Perceived audit quality and firm value: Evidence from investors’ reaction to therevelation of limiting liability agreements in audit engagement letters
Henock Louis, Penn State University
Dahlia Robinson, University of South Florida
Amy X. Sun, University of Houston
Abstract
We examine the value changes in U.S. investors’ actual perceptions of audit quality by analyzing
the market reaction to the first public revelation of liability limiting agreements (LLAs) in audit
engagement letters of publicly traded firms. The revelation of the existence of liability limiting
agreement (LLA) clauses in audit engagement letters of publicly traded companies results insubstantial losses in their values and lower shareholders’ approval of their auditors. Consistent
with investors’ reaction to the revelation being associated with concerns about audit quality, theloss in value is strongly related to clients’ incentives and opportunity to misreport. Specifically,
the loss is more pronounced when a firm’s earnings quality is low, the firm’s recent reported
earnings barely meet the average analyst earnings forecast, the firm has recently issued stocks, andthe managers have recently sold stocks on their own accounts. The loss is also attenuated whenoutsiders constitute a super-majority of the firm’s board of directors. Overall, the evidence
suggests that investors attribute a substantial premium to external audits and that investors’
negative perception of audit quality significantly increases issuers’ cost of capital and,
consequently, adversely affects firm value.
JEL classification: M42, K22, K41
Keywords: Value of external audits; liability limiting agreement; auditor approval*This paper benefits from comments by Anil Arya, Bjorn Berg, Bobby Carnes, Cory Cassell, Kimball Chapman, Dane
Christensen, Junfang (Zero) Deng, Dan Givoly, Jeremiah Green, Di Guo, Delroy Hunter, Gerald Lobo, Pablo
Machado, Jong Chool Park, Anywhere Sikochi, Ian Tarrant, Hal White, Annika Wu, Yuping Zhao, and workshop
participants at Florida State University, Lehigh University, Morgan State University, and Penn State University. We
are particularly grateful for insights from Jay Brodish, Professor of Practice at Lehigh University, and former National
Director of Auditing, and former US and Americas Risk Management Leader at PwC.

Perceived audit quality and firm value: Evidence from investors’ reaction to therevelation of limiting liability agreements in audit engagement letters
Abstract
We examine the value changes in U.S. investors’ actual perceptions of audit quality by analyzing
the market reaction to the first public revelation of liability limiting agreements (LLAs) in audit
engagement letters of publicly traded firms. The revelation of the existence of LLAs in audit
engagement letters of publicly traded firms results in substantial losses in their values and lower
shareholders’ approval of their auditors. Consistent with investors’ reaction to the revelation being
associated with concerns about audit quality, the loss in value is strongly related to clients’
incentives and opportunity to misreport. Specifically, the loss is more pronounced when a firm’s
earnings quality is low, the firm’s recent reported earnings barely meet the average analyst
earnings forecast, the firm has recently issued stocks, and the managers have recently sold stocks
on their own accounts. The loss is also attenuated when outsiders constitute a super-majority of
the firm’s board of directors. Overall, the evidence suggests that investors attribute a substantial
premium to external audits and that investors’ negative perception of audit quality significantly
increases issuers’ cost of capital and, consequently, adversely affects firm value.

1

Accounting and auditing professionals serve an absolutely vital role in our capital markets. Transparent, informative,
and accurate financial reporting are the lifeblood of the capital markets and are essential for investors to makeinformed decisions as to how to allocate their capital. Without accurate and reliable corporate disclosures andfinancial statements -- and competent auditors to audit them -- our competitive free market system could not function
properly. Steven Harris – member of the Public Company Accounting Oversight Board (PCAOB).1

1. Introduction
External audits are presumably indispensable for a well-functioning capital market, withthe cost of capital being prohibitively large for many firms without independent attestations of
the credibility of the financial reports. However, in spite of the strong presumption about theimportance of auditing, extant academic studies provide no conclusive evidence on the value of
improved audit quality,2 leading Healy and Palepu (2001, p. 415) to conclude that there is “apaucity of evidence on the value of auditor opinions to investors.” More recently, Donovan et al.
(2014) also question the value of audit quality in the U.S., observing that there is little evidenceof concerns about variations in audit quality among equity investors in the U.S.
Assessing the impacts of cross-sectional variations in audit quality in the U.S. is difficult
because auditing is mandatory for every publicly traded firm and cross-sectional variations in audit
quality is largely unobservable (Lawrence et al. 2011). Moreover, an argument has been made thatvariations in external financial reporting quality (EFRQ) in the U.S. have little impact on firm
value. Zimmerman (2013, p. 888) asserts, for instance, that “EFRQ has on average at best a secondorder effect on firm value of US publicly listed companies and improvements in these firms’ EFRQ
have a third-order effect on firm value.” Donovan et al. (2014) note that Zimmerman’s (2013)
doubt about the benefits of changes in reporting quality in the U.S. also applies to changes in audit
quality. More recently, Jiang, Wang, and Wang (2019 p. 205) document improvements in someaudit quality proxies following the acquisition of a non-Big N auditor by a Big N auditor and conclude

that the capital markets apparently do not “attach any premium to the improved audit quality”

1http://pcaobus.org/News/Speech/Pages/03202014_American.aspx.

2See, e.g., Dodd et al. (1984), Dodd et al. (1986), Dopuch et al. (1987), Nichols and Smith (1983), Johnson and Lys(1990), and Klock (1994).

2

based on the merger announcement abnormal returns. However, investors could simply fail toanticipate the non-Big N auditor acquisition effect. Therefore, whether changes in U.S. investors’
perception of audit quality substantially affect firm value remains an important empirical question.
Our study contributes to the understanding of the value of changes in U.S. investors’ actual
perceptions of audit quality by analyzing the market reaction to the first public revelation of
liability limiting agreements (LLA) in audit engagement letters of publicly traded firms.
To curb their litigation costs and the risk of the failure of another auditing firm, auditors
have been lobbying for regulations limiting their liability, but to no avail (Johnson 2007; Dickey2008). The Federal Financial Institutions Examination Council (FFIEC) opposes LLA, arguing:“Limits on external auditors’ liability may weaken the external auditors’ objectivity, impartiality,and performance and, thus, reduce the Agencies’ ability to rely on audits.”3 The FFIEC opposes
any alternative dispute resolution clause and any limitation of liability provision in audit
engagement letters, even if the limitation applies only to the clients’ rights.4 The Securities andExchange Commission (SEC) also maintains that any move to indemnify auditors against liability
would violate auditor independence (SEC 2003).
As U.S. regulators were resisting auditors’ efforts to limit their liability, LLA clauses were
becoming a standard feature of audit engagement letters, while remaining unknown to investors(Rapoport 2005). However, on September 20, 2005, Sun Microsystems disclosed in a DEF 14A
filing: “In connection with the audit of the 2005 financial statements, Sun entered into an
engagement agreement with Ernst & Young ... That agreement is subject to alternative dispute
resolution procedures and an exclusion of punitive damages.” This statement was followed on
November 28, 2005 by a Wall Street Journal (WSJ) article discussing the issue and the major audit
firms’ involvement. We use the context of the LLA clause disclosure and the WSJ article toanalyze the effect of U.S. investors’ perception of audit quality on firm value.
3http://www.ffiec.gov/press/proposedinteragencyadvisory.pdf
4Major lawsuits by clients against auditors include suits by Cendant and HealthSouth against EY, Adelphia and Navistar against

Deloitte, AMERCO against PwC, and Fannie Mae against KPMG. We provide more details on these cases in the next section.

3

Although Louis et al. (2019) find that LLA clauses are associated with a reduction in audit
fees, they find no evidence that they negatively affect reporting quality. However, ultimately,
investors’ reaction to the LLA disclosure is likely to be determined not by the actual effects of theclauses but by investors’ perception of their potential effects. U.S. regulators are actually quite
concerned about the perception that a LLA clause could convey about auditor independence. The
SEC argues that, if a “reasonable investor believes such a provision causes a conflict of interest,
then it impairs independence” (Rapoport 2005). The PCAOB also opines that limiting auditor
liability could “undermine investor confidence in the auditor’s objectivity and the quality ofcompanies’ financial reports” (PCAOB 2006). The position of the regulators is consistent withextant analytical studies that suggest that a reduction in an auditor’s total litigation cost would
reduce its incentives to provide high quality audits (Dye 1993; Dye 1995; and Chan and Pae 1998).
As Lennox and Li (2012, p. 155) note, there is “a widespread belief that unlimited liability
is important for incentivizing auditors to provide high quality audits.” Accordingly, institutional
investors’ reaction to the LLA disclosure was very negative. The Council of Institutional Investors
maintains, for instance, that LLAs could impair auditor independence and “potentially place U.S.
companies, shareholders, and capital markets at risk” (Mahoney 2006). Cynthia Richson, the Ohio
Public Employees Retirement System’s governance officer, also argues that LLAs are a“disservice to investors” (Rapoport 2005). As a direct evidence of shareholders’ opposition to
LLAs, Sun’s revelation of its LLA led shareholders to vote against retaining EY as Sun’s auditor(Reilly 2006). The approval rate of EY by Sun’s shareholders fell from 83.3% in the year prior to
the disclosure to 73.2% about one month after the disclosure, which constitutes an enormous
decline, considering that auditor reappointment is a routine matter and that the approval rate is
generally quite sticky. Gregory Smith, director of operations for the Investment Company Institute(ICI), also suggested that shareholders would incorporate LLA clause information in theirdeliberation on auditor selection (Smith 2006). Accordingly, we find a significant reduction inshareholders' approval of their auditors in the year after the WSJ publication. Hence, the context
4

of the LLA disclosure and the WSJ article provides an excellent and unique setting to analyze theeffect of investors’ perception of audit quality on firm value.
Because the LLA clauses limit only clients’ rights and do not preclude investors from suing
auditors, one might argue that the LLA clauses do not matter and would not be of much concern
to shareholders, notwithstanding the regulators’ claim. However, it appears that the audit firms
would not have included the clauses in the contracts unless they believe that the clauses provide
them some benefits.5 Moreover, because investors’ alleged losses from impaired audit quality
generally far exceed the amount that they recover,6 investors might want to avoid any action that
could increase the perception that audit quality is impaired. Furthermore, limitations on a client’s
rights to sue also restrict investors’ rights to sue. Because of the restrictions imposed by the Private
Securities Litigation Reform Act (PSLRA) of 1995 and the Securities Litigation Uniform
Standards Act (SLUSA) of 1998 on shareholders’ ability to successfully file class-action lawsuits,client litigation now comprises one of the major sources of auditor concerns. Shareholders can
bypass the requirements of the PSLRA and the SLUSA by filing derivative lawsuits, where “therights of the plaintiff shareholders derive from the primary corporate right to redress the wrongs
against it” (Desaigoudar v. Meyercord, 108 Cal.App.4th 173, 183 (2003)).
Because audit engagement letters are not publicly disclosed, the LLA clauses were largely
unknown to investors and, hence, their potential information content was not impounded into price.
The WSJ notes that “these liability-limiting provisions never had been disclosed before with regard
to individual companies, and so some investors were surprised and dismayed” by the disclosure(Rapoport 2005). We perform an extensive search and do not find any evidence of a similar
disclosure prior to September 20, 2005. The WSJ also notes that “[i]nvestors generally have been

5Partners from a Big 4 audit firm indicate, in private conversations, that their legal counsels strongly encourage them to include theclauses in their audit engagement letters and that the LLAs have been effective in reducing their litigation costs.
6

For instance, a U.S. Chamber of Commerce report concludes that securities class action lawsuits result in a recovery
of $5 billion, while costing investors nearly $39 billion per year. The report finds that the simple filing of a suit erases
about 4.4% of market value (U.S. Chamber 2014).

5

unaware of the provisions because they are contained in audit-engagement letters” (Reilly 2006).7
Hence, the market reaction to the first LLA disclosure could be informative about the effect ofperceived audit quality on firm value.
We observe a substantial decrease in the market value of Sun Microsystems (-2.42%) after
the LLA disclosure. The loss extends to the entire US market, with the average US firm
experiencing a negative abnormal return of -1.70%. The extent of the market loss, the fact that
Sun’s return was significantly more negative than the return for the overall market and the huge
subsequent decline in the approval rate of Sun’s auditor by Sun’s shareholders strongly suggestthat shareholders were reacting to Sun’s LLA disclosure.
Extant studies have examined the overall stock market effects of certain events (see, e.g.,Dee, Lulseged, and Zhang 2011); however, such studies are susceptible to the effects ofconfounding events. There were two potentially confounding events around Sun’s disclosure that
could affect our interpretation of the returns associated with Sun's disclosure: the September 20,
2005 decision of the Federal Open Market Committee (FOMC) to raise the Federal Funds Rateand the Federal Discount Rate by a quarter percentage point and the approach of Hurricane Rita.
As discussed in Section 4.2, we find reliable evidence that these events are unlikely to explain theobserved negative abnormal returns.
To further link the stock market movement on September 20, 2005 to the LLA disclosure
by Sun Microsystems, we exploit the fact that the disclosure concerns an audit engagement letterfrom EY. At the time of the disclosure, investors did not know the extent of the LLA practice.
Consistent with the negative market reaction that we observe on September 20, 2005 being at least
partly associated with the LLA disclosure, the negative return is, on average, significantly stronger
for the EY clients than for the non-EY clients.
7In its proposed advisory, the FFIEC noted an increase in the type and frequency of LLA clauses in financial institutions’engagement letters. However, it is generally presumed that the audit firms have LLA clauses in their contracts with unlisted clients.
Given that the majority of banks are unlisted and the strong opposition of US regulators to LLA, the FFIEC's mention of LLA
clauses in engagement letters in no way implies that listed firms had LLA clauses in their contracts.

6

Louis et al.’s (2019) suggestion that the extant LLA clauses do not negatively affectreporting quality would indicate that the negative market reaction to Sun’s disclosure would be
driven by unsophisticated investors. However, the market reaction to the disclosure is actually
substantially stronger for firms that have large concentrations of institutional ownership than forother firms. This evidence is consistent with the extant anecdotal evidence that institutional
investors strongly oppose the LLA practice and the fact that individual investors could be lesslikely to discover Sun’s LLA disclosure on time and move stock so strongly and so fast.
In spite of our best effort, we cannot rule out the possibility that our results could becontaminated by the concurrent events. However, there was no obvious contaminating event on
the day the WSJ publicized the LLA practice, offering a rather clean setting to examine the market
reaction to the revelation of the LLA practice. Because Sun’s disclosure preceded the WSJ article,
the information content of the article was not totally new. However, the market can respond torecycled news many months after the same news was first reported (Huberman and Regev 2001).
More importantly, upon reading Sun’s disclosure, investors would not know the extent to which
the LLA practice is limited to EY and a few clients. The WSJ article indicated that the LLA practice
was widespread, provided broader dissemination of the LLA practice, and extensively discussed
the involvement of the audit firms. For instance, the article reported the observation by Lynn
Turner, a former SEC chief accountant, that “all four accounting firms are demanding thecompanies include these liability cap clauses in their contracts." Therefore, the market reaction to
the publication is likely to be informative about investors’ perception of LLA.
Sun Microsystems experienced a substantially more negative return than the overall market
when it disclosed the inclusion of the LLA clause in its audit engagement letter. However, there is
no reason why Sun should be overly punished for disclosing a practice that is common at otherfirms, who choose to not disclose the practice. Accordingly, Sun’s losses partly reversed when the
WSJ article confirms that the LLA practice is widespread, and not limited to Sun Microsystems.
7

In contrast, the rest of the U.S. market experienced further losses after the WSJ publication(−0.835% or a total market loss of $145.24 billion). The negative abnormal returns could beconsistent with the fact that LLA clauses can reduce the insurance value of the audit. However,considering the relatively small sizes of the audit firms, the market loss we observe is too large torepresent only the marginal change in the insurance value. Note, however, that, while the $145.24
billion loss is very large, it represents only a 0.835% reduction in market value, which is quiteplausible if investors believe that LLA would lead to less stringent audits. To obtain a 0.835%
reduction in the value of a firm that has a cost of capital of 10% (for instance), the cost of capitalwould need to increase only to about 10.087%, which is reasonable given that we are concernedby the effect of only a marginal change in perceived audit quality.8
Finally, we conduct cross-sectional tests that more directly link the market reaction topotential concerns about audit quality. Consistent with the stock market losses being associatedwith concerns about audit quality, the reduction in firm value is strongly related to clients’
incentives and ability to misreport. Specifically, the negative market reaction is less pronounced
when a firm’s board of directors is dominated by outsiders and more pronounced when a firm’s
earnings reporting quality is low, the firm’s recent reported earnings barely meet the average
analyst earnings forecasts, the firm recently issued stocks, and the managers have recently soldstocks on their own accounts. Overall, the evidence suggests that investors attribute a substantial
premium to external audits and that investors’ negative perception of audit quality significantly
increases issuers’ cost of capital and, consequently, adversely affects firm value.
The remainder of this paper is organized as follows. The next section describes the context
and relevance of the LLA clauses. Section 3 analyzes the effect of the LLA disclosure on auditor
ratification by shareholders. Section 4 analyzes the effect of the LLA disclosure on firm value. We
conclude in Section 5.
8The present value of a perpetuity will change by about 0.827% if the capitalization rate increases from 10% to 10.087%.

8

2. Background information on the LLA clauses
Concerned about their huge litigation costs, the audit firms were among the strongest
supporters of the PSLRA and the SLUSA. The acts create a more favorable litigation environment
for the audit firms (SEC 2000), by replacing joint-and-several liability by proportionate liability
in most allegations of Rule 10b-5 violations and restricting shareholders’ ability to successfully
file class-action lawsuits against auditors.
To further limit their liabilities, the audit firms started to include LLA clauses in theengagement letters. The extant LLA agreements provide for alternative dispute resolution
procedures and exclusions of punitive damages, which can be awarded if an audit firm is foundnegligent in failing to detect a fraud.9 EY admits that such “clauses have been part of our standard
client agreements for some time and are not new” (Rapoport 2005). KPMG argues that therequirement to seek arbitration “is a common mechanism for a cost-effective forum, which allows
both parties the ability to control the costs normally associated with litigation. We believe
alternative dispute resolution is consistent with maintaining auditor independence” (Reilly 2006).
The LLA agreements are likely to provide meaningful protections to the audit firms against somecostly lawsuits. The agreements are not legally prohibited, although the SEC is concerned that they
could give the appearance of a conflict of interest and impair independence.10 Details on the natureand the legal aspects of the LLA clauses are provided in Section II of Louis et al. (2019).
The LLA clauses do not preclude third-party lawsuits. However, because of the limits
imposed by the 1990s’ acts on investors’ ability to sue auditors, client lawsuits, either directly by
the clients or by derivative shareholder plaintiffs, have become one of the major sources of auditor
concerns. For instance, in 1999, Cendant sued EY after the company faced a multi-billion dollar

9

It is quite common for plaintiffs to claim that auditors are negligent and to ask for punitive damages. Using the Google
search engine, we were able to find numerous examples where the plaintiffs argued that the audit firm should be
subject to punitive damages (We search, for instance, for KPMG “punitive damages”; EY “punitive damages”; PwC“punitive damages”; and Deloitte “punitive damages”). In one case, a court required BDO Seidman to pay more than$351 million in punitive damages.
10
http://www.ffiec.gov/press/proposedinteragencyadvisory.pdf

9lawsuit by shareholders in connection with a 1998 accounting scandal.11 In 2002, Adelphia sued
Deloitte, claiming that Deloitte is partly responsible for the alleged massive fraud that led Adelphia
to file for bankruptcy protection and cost its shareholders billions of dollars.12 In 2003, stockholder
derivative plaintiffs, acting on behalf of HealthSouth, also filed a lawsuit against EY alleging that
EY acted recklessly and with gross negligence and failed to perform reviews and audits of its
financial statements with due professional care.13 In 2003, AMERCO (parent of U-Haul) also sued
PwC for $2.5 billion, claiming negligence and fraud in relation to a series of events that led to
AMERCO restating its financial results. In 2006, Fannie Mae sued KPMG for $2 billion, alleging
that the auditor failed to prevent $6.3 billion in accounting errors that resulted in restatements.14
In 2011, Navistar also filed a lawsuit against Deloitte for damages in excess of $500 million, many
years after the company dismissed Deloitte as its auditor, alleging that Deloitte committed fraud
and negligence that forced Navistar to restate earnings.15
EY ultimately paid $298.5 million to settle the suit with Cendant, almost as much as the$335 million it paid to the shareholders of Cendant in a separate lawsuit (Reilly and Koppel 2008).
Similarly, Deloitte paid $167.5 million to Adelphia, which was only slightly lower than thesettlement of $210 million to Adelphia’s stockholders. In 2004, PwC settled its suit with
AMERCO for more than $50 million. In May 2010, Fannie Mae and KPMG revealed that they
had reached an undisclosed settlement. Most recently, in January 2013, Deloitte settled for an
undisclosed sum the lawsuit by Navistar. However, the lawsuit by HealthSouth was referred toarbitration and resulted in a ruling in favor of EY.

11

http://online.wsj.com/articles/SB917311181894647000

12

http://ww2.cfo.com/accounting-tax/2007/08/deloitte-to-pay-167-5m-in-adelphia-case and http://www.nytimes.com/2006/12/09/business/09adelphia.html.
13

http://www.prnewswire.com/news-releases/healthsouth-announces-decision-of-ernst--young-arbitration-panelrules-against-healthsouth-on-legal-defense-184022831.html
1415

http://www.nytimes.com/2006/12/12/business/worldbusiness/12iht-suit.3880001.html?_r=0
http://www.reuters.com/article/2011/04/26/navistar-deloitte-lawsuit-idUSN2629823320110426

10

Shareholders could be concerned about the LLA clauses undermining the value of theinsurance provided by the auditors. However, we find no indication in the discussions about theissue that the loss of the insurance value is a major concern for investors. Their main concern wasthat the agreements are relieving "auditors of responsibility and thus encouraging less stringent
audits" (Rapoport 2005). Investors’ potential losses from impaired audit quality may not be fully
recovered from litigation against the company and the auditor. Thus, investors are concerned about
any issue that they perceive to have the potential to impair audit quality, despite the ability to sue
for recovery of their losses.
The anecdotal evidence also suggests that many firms do not appear to have “a lot ofleverage to remove the language” in their engagement letters and maintain that they felt pressured
into accepting the clauses “rather than risk being dumped by their auditors” (Reilly 2006). As Judy
McReynolds, the chief financial officer of Arkansas Best, puts it, although she is not necessarily
opposed to the clauses, her firm simply did not “have the ability to say no” (Reilly 2006). Lynn
Turner, the chairman of Sun Microsystems’s audit committee, justifies his decision to accept the
LLA clause by arguing that audit-committee chairs are faced with a fait accompli when asked tosign the agreements (Rapoport 2005).
There is also a concern that some managers could sign audit engagement letters without
reviewing all of the provisions in the letters or understanding the full implications of the provisions.
The oversight is possible if some managers focus on negotiating audit fees and consider the restof the engagement letter a routine matter. The FFIEC and the agencies that it represents wereconcerned enough about this possibility that they “encourage boards of directors, audit
committees, and management to closely review all of the provisions in the external audit
engagement letter before agreeing to sign.” They also maintain that, “[t]o assure that those charged
with engaging the external auditor make a fully informed decision, any agreement such as anengagement letter that affects the financial institution’s legal rights should be carefully reviewed
11

by the financial institution’s legal counsel,”16 suggesting that the implications of LLA clauses may
not be fully understood even by the managers who sign the contracts. Ted White, deputy directorof the Council of Institutional Investors, is also unconvinced that audit committees are aware of
the LLA practice (Rapoport 2005).
The reason why clients started to disclose the existence of the LLA clauses is not obvious.
However, the WSJ links the movement to the “growing debate within accounting and regulatory
circles” (Reilly 2006). Judy McReynolds admits that the managers of Arkansas Best, one of thefirms that publicly disclosed LLA clauses in their engagement letter, have "thought that really ourshareholders ought to understand the fact that the language exists in our agreement” (Reilly 2006).
We also note that Sun Microsystems became the first publicly traded company to disclose theexistence of an LLA clause in its audit engagement letter on September 20, 2005, only a few
months after the FFIEC issued its May 4, 2005 advisory opposing any form of agreement that
limits auditor liability. It is also relevant that Lynn Turner was a former SEC chief accountant andwas leaving his post as the chairman of Sun’s audit committee when Sun made the disclosure.
3. The effect of the LLA disclosure on auditor ratification
The auditor ratification process is arguably one of the most direct avenues for investors toregister their dissatisfaction with their auditors. The ratification vote is a routine process thatgenerally does not vary much. For instance, Vanguard generally supports “management’s
recommendation for the ratification of the auditor, except in instances where audit and auditrelated fees make up less than 50% of the total fees paid by the company to the audit firm.”17
Nonetheless, if investors believe that LLA clauses are not in the interest of shareholders, it isplausible that their displeasure could translate into a lower auditor approval rate after the existence

16http://www.ffiec.gov/press/proposedinteragencyadvisory.pdf

17

https://about.vanguard.com/vanguard-proxy-voting/voting-guidelines/. The Institutional Shareholder Services (ISS)also recommends a positive vote on auditor ratification unless: (1) an auditor has a financial interest in or association
with the company; (2) there is reason to believe that the independent auditor has rendered an opinion that is neither
accurate nor indicative of the company’s financial position; (3) poor accounting practices are identified that rise to aserious level of concern; or (4) fees for non-audit services are excessive.

12

of the LLA clauses was revealed. In fact, extant anecdotal evidence does suggest that investors
would take the LLA practice into consideration when voting to ratify auditors (see Reilly 2006 andSmith 2006). We therefore analyze how shareholders responded to the LLA disclosure byexamining the change in the auditor ratification rate around the LLA disclosure.
3.1 Modeling the change in the auditor ratification rate
On September 20, 2005, Sun Microsystems became the first case of a publicly traded U.S.
firm to disclose the existence of LLA clauses in its engagement letters. On November 28, 2005,
the WSJ published an article discussing the use of LLA clauses in audit engagement letters. We
analyze how investors reacted to these events by first examining the effects of these events on therate of auditor approval by shareholders.
As shown in Figure 1, the auditor ratification rate was increasing prior to the September
20, 2005 disclosure. Therefore, the change in the ratification rate is likely a biased measure ofshareholder reaction to the LLA disclosure. To mitigate the bias, we de-trend the series byanalyzing the difference between the change in the approval rate before and after the LLA
disclosure. Because auditor ratification is voluntary, to control for differences across firms andmitigate potential self-selection biases, we also hold the sample in the pre-disclosure year and thepost-disclosure year constant. However, some firm characteristics and other determinants ofauditor ratification rates can change from one year to the next. To ensure that our findings are notdue to some correlated omitted variable effect, we extend our analysis to a multivariate setting,where we control for various factors that could explain the change in the approval rate.
Prior studies suggest several variables that could be associated with shareholders’ approvalof their auditors. Sainty, Taylor, and Williams (2002) suggest that shareholders are more likely tovote against auditor reappointment after an auditor issues a going concern opinion. Raghunandan(2003) and Mishra, Ragahunandan, and Rama (2005) find that shareholders are more likely to voteagainst auditor reappointment when an auditor performs a high level of nonaudit services.
13

Actually, many institutions indicate that a high level of nonaudit services is the main reason why
they would vote against the reappointment of an auditor. Dao, Mishra, and Raghunandan (2008)
suggest that auditor tenure could be positively related to shareholder votes against auditors.
Finally, Liu, Raghunandan, and Rama (2009) and Hermanson, Krishnan, and Ye (2009) suggestthat a restatement increases the likelihood that shareholders would vote against an auditor. We
control for these variables and other potentially relevant factors. More specifically, we model thechange in the auditor approval rate as follows:∆APPit = 1AFTERit + 2∆IOit + 3∆LASSETit + 4∆BMit +5∆LEVit +6∆LACOVERAGEit+7∆GCOit +8∆RESTATEit +9∆LOSSit +10∆UNQUALIFIEDit +11∆ICWit+ 12∆NASRATIOit +13∆DIRVOTESit + 14LTENUREit + 15NBIG4it+ Firm Fixed Effects +it,
(1)
where
∆APP is the annual change in a firm’s auditor approval rate by shareholders in year t [which iseither the year (365 days) before September 20, 2005 (the date of the first disclosure of LLA in
audit engagement letters) or the year after September 20, 2005];
AFTER is a binary variable taking the value one for the year after September 20, 2005 (the date of
the first disclosure of LLA in audit engagement letters) and zero for the year before September 20,
2005;∆IO is the annual change in proportion of institutional ownership at the end of the fiscal year prior
to the vote in year t;∆LASSET is the change in natural logarithm of a company’s total assets (ASSET) at the end of the
fiscal year prior to the vote in year t;∆BM is the change in firm’s book-to-market value of equity at the end of the fiscal year prior to
the vote in year t;∆LEV is the change in firm’ leverage ratio (debt divided by equity) at the end of the fiscal year
prior to the vote in year t;∆LACOVERAGE is the change in log of one plus the number of analysts covering the firm in thelast IBES analyst consensus annual earnings forecast prior to the vote in year t (the number ofanalysts is set to zero if the firm has no forecast);∆GCO is the change in an indicator variable that takes the value one if the company receives agoing concern opinion during the fiscal year prior to the vote in year t and zero otherwise;

14

∆RESTATE is the change in an indicator variable that takes the value one if the company restates
its financial statements during the fiscal year prior to the vote in year t and zero otherwise;∆LOSS is the change in an indicator variable that takes the value one if a company’s net income forthe current fiscal year prior to the vote in year t is negative and zero otherwise;∆UNQUALIFIED is the change in an indicator variable that takes the value one if the company
receives a clean audit opinion in the fiscal year prior to the vote in year t and zero otherwise (i.e., if
the company receives an adverse opinion, no opinion, a qualified opinion, or an unqualified opinion
with additional language);∆ICW is the change in an indicator variable that takes the value one if the company has been
identified to have one or more internal control weaknesses in the fiscal year prior to the vote in year
t and zero otherwise;∆NASRATIO is the change in ratio of nonaudit fees to audit fees in the fiscal year prior to the votein year t;∆DIRVOTES is the change in minimum percentage of the votes against the election of a director
prior to the vote in year t;
LTENURE is the natural logarithm of auditor tenure with the client prior to the vote in year t; andNBIG4 is a binary variable taking the value one if the firm is audited prior to the vote in year t bya non-Big 4 audit firm and zero otherwise.
3.2 Descriptive statistics
We first present the characteristics of the sample firms used in the auditor ratification testin Table 1. The statistics reported in Column (1) of Table 1 show that the sample firms experienced
some significant changes. On average, institutional ownership, analyst coverage, total assets, thenumber of restatements, and the proportion of unqualified opinions have been increasing for the
sample firms. Book-to-market value of equity, the proportion of going concern opinions, theproportion of firms reporting losses, the proportion of firms reporting internal control weaknesses,
and the ratio of non-audit fees to audit fees have been decreasing.
We also present the average characteristics of the clients of the Big 4 audit firms and theclients of the non-Big 4 audit firms separately in Columns (2) and (3), respectively. As expected,

15

most of the observations involve clients of the Big 4 audit firms. However, except for the numberof restatements and the proportion of firms reporting losses, the patterns are similar across theclients of the Big 4 audit firms and the clients of the non-Big audit firms.
3.3 Univariate results
Sun Microsystem was the first publicly traded firm to disclose the existence of an LLA
clause in its audit engagement letter. The disclosure was made on September 20, 2005. On October27, 2005, about one month after the LLA disclosure, Sun’s shareholders had the opportunity tovote to reappoint EY as Sun’s auditor. The approval rate of EY by Sun’s shareholders fell from
83.3% in the year prior to the disclosure to 73.2% in the year after the disclosure, which constitutes
a massive decline for a routine procedure like the ratification of an auditor’s reappointment.
In Figure 1, we plot the pattern of auditor ratification rate over the seven years centered on
the year after the September 20, 2005 disclosure for the broader sample of firms with ratification
votes on RiskMetrics. Again, we use a constant sample of firms. As indicated in the graph, theauditor ratification rate shows a strong upward trend prior to the first LLA disclosure, as thecountry was emerging from the accounting scandals of the early 2000s. The ratification rate peaked
right before the first LLA disclosure and trended down afterwards. These observations are
consistent with the conjecture that investors reacted negatively to the LLA disclosure by voting
against the ratification of their auditors.
The univariate results in Table 2 show that the average changes in auditor approval rates
after the first LLA disclosure for the full sample, the clients of the Big 4 audit firms, and the clientsof the non-Big 4 audit firms are -0.43%, -0.44%, and -0.16%, respectively. The average change in
the auditor approval rates is statistically significant at the 5 percent level in a one-tail test for thefull sample and the Big 4 sample and is statistically insignificant for the non-Big 4 sample. The
weaker results for the clients of the non-Big 4 auditors are consistent with the fact that the LLA
practice was directly associated with the Big 4 audit firms, as opposed to the non-Big 4 firms.
16

Shareholders are also likely to hold the Big 4 auditors to higher standards. Moreover, Lynn Turner,a former SEC chief accountant, linked the LLA practice to the Big 4 firms, noting in the WSJ
article that “all four accounting firms are demanding the companies include these liability cap
clauses in their contracts."
Considering that auditor ratification is a routine procedure, the 0.43% decrease in theratification rate for the full sample is quite material. Moreover, the -0.43% is likely a biased
measure of the market reaction to the LLA disclosure, given that the ratification rate was nonstationary prior to the first LLA disclosure, as shown in Figure 1. Therefore, an alternative, andarguably better, measure of the market reaction to the disclosure is the difference between thechange in the approval rate after the LLA disclosure and the change in the ratification rate before
the disclosure. As shown in Column (3) of Table 2, the difference in the change in the approvalrate for the full sample is -1.82%, which is statistically significant at the 1 percent level.
We also report Pearson and Spearman correlations in Table 3. Again, we find a strong
negative correlation between the change in the auditor ratification rate (∆APP) and AFTER, theindicator for the year after the first LLA disclosure (as opposed to the year before). ∆APP is also
positively related to the change in institutional ownership and the change in the proportion ofunqualified opinions, and negatively related to the change in the ratio of non-audit fees to audit
fees. The negative association between auditor ratification rate and non-audit fees is consistent
with the fact that a high level of non-audit services is the main reason why institutional investors
and the Institutional Shareholder Services (ISS) would vote, or recommend a vote, against thereappointment of an auditor.
We also note that many of the sample firms’ characteristics changed between the year prior
to the first LLA disclosure and the year after the disclosure. The indicator for the year after thedisclosure (AFTER) is negatively correlated with the proportion of clients audited by the Big 4
firms and the changes in institutional ownership, analyst coverage, assets, the number of17restatements, the proportion of unqualified opinions, and the proportion of firms with internal
control weaknesses. It is positively related to auditor tenure and the changes in book-to-market
value of equity, leverage, the proportion of firms reporting losses, and the ratio of non-audit fees
to audit fees. Below, we control for these variables and others in our multivariate analyses.
3.4 Multivariate results
We report the regression results in Table 4. The multivariate results are consistent with theunivariate results reported in Tables 2 and 3. More specifically, we find that the conditional
difference in the change in auditor approval rates from the year before to the year after the first
LLA disclosure is -1.5%, with a t-value of -3.30. We find no evidence that the apparent LLA effectis different across Big 4 and non-Big 4 audit firms. Combined with the anecdotal evidence linking
LLA clauses to their deliberation on auditor selection (Reilly 2006; Smith 2006), the empiricalevidence strongly supports the notion that investors disapprove of the LLA practice.
4. The effect of the LLA disclosure on firm value
There are two important dates when the stock market could have reacted to the LLA
disclosure: September 20, 2005 and November 28, 2005. The former is the date when Sun
Microsystems became the first publicly traded U.S. firm to disclose the existence of LLA clauses
in its engagement letters. The latter is the date when the WSJ discussed the use of LLA clauses inaudit engagement letters. To analyze the effect of perceived audit quality on firm value, we
examine the market reactions to the two events.
4.1 Measuring abnormal returns
Because we are dealing with a market-wide event, it is very important to pinpoint the event
time to minimize noise associated with the potential effects of concurrent events. The timing of
the WSJ article is clear. The contents of WSJ articles are available to the market the morning of
the publication date or the night before. Therefore, the effect of the publication should be reflected18

in stock prices on the day of the publication. Hence, we measure the market reaction to the content
of the WSJ article by the abnormal return on the day of the publication (Day 0). The timing of Sun
Microsystems’ disclosure is less clear. The disclosure can be filed early in the day, late in theafternoon, or after the regular trading hours. It can also bear an after-hour time stamp, although it
was disclosed earlier in the day. Therefore, to ensure that we capture the time when the information
reached the market, we measure the abnormal return on the day of, and the day after, the disclosure(Days 0 and +1).
To estimate a firm's abnormal return, we use a market model, relying on an index of foreign
stocks as the benchmark. Following Francis, Nanda, and Wang (2006), we compute the foreign
market index using Level II and Level III American Deposit Receipts (ADRs) listed on the New
York Stock Exchange (NYSE), the American Stock Exchange (AMEX), or the National
Association of Securities Dealers Automated Quotations (NASDAQ). The LLA revelation mightraise concerns about foreign firms’ audit quality, biasing the abnormal returns downwards.
However, because the LLA revelation relates to U.S. firms and given that the U.S. tend to berelatively very litigious, the effect of the revelation should be more pronounced for U.S. firms.
Moreover, given that audits performed in the U.S. are generally perceived to be of higher quality
than those performed overseas, anything that adversely affects that perception would have anegative impact on the U.S. firms and such impact would generally be more negative for the U.S.
firms. Therefore, to test whether the market reacted negatively to the LLA disclosure, we use thefollowing model:
1

RETi,t = 0 + 1ADRt + ∑1+eEvent_Dayt,e + i,t,

(2)

e=0

where RETi,t is the return of firm i on day t; ADRt is the return of the ADR index on day t; Event_Dayt,e is an indicator variable taking the value one on the event day e and zero otherwise. For Sun
Microsystems’ disclosure, the event days are September 20 and 21, 2005 and the model is19estimated over the six months ending on November 20, 2005 (or two months after the event date).
For the WSJ publication, the event day is November 28, 2005 and the model is estimated over thesix months starting on September 28, 2005 (or two months before the event date). We chose thesewindows to avoid cross-contaminations. The abnormal return associated with an event date isgiven by the coefficient on Event_Day and is essentially identical to the forecast error from asimilar model that excludes Event_Day as a regressor. We use the coefficient on Event_Day, as
opposed to the forecast error, because the potential bias in the standard error of the coefficient ismore amenable to corrections for cross-sectional correlations than the forecast error. We correct
for cross-sectional correlations by clustering the standard errors at the firm level in pooled
regressions.
4.2 The stock price effect of the first LLA clause disclosure
4.2.1 Main findings
We report the market reaction to Sun Microsystems' LLA disclosure in Table 5. Sun
Microsystems suffers a substantial loss (−2.490%) upon its disclosure of the LLA clause in its
audit engagement letter. The loss apparently extends to the entire US market, with the overallmarket experiencing an average loss of −1.554%. The abnormal return for Sun Microsystems is−2.421% and the mean abnormal return for the whole US market (ex Sun) is −1.701%, for a total
market capitalization loss of about $299.93 billion.18 These findings, coupled with the change in
the auditor ratification votes, strongly suggest that investors reacted negatively to the disclosure of
LLA in audit engagement letters.
It is worth noting that the immediate market reaction on September 20, 2005 is much
18To estimate the total market loss, we first compute the loss for each firm by multiplying the market value of the firm at the market

close on September 19, 2005 by its abnormal return and then sum up the losses for all the firms. The total market loss is estimatedat $274.43 billion if we use the raw returns instead of the abnormal returns.

20stronger for Sun Microsystems than for the overall market. The stronger reaction for the overallmarket occurs on the following day, September 21. It appears that investors first discount Sun
Microsystems’ stock price and then discount the rest of the market. The market adjusts firm values
across the board, mainly on September 21, as if it presumes that audit firms are generally using,or will be using, LLA clauses in their engagement letters. The $299.93 billion loss in market
capitalization is quite large. However, in a world without auditing or with unreliable auditing, thecost of capital is likely to be prohibitively large. Note that, to obtain the 1.7% reduction in thevalue of a firm that has a cost of capital of 10% (for instance), the cost of capital needs to increase
only to about 10.173%. Therefore, it is conceivable that the disclosure of the LLA clauses could
have an enormous impact on firm value if investors believe that they lead to less stringent audits.
Sun Microsystems could perform worse than the rest of the U.S. market because there wereother events around Sun’s disclosure that affected Sun’s industry (SIC code 3571: electronic
computers) more than the market. However, untabulated results show that the average return ofthe other firms in Sun’s industry is actually positive over the day of, and the day after, Sun’s
disclosure, with an average raw return of 0.394% and an average abnormal return of 0.148%.
Hence, it does not appear that Sun Microsystems’ effect reflects some sort of industry-wide effect.
The extent of the market losses and the fact that Sun’s return was significantly morenegative than the return for the overall market as well as the returns of its industry peers aresupportive of the notion that investors were reacting to Sun’s disclosure. Investors could respondnegatively to the LLA disclosure if they perceive that the LLA clauses indirectly undermine theirpotential claims against the auditors. However, the total market loss of $299.93 billion is muchlarger than the total value of the US audit firms. Such a loss cannot represent only the marginalchange in the value of the insurance offered by the audit firms. In addition, we find no indicationin the discussions about the LLA issue that shareholders are concerned about the LLA clauses

21undermining the value of the insurance provided by the auditors. Instead, their concern was thatthe agreements are relieving auditors of responsibility and thus encouraging less stringent audits.
4.2.2 Controlling for the potential impact of confounding events
There were two potentially confounding events around Sun’s disclosure. First, on
September 20, 2005, the FOMC raised the Federal Funds Rate and the Federal Discount Rate by
a quarter percentage point, which could induce a negative market reaction. Second, Hurricane Rita
entered the Straits of Florida on September 20, 2005, before strengthening into a Category 2
hurricane. Less than a month after Hurricane Katrina devastated the Southeast region of the U.S.,
investors could have been concerned about the potential impact of Rita on the economy.
To ascertain whether the returns associated with Sun’s LLA disclosure is likely to be
attributable to the September 20, 2005 FOMC decision to raise short-term interest rates, we
compare the market reaction to the September 20, 2005 decision with the market reaction to theother FOMC rate-increase decisions made around the same period. If the market reacts negatively
to the September 20, 2005 LLA disclosure, we expect the September 20, 2005 returns to be morenegative than the returns on the other FOMC rate-increase decision date. We also analyze thereturns for those firms that are likely to benefit from increases in short-term interest rates. While
stock prices generally respond negatively to increases in short-term interest rates, the prices of afew stocks tend to respond positively. Some firms benefit from increases in short-term interest
rates because they manage substantial amounts of cash that they invest in short-term instruments(see Walia 2013). These firms include insurance brokers, security brokers, commodity contracts
brokers, and payroll processors. A negative return for these firms on September 20, 2005 cannot
be attributed to the September 20, 2005 FOMC decision. We follow a similar approach to ascertain
whether the returns could be attributable to the expected cost of Rita. More specifically, we analyze
the returns for those firms that are likely to benefit from hurricanes, which include firms in thefollowing industries: (1) building materials, hardware, and mobile home dealers; (2) pumps and22

pumping equipment; (3) building construction; (4) heavy construction; and (5) construction special
trade. Because firms in these industries tend to benefit from hurricanes, a negative abnormal returnfor these firms on September 20, 2005 cannot be attributed to Hurricane Rita.
The results reported in Panel A of Table 6 provides strong evidence that the FOMC rateincrease decision is unlikely to be the primary driver of the negative abnormal returns following
Sun’s September 20, 2005 LLA disclosure. The abnormal returns for the six rate-hikeannouncements surrounding the September 20, 2005 event were relatively small, with an averageof -0.031%, compared to -1.550% for the September 20, 2005 event. The abnormal returns after
the rate hike announcements were small because the increases were expected. The Federal Reserve
was consistently increasing the Federal Funds Rate and the Federal Discount Rate by 25 basis
points at each meeting from June 30, 2004 until June 29, 2006.
It is conceivable that, although the other rate hikes were expected, the September 20, 2005
hike was not, which could explain the large negative return around Sun’s September 20, 2005
disclosure. To assess this possibility, we analyze the abnormal returns for insurance brokers,
security brokers, commodity contracts brokers, and payroll processors, which are firms that arelikely to benefit from increases in short-term interest rates. If the September 20, 2005 FOMC
decision was unexpected and Sun’s LLA disclosure had no effect on US stock prices, then wewould expect these firms to experience positive returns around the September 20, 2005 disclosure.
The results reported in Panel B of Table 6 show that these firms also experienced strong negative
returns around the September 20, 2005 announcement. In contrast, they experienced positive,
though statistically insignificant, abnormal returns after both the pre-9/20/2005 and the post9/20/2005 rate hike announcements. These results are consistent with the notion that these firms
tend to benefit from increases in short-term interest rates and that the rate hikes in question weregenerally expected, and strongly indicate that the negative abnormal returns around Sun’s
September 20, 2005 disclosure cannot be attributed to the September 20, 2005 FOMC decision.
23

We also ascertain whether the returns could be attributable to the expected cost of
Hurricane Rita. We conduct the analysis by examining the returns for those firms that are likely tobenefit from a hurricane, including firms in the following industries: (1) building materials,
hardware, and mobile home dealers; (2) pumps and pumping equipment; (3) heavy construction;and (4) construction special trade. The results reported in Panel C of Table 6 show that even thesefirms experience strong negative returns after Sun’s September 20, 2005 LLA disclosure. Given
that firms in these industries should generally benefit from hurricanes, their negative abnormal
return around the LLA disclosure cannot be attributed to the approach of Hurricane Rita.
4.2.3 EY clients versus Non-EY clients
The September 20, 2005 LLA disclosure by Sun Microsystems concerns an audit
engagement letter from EY. At the time of the disclosure, investors did not know the extent of the
LLA practice. It would appear then that, after reading Sun’s disclosure, investors would assign ahigher likelihood to the inclusion of LLA in engagement letters from EY than from the other audit
firms. Therefore, if the negative market reaction that we observe is at least partly due to the LLA
disclosure, then the effect should be stronger for the EY clients than for the non-EY clients.
The results reported in Table 7 strongly support the notion that the market reaction isassociated with the LLA disclosure. The average EY clients suffers a negative abnormal return of-1.962% upon the disclosure that EY includes an LLA clause in Sun’s audit engagement letter. In
contrast, the average non-EY clients suffers a negative abnormal return -1.627%. The differential
return across the two groups is significant below the 1% level.
4.2.4 Institutional vs. Non-Institutional Investors
We also analyze the association between the market reaction to the disclosure andinstitutional ownership. Louis et al. (2019) find no evidence suggesting that LLA clauses
24negatively affect reporting quality, which would suggest that the negative market reaction is driven
by unsophisticated investors. However, as discussed earlier, extant anecdotal evidence indicatesthat institutional investors strongly oppose the LLA practice.19 Moreover, it seems unlikely that
there would be many small individual investors who could discover Sun’s LLA disclosure on time
and who would have the trading speed and power to have the strong and quick impact on stock
prices that we observe immediate after the disclosure. Accordingly, the results reported in Table
8, show that the market reaction to the disclosure is substantially stronger for firms that have large
concentrations of institutional ownership (−2.745%) than for other firms (−1.438%).
4.3 The market reaction to the publication of the WSJ article
In spite of our best effort, we cannot rule out the possibility that the confounding events
contaminated our results. Hence, the returns around Sun Microsystems’ disclosure should beinterpreted with caution. However, an extensive search provides no evidence of contaminating
events on November 28, 2005, when the WSJ publicized the LLA practice. Moreover, it is notclear how widespread the knowledge of Sun’s disclosure was. Moreover, it was practically
impossible for those investors who access the disclosure to determine the extent of the LLA
practice from reading the disclosure. The WSJ article, in contrast, provided broader disseminationand discussion of the LLA practice and indicated that it was an industry-wide practice, particularly
among the Big 4 firms. Therefore, the WSJ publication provides a cleaner setting to analyze
investors’ perception of LLA clauses. Accordingly, we will focus the rest of the analysis on the
WSJ article.

The Council of Institutional Investors argue that LLAs could impair auditor independence and “potentially place US
companies, shareholders, and capital markets at risk” (Mahoney 2006). Cynthia Richson, the Ohio Public Employees
Retirement System’s governance officer, also claims that LLAs are a “disservice to investors” (Rapoport 2005).
Gregory Smith, director of operations for the Investment Company Institute (ICI), also suggested that shareholders
would incorporate LLA clause information in their deliberation on auditor selection (Smith 2006).
1925

4.3.1 The average effect
The results reported in Table 9 show that the market reacts negatively to the November 28,
2005 WSJ publication. The mean market abnormal return on the day of the publication is −0.835%,
for a total market loss of $145.24 billion. We obtain this estimate by multiplying the market valueof each firm at the market close on November 27, 2005 by its abnormal return and then sum up
the losses for all the firms.
The results reported in Table 5 show that the Sun Microsystems experienced a substantiallymore negative return than the overall market when it disclosed the inclusion of the LLA clause in
its audit engagement letter (−2.49% versus −1.554%). We would then expect Sun Microsystems
to fare significantly better than the rest of the market when the WSJ article confirms that the LLA
practice is widespread, not being limited to Sun Microsystems. The results reported in Table 9 are
consistent with our expectations. While the overall market experienced a negative average raw(abnormal) return of −0.956% (−0.835%) on the day of the WSJ article publication, Sun
Microsystems actually experience a positive raw (abnormal) return of 0.513% (0.501%).
4.3.2 Cross-sectional variations: Regression model
Investors’ concerns about auditor independence are that the audit could be more lenient,
allowing managers to misreport. Therefore, if the loss in market value on the day of the WSJ

publication is due to concerns about auditor independence, then we expect the loss to be more
pronounced when a client’s incentives and ability to misreport are stronger. More specifically, we
expect the market reaction to the WSJ publication to be associated with a client’s financial
reporting quality, the extent to which a client’s recent reported earnings might seem suspicious,
the amount of equity recently issued by the client, the amount of stocks recently sold by insiders
on their own accounts, and the independence of the client’s board of directors.
We measure financial reporting quality by the average of the absolute value of a client’s
abnormal accruals over the five years prior to the WSJ publication. We sort the absolute value of26

the abnormal accruals into quintiles and create a variable, PoorQuality, which takes the value 0.5
if the absolute value of the abnormal accruals falls into the top quintile, -0.5 if it falls into thebottom quintile, and 0 otherwise. We proxy for the extent to which client’s recent reported earnings
might seem suspicious using a binary variable, JustMeet, which takes the value one if the client
meets the average analysts’ earnings forecast by two cents or less at least half of the time over thefour quarters prior to the event date and zero otherwise. We proxy for the managers’ incentives tomisreport by the extent of their trading activities in their companies’ stocks against outsiders.
Specifically, we use two binary variables: StockIssused and NetInsiderSelling. The former takes thevalue one if the client’s stock issuance (Compustat data item: SSTK) scaled by market value over
the year prior to the WSJ publication is in the top quintile and zero otherwise. The latter takes thevalue one if the market value of net selling by insiders over the year prior to the WSJ publication
is in the top quintile and zero otherwise. We use the proportion of external directors on a client’s
board of directors to proxy for board independence. Because the proportion of external directorsthat is necessary to constrain a manager’s incentives to misreport is not clearly determined, we use
two separate board independence variables, corresponding to two different thresholds:
BoardInd_Super and BoardInd_Simple. The former is a binary variable taking the value one if thefirm’s external board members make up more than 80 percent of the board over the year prior to
the event date and zero otherwise. The latter is a binary variable taking the value one if the firm’s
external board members make up more than 50 percent of the board over the year prior to the event
date and zero otherwise. In sum, we analyze the cross-sectional variations in investors’ reaction to
WSJ publication using the following regression model:
ABRET_NOVi = 1LogSizei + 2High_IOi + 3BMi + 4NBIG4i +5EYi +6PoorQualityi + 7JustMeeti + 8StockIssuedi + 9NetInsiderSellingi +10BoardInd_Superi +11BoardInd_simplei + Industry Fixed Effectsi +i(3)where ABRET_NOV is firm i’s abnormal returns on November 28, 2005, the day of the WSJ
publication; and the other variables are described as before.
27

The data needed to estimate abnormal accruals and the stock issuance data are obtained
from Compustat.20 Quarterly analyst earnings forecast data are obtained from the Institutional
Brokers Estimate System (IBES). Board of director information is obtained from the Institutional
Shareholder Services (ISS). We obtain insider trading data from the Thomson Financial Insider
Filings database. A total of 1,181 firms have all the necessary data. We create the binary variables
by sorting all the available observations in a respective dataset before we merge the datasets tocreate the final sample.
4.3.3 Cross-sectional variations: Results
The Pearson and Spearman correlations reported in Table 10 are consistent the notion thatthe market reaction to the WSJ publication is related to concerns about audit quality. Specifically,
the abnormal return is negatively correlated with PoorQuality, JustMeet, StockIssused, and
NetInsiderSelling; and it is positively correlated with BoardInd_Super. There is a quite strong
correlation between PoorQuality and JustMeet, consistent with firms that just meet benchmarks
being more likely to have poor earnings quality. It is remarkable that the correlation between
StockIssused and NetInsiderSelling is also quite strong, consistent with managers simultaneously
selling both on their firms’ accounts and on their own accounts. We also note that BoardInd_Superis negatively correlated with PoorQuality, JustMeet, StockIssused and NetInsiderSelling,
20

Abnormal accrual is measured by the residual from the Jones (1991) model. For each calendar year and two-digit
SIC-code industry, we estimate the following model using all firms that have the necessary data on Compustat:
TAi = 1 + 2∆SALESi + 3 PPEi + 4 LTAi + 5ASSETi +i,
where TA is total accruals (earnings before extraordinary items and discontinued operations minus operating cash
flows); ΔSALE is the annual change in sales; PPE is property, plant, and equipment at the beginning of the year; LTA
is the lag of total accruals (which controls for the fact that some firms inherently have higher accruals and accruals
are likely to be correlated over time); and ASSET is total assets at the beginning of the year. All the variables are scaled
by total assets at the beginning of the year. Deflating the model by assets transforms ASSET into a column of ones,
allowing us to estimate the model with a standard intercept. To mitigate the effect of outliers and errors in the data,
we delete the top and bottom percentiles of the deflated TA, ∆SALE, PPE, and LTA. We also require at least 20
observations for each estimation. We adjust the estimated abnormal accruals for performance using Kothari, Leone,
and Wasley’s (2005) procedure. For each year and each industry (two-digit SIC code), we create five portfolios withat least four firms each by sorting the data into quintiles based on the return-on-assets from the previous year. The
performance-matched abnormal accruals for a firm are the firm-specific abnormal accruals minus the mean abnormal
accruals for its respective industry-performance-matched portfolio.

28

consistent with a super-majority of outsiders on a board constraining opportunistic behaviors bymanagers. No pair of variables displays excessive correlation, mitigating multicolinearity
concerns.
The results of the regression analysis are reported in Table 11. Firms that fall in the top
quintile of abnormal accruals experience a more negative market reaction to the WSJ publication
than those that fall in the bottom quintile. The difference across the two groups is 0.412% and issignificant at the 5% level. Clients that have barely met analyst earnings forecasts also experiencea more negative market reaction than other clients. The difference across the two groups of 0.328%
is significant at the 1% level. These findings suggest that investors react more negatively to the
publication of the WSJ article when they have suspicions that the reported earnings numbers might
have been manipulated.
We also find that investors react much more strongly to the WSJ journal publication forfirms that recently issue stocks as well as those whose insiders have recently sold large amountsof stocks. More specifically, clients with stock issuance (Compustat data item: SSTK), scaled bymarket value, in the top quintile experience 0.452% more negative abnormal returns than otherclients. Similarly, clients with net insider selling in the top quintile experience 0.202% morenegative abnormal returns than other clients.21 These results strongly suggest that investors inferthat managers issuing stocks have strong incentives to misreport and that the opportunity to do so
is higher when auditor independence is impaired.
Moreover, we find that the market reaction to the WSJ article publication is attenuatedwhen a client has a super majority of outsiders on its board of directors. Specifically, clients thathave at least 80% of outsiders on their boards experience 0.212% higher abnormal returns thanthose that have less than 80% outsider representation. This difference is significant at the 5% level21

We do not scale insider trading because the incentives of a manager trading on his personal account is generally
more related to the dollar amount of the trade, as opposed to the ratio of that amount to the size of the firm. In any
case, we include size as a control variable in the regression model, reducing the probability that the coefficient on themarket value of insider trading would capture the effect of firm size. Managers’ wealth could be an important factor,
but we do not observe it.

29and is consistent with a lack of auditor independence being less concerning to investors when an
audit client’s board of directors is highly independent.
We also find that the negative market reaction to the WSJ article is significantly stronger
for firms that have large concentrations of institutional ownership than for other firms, which isconsistent with extant anecdotal evidence indicates that institutional investors strongly oppose the
LLA practice. We also observe that the loss in market value on the day of the WSJ article
publication is smaller for the clients of the non-Big 4 auditors than for the clients of the Big 4
auditors. The auditor-size effect is consistent with the fact the Big 4 auditors have presumably
more to lose from a loss of confidence in the audit process. If their clients pay higher audit fees
and are traded at a premium because their audit quality is considered superior, any negative shift
in investor perception of audit quality could have a more pronounced effect on the valuation of
their clients. Smaller audit clients generally face more pressure to accept LLA clauses.22 Moreover,smaller audit firms generally face higher risk because they audit more risky firms. Their survival
is also more at stake because of their limited ability to face punitive damages. The Big 4 firms also
have stronger incentives to protect their brand and avoid the dilution that would potentially be
associated with the adoption of LLA clauses. Therefore, once investors discover an LLA clause in
an engagement letter, they could assume that the practice is, or would become, more prevalent
among the non-Big 4 clients. However, the publication of the WSJ article was the first widespread
public dissemination of the LLA practice. In this article, Lynn Turner, a former SEC chief
accountant, linked the practice to the Big 4 firms, noting that “all four accounting firms aredemanding the companies include these liability cap clauses in their contracts".
The results suggest that investors believe that LLA clauses impair audit quality and that
audit quality impairment reduces firm value. We note, however, that the negative market reaction
by itself does not indicate whether investors favor LLA clauses or not. Because LLA clauses

22See the discussion at: http://www.ffiec.gov/press/comments /icba.pdf.

30

involve a tradeoff between a client's rights to freely sue its auditors and lower audit fees (Louis etal. 2019), investors could support an LLA clause even if it reduces audit quality. Audit fees are
generally in the public domain whereas engagement letters are not. Hence, while the negative
effects of LLA clauses were not impounded in stock price before the LLA disclosure, the positiveeffects of the lower audit fees were (when capitalized, these fees represent a non-negligible shareof firm value). Therefore, the market reaction to the LLA disclosure reflects only one side of theequation (the negative effects of the LLA clauses), whereas investors are likely to consider boththe benefit (lower audit fees) and the cost (lower audit quality). However, although the capitalized
value of audit fees is not trivial, the capitalized value of the discount that an auditor would offer toa client for accepting the LLA clauses cannot amount to anything close to the abnormal returns
that we observe.23 Therefore, the change in value associated with the LLA disclosure cannot be
attributed only to the potential audit fee differential associated with the LLA clauses. Instead, theresults suggest that the effect of the cost of capital increase associated with the negative investor
perception of the LLA clauses far exceeds the lower audit cost benefit.24
5. Summary
We find a significant reduction in shareholders' approval of their auditors after thedisclosure that audit engagement letters include LLA clauses. Moreover, we observe a substantial
decrease in the market value of Sun Microsystems, after it became the first publicly traded firm todisclose the existence of LLA clauses in its audit engagement letter, with the loss of value
extending to the entire US market. The extent of the market losses and the fact that Sun’s return

23In 2005, audit fee as a proportion of market value of equity was on average 0.237%. Even with a capitalization rate of 5% in

perpetuity, the removal of the LLA clauses would have to cause the average audit fee to increase by more than 20%% to result ina 1% decrease in firm value.
24To understand why this is plausible, it is sufficient to consider the extreme case where auditing is non-existent or unreliable.

Corporations would save all or most of the audit fees but their values would plummet because their cost of capital would increase
substantially.

31

was significantly more negative than the return for the overall market are supportive of the notionthat the market reacted negatively to Sun’s disclosure.
There were potential confounding events around Sun’s disclosure that could contaminate
our results. We show however that these events are unlikely to fully explain the results. Moreover,there is no evidence of any potentially contaminating event on the day when the WSJ publicized
the LLA practice, thereby providing a cleaner setting to test for investors’ perception of LLA. We
find a strong negative reaction to the WSJ publication, which supports the notion that investors
have a negative perception of LLA. Consistent with the reaction being associated with concerns
about audit quality, the loss is strongly related to clients’ incentives and ability to misreport.
Specifically, the loss is more pronounced when a firm’s earnings quality is low, the firm’s recent
reported earnings barely meet the average analyst earnings forecast, the firm has recently issued
stocks, and when the managers have recently sold stocks on their own accounts. The loss is
attenuated when outsiders constitute a super-majority of the firm’s board of directors. The
reduction in the market value of U.S. firms is also larger for the Big 4 than for the non-Big 4
clients, which is consistent with the fact that Big 4 auditors have presumably more to lose from aloss of confidence in the audit process.
Our results have implications not only for the debate around auditors' liability exemptions
but also for the literature on the value of audit quality in the U.S. Extant studies provide little
evidence that stock prices respond to auditor switches. Furthermore, while audit quality is often
proxied by the Big 4 versus non-Big 4 dichotomy, the validity of this proxy has recently beenquestioned. Overall, our empirical evidence suggests that U.S. investors attribute a substantial
premium to the external audits and that investors’ negative perception of audit quality has anadverse effect on firm value.

32

References
Chan, D., and S. Pae, 1998. An analysis of the economic consequences of the proportionate
liability rule. Contemporary Accounting Research 15, 457-480.
Dao, M., S. Mishra, and K. Raghunandan, 2008. Auditor tenure and shareholder ratification of theauditor. Accounting Horizons 22 (3): 297-314.
Dee, C., Lulseged, and T. Zhang, 2011. Client stock market reaction to PCAOB sanctions against
a Big 4 auditor. Contemporary Accounting Research 28, 263-291.
Dickey, J., 2008. Auditor liability “caps” – The politics of catastrophe. Securities Litigation
Report 5, 1-6.
Dodd, P., N. Dopuch, R. Holthausen, and R. Leftwich, 1984. Qualified audit opinions and stock
prices: Information content, announcement dates, and concurrent disclosures. Journal of
Accounting and Economics 6, 3-39.
Dodd, P., R. Holthausen, and R. Leftwich, 1986. Abnormal stock returns associated with media
disclosures of ‘subject to’ qualified audit opinions. Journal of Accounting and Economics 8,
93-118.
Donovan, J., R. Frankel, J. Lee, X. Martin, and H. Seo, 2014. Issues raised by studying DeFond
and Zhang - What should audit researchers do? Journal of Accounting & Economics 58, 227338.
Dopuch, N., R. Holthausen, and R. Leftwich, 1987. Predicting audit qualifications with financial
and market variables. The Accounting Review 62, 431-454.
Dye, R., 1993. Auditing standards, legal liability, and auditor wealth. Journal of Political Economy
101, 887-914.
Dye, R., 1995. Incorporation and the audit market. Journal of Accounting and Economics 19, 75114.
Francis, J., D. Nanda, and X. Wang, 2006. Re-examining the effects of regulation fair disclosureusing foreign listed firms to control for concurrent shocks. Journal of Accounting andEconomics 41, 271–292.
Healy, P. and K. Palepu, 2001. Information asymmetry, corporate disclosure, and the capital
markets: A review of the empirical disclosure literature. Journal of Accounting and Economics
31, 405–440.
Hermanson, D., J. Krishnan, and Z. Ye. 2009. Adverse Section 404 opinions and shareholder
dissatisfaction towards auditors. Accounting Horizons 24 (4): 391-409.
Huberman, G., and T. Regev, 2001. Contagious speculation and a cure for cancer: A nonevent thatmade stock prices soar. Journal of Finance 56, 387-396.
33

Hughes, J., 2009. SEC blocks auditor liability deals. Financial Times (online) March 10, 2009.
http://www.ft.com/intl/cms/s/0/0c242174-0dbb-11de-8ea3-0000779fd2ac.html#axzz2z3
wmPxOK
Jiang, J., I. Wang, and K. Wang, 2019. Big N auditors and audit quality: New evidence from quasiexperiments. The Accounting Review 94, 205-227.
Johnson, C., 2007. Accounting for the future: Down to four big firms and fearing the effects ofeven one more suit, the audit industry presses for legal relief. The Washington Post, March 9,
D.1.
Johnson W., and T. Lys, 1990. The market for audit services: Evidence from voluntary auditor
changes. Journal of Accounting and Economics 12, 281-308.
Klock, M., 1994. The stock market reaction to a change in certifying auditor. Journal of
Accounting, Auditing and Finance 9, 330-347.
Kothari, S.P., A. Leone, and C. Wasley, 2005. Performance matched discretionary accrual
measures, Journal of Accounting and Economics 39, 163-197.
Lawrence, A., M. Minutti-Meza, and P. Zhang, 2011. Can Big 4 versus Non-Big 4 differences inaudit-quality proxies be attributed to client characteristics? The Accounting Review 86, 259286.
Louis, H, T. Pearson, D. Robinson, M. Robinson and A. Sun, 2019. The effects of the extant
clauses limiting auditor liability on audit fees and overall reporting quality. Journal of
Empirical Legal Studies (Forthcoming).
Liu, L., K. Raghunandan, and D. Rama. 2009. Financial restatements and shareholder ratificationsof the auditor. Auditing: A Journal of Practice & Theory 28, 225-240.
Mahoney, J., 2006. Comment letter sent to Professional Ethics Committee (PEEC) -- AICPA.
http://www.aicpa.org/InterestAreas/ProfessionalEthics/Community/ExposureDrafts/Downloa
dableDocuments/2006Sept8CommentLetters101-16only.pdf.
Mishra, S., K. Raghunandan, and D. Rama. 2005. Do investors’ perceptions vary with types of
nonaudit fees? Evidence from auditor ratification voting. Auditing: A Journal of Practice &Theory 24 (2): 9-25.
Nichols, D. and D. Smith, 1983. Auditor credibility and auditor changes, Journal of Accounting
Research, 534-544.
Public Company Accounting Oversight Board - Standing Advisory Group, 2006. Emerging issue– The effects on independence of indemnification, limitation of liability, and other litigation-34

related clauses in audit engagement letters, Appendix A. http://www.pcaobus.
org/Standards/Standing_Advisory_Group/Meetings/2006/02-09/Indemnification.pdf.
Raghunandan, K. 2003. Nonaudit services and shareholder ratification of auditors. Auditing: A
Journal of Practice & Theory 22 (1): 155-163.
Rapoport, M., 2005. Auditing ‘liability caps’ face fire: Sun and Silicon Graphics disclose terms inproxies; investors call for openness. Wall Street Journal (online edition), Nov 28.
Reilly, D., 2006. Audit-engagement provisions raise queries more companies disclose pacts thatprevent suits, limit awards if accounting problems arise. Wall Street Journal (Online Edition),
March 6.
Reilly, D., and N. Koppel. 2008. Cendant case costs Ernst almost $300 million more. Wall Street
Journal (Online Edition), February 16.
Sainty, B., G. Taylor, and D. Williams. 2002. Investor dissatisfaction toward auditors. Journal of
Accounting, Auditing & Finance 17 (2): 111-136.
Securities and Exchange Commission (SEC), 2000. Revision of the commission’s auditor
independence requirements. Release Nos. 33-7919; 34-43602.
Securities and Exchange Commission (SEC), 2003. Codification of financial reporting policies.
Section 602.02.f.i.
Smith, G., 2006. Comment letter to the AICPA Professional Ethics Division. Re: Proposed
Interpretation 101-16, Indemnification, Limitation of liability, and ADR Clauses inEngagement Letters.
U.S. Chamber Study: Investors incur significant losses due to securities class actions. Feb. 28,
2014. https://www.uschamber.com/press-release/us-chamber-study-investors-incursignificant-losses-due-securities-class-actions
Walia, H., 2013. How to profit from rising interest rates? Forbes (July 12).
White, H. 1980. A heteroskedasticity-consistent covariance matrix estimator and a direct test forheteroskedasticity. Econometrica 48, 817–838.
Zimmerman, J., 2013. Myth: External financial reporting quality has a 1st order effect on firm
value. Accounting Horizons 27, 887-894.

35

Appendix: Variable description
ABRET_NOVACOVERAGE

AFTER

∆APP

= a firm’s abnormal returns on the day of the first WSJ publication on the issue of
LLA clauses in audit engagement letters on November 28, 2005. Data source:
CRSP.
= the number of analysts covering the firm in the last IBES analyst consensus
annual earnings forecast (the number of analysts is set to zero if the firm has noforecast). Data source: I/B/E/S.
= a binary variable taking the value one for the year after September 20, 2005
(the date of the first disclosure of LLA in audit engagement letters) and zerofor the year before September 20, 2005.
= the annual change in a firm’s auditor approval rate by shareholders in year t(which is either the year (365 days) before September 20, 2005 (the date of thefirst disclosure of LLA in audit engagement letters) or the year after September
20, 2005). Data source: RiskMetrics Group.

= a firm’s book-to-market value of equity at the end of the fiscal year. Data source:
COMPUSTAT.
BoardInd_Simple = a binary variable taking the value one if the firm’s external board members makeup more than 50 percent of the board over the year prior to the event date andzero otherwise. Data source: IRRC RiskMetrics.
BoardInd_Supera binary variable taking the value one if the firm’s external board members makeup more than 80 percent of the board over the year prior to the event date andzero otherwise. Data source: IRRC RiskMetrics.
= minimum percentage of the votes against the election of a director. Data source:
DIRVOTES
RiskMetrics Group.
= a binary variable taking the value one if the firm is audited by EY and zero
EYotherwise. Data source: COMPUSTAT.
GCO= an indicator variable that takes the value one if the firm receives a going concern
opinion during the fiscal year and zero otherwise. Data source: Audit Analytics.
ICW= an indicator variable that takes the value one if the firm has been identified tohave one or more internal control weaknesses and zero otherwise during the
fiscal year. Data source: Audit Analytics.
IO= the proportion of institutional ownership in the firm at the end of the fiscal year.
Data source: Thomson-Reuters Institutional Holdings (13F) Database.
High_IO= a binary variable taking the value one if the proportion of institutional ownershipin the firm at the beginning of the fiscal year is in the top quintile, and zerootherwise. Data source: Thomson-Reuters Institutional Holdings (13F)
Database.
JustMeet= a binary variable taking the value one if actual earnings meet or beat the average
analyst forecast by two cents or less at least half of the time over the four
quarters prior to the event date and zero otherwise. Data source: I/B/E/S.
LASSET= the logarithm of a firm’s total assets (ASSET) at the end of the fiscal year. Data
source: COMPUSTAT.
LogSize= the logarithm of the firm’s market value of equity (SIZE) at the end of the year
prior to the event date. Data source: COMPUSTAT.
BM

36

= a firm’s leverage (total debt/assets) ratio at the end of the fiscal year. Data
source: COMPUSTAT.
LOSS= an indicator variable that takes the value one if a firm’s net income for the fiscal
year is negative and zero otherwise. Data source: COMPUSTAT.
LTENURE= the natural logarithm of auditor tenure with the client. Data source:
COMPUSTAT.
= the ratio of nonaudit fees to audit fees during the fiscal year. Data source:
NASRATIO
Audit Analytics
NetInsiderSelling = a binary variable taking the value one if the market value of net insider
selling at a client over the year prior to the WSJ publication is in the top
quintile, and zero otherwise. Data source: Thomson Reuters.
NBIG4= a binary variable taking the value one if the firm is audited by a non-Big 4 audit
firms and zero otherwise. Data source: COMPUSTAT.
PoorQuality
is a binary variable taking the value -0.5 if the absolute value of a firm’s average
performance adjusted abnormal accruals is in the bottom quintile over the last
five years, 0.5 if it is in the top quintile, and zero otherwise. Data source:
COMPUSTAT.
RESTATE= an indicator variable that takes the value one if the firm restates its financial
statements during the fiscal year and zero otherwise. Data source: Audit
Analytics.
UNQUALIFIED = an indicator variable that takes the value one if the firm receives a clean audit
opinion and zero otherwise (i.e., if the firm receives an adverse opinion, no
opinion, a qualified opinion, or an unqualified opinion with additional
language). Data source: COMPUSTAT.
LEV

37

Table 1
Average characteristics of the firms used in the auditor ratification analysis∆IO∆LACOVERAGE∆LASSET
∆BM
∆LEV
∆GCO

(1)
Full sample(N = 1,994)
0.041 (0.000)
0.035 (0.000)
0.114 (0.000)-0.017 (0.000)-0.003 (0.191)-0.002 (0.083)(2)
Big 4 clients(N = 1,910)
0.040 (0.000)
0.033 (0.000)
0.114 (0.000)-0.017 (0.000)-0.002 (0.248)-0.001 (0.157)(3)
Non-Big 4 clients(N = 84)
0.068 (0.000)
0.070 (0.228)
0.116 (0.000)-0.015 (0.478)-0.009 (0.463)-0.012 (0.320)∆RESTATE

0.019 (0.037)

0.020 (0.025)-0.024 (0.567)∆LOSS∆UNQUALIFIED∆ICW-0.030 (0.000)
0.191 (0.000)
0.057 (0.000)-0.032 (0.000)
0.193 (0.000)
0.055 (0.000)

0.012 (0.708)
0.155 (0.004)
0.083 (0.070)∆NASRATIO-0.278 (0.000)-0.283 (0.000)-0.156 (0.000)∆DIRVOTESLTENURE-0.007 (0.252)
2.272 (0.000)-0.007 (0.238)
2.313 (0.000)

0.005 (0.111)
1.343 (0.000)

Notes: The variables are defined in the appendix, with ∆ being a one-year change indicator. The
statistics are reported for observations for the year (365 days) before September 20, 2005 (the dateof the first LLA disclosure) and the year after September 20, 2005. We hold the sample constantacross the two years. Two-tail p-values are reported in parentheses.

38

Table 2
Univariate comparison of the change in the ratification rate

Full Sample

Big 4 clients

Non-Big 4 clients(1)
Year before
September 20, 2005

(2)
Year after
September 20, 2005

Mean
1.39%
(0.000)N = 9971.38%(0.000)N = 963
1.58%(0.266)
N = 34Mean-0.43%[0.040]N = 997-0.44%[0.036]
N = 947-0.16%[0.457]
N = 50Median1.04%(0.000)N = 9971.00%(0.000)N = 963
1.64%(0.008)N = 34

Median-0.15%[0.057]
N = 997-0.15%[0.083]N = 947-0.16%[0.176]
N = 50(3)
Difference(2)-(1)Mean-1.82%[0.000]Median-1.19%[0.000]-1.82%[0.000]-1.15%[0.000]-1.74%[0.195]-1.79%[0.006]

Notes: This table reports the annual change in auditor ratification rates in the year (365 days)
before September 20, 2005 (the date of the first LLA disclosure) in Column (1) and the change inthe ratification rate in the year (365 days) after September 20, 2005 in Column (2). It also compares
the change in the ratification rate across the pre-disclosure year and the post-disclosure year in
Column (3). We use a constant sample across the two periods. One-tail p-values are reported insquare brackets for the change in the ratification rate in the post-disclosure year in Column (2) andfor the difference across the pre-disclosure year and the post-disclosure year in Column (3).
Because we have no prediction for the change in the ratification rate in the pre-disclosure year, we
report two-tail p-values in Column (1), which we report in parentheses.

39

Table 3
Simple correlations between the variables used in the auditor ratification analysis
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(1) ∆APP

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

-0.113 0.023 0.040 0.008 0.015 -0.040 0.014 -0.015 -0.062 0.040 -0.016 -0.104 0.035 0.019 0.002(0.000) (0.297) (0.073) (0.712) (0.493) (0.071) (0.518) (0.509) (0.006) (0.075) (0.473) (0.000) (0.116) (0.393) (0.939)(2) AFTER-0.154-0.177 -0.090 -0.082 0.110 -0.003 0.013 -0.115 0.110 -0.149 -0.098 0.154 0.017 0.050 0.040(0.000)(0.000) (0.000) (0.000) (0.000) (0.883) (0.564) (0.000) (0.000) (0.000) (0.000) (0.000) (0.454) (0.025) (0.075)(3) ∆IO
0.075 -0.221
0.192 0.127 -0.158 0.013 -0.091 0.037 -0.106 0.004 0.034 -0.026 -0.038 -0.083 0.055(0.001) (0.000)(0.000) (0.000) (0.000) (0.564) (0.000) (0.102) (0.000) (0.852) (0.134) (0.245) (0.094) (0.000) (0.014)(4) ∆LACOVERAGE
0.012 -0.112 0.119
0.160 -0.011 -0.018 -0.064 0.012 -0.048 0.002 -0.022 -0.035 0.023 -0.035 0.022(0.587) (0.000) (0.000)(0.000) (0.620) (0.426) (0.004) (0.602) (0.032) (0.927) (0.328) (0.123) (0.304) (0.119) (0.334)(5) ∆LASSET
0.030 -0.120 0.130 0.141
0.110 0.125 -0.025 0.000 -0.037 -0.017 0.013 -0.014 -0.033 -0.092 0.002(0.178) (0.000) (0.000) (0.000)(0.000) (0.000) (0.265) (0.985) (0.098) (0.460) (0.550) (0.526) (0.138) (0.000) (0.937)(6) ∆BM-0.013 0.103 -0.160 -0.032 0.045-0.168 -0.098 -0.029 0.010 0.019 0.020 0.003 0.018 0.009 0.002(0.550) (0.000) (0.000) (0.159) (0.046)(0.000) (0.000) (0.199) (0.641) (0.406) (0.368) (0.877) (0.435) (0.689) (0.924)(7) ∆LEV-0.012 0.065 -0.022 -0.012 0.102 -0.085
0.036 -0.002 0.066 -0.004 0.005 0.024 -0.079 -0.026 -0.015(0.584) (0.004) (0.333) (0.606) (0.000) (0.000)(0.110) (0.945) (0.003) (0.850) (0.831) (0.292) (0.000) (0.250) (0.508)(8) ∆GCO
0.023 0.013 -0.034 -0.033 -0.029 -0.036 0.015
0.002 0.075 -0.011 0.007 -0.002 -0.001 0.036 -0.056(0.298) (0.564) (0.134) (0.137) (0.195) (0.104) (0.500)(0.936) (0.001) (0.633) (0.753) (0.946) (0.973) (0.108) (0.012)(9) ∆RESTATE-0.012 -0.115 0.024 0.004 0.007 0.008 0.019 0.002-0.007 -0.079 0.271 0.025 0.050 0.010 -0.022(0.604) (0.000) (0.291) (0.858) (0.769) (0.734) (0.396) (0.930)(0.746) (0.000) (0.000) (0.256) (0.026) (0.642) (0.318)(10) ∆LOSS-0.027 0.110 -0.093 -0.032 -0.044 -0.004 0.083 0.076 -0.007-0.046 0.051 0.015 0.002 0.022 0.027(0.232) (0.000) (0.000) (0.150) (0.051) (0.869) (0.000) (0.001) (0.765)(0.040) (0.023) (0.516) (0.947) (0.320) (0.230)(11) ∆UNQUALIFIED 0.052 -0.154 0.027 0.001 0.003 0.029 -0.023 -0.010 -0.075 -0.045-0.080 -0.015 -0.035 -0.037 -0.015(0.021) (0.000) (0.227) (0.967) (0.910) (0.194) (0.305) (0.644) (0.001) (0.046)(0.000) (0.490) (0.117) (0.098) (0.510)(12) ∆ICW-0.006 -0.096 0.043 -0.026 -0.008 0.027 0.013 0.007 0.271 0.051 -0.077-0.039 0.010 -0.015 0.018(0.805) (0.000) (0.055) (0.244) (0.726) (0.236) (0.551) (0.745) (0.000) (0.022) (0.001)(0.082) (0.651) (0.499) (0.424)(13) ∆NASRATIO-0.186 0.334 -0.059 -0.022 -0.038 -0.012 0.071 0.004 -0.053 0.036 -0.071 -0.093-0.004 -0.003 0.027(0.000) (0.000) (0.008) (0.320) (0.091) (0.583) (0.002) (0.873) (0.018) (0.106) (0.002) (0.000)(0.853) (0.888) (0.231)(14) ∆DIRVOTES-0.019 -0.010 -0.043 0.032 0.004 -0.030 0.014 0.012 -0.009 0.022 -0.029 -0.003 0.025
0.009 0.009(0.395) (0.649) (0.056) (0.148) (0.868) (0.175) (0.522) (0.601) (0.676) (0.327) (0.200) (0.892) (0.262)(0.675) (0.676)(15) LTENURE
0.035 0.068 -0.087 -0.026 -0.074 0.001 -0.027 0.032 0.007 0.025 -0.031 -0.019 -0.042 -0.001-0.274(0.117) (0.000) (0.000) (0.252) (0.001) (0.962) (0.231) (0.154) (0.761) (0.265) (0.173) (0.395) (0.061) (0.969)(0.000)(16) NBIG4
0.003 0.040 0.039 0.017 -0.014 -0.012 -0.013 -0.056 -0.022 0.027 -0.016 0.019 0.043 0.025 -0.227(0.902) (0.075) (0.085) (0.459) (0.531) (0.591) (0.564) (0.012) (0.317) (0.228) (0.470) (0.393) (0.054) (0.258) (0.000)

40Notes: Spearman/Pearson correlations among the variables used in the auditor ratification tests are reported above/below the diagonallines. The variables are defined in the appendix, with ∆ being a one-year change indicator. The statistics are reported for observations
for the year (365 days) before September 20, 2005 (the date of the first LLA disclosure) and the year after September 20, 2005. We holdthe sample constant across the two periods. Two-tail p-values are reported in parentheses.

41

Table 4
Conditional association between the LLA disclosure and the change in auditor ratification
rate∆APPit = 1AFTERit + 2∆IOit + 3∆LASSETit + 4∆BMit +5∆LEVit +6∆LACOVERAGEit+7∆GCOit +8∆RESTATEit +9∆LOSSit +10∆UNQUALIFIEDit +11∆ICWit+ 12∆NASRATIOit +13∆DIRVOTESit + 14LTENUREit + 15NBIG4it+ 16NBIG4it×AFTERit + Firm Fixed Effectsit +it

AFTER
∆IO
∆LACOVERAGE∆LASSET
∆BM
∆LEV
∆GCO
∆RESTATE∆LOSS∆UNQUALIFIED∆ICW∆NASRATIO∆DIRVOTESLTENURE
NBIG4

(1)

(2)

-0.015(-3.30)0.000(0.00)
0.010(1.34)
0.008(0.60)
0.014(0.83)-0.056(-1.76)0.063(0.85)-0.003(-0.51)-0.013(-1.76)0.006(1.15)-0.005(-0.55)-0.005(-1.55)0.023(2.00)
0.005(0.33)-0.027(-0.87)-0.015(-3.20)0.000(0.01)
0.011(1.35)
0.008(0.59)
0.014(0.83)-0.056(-1.77)0.063(0.84)-0.003(-0.50)-0.013(-1.76)0.006(1.15)-0.005(-0.56)-0.005(-1.55)0.023(2.00)
0.005(0.33)-0.023(-0.64)-0.005(-0.23)Yes-0.241
1,994

NBIG4×AFTER
Firm FE
Adjusted R2
N

Yes-0.2401,99442Notes: The variables are defined in the appendix, with ∆ being a one-year change indicator. The
observations are for the year (365 days) before September 20, 2005 (the date of the first LLA
disclosure) and the year after September 20, 2005. We hold the sample constant across the two
periods. T-values are reported in parentheses.

43

Table 5
Stock market reaction to the first LLA clause disclosure

September
20, 2005
September
21, 2005
Total

Average raw return (%)

Average abnormal return (%)

Sun
US Market Difference
Microsystems (ex Sun)
-1.485-0.541-0.945(0.000)(0.000)Sun
US market Difference
Microsystems (ex Sun)
-1.363-0.526-0.836(0.000)(0.000)(0.000)-1.005-2.490-1.013(0.000)-1.554(0.000)0.008(0.421)-0.936(0.000)-1.058(0.000)-2.421(0.000)-1.175(0.000)-1.701(0.000)0.116(0.003)-0.720(0.000)Notes: We compute a firm’s return over a two-day window (0, 1) around the Sun Microsystems'
disclosure of an LLA clause in its audit engagement letter on September 20, 2005. We computethe abnormal returns using the following pooled regression:
RETi,t = 0 + 1ADRt + 2Event_Day0t + 3Event_Day1t + 4Suni, + 5Event_Day0t × Suni
+ 6Event_Day1t × Suni + Industry Fixed Effectsi + i,t,
where RETi,t is the return of firm i on day t; ADRt is the return of the ADR index on day t;
Event_Day0 is an indicator variable taking the value one for September 20, 2005 and zerootherwise; Event_Day1 is an indicator variable taking the value one for September 21, 2005 andzero otherwise; and Sun is an indicator variable taking the value one for Sun Microsystems andzero otherwise. The model is estimated over the six months ending on November 20, 2005 (or twomonths after the event date). The abnormal return on September 20 is 2 + 5 for Sun and 2 for
the US market (ex Sun). The abnormal return on September 21 is 3 + 6 for Sun and 3 for the
US market (ex Sun). Industry fixed effects are based on the two-digit SIC code classification. Onetailed p-values are reported in parentheses. We cluster the standard errors at the firm level tocontrol for cross-sectional correlations.

44

Table 6
The effects of contaminating events on the cumulative abnormal returns (CAR) aroundSun’s LLA clause disclosure: Counterfactual evidencePanel A: Market reaction to FOMC rate increases from May 3, 2005 to January 31, 2006
Announcement date
5/3/2005
6/30/2005
8/9/2005

Average CAR (%)
0.126
0. 400-0.856

Two-tail p-value
0.024
0.000
0.000

9/20/2005
11/1/2005-1.550-0.076

0.000
0.180

12/13/2005
01/31/2006-0.038
0.260

0.394
0.000

Panel B: Returns for those firms that are most likely to benefit from short-term rate increases
Announcement date→
Average CAR (%)
Two-tail p-value

Pre-9/20/2005
0.223
0.554

9/20/2005-1.244
0.002

Post-9/20/2005
0.175
0.404

Panel C: Returns for those firms that are most likely to benefit from hurricanes
Event date→
Average CAR (%)
Two-tail p-value

9/20/2005-1.8500.004

Notes: We compute a firm’s return over a two-day window (0, 1) around the event date, using thefollowing pooled regression:
RETi,t = 0 + 1ADRt + 2Event_Day0t + 3Event_Day1t + Industry Fixed Effectsi + i,t,
where RETi,t is the return of firm i on day t; and ADRt is the return of the ADR index on day t. In
Panels A and B, Event_Day0 is an indicator variable taking the value one for a given FOMC
interest rate increase announcement date and zero otherwise and Event_Day1 is an indicatorvariable taking the value one for the trading day after the interest rate increase announcement dateand zero otherwise. The model is estimated over the period starting on February 3, 2005 and ending
on April 30, 2006. CAR for a given date is the sum of 2 + 3. Industry fixed effects are based on
the two-digit SIC code classification. We cluster the standard errors at the firm level to control forcross-sectional correlations. In Panel B, the pre-9/20/2005 (post-9/20/2005) period covers the three
FOMC rate hike announcements that immediately preceded (followed) the September 20, 2005
announcement. A firm is deemed to generally benefit from short-term rate increases if it is in one
45

of the following industries: Insurance agents, brokerage, and service; security brokerage andflotation; commodity contracts brokerage; and payroll processing. In Panel C, Event_Day0 is anindicator variable taking the value one on September 20, 2005 and zero otherwise and Event_Day1
is an indicator variable taking the value one on September 21, 2005 and zero otherwise. The modelis estimated over the six months ending on November 20, 2005. A firm is deemed to generally
benefit from hurricanes if it is in one of the following industries: Building materials, hardware,and mobile home dealers; pumps and pumping equipment; heavy construction other than building
construction contractors; and construction special trade.

46

Table 7
Stock market reaction to the first LLA clause disclosure: EY vs. Non-EY clients
Average raw return (%)

September
20, 2005
September
21, 2005
Total

EY clients
Others(N = 1,182) (N = 4,292)-0.610-0.521-1.213-0.959-1.823-1.479Difference-0.090(0.269)-0.254(0.002)-0.344(0.002)Average abnormal return (%)
EY clients
OthersDifference(N = 1,182) (N = 4,292)-0.579-0.511-0.068(0.405)-1.384-1.117-0.267(0.001)-1.962-1.627-0.335(0.003)

Notes: We compute a firm’s return over a two-day window (0, 1) around the Sun Microsystems'
disclosure of an LLA clause in its audit engagement letter on September 20, 2005. We computethe abnormal returns using the following pooled regression:
RETi,t = 0 + 1ADRt + 2Event_Day0t + 3Event_Day1t + 4EYi, + 5Event_Day0t × EYi+ 6Event_Day1t × EYi + Industry Fixed Effectsi + i,t,
where RETi,t is the return of firm i on day t; ADRt is the return of the ADR index on day t;
Event_Day0 is an indicator variable taking the value one for September 20, 2005 and zerootherwise; Event_Day1 is an indicator variable taking the value one for September 21, 2005 andzero otherwise; and EY is an indicator variable taking the value one for the EY clients and zerootherwise. The model is estimated over the six months ending on November 20, 2005 (or twomonths after the event date). The abnormal return on September 20 is 2 + 5 for the EY clientsand 2 for the non-EY clients. The abnormal return on September 21 is 3 + 6 for the EY clientsand 3 for the non-EY clients. Industry fixed effects are based on the two-digit SIC codeclassification. One-tailed p-values are reported in parentheses. We cluster the standard errors at
the firm level to control for cross-sectional correlations.

47

Table 8
Stock market reaction to the first LLA clause disclosure: Impact of institutional ownership
Average raw return (%)

September
20, 2005
September
21, 2005
Total

High IO(N=1,095)-1.008Others(N=4,379)-0.423-1.616-0.863-2.624-1.286

Average abnormal return (%)

Difference-0.585(0.000)-0.753(0.000)-1.338(0.000)High IO(N=1,095)-0.960

Others(N=4,379)-0.417-1.785-1.022-2.745-1.438Difference-0.543(0.000)-0.764(0.000)-1.307(0.000)Notes: We compute a firm’s return over a two-day window (0, 1) around the Sun Microsystems'
disclosure of an LLA clause in its audit engagement letter on September 20, 2005. We computethe abnormal returns using the following pooled regression:
RETi,t = 0 + 1ADRt + 2Event_Day0t + 3Event_Day1t + 4High_IOi, + 5Event_Day0t
× High_IOi + 6Event_Day1t × High_IOi + Industry Fixed Effectsi + i,t,
where RETi,t is the return of firm i on day t; ADRt is the return of the ADR index on day t;
Event_Day0 is an indicator variable taking the value one for September 20, 2005 and zerootherwise; Event_Day1 is an indicator variable taking the value one for September 21, 2005 andzero otherwise; and High_IO is an indicator variable taking the value one if a firm’s proportion of
institutional ownership at the beginning of the year is in the top quintile, and zero otherwise. The
model is estimated over the six months ending on November 20, 2005 (or two months after the
event date). The abnormal return on September 20 is 2 + 5 for the High_IO group and 2 for theother firms. The abnormal return on September 21 is 3 + 6 for the High_IO group and 3 for theother firms. Industry fixed effects are based on the two-digit SIC code classification. One-tailed pvalues are reported in parentheses. We cluster the standard errors at the firm level to control forcross-sectional correlations.

48

Table 9
Average stock market reaction to the November 28, 2005 WSJ article

US Market
Sun Microsystems

Raw return (%)

Abnormal return (%)-0.956(0.000)0.513-0.835(0.000)0.501(0.000)Notes: We compute a firm’s return on the day of the first WSJ publication on the issue of LLA
clauses in audit engagement letters. We compute abnormal returns using the following regression:
RETi,t = 0 + 1ADRt + 2Event_Dayt + 3Suni, + 4Event_Dayt × Suni + Industry Fixed Effectsi+ i,t, where RETi,t is the return of firm i on day t; ADRt is the return of the ADR index on day t;
Event_Day is an indicator variable taking the value one for November 28, 2005 and zero otherwise.
Industry fixed effects are based on the two-digit SIC code classification. The model is estimatedover the six months starting September 28, 2005 (or two months before the event date). The modelis estimated as a pooled regression, with the standard errors clustered at the firm level to control
for cross-sectional correlations.

49

Table 10
Simple correlations between the variables used in the return analysis
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(1) ABRET_NOV

0.223 -0.109 -0.073 -0.012 -0.020 -0.165 -0.046 -0.105 -0.055 0.070 0.016(0.000) (0.000) (0.013) (0.671) (0.497) (0.000) (0.111) (0.000) (0.058) (0.016) (0.594)(2) LogSize
0.162-0.111 -0.302 -0.209 0.005 -0.210 0.004 -0.026 0.358 0.093 0.014(0.000)(0.000) (0.000) (0.000) (0.866) (0.000) (0.887) (0.374) (0.000) (0.001) (0.632)(3) High_IO-0.086 -0.137-0.010 0.001 0.047 0.078 -0.005 0.068 0.096 0.061 0.018(0.003) (0.000)(0.739) (0.974) (0.108) (0.007) (0.871) (0.020) (0.001) (0.036) (0.538)(4) BM-0.042 -0.297 -0.014
0.063 -0.002 -0.134 -0.131 0.063 -0.259 -0.018 0.015(0.151) (0.000) (0.627)(0.030) (0.957) (0.000) (0.000) (0.029) (0.000) (0.537) (0.604)(5) NBIG4
0.019 -0.203 0.001 0.073-0.135 0.063 -0.033 -0.035 -0.070 -0.069 -0.001(0.520) (0.000) (0.974) (0.013)(0.000) (0.030) (0.250) (0.229) (0.016) (0.018) (0.974)(6) EY-0.006 0.003 0.047 0.013 -0.135
0.046 -0.006 0.006 0.024 -0.049 -0.070(0.836) (0.909) (0.108) (0.654) (0.000)(0.114) (0.849) (0.846) (0.406) (0.090) (0.016)(7) PoorQuality-0.122 -0.201 0.083 -0.120 0.066 0.046
0.125 -0.011 -0.030 -0.055 0.042(0.000) (0.000) (0.004) (0.000) (0.024) (0.113)(0.000) (0.707) (0.311) (0.059) (0.154)(8) JustMeet-0.062 0.015 -0.005 -0.113 -0.033 -0.006 0.129-0.007 0.074 -0.061 -0.059(0.034) (0.595) (0.871) (0.000) (0.250) (0.849) (0.000)(0.817) (0.011) (0.037) (0.043)(9) StockIssued-0.119 -0.055 0.067 0.041 -0.034 0.006 -0.006 -0.003
0.141 -0.057 0.011(0.000) (0.057) (0.022) (0.158) (0.238) (0.831) (0.836) (0.905)(0.000) (0.050) (0.699)(10) NetInsiderSelling -0.048 0.342 0.096 -0.243 -0.070 0.024 -0.030 0.074 0.141-0.051 0.005(0.100) (0.000) (0.001) (0.000) (0.016) (0.406) (0.304) (0.011) (0.000)(0.081) (0.870)(11) BoardInd_Super 0.070 0.091 0.061 -0.009 -0.069 -0.049 -0.052 -0.061 -0.060 -0.051
0.191(0.016) (0.002) (0.036) (0.747) (0.018) (0.090) (0.073) (0.037) (0.040) (0.081)(0.000)(12) BoardInd_Simple 0.010 0.021 0.018 0.006 -0.001 -0.070 0.043 -0.059 0.011 0.005 0.191(0.724) (0.465) (0.538) (0.839) (0.974) (0.016) (0.140) (0.043) (0.708) (0.870) (0.000)

Notes: Spearman/Pearson correlations are reported above/below the diagonal lines. We computeabnormal returns by estimating the following regression for each firm: RETt = 0 + 1ADRt +2Event_Dayt + Industry Fixed Effectsi + t, where RETt is the firm's return on day t; ADRt is thereturn of the ADR index on day t; Event_Day is an indicator variable taking the value one for November
28, 2005 and zero otherwise. The model is estimated over the six months starting September 28, 2005
(or two months before the November 28, 2005 event date). LogSize is the logarithm of the firm’s market
value of equity (SIZE) at the end of the year prior to the event date. High_IO is a binary variable taking
the value one if the proportion of institutional ownership in the firm at the beginning of the year is in
the top quintile, and zero otherwise. BM is the firm’s book-to-market value of equity at the end of
the year prior to the event date. NBIG4 is a binary variable taking the value one if the firm is audited
by a non-Big 4 audit firm and zero otherwise. EY is a binary variable taking the value one if the firm
is audited by EY and zero otherwise. PoorQuality is a binary variable taking the value -0.5 if theabsolute value of a firm’s average performance adjusted abnormal accruals is in the bottom quintile
over the last five years, 0.5 if it is in the top quintile, and zero otherwise. JustMeet is a binary
variable taking the value one if actual earnings meet or beat the average analyst forecast by twocents or less at least half of the time over the four quarters prior to the event date and zerootherwise. StockIssused takes the value one if the client’s stock issuance (Compustat data item: SSTK)
scaled by market value over the year prior to the WSJ publication is in the top quintile, and zerootherwise. NetInsiderSelling takes the value one if the market value of net insider selling at a client
over the year prior to the WSJ publication is in the top quintile, and zero otherwise. BoardInd_Super50

is a binary variable taking the value one if the firm’s external board members make up more than 80
percent of the board over the year prior to the event date and zero otherwise. BoardInd_Simple is abinary variable taking the value one if the firm’s external board members make up more than 50 percentof the board over the year prior to the event date and zero otherwise. The industry fixed effects are
based on two-digit SIC codes. All the independent variables are measured at the end of, or over, theyear prior to the event date, November 28, 2005. We create the binary variables by sorting all theavailable observations in a respective dataset before we merge the datasets to create the final sample.

51

Table 11
Cross-sectional variations in the market reaction to the November 28, 2005 WSJ article:
Multivariate analysis
ABRET_NOVi = 1LogSizei +2High_IOi + 3BMi + 4NBIG4i +5EYi + 6PoorQualityi+7JustMeeti +8StockIssuedi + 9NetInsiderSellingi +10BoardInd_Superi+11BoardInd_Simplei + Industry Fixed Effectsi +i

LogSize
High_IOBM
NBIG4EY
PoorQuality
JustMeet
StockIssued
NetInsiderSelling
BoardInd_super
BoardInd_simple
Industry FE
Adjusted R2
N

(1)

(2)

0.258
(6.70)-0.202(-2.02)0.166(0.77)
0.496(1.65)
0.005(0.05)-0.412(-2.20)-0.328(-3.15)-0.452(-3.87)-0.202(-2.04)0.212(2.20)
0.062(0.28)
Yes
0.203

0.259
(6.69)-0.201(-2.01)0.167(0.77)
0.496(1.65)
0.003(0.03)-0.409(-2.19)-0.330(-3.16)-0.452(-3.86)-0.202(-2.04)0.217(2.26)
Yes
0.203
1,181

Notes: We compute abnormal returns by estimating the following regression for each firm: RETt = 0
+ 1ADRt + 2Event_Dayt + Industry Fixed Effectsi + t, where RETt is the firm's return on day t; ADRt
is the return of the ADR index on day t; Event_Day is an indicator variable taking the value one for
November 28, 2005 and zero otherwise. The model is estimated over the six months starting September
28, 2005 (or two months before the November 28, 2005 event date). LogSize is the logarithm of thefirm’s market value of equity (SIZE) at the end of the year prior to the event date. High_IO is a binary
variable taking the value one if the proportion of institutional ownership in the firm at the beginningof the year is in the top quintile, and zero otherwise. BM is the firm’s book-to-market value of equity52

at the end of the year prior to the event date. NBIG4 is a binary variable taking the value one if thefirm is audited by a non-Big four audit firm and zero otherwise. EY is a binary variable taking the value
one if the firm is audited by EY and zero otherwise. PoorQuality is a binary variable taking the value-0.5 if the absolute value of a firm’s average performance adjusted abnormal accruals is in thebottom quintile over the last five years, 0.5 if it is in the top quintile, and zero otherwise. JustMeet
is a binary variable taking the value one if actual earnings meet or beat the average analyst forecastby two cents or less at least half of the time over the four quarters prior to the event date and zerootherwise. StockIssused takes the value one if the client’s stock issuance (Compustat data item: SSTK)
scaled by market value over the year prior to the WSJ publication is in the top quintile, and zerootherwise. NetInsiderSelling takes the value one if the market value of net insider selling at a client
over the year prior to the WSJ publication is in the top quintile, and zero otherwise. BoardInd_Superis a binary variable taking the value one if the firm’s external board members make up more than 80
percent of the board over the year prior to the event date and zero otherwise. BoardInd_Simple is abinary variable taking the value one if the firm’s external board members make up more than 50 percentof the board over the year prior to the event date and zero otherwise. The industry fixed effects are
based on two-digit SIC codes. All the independent variables are measured at the end of, or over, theyear prior to the event date, November 28, 2005. We create the binary variables by sorting all theavailable observations in a respective dataset before we merge the datasets to create the final sample.
We use White's (1980) heteroskedastic consistent standard errors to compute the t-values.

530.895
0.89

Auditor ratification rate

0.885
0.88
0.875
0.87
0.865
0.86
0.855
0.85
-3

-2

-1

0

1

2

3

Year relative to the first LLA disclosure date
Mean

MedianFigure 1: Time-series pattern of auditor ratification rate. Year 0 is the year after the September
20, 2005 disclosure by Sun Microsystems of an LLA clause in its audit engagement letter.

54