).
SIZE – Natural log of market value of equity, computed as (Compustat #25 x #199).
BM – Book-to-market ratio, computed as total book value of equity (Compustat #60) divided by market value of
equity (Compustat #25 x #199).
48
TABLE 5
Univariate Statistics for the Merged Earnings Management (EM) and Audit Committee
Independence (ACI) Samples
Panel A: Descriptive Statistics for Merged EM and ACI Samples (N = 1,010)
Variable
Mean
Std.Dev.
Minimum
25%
Median
75%
Maximum
PMMJ
-0.012
0.077
-0.385
-0.055
-0.007
0.032
0.322
AUIND
0.895
0.183
0.000
0.800
1.000
1.000
1.000
ROA
0.011
0.170
-2.131
-0.004
0.033
0.069
0.346
SIZE
7.403
1.527
2.839
6.348
7.270
8.410
12.881
BM
0.536
0.429
0.004
0.271
0.450
0.677
3.680
Panel B: Pearson (Lower Diagonal) and Spearman (Upper Diagonal) Correlations for Merged EM
and ACI Samples (P-values Below Each Correlation in Parentheses)
N = 1,010
PMMJ
PMMJ
AUIND
AUIND
ROA
SIZE
BM
0.018
(0.568)
0.009
(0.780)
-0.094
(0.003)
0.168
(<.0001)
-0.062
(0.048)
-0.054
(0.085)
0.053
(0.090)
0.279
(<.0001)
-0.463
(<.0001)
0.027
(0.384)
ROA
0.195
(<.0001)
0.030
(0.345)
SIZE
-0.093
(0.003)
-0.046
(0.146)
0.200
(<.0001)
BM
0.133
(<.0001)
0.075
(0.018)
-0.152
(<.0001)
See Tables 3 and 4 for variable definitions.
49
-0.502
(<.0001)
-0.499
(<.0001)
TABLE 6
Earnings Management (EM) Analysis: Regressions of Portfolio Returns on Equal-Weighted Market
Returns and Event Dummy Variables, With Sample Partitioning Based on High, Medium, and Low
EM Status
RtHEM = 0 HEM + 1 HEM Rmt + iHEM Di + tHEM
(1)
RtMEM = 0 MEM + 1 MEM Rmt + iMEM Di + tMEM
(2)
RtLEM = 0 LEM + 1 LEM Rmt + iLEM Di + tLEM
OLS
0
Rmt
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12
Seemingly Unrelated Regression (SUR)
(1)
(2)
(3)
ALL
HIGH EM
MED EM
LOW EM
(N = 3,713)
(N = 1,238)
(N = 1,238)
Est Coeff
(t-Stat)
Est Coeff
(t-Stat)
-0.0003***
(-3.53)
1.2302***
(164.16)
-0.0001
(-0.19)
0.0003
(0.51)
0.0009
(1.27)
-0.0005
(-0.93)
0.0000
(0.07)
0.0000
(0.07)
0.0013**
(2.19)
0.0000
(-0.05)
0.0001
(0.16)
0.0010
(1.49)
0.0018**
(2.56)
0.0002
(0.32)
-0.0003**
(-2.16)
1.1231***
(95.66)
-0.0007
(-0.67)
0.0000
(-0.05)
0.0017
(1.58)
-0.0002
(-0.31)
-0.0001
(-0.12)
-0.0014
(-1.33)
0.0001
(0.09)
-0.0005
(-0.45)
-0.0003
(-0.31)
0.0009
(0.83)
0.0016
(1.50)
-0.0007
(-0.75)
(3)
Tests for Differences
(N = 1,237)
HIGH –
MED EM
LOW –
MED EM
Est Coeff
(t-Stat)
Est Coeff
(t-Stat)
Difference
(F-Value)
Difference
(F-Value)
-0.0002
(-1.32)
1.1466***
(103.34)
0.0009
(0.87)
0.0010
(1.30)
0.0008
(0.78)
-0.0003
(-0.35)
0.0009
(1.06)
0.0008
(0.77)
0.0003
(0.29)
-0.0012
(-1.18)
-0.0013*
(-1.67)
-0.0007
(-0.69)
0.0005
(0.46)
0.0012
(1.38)
-0.0005**
(-2.17)
1.4210***
(78.15)
-0.0006
(-0.34)
-0.0002
(-0.13)
0.0001
(0.07)
-0.0009
(-0.74)
-0.0007
(-0.48)
0.0008
(0.48)
0.0035**
(2.47)
0.0016
(0.95)
0.0018
(1.42)
0.0028*
(1.73)
0.0032*
(1.92)
0.0000
(0.03)
-0.0001
-0.0003
-0.0234
0.2745***
-0.0016
(0.90)
-0.0011
(0.67)
0.0009
(0.29)
0.0000
(0.00)
-0.0010
(0.51)
-0.0022
(1.72)
-0.0002
(0.01)
0.0007
(0.18)
0.0011
(0.66)
0.0016
(0.90)
0.0011
(0.46)
-0.0019
(1.72)
-0.0014
(0.60)
-0.0012
(0.66)
-0.0007
(0.13)
-0.0006
(0.22)
-0.0016
(0.99)
0.0000
(0.00)
0.0033**
(4.13)
0.0027
(2.19)
0.0031**
(4.67)
0.0035*
(3.65)
0.0028
(2.12)
-0.0012
(0.52)
50
D13
D14
D15
D16
D17
D18
D19
D20
-0.0020***
(-2.93)
-0.0014**
(-2.07)
0.0006
(0.83)
0.0021**
(2.49)
-0.0009
(-1.35)
0.0004
(0.58)
0.0007
(1.04)
-0.0012**
(-2.00)
-0.0015
(-1.36)
-0.0022**
(-2.04)
-0.0007
(-0.61)
0.0017
(1.31)
0.0002
(0.18)
0.0013
(1.25)
0.0019*
(1.77)
0.0006
(0.70)
-0.0003
(-0.25)
-0.0002
(-0.24)
0.0011
(1.10)
0.0032***
(2.64)
-0.0023**
(-2.28)
-0.0002
(-0.18)
-0.0012
(-1.23)
-0.0018*
(-2.01)
*
Statistically significant at the 0.1 level (two-tailed).
Statistically significant at the 0.05 level (two-tailed).
***
Statistically significant at the 0.01 level (two-tailed).
**
51
-0.0043**
(-2.59)
-0.0018
(-1.10)
0.0012
(0.75)
0.0012
(0.62)
-0.0007
(-0.40)
0.0000
(0.02)
0.0015
(0.90)
-0.0024*
(-1.70)
-0.0012
(0.52)
-0.0019
(1.34)
-0.0018
(1.11)
-0.0015
(0.57)
-.0025
(2.21)
0.0015
(0.82)
0.0031*
(3.50)
0.0024*
(2.77)
-0.0040**
(4.65)
-0.0016
(0.71)
0.0001
(0.01)
-0.0020
(0.78)
0.0016
(0.77)
0.0002
(0.01)
0.0027
(2.15)
-0.0007
(0.17)
TABLE 7
Audit Committee Independence (ACI) Analysis: Regressions of Portfolio Returns on Equal-Weighted
Market Returns and Event Dummy Variables, With Sample Partitioning Based on High and Low
ACI Status
RtHACI = 0 HACI + 1 HACI Rmt + iHACI Di + tHACI (1)
RtLACI = 0 LACI + 1 LACI Rmt + iLACI Di +  tLACI (2)
OLS
Seemingly Unrelated Regression
(SUR)
Test for
Differences
(1)
(2)
ALL
HIGH ACI
LOW ACI
(N = 1,280)
(N = 900)
(N = 380)
HIGH – LOW
ACI
Est Coeff
(t-Stat)
Est Coeff
(t-Stat)
Est Coeff
(t-Stat)
Difference
(F-Value)
-0.0005
(-1.41)
1.5341***
(53.48)
0.0008
(0.31)
0.0017
(0.86)
-0.0006**
(-2.02)
1.5224***
(56.02)
0.0009
(0.37)
0.0020
(1.05)
-0.0005
(-1.49)
1.4505***
(54.16)
0.0006
(0.24)
0.0017
(0.92)
-0.0002
-0.0039
(-1.49)
0.0010
(0.56)
0.0018
(0.82)
0.0040
(1.54)
0.0025
(1.11)
-0.0035
(-1.46)
0.0009
(0.55)
0.0013
(0.61)
0.0038
(1.60)
0.0025
(1.18)
-0.0037
(-1.55)
0.0012
(0.70)
0.0029
(1.41)
0.0047**
(1.99)
0.0027
(1.29)
0.0002
(0.02)
-0.0002
(0.09)
-0.0016*
(3.01)
-0.0009
(0.62)
-0.0002
(0.04)
D8
0.0034
(1.31)
0.0037
(1.53)
0.0029
(1.21)
0.0008
(0.56)
D9
-0.0016
(-0.77)
-0.0027
(-1.04)
-0.0018
(-0.98)
-0.0029
(-1.20)
-0.0013
(-0.72)
-0.0021
(-0.88)
-0.0005
(0.35)
-0.0008
(0.53)
0.0004
(0.13)
0.0005
(0.22)
-0.0017
(-0.72)
0.0023**
(4.26)
0
Rmt
D1
D2
D3
D4
D5
D6
D7
D10
D11
52
0.0719***
0.0003
(0.09)
0.0003
(0.10)
0.0084***
(3.76)
-0.0015
(-0.57)
0.0046*
(1.89)
-0.0007
(-0.29)
0.0041*
(1.74)
-0.0016
(-0.68)
0.0004
(0.15)
0.0009
(0.68)
D14
0.0027
(1.03)
0.0033
(1.36)
0.0022
(0.94)
0.0010
(0.90)
D15
0.0036
(1.39)
0.0041*
(1.71)
0.0038
(1.60)
0.0003
(0.10)
D16
0.0039
(1.23)
0.0043
(1.45)
0.0041
(1.41)
0.0002
(0.02)
D17
-0.0070***
(-2.72)
-0.0072***
(-2.98)
-0.0058**
(-2.45)
-0.0014
(1.57)
D18
-0.0038
(-1.47)
-0.0061**
(-2.36)
-0.0035
(-1.44)
-0.0049**
(-2.04)
-0.0037
(-1.55)
-0.0075***
(-3.13)
0.0002
(0.03)
0.0025**
(5.33)
-0.0041*
(-1.82)
-0.0043**
(-2.08)
-0.0037*
(-1.80)
-0.0006
(0.44)
D12
D13
D19
D20
*
Statistically significant at the 0.1 level (two-tailed).
Statistically significant at the 0.05 level (two-tailed).
***
Statistically significant at the 0.01 level (two-tailed).
**
53
TABLE 8
Sefcik-Thompson Regressions of PMMJ and AUIND Portfolio Returns on Equal-Weighted Market
Returns and Event Dummy Variables Using the High and Medium Earnings Management (EM) Samples
for Equation (1), the Low and Medium EM Samples for Equation (2), and the Audit Committee
Independence (ACI) Sample for Equation (3)
RtPMMJ_HM = 0 PMMJ_HM + 1 PMMJ_HM Rmt + iPMMJ_HM Di + tPMMJ_HM
Rt
PMMJ_LM
= 0
PMMJ_LM
+ 1
PMMJ_LM
Rmt + 
PMMJ_LM
Di
i
+ t
RtAUIND = 0 AUIND + 1 AUIND Rmt + iAUIND Di + tAUIND
0
Rmt
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12
D13
D14
D15
D16
D17
D18
D19
D20
(1)
High and Med EM Firms
(N = 2,476)
PMMJ
(2)
Low and Med EM Firms
(N = 2,475)
PMMJ
Est Coeff
-0.001
Est Coeff
(2)
(3)
(3)
ACI Sample Firms
(N = 1,280)
AUIND
Est Coeff
-0.001
t-Stat
-1.46
6.92
-0.004
2.563***
t-Stat
-2.39
16.05
0.090***
2.94
-0.018
-1.49
-0.008
-0.56
0.001
0.23
-0.007
-0.73
-0.010
-0.88
0.002
0.74
0.001
0.09
-0.001
-0.05
0.001
0.25
0.002
0.20
-0.010
-0.95
-0.001
-0.41
-0.003
-0.25
-0.011
-0.89
-0.003
-1.10
*
-1.70
***
0.914
t-Stat
-0.94
(1)
PMMJ_LM
**
-0.004
-0.37
-0.009
-0.66
-0.005
-0.003
-0.30
0.022*
1.75
-0.002
-0.73
*
0.021
1.77
0.026
*
1.81
0.002
0.90
0.000
-0.05
0.030***
2.69
-0.003
-1.27
0.016
1.35
0.049
***
3.43
-0.006
0.013
1.12
0.032**
2.23
0.003
0.94
-0.015
-1.50
-0.010
-0.77
0.003
1.15
-0.006
-0.50
-0.027*
-1.88
0.005*
1.68
**
-2.14
-0.027
*
-1.91
**
2.40
-0.023*
-1.94
-0.001
-0.10
-0.025
0.007
**
0.000
-2.27
0.02
**
2.21
0.016
1.33
-0.005
-0.34
0.006
0.017
1.44
0.019
1.31
-0.001
-0.44
0.005
0.45
-0.003
-0.19
-0.002
-0.83
0.017
1.42
0.041***
2.86
0.004
1.39
0.016
1.60
-0.009
-0.72
-0.002
-0.90
*
Statistically significant at the 0.1 level (two-tailed).
Statistically significant at the 0.05 level (two-tailed).
***
Statistically significant at the 0.01 level (two-tailed).
**
54
TABLE 9
Sefcik-Thompson Regressions of PMMJ and AUIND Portfolio Returns on Equal-Weighted Market
Returns and Event Dummy Variables Using the Merged Earnings Management (EM) and Audit
Committee Independence (ACI) Samples, With Separate Comparisons of High and Medium EM
Firms (Panel A) and Low and Medium EM Firms (Panel B)
Panel A: High and Medium EM Samples (N = 674)
RtPMMJ_HM = 0 PMMJ_HM + 1 PMMJ_HM Rmt + iPMMJ_HM Di + tPMMJ_HM
RtAUIND = 0 AUIND + 1 AUIND Rmt + iAUIND Di + tAUIND
(1)
PMMJ
(1)
(2)
(2)
AUIND
Est Coeff
-0.005**
t-Stat
-2.23
Est Coeff
-0.001
t-Stat
-1.09
Rmt
D1
D2
D3
D4
D5
D6
D7
0.794***
4.10
0.321***
6.52
-0.004
-0.22
0.001
0.25
-0.006
-0.46
0.003
0.85
-0.004
-0.21
0.000
-0.05
0.011
0.92
0.002
0.50
0.014
0.95
-0.003
-0.80
-0.008
-0.47
-0.009
*
-1.97
0.014
0.96
0.001
0.32
D8
D9
D10
D11
D12
D13
D14
D15
D16
**
2.31
0.002
0.47
0.004
0.28
-0.002
-0.59
0.003
0.16
-0.005
-1.03
0.009
0.50
0.004
0.98
-0.019
-1.27
0.000
-0.04
-0.030*
-1.70
0.001
0.20
-0.008
-0.47
0.006
1.35
0.005
0.27
0.001
0.12
0.010
0.57
-0.002
-0.35
0.011
0.63
-0.006
-1.41
-0.001
-0.05
-0.007
*
-1.70
0.006
0.35
0.003
0.63
0.013
0.85
0.002
0.61
0
D17
D18
D19
D20
0.040
*
Statistically significant at the 0.1 level (two-tailed).
Statistically significant at the 0.05 level (two-tailed).
***
Statistically significant at the 0.01 level (two-tailed).
**
55
TABLE 9 - Continued
Panel B: Low and Medium EM Samples (N = 673)
RtPMMJ_LM = 0 PMMJ_LM + 1 PMMJ_LM Rmt + iPMMJ_LM Di + tPMMJ_LM
RtAUIND
0
Rmt
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12
D13
D14
D15
D16
D17
D18
D19
D20
= 0
+ 1
(1)
PMMJ
AUIND
AUIND
Rmt + 
AUIND
Di
i
+
AUIND
t
(1)
(2)
(2)
AUIND
Est Coeff
t-Stat
Est Coeff
t-Stat
-0.005
-1.46
-0.001
-1.57
***
3.426
11.88
0.128
***
3.16
0.012
0.46
0.000
-0.07
-0.029
-1.42
0.001
0.45
0.014
0.54
0.000
0.04
-0.009
-0.47
-0.002
-0.68
0.011
0.49
-0.001
-0.20
-0.015
-0.56
-0.005
-1.38
0.016
0.71
0.000
0.016
**
0.061
2.37
0.004
0.98
0.036*
1.79
-0.003
-0.93
0.020
0.76
-0.005
-1.44
0.097***
3.69
0.001
0.26
0.007
**
-0.019
-0.84
-0.065**
-2.48
0.001
0.23
-0.035
-1.35
0.004
1.12
0.043*
1.64
0.003
0.71
-0.039
-1.51
0.005
0.20
0.001
0.39
0.001
0.02
-0.002
-0.42
0.029
1.11
0.005
1.36
-0.003
-0.14
0.000
-0.14
*
Statistically significant at the 0.1 level (two-tailed).
Statistically significant at the 0.05 level (two-tailed).
***
Statistically significant at the 0.01 level (two-tailed).
**
56
0.009
**
2.06
2.43