1

Corporate Litigation and Changes in Executive Reputation

Chelsea Liu1

Business School

The University of Adelaide

chelsea.liu@adelaide.edu.au

Abstract

When public companies are accused of breaching the law, their CEOs can experience

reputational damage even in the absence of fraud allegations. Using a hand-collected sample

of filed and settled environmental, antitrust, intellectual property, and contractual lawsuits in

the US Federal Courts from 2000 through 2007, I document poorer reemployment prospects

for CEOs who depart from the sued companies following the lawsuits. However, the natures

of the allegations and the lawsuit outcomes are important in predicting the reputational

penalties. A key policy issue arises because post-litigation declines in executive reputation

occur only following contractual lawsuits, but not politically sensitive environmental

allegations.

Keywords executive reputation, corporate litigation, corporate governance, executive labor

market, lawsuits.

JEL code G30

1 I am grateful to Professors Joseph Aharony, Bernard Black, Martin Bugeja, Paul Brockman, Stephen Brown,

Espen Eckbo, Robert Faff, Edward Kane, Jun-Koo Kang, Michael Klausner, Michael Lemmon, Zoltan

Matolcsy, Stephen LeRoy, Donghui Li, Kate Litvak, Ron Masulis, Roberta Romano, Greg Schwann, Garry

Twite, Peter Wells, Sue Wright, Alfred Yawson, David Yermack, and participants at The 2011 Journal of

Contemporary Accounting and Economics Doctoral Consortium, The 2012 Accounting and Finance Association

of Australia and New Zealand Doctoral Colloquium, The 6th Conference on Empirical Legal Studies

(Northwestern University), The 7th Conference on Empirical Legal Studies (Stanford University), The 2013

UTS Early Career Accounting Researcher Consortium, The 2013 AFAANZ Annual Conference, Research

Seminars at the University of Adelaide, University of Technology Sydney, and Macquarie University for their

helpful feedback and suggestions. This paper was awarded the Best Paper Award (Corporate Governance

stream) at the 2013 AFAANZ Annual Conference.

2

1. Introduction

Corporate litigation can be a double-edged sword for the reputations of chief executive

officers (‘CEOs’). On the one hand, as the public faces of listed firms, CEOs may take a hit

to their personal reputation when their companies allegedly breach the law, despite the

absence of any personal culpability. This was amply illustrated by the disrepute suffered by

BP’s Tony Hayward following the environmental lawsuits over the Gulf of Mexico oil spill

(Webb and Miedema, 2011). On the other hand, a firm’s encounter with lawsuits may allow

the CEO to develop or demonstrate the ability to effectively deal with the dispute, thus

enhancing the executive labor market’s assessment of her experience and skillset.

Employing a sample of lawsuits filed and settled against the Standard & Poor’s 1,500

companies in the US Federal Courts between 2000 and 2007, including environmental,

antitrust, intellectual property, and contractual lawsuits, this paper examines three questions

that add to our understanding of the executive labor market.

First, following non-fraud lawsuits against public companies, do their CEOs experience

a decline or an improvement in personal reputation? Prior studies document that CEOs do

suffer reputational damage following securities fraud allegations against their companies

(Karpoff, Lee, and Martin, 2008b; Fich and Shivdasani, 2007).2 Securities fraud is usually

perpetrated against investors – a stakeholder group with direct power to penalize the

offending managers. It remains unknown, however, whether CEOs will suffer equal

reputational penalties when the plaintiffs/complainants are external stakeholder groups. The

results shed light on the operation of the executive labor market, in particular, how alleged

breaches of the law by corporations are penalized by impaired executive reputation. In light

2 I also collect data on securities lawsuits filed against the S&P1,500 companies during the 2000-2007 period.

Given that prior literature has documented the role of securities lawsuits in predicting a decline in CEO

reputation (Desai, Hogan, and Wilkins 2006; Fich and Shivdasani 2007; Collins, Reitenga, and Sanchez 2008;

Correia and Klausner 2012), in order to avoid the potential confounding effects of securities lawsuits, I exclude

from the dataset all firm-years with securities lawsuit filings during the (0,+2) period in the empirical analysis.

3

of the increasing importance of corporate social responsibility (Mahoney and Thorne, 2005;

Deegan, Rankin, and Tobin, 2002; Callan and Thomas, 2011), these results inform

shareholders, regulators, and lawmakers as to any market-based deterrent that serves to

prevent companies from breaking the law.

Secondly, what type of allegation is most significantly associated with reputational

penalties? Politically sensitive allegations such as environmental violations may be expected

to lead to greater reputational penalties, because of their significant impacts on society

(Bhagat, Bizjak, and Coles, 1998). A competing view is that reputational penalties are only

imposed following contractual lawsuits, where the plaintiffs have the power to penalize the

sued firms through the process of repeated contracting (Karpoff, Lott, and Wehrly, 2005;

Murphy, Shrieves, and Tibbs, 2009). Given the implied social contracts under which a public

company operates (Alrazi, de Villiers, and van Staden, 2015; Mitchell, Agle, and Wood,

1997), the type of lawsuit, to which the executive labor market responds in imposing

reputational penalties, can shed light on corporate attitudes towards various stakeholder

groups.

Thirdly, does lawsuit merit and magnitude matter in predicting the change in CEO

reputation? Given the high volume of frivolous lawsuits filed in the US courts (Eisenberg and

Lanvers, 2009), it is important to determine whether the executive labor market is able to

distinguish meritorious allegations from frivolous ones.

I examine two measures of executive reputation: (i) the reemployment prospects of

CEOs in the event of departures within two years following the lawsuit filings, and (ii) the

change in the number of outside directorships held by the CEO during the two-year period

following lawsuits. The empirical evidence from this paper contributes to the existing

literature in the following respects:

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First, this paper documents changes in CEO reputation following non-fraud lawsuits,

which extends the focus of existing research beyond securities fraud (Collins, Reitenga, and

Sanchez, 2008; Desai, Hogan, and Wilkins, 2006; Correia and Klausner, 2012; Fich and

Shivdasani, 2007). In the absence of allegations of fraud against shareholders, CEOs can

nonetheless experience reputational penalties in the form of poorer reemployment prospects,

even when the alleged misdemeanor is perpetrated against stakeholders external to the firm.

These results are robust after controlling for potential endogeneity associated with different

litigation risks faced by companies.

Second, the change in CEO reputation differs significantly following various types of

lawsuit. These differences provide insights into corporate attitudes towards each type of

allegation, and towards the stakeholder group commonly involved as complainants. Declines

in CEO reputation occur only following contractual lawsuits, where the plaintiffs usually

have existing contractual relationships with the sued firms, because these plaintiffs have the

power to penalize the sued firms by increasing their future costs through the process of

repeated contracting. In contrast, the more socially culpable environmental lawsuits are

generally disregarded. Some evidence suggests a marginal improvement in director

reputation following intellectual property lawsuits, which commonly involve disputes with

competitors over IP rights.

Third, lawsuit merit, as proxied by outcomes, significantly predicts the change in CEO

reputation. CEOs are more likely to face poorer reemployment prospects if they depart

following drawn-out lawsuits with non-terminating outcomes. Conversely, for those CEOs

who remain with the sued firms, their reputation is likely to improve, as evidenced by

increased outside directorships, if lawsuits featuring larger demands for compensation are

defended in court by the sued firms. This evidence is consistent with the view that, from an

executive perspective, litigation appears to be a double-edged sword. If a CEO departs from a

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company in the wake of lawsuits, she is likely to face impaired reemployment prospects,

especially following contractual disputes. However, for those CEOs who successfully retain

their jobs, they may experience an average increase in reputation, potentially attributable to

the additional litigation experience, which is regarded favorably by the executive labor

market.

2. Literature Review and Hypothesis Development

Labor market forces and reputational concerns have a disciplining effect on managers

of corporations with a separation of ownership and control (Fama et al., 1969; Jensen and

Meckling, 1976). This study investigates the change in reputation experienced by CEOs of

public companies, which have been accused of breaching the law.

Prior studies have investigated the impacts of securities fraud allegations on the

reputation of the accused firms (Karpoff, Lee, and Martin, 2008a; Dyck, Morse, and

Zingales, 2010), their executive officers (Collins, Reitenga, and Sanchez, 2008; Desai,

Hogan, and Wilkins, 2006; Correia and Klausner, 2012) and directors (Brochet and

Srinivasan, 2014; Gao et al., 2014; Srinivasan, 2005; Yermack, 2004). Allegations of

securities fraud are documented to adversely affect managerial reputation (Alexander, 1999;

Desai, Hogan, and Wilkins, 2006; Fich and Shivdasani, 2007), because the alleged

wrongdoings are perpetrated against shareholders, who directly possess the power to

discipline management. 3 However, shareholders are not the only salient stakeholder group in

the context of a public company (Mitchell, Agle, and Wood, 1997). Public corporations

operate under an implied social contract (Jamali, 2008; Deegan, Rankin, and Tobin, 2002),

3 Several different types of securities fraud have been examined by prior researchers, including earnings

restatements (Agrawal and Cooper, 2007; Srinivasan, 2005; Desai, Hogan, and Wilkins, 2006), shareholders

class actions (Niehaus and Roth, 1999; Strahan, 1998; Correia and Klausner, 2012), securities derivative actions

(Romano, 1991; Ferris et al., 2007; Cheng et al., 2010), and SEC enforcement actions (Beneish, 1999; Karpoff,

Lee, and Martin, 2008b; Correia and Klausner, 2012).

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where different stakeholder groups other than shareholders play important roles in

determining a firm’s legitimacy (Alrazi, de Villiers, and van Staden, 2015). The roles of these

stakeholders cannot be adequately captured by examining securities fraud alone.

Distinguishable from prior research, this study investigates the reputational

consequences experienced by CEOs when their firms face a variety of legal allegations,

including environmental violations, antitrust breaches, intellectual property infringements,

and contractual disputes. Each type of lawsuit is likely to involve a different stakeholder

group as plaintiffs. In environmental lawsuits, the alleged victims are often members of the

local community, usually with no direct contractual relationships with the sued firms.

Antitrust lawsuits are frequently brought by regulatory or consumer bodies. Intellectual

property lawsuits usually involve competitors disputing over the use of IP. Finally, in

contractual lawsuits, the plaintiffs are parties with whom the sued firms have existing

contractual relationships. By examining the change in CEO reputation following the

allegations of corporate wrongdoing from these different stakeholder groups, the evidence

sheds light on the attitudes of public corporations to their various stakeholders, as collectively

manifested through the operation of the executive labor market.

Drawing on prior literature, two measures of executive reputation are employed. First,

I examine the reemployment prospects of CEOs following their departures from their existing

employers (Collins, Reitenga, and Sanchez, 2008; Desai, Hogan, and Wilkins, 2006; Correia

and Klausner, 2012). Increased CEO turnover is a significant mechanism for disciplining

executive officers of public companies (Arthaud-Day et al., 2006; Srinivasan, 2005; Niehaus

and Roth, 1999; Humphery-Jenner, 2012). However, “for such discipline to be effective, it is

necessary that the managerial labor market also views the departure as informative and

imposes further discipline in the form of ex post settling up” (Desai, Hogan, and Wilkins,

2006, 103). In the context of securities fraud, prior studies document declines in executive

7

reputation following the allegations. Desai, Hogan, and Wilkins (2006) find that, following

accounting restatements between 1997 and 1998, CEOs tend to face poorer prospects of

being reemployed at a public or private firm for similar office-holdings, when they depart

from the restating firms within 2 years. Collins, Reitenga, and Sanchez (2009) find similar

penalties experienced by CFOs following accounting restatements. Correia and Klausner

(2012) study a sample of securities class actions filed between 2000 and 2011, and find that

amongst the displaced officers, CEOs facing SEC enforcement proceedings are less likely to

find reemployment, potentially attributable to the officer and director bars imposed by the

SEC.

Second, I observe the change in the number of major board seats held by the CEOs in

other corporations. The number of outside directorships is a well-documented proxy for

executive reputational capital (Gilson, 1990; Kaplan and Reishus, 1990; Knyazeva,

Knyazeva, and Masulis, 2013; Wu, 2004). Fich and Shivdasani (2007) find that, following

allegations of securities fraud between 1998 and 2006, independent directors of the accused

firms face increased risk of losing board seats held in other firms, evidencing a decline in

their reputation. Similarly, Srinivasan (2005) examines the reputation of the outside directors

of 409 firms with earnings restatements between 1997 and 2001, and documents an average

loss of 25% of the directorships on other boards. In contrast, Helland (2006) documents that,

following securities lawsuits between 1985 and 2002, directors experience a net increase in

the number of other board seats over an eight-year sampling period.

Based on the prior studies examining securities fraud allegations, firstly it is a priori

expected that CEOs of sued companies would experience declines in reputation as a result of

the legal allegations, in the forms of impaired prospects of finding comparable reemployment

and net losses of outside directorships held on the boards of other companies.

8

Second, it is a priori expected that lawsuits of greater economic magnitude and

stronger legal merit are more likely to be followed by impaired reputation for the sued

companies’ executives. By examining the role of these lawsuit-specific characteristics, this

study provides further insights into the ways in which the executive labor market operates to

impose reputational penalties.

Third, competing theories exist with respect to what types of allegations are most likely

to damage the reputation of sued companies and their executives. On the one hand, politically

sensitive allegations, such as environmental violations, are expected to lead to greater

reputational penalties, because of their significant impacts on society (Bhagat, Bizjak, and

Coles, 1998). On the other hand, an alternative theory suggests that reputational penalties are

only imposed, when the legal disputes are brought by parties with existing contractual

relationships with the company (such as customers or suppliers in contractual lawsuits).

Researchers (Karpoff, Lott, and Wehrly, 2005; Murphy, Shrieves, and Tibbs, 2009) argue

that only parties with such pre-existing contractual relationships possess the power to

discipline the sued companies, by increasing their costs of operation through repeated

contracting. In contrast, under this theory, alleged victims in environmental lawsuits (usually

local residents) lack such direct contractual power to impose market-based penalties on the

alleged offenders. Given the alternative theories, this study provides empirical evidence on

which of the two more accurately depicts the operation of the executive labor market in

imposing reputational penalties on the sued companies’ executives.

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3. Litigation Data and Research Design

3.1. Sample Construction and Data Collection

The sample of corporate litigation filed against US public companies is collected from

the Public Access to Court Electronic Records (PACER) database, which hold records of

litigation filed in the United States Federal Courts. The data gathering procedures are similar

to those adopted in the studies by Haslem (2005) and Bhattacharya, Galpin, Haslem (2007).4

First, searches are conducted within the PACER database for all lawsuits filed between

1 January 2000 and 31 December 2007, which fall into one of the following categories

examined in this paper: environmental lawsuits, antitrust lawsuits, intellectual property

infringements, and contractual disputes.5 The sampling period, which ends on 31 December

2007, allows subsequent time during which to observe any ensuing change in CEO

reputation. The initial search yields a total of 191,135 lawsuit filings.

In the second stage, from the initial pool of 191,135 lawsuits, I remove lawsuits that do

not involve a company with available data from the Compustat Executive Compensation

(‘Execucomp’) Database and RiskMEtrics Directors Database. Execucomp Database

provides data on the Standard & Poor’s 1,500 companies. A total number of 1,671 companies

are included, from which 18 companies are excluded due to either missing accounting data

from Compustat or missing board data from RiskMetrics. The final sample consists of 1,653

companies; 16,901 lawsuits are filed against one of these companies as a first-named

defendant from 2000 through 2007.

4 As identified by prior researchers (Bhattacharya, Galpin, and Haslem, 2007; Haslem, 2005), a significant

advantage of gathering corporate litigation data from the PACER database, rather than from newspaper sources

such as the Wall Street Journal, is that PACER provides information on all lawsuits filed in the US federal

courts. By obtaining lawsuit data directly from the court filings, this data collection method avoids media bias.

The resultant litigation sample covers a much more comprehensive range of lawsuits, not necessarily those

reported in a certain media outlet. 5 Data on securities securities lawsuits filed during the sampling period are also collected, for the purpose of

replicating the results from prior studies investigating securities lawsuits. In order to avoid the confounding

effects of securities lawsuits, in the regression analysis, all firm-years with securities lawsuits filed are removed

from the dataset.

10

In the third stage, individual court dockets for these 16,901 lawsuits are downloaded

from the PACER database, from which litigation-specific information, such as lawsuit

disposition, is manually extracted. Only lawsuits that result in ‘settlement’, as defined by

Eisenberg and Lanvers (2009) to proxy the plaintiff’s litigation success, are included in the

final litigation sample.6 After excluding those lawsuits that do not satisfy the definition of

‘settlement’, the final lawsuit sample consists of 9,959 lawsuits filed against the 1,653 firms.

3.2. Litigation Descriptive Statistics

Table 1 reports the breakdown of corporate lawsuits by filing year and lawsuit

category. Panel A reports the total number of lawsuits filed; Panel B reports the number of

settled lawsuits included in the final litigation sample. Approximately 59% of the filed

lawsuits are classified as settled. In particular, 6,330 contractual lawsuits result in settlements,

constituting 61% of the filed lawsuits, which is similar to the settlement rate of 58.9%

amongst contractual lawsuits reported by Eisenberg and Lanvers (Eisenberg and Lanvers,

2009, 130).

Across the eight-year period, no general linear trend is observable in the annual volume

of lawsuits. The number of settled contractual lawsuits peaks in 2002 and 2005.

Environmental and antitrust lawsuits do not exhibit any notable temporal pattern. The number

of settled intellectual property lawsuits follows an upward trajectory during the sample

period, consistent with observations made by Choi (2010).

Among the four types of litigation, contractual lawsuits account for 63.65% of the

sample of settled lawsuits, confirming the view that corporate contractual disputes constitute

6 For the purpose of constructing the lawsuit sample, settlement is defined in accordance with Eisenberg and

Lanvers (2009)’s measure which proxies for ‘plaintiff’s success’ in the lawsuits. Lawsuits are classified as

settled if one of the following dispositions are recorded: settled, dismissal - want of prosecution, judgment on

default, judgment on consent, dismissal - voluntarily, dismissal - other, and judgment on statistical closing

(Eisenberg and Lanvers, 2009, 116-117). According to Eisenberg and Lanvers, this definition of ‘settlement’ of

lawsuits serves as a proxy for plaintiff success.

11

the largest category of US federal civil suits (Bhagat, Bizjak, and Coles, 1998). Intellectual

property lawsuits and antitrust lawsuits constitute 24.88% and 8.64%, respectively, of the

final sample of settled lawsuits, leaving 2.92% attributable to environmental lawsuits.

[Insert Table 1]

4. Empirical Results

4.1. Univariate Analysis

Table 2 reports the univariate analysis (in mean and median) for those firm-years in

which at least one lawsuit is filed against the company which subsequently results in

settlement; while the control sample comprises firm-years in which no lawsuit is filed against

the company. Results are reported from the test of difference in the mean, and the test of

difference in the median, between the lawsuit sample and the control sample.

The mean likelihood for a CEO to gain reemployment after departing from the

company (RETOP3t(0,+2),t(-1,+2)) is not significantly different (at the 10% level) between the

lawsuit and control sample. No significant difference in mean or median is observed for the

change in number of outside directorships over the (0,+2) period. However, the mean change

in the number of outside directorships over the (-1+2) period (∆DIRECTt(-1,+2)) is marginally

higher in the lawsuit sample than the control sample, the difference being statistically

significant at the at 1% level.

Amongst the firm-level control variables, the lawsuit sample appears to exhibit larger

average firm size (LogTAt-1) and marginally better average performance (ROAt-1) than the

control sample (significant at the 1% level). Amongst the executive-level control variables,

CEOs within the lawsuit sample are more likely to be internally appointed, with a lower level

12

of stock ownership and a shorter duration of tenure, and holding a greater number of existing

outside directorships on the boards of other firms (all differences in the mean are significant

at the 1% level).

[Insert Table 2]

4.2. CEO Reemployment Prospects

For lawsuits to have real disciplinary effects on CEOs, the CEOs must not only lose

their jobs, but also experience subsequent difficulties in obtaining comparable reemployment.

This paper examines the reemployment prospects of those CEOs who depart from the sued

firms during the periods surrounding the lawsuits. In the probit model, the dependent variable

RETOP3t(0,+2) is a dummy variable that takes on the value of one if the CEO, who departs

from the sued firm during the (0,+2) period following the lawsuit, subsequently obtains

reemployment as the CEO, president, or chairman of the board at another S&P1,500

company. An alternative observation period (-1,+2) is employed to capture any preemptive

CEO departures in year -1 in anticipation of imminent lawsuits. The dataset in this section

consists of firm-years with CEO turnovers over the (0,+2) period (excluding those turnovers

caused by deaths). In order to avoid the confounding effect of securities litigation, all firm-

years with securities lawsuits are excluded from the analysis.

011010

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LAWSUITt=0 is first specified as a dummy variable in Models (1) and (2), which is

assigned a value of one if the company has experienced one or more lawsuit filings during the

(0,+2) period that result in settlement, and zero otherwise. Additionally, the LAWSUITt=0

variable is alternatively specified as a continuous variable in Models (3) and (4) to capture

the number of lawsuits filed during the (0,+2) period that result in settlement. As reported in

Table 3, the estimated coefficient of the dummy variable LAWSUITt=0 is negative and

significant at the 5% level in predicting RETOP3t(-1,+2) in Model (2). This indicates that,

holding all else constant, if any lawsuit is filed against the CEO’s existing employer prior to

her departure, the CEO faces diminished prospects of finding comparable reemployment

elsewhere.7 When the LAWSUITt=0 variable is specified as a continuous variable in Models

(3) and (4), its estimated coefficient remains negative but is no longer statistically significant

in predicting RETOP3t(0,+2),t(-1,+2).

[Insert Table 3]

In Models (5) to (8) of Table 3, the encounter with settled lawsuits is disaggregated by

the nature of the allegations. A set of individual lawsuit-category variables (ENVt=0, ANTt=0,

IPt=0, and CONt=0) are employed in lieu of a single LAWSUITt=0 variable, each representing (as

a dummy and continuous variable in turn) the encounter with environmental, antitrust,

intellectual property, and contractual lawsuits, respectively, during the (0,+2) period that

result in settlement.

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7 The magnitudes of Adjusted R-square observed from these regressions are consistent with prior research

(Desai, Hogan, and Wilkins, 2006).

14

As reported in Table 3, environmental lawsuits (ENVt=0) are not significant in predicting

CEO reemployment prospects, in spite of the anecdotal example of BP’s oil spill causing

substantial reputational damage to its CEO. Contractual lawsuits alone are significant in

predicting a decline in CEO reemployment prospects. The estimated coefficient of the

dummy variable CONt=0 is negative and significant (at the 10% and 5% levels, respectively)

in predicting RETOP3t(0,+2) and RETOP3t(-1,+2) in Models (5) and (6). The estimated coefficient

of the continuous variable CONt=0 is also negative in predicting RETOP3t(0,+2),t(-1,+2), significant

at the 5% and 1% levels in Models (7) and (8), respectively. These results indicate that a

company’s encounter with contractual lawsuits is significantly associated with diminished

career prospects for its departing CEO, especially when the number of lawsuits is taken into

account to capture multiple lawsuits.8 On average, CEOs who exit from sued companies are

less likely to find reemployment comparable to the positions they have just vacated. These

results support the expectation that the executive labor market imposes penalties on CEOs

whose firms encounter contractual lawsuits. Contractual lawsuits involve parties who have

existing contractual relationships with the sued companies (typically customers, suppliers,

and trading partners). Prior literature suggests that only such parties, through the process of

repeated contracting, are capable of penalizing the sued companies (Karpoff, Lott, and

Wehrly, 2005; Murphy, Shrieves, and Tibbs, 2009). On the other hand, alleged victims in

environmental violations are usually third parties (local residents), with no direct contractual

power to penalize the alleged offenders.

In contrast, in Models (7) and (8), the estimated coefficient of intellectual property

lawsuits (IPt=0) is positive and significant at the 5% and 1% levels, respectively, in predicting

8 The predictive power of the continuous variable CONt=0 is more significant than that of its dummy counterpart.

This indicates that the number of lawsuits filed plays a significant role in determining subsequent CEO

reemployment prospects. This is consistent with prior research, which documents that multiple lawsuits within a

short time period have greater impacts on the sued firms than single isolated lawsuits (Atanasov, Ivanov, and

Litvak, 2012).

15

RETOP3t(0,+2) and RETOP3t(-1,+2). These results indicate that, far from suffering a decline in

reputation in the form of poorer reemployment prospects, CEOs whose companies have

encountered intellectual property lawsuits are more likely to find reemployment upon

departing from the sued firms. This observation is potentially attributable to the experience

acquired by the CEO from defending IP lawsuits, which are highly specialized and often

complicated. Such litigation experience may be regarded by the executive labor market as a

valuable attribute, in light of the increasing frequency of IP disputes (Choi, 2010).

Amongst the control variables included in Table 3, firm size (LogTAt-1) is positive and

significant at the 1% level in predicting RETOP3t(0,+2),t(-1,+2). Firm performance (ROAt-1) is also

positive and significant (at the 10% level) in Models (2) and (4) in predicting RETOP3t(-1,+2),

consistent with the expectation that CEOs exiting from larger and better-performing firms are

more likely to find reemployment. Amongst the CEO-specific characteristics, GENDERt=0 (a

dummy variable denoting female executives) is positive and significant at the 1% level,

indicating that female CEOs are more likely to find reemployment post-turnover. Affirmative

action is a potential but unlikely explanation, because RETOP3t(0,+2),t(-1,+2) captures only

reemployment as the CEO, president, or chairman of the board within a firm, but not non-

executive positions on the board (where female executive officers might be appointed to

enhance diversity). Given the patriarchal corporate environment, arguably women must have

demonstrated superior abilities to their male counterparts to break through the glass ceiling

and become CEOs (Erhardt, Werbel, and Shrader, 2003; Davidson, 2002). Therefore, the

better reemployment prospects associated with female CEOs may be attributable to their

inherently higher managerial quality.

The degree of CEO entrenchment is captured by three variables. Firstly, internally

appointed CEOs (INTERNALt=0) are less successful at gaining reemployment elsewhere, as

evidenced by the negative estimated coefficient significant at the 1% level. Second,

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TENUREt=0 (measuring duration of service) also exhibits significant negative explanatory

power at the 1% level, indicating that CEOs who have served longer in their positions are less

likely to find post-turnover reemployment. Third, EXECOWNt=0 measures the CEO’s

ownership of common stock. Its estimated coefficient is consistently negative, and is

significant at the 5% and 10% levels in predicting RETOP3t(0,+2) in Models (1), (3), (5), and

(7) of Table 3. These results show that more entrenched CEOs face a reduced likelihood of

finding comparable jobs elsewhere upon leaving their firms.

Finally, two variables are included to capture the potential reasons for CEO turnover.

First, the dummy variable RETAINt=0 equals one if the CEO continues to be employed by the

company for a year or more after stepping down as its CEO, usually as part of a succession

plan. RETAINt=0 therefore serves as a proxy for retirement. Its estimated coefficient is

negative and significant at the 10% level, indicating that the retained (possibly retiring) CEOs

are less likely to seek reemployment. Secondly, the dummy variable RESIGNt=0 equals one if

the CEO’s departure is accompanied by an announcement of her resignation. The positive

estimated coefficient is consistently significant at the 1% level in predicting CEO

reemployment prospects. This is potentially attributable to the fact that a CEO is more willing

to publicly resign from her company if she is confident of comparable job opportunities

elsewhere.

4.3. Changes in Outside Directorships

Even when a CEO of a sued company does not experience turnover following the

lawsuits, she may nonetheless experience another form of reputational penalty by a loss of

existing directorships held on the boards of other companies. The following ordinary least

square (OLS) regressions are estimated.9 In Equations (3) and (4) below, the dependent

9 In all OLS regressions, White heteroscedasticity-consistent standard errors are employed.

17

variable ∆DIRECTt(0,+2) is calculated as the change in the number of outside directorships held

by the CEO over the observation period from year 0 through year +2. An alternative

dependent variable ∆DIRECTt(-1,+2) is calculated over the (-1,+2) observation period. The

regressions are estimated using a dataset consisting of firm-years which do not experience

CEO turnovers during the observation periods.

110

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(4)

As reported in Models (1) and (2) of Table 4, the estimated coefficient of the dummy

variable LAWSUITt=0 is positive and significant at the 5% and 1% levels in predicting

∆DIRECTt(0,+2) and ∆DIRECTt(-1,+2), respectively. However, when lawsuit filings are measured

by a continuous variable in Models (3) and (4), the estimated coefficient of LAWSUITt=0

remains positive but is no longer statistically significant. When different categories of lawsuit

are disaggregated in Models (5) and (6), contractual lawsuits (CONt=0) are significantly

associated with an increase in the number of outside directorships over the (0,+2) and (-1,+2)

periods, at the 10% and 1% levels, respectively. Furthermore, the estimated coefficient of the

dummy variable IPt=0 is positive and significant at the 1% level in predicting ∆DIRECTt(-1,+2)

in Model (6). In Models (7) and (8), when the lawsuit filings are represented by continuous

variables, antitrust lawsuits (ANT=0) alone are significantly associated with an increase in both

∆DIRECTt(0,+2) and ∆DIRECTt(-1,+2), at the 5% and 1% levels, respectively.

18

The evidence suggests that, far from being penalized by experiencing losses of outside

directorships, CEOs of firms that have experienced settled lawsuits appear to gain additional

board seats. This is potentially attributable to the experience of combating litigation, which is

considered by corporate boards to be a desirable quality in an outside director. One important

distinction between these observations and those from the previous section, which show a

decline in CEO reputation following contractual lawsuits, is that in this part of the analysis,

the sample consists of those firm-years in which the CEOs do not experience turnover. If a

CEO is retained by a sued firm, then the evidence suggests that she would not experience

reputational penalties by losing outside board seats. It is also noteworthy that not even

environmental lawsuits, which are the most socially culpable type of allegations, are

associated with any loss of outside directorships. Given the catastrophic consequences of

environmental violations by large companies, this evidence raises doubts over the ability and

inclination of the executive labor market to penalize CEOs for alleged socially irresponsible

behaviors by their companies.

[Insert Table 4]

Amongst the control variables in Table 4, the proportion of outside directors on the

board (%OUTSIDEt-1) is positive and significant at the 5% and 1% levels in predicting

∆DIRECTt(0,+2) and ∆DIRECTt(-1,+2), respectively. Consistent with the view that appointing

CEOs as outside directors is a reciprocal practice amongst corporations (Fich and White,

2005), if a firm appoints more outside directors, the broadened network can enable the CEO

to be appointed onto the boards other companies. Additionally, the estimated coefficients of

TENUREt=0 and NUMDIRt–1 are both negative and significant at the 1% level. CEOs with a

shorter duration of tenure, indicating less entrenchment, are more likely to experience a net

19

gain in outside directorships. CEOs who already hold a large number of existing directorships

are less likely to take up additional appointments due to over-commitment of time.

5. Robustness Tests

5.1. Restricted Sample for Individual Lawsuit Categories

A firm can experience more than one type of lawsuit at any given time. In order to

isolate the predictive power of individual categories of lawsuit, in this section of the

robustness analysis, the regressions in the previous sections are re-estimated to examine IPt=0

and CONt=0 in isolation, by employing a restricted sample that excludes any firm-years with

lawsuit filings in any other category during the (0,+2) period.

As reported in Models (1) to (4) of Table 5, Equation (1) which predicts CEO

reemployment prospects is re-estimated by replacing LAWSUITt=0 with IPt=0, in order to

examine the predictive power of intellectual property lawsuits. The estimated coefficient of

the dummy or continuous variable IPt=0 is statistically insignificant in predicting

RETOP3t(0,+2),t(-1,+2).

As reported in Models (5) to (8) of Table 5, Equation (1) is further re-estimated to

examine contractual lawsuits (CONt=0), by employing a restricted sample excluding any firm-

years that experience other types of lawsuit (environmental, antitrust, or intellectual property

lawsuits) during the (0,+2) period. In Model (6), the estimated coefficient of the dummy

variable CONt=0 is negative and significant at the 5% level in predicting CEO reemployment

prospects. Similarly, the continuous variable CONt=0 is also significant with a negative

estimated coefficient at the 10% and 5% levels, respectively, in predicting RETOP3t(0,+2) and

RETOP3t(-1,+2) in Models (7) and (8). These results confirm the robustness of the evidence

20

from Table 3, that contractual lawsuits are significantly associated with poorer reemployment

prospects for CEOs exiting from the sued firms.

[Insert Table 5]

Similarly, Equation (3) which predicts the change in the CEO’s outside directorships is

re-estimated, by employing ENVt=0, ANTt=0, IPt=0, and CONt=0 as the key independent variable

in turn, and employing a restricted sample of observations excluding firm-years with lawsuits

filed in other categories during the (0,+2) period. As reported in Model (1) of Table 6, the

estimated coefficient of the dummy variable ENVt=0 is positive and significant at the 10%

level in predicting the change in CEO outside directorships over the (0,+2) period, but the

statistical significance does not persist in Model (2). In Models (3) and (4), antitrust lawsuits

(ANTt=0) are not statistically significant in predicting ∆DIRECTt(-1,+2). Consistent with the

results reported in Table 4, the dummy variable IPt=0 is significant at the 5% level, with a

positive estimated coefficient of 0.075 (which is similar to the estimated coefficient of 0.080

in Table 4) in predicting ∆DIRECTt(-1,+2) in Model (5). Furthermore, in Models (7) and (8),

contractual lawsuits, as captured by both the dummy and continuous variable CONt=0, are

significant (at the 1% and 5% levels, respectively), in predicting the change in the number of

board seats held by the CEO. Consistent with the evidence from Table 4, following

intellectual property lawsuits and contractual lawsuits that result in settlement, those CEOs

who do not lose their jobs tend to experience an increase in the number of outside

directorships held, potentially attributable to the executive labor market favorably regarding

such litigation experience.

[Insert Table 6]

21

5.2. Propensity Score Matching

For robustness analysis, the regressions predicting CEO reemployment prospects in

Equations (1) and (2) are re-estimated using a propensity score matched dataset, where the

control sample is matched on the basis of five criteria: firm size, performance, leverage,

market-to-book ratio, and industry (using the three-digit SIC code). Further, using the

propensity score matched dataset, Equations (3) and (4) are also re-estimated to predict the

change in the number of directorships.

In the untabulated results, the significance of the estimated coefficients of key

independent variables remains unchanged from those discussed in sections 4.2 and 4.3. In the

regressions predicting CEO reemployment prospects, the dummy LAWSUITt=0 variable

remains negative and significant at the 10% and 5% levels, in predicting RETOP3t(0,+2) and

RETOP3t(-1,+2). The estimated coefficient of the continuous variable IPt=0 remains positive and

significant in predicting RETOP3t(0,+2),t(-1,+2). The estimated coefficient of CONt=0 remains

negative and significant at the 5% level, indicating that the encounter with contractual

lawsuits is associated with a decline in CEO reputation as proxied by reemployment

prospects. In the re-estimated regressions predicting ∆DIRECTt(0,+2),t(-1,+2), the dummy

variables IPt=0 and CONt=0 remain significant at the 1% level in predicting a positive change

in the number of outside directorships held by the CEO. Similarly, the estimated coefficient

of the continuous variable ANTt=0 remains positive and significant at the 1% and 5% levels in

predicting ∆DIRECTt(0,+2) and ∆DIRECTt(-1,+2). Overall, these results confirm the robustness of

those reported in Table 3 and Table 4.

5.3. Lawsuits with Large Demands for Pecuniary Compensation

As an additional robustness test, I re-construct the sample of lawsuits by including only

those lawsuit filings with demands for pecuniary compensation that exceed $1 million. I

22

obtain data on the amount of pecuniary compensation sought by the plaintiffs in the lawsuits

from the court dockets on each lawsuit obtained from the PACER Database. In the re-

estimation of Equations (1) and (2) to predict CEO reemployment prospects, the dummy

variable LAWSUITt=0 equals one if any lawsuit is filed against the firm during the (0,+2)

period with a recorded demand for pecuniary compensation exceeding $1 million. Similarly,

the dummy variables IPt=0 and CONt=0 equal one if any such lawsuits are filed in the category

of intellectual property and contractual lawsuits, respectively. In the untabulated results, the

estimated coefficient of IPt=0 (expressed as a dummy or a continuous variable) is consistently

positive and significant (at the 5% level) in predicting RETOP3t(0,+2),t(-1,+2). Contractual

lawsuits (as represented by the dummy and continuous variable CONt=0) remain negatively

and significantly associated with RETOP3t(-1,+2) at the 5% level. These results confirm the

robustness of those reported in Table 3, and show that CEOs whose firms encounter

contractual lawsuits face poorer reemployment prospects upon departure from the sued firms,

and those who depart following intellectual property lawsuits are more likely to gain

reemployment.

5.4. Alternative Measure of Reemployment

An alternative measure of reemployment, REEMPLOYt(0,+2),t(-1,+2), is employed in the re-

estimation of Equations (1) and (2) in Section 4.2, to capture a broad range of positions. In

lieu of RETOP3t(0,+2),t(-1,+2), the dependent variable REEMPLOYt(0,+2),t(-1,+2) equals one if a CEO

who departs during the (0,+2) or (-1,+2) period subsequently gains reemployment at another

S&P1,500 company in any senior executive capacity, including (apart from CEO, president,

and chairman) vice president, chief financial officer, chief operating officer, or as a non-

23

executive director. 10 In the untabulated results, the estimated coefficients and statistical

significance of the key litigation variables remain consistent with those reported in Section

4.2.

5.5. Heckman Selection Model

Endogeneity is a potential issue given that different firms face varying levels of

litigation risks. I utilize the two-stage Heckman (1979) Selection Model to control for

potential selection bias that may arise from these different levels of litigation risks. In the

first-stage regression, I estimate a binary probit model predicting the likelihood for a firm to

encounter litigation. Apart from the control variables from the original model, two

instrumental variables (‘IV’s) are included: organizational complexity (SEGt-1) and litigious

industry (RISKINDQt-1). In the second-stage, I estimate the two measures of executive

reputation, by including the inverse Mills ratio (lambda) calculated from the first-stage

regression, and the continuous test variable LAWSUITt=0 measuring the number of lawsuits

filed during the (0,+2) period.

The first IV SEGt-1 represents the number of business segments of a firm at the

beginning of year 0, as reported in the Compustat Segment Database. Firms with more

complex structures are a priori expected to be more exposed to legal liabilities, arising from

their more diverse areas of operations (Cohen and Lou, 2012). The second IV RISKINDQ

captures the inherent litigation risk associated with industry (Field, Lowry, and Shu, 2005).

As a dummy variable, it is assigned a value of one if a firm’s two-digit Standard Industry

Classification (SIC) code is amongst the top quartile of the most litigious industries during

the 2000-2007 sampling period, and zero otherwise.11

10 REEMPLOY is a cumulative measure in relation to RETOP3. For those displaced CEOs who have a value of

one recorded for RETOP3, they would also have a value of one recorded for REEMPLOY. 11 Consistent with the a priori expectation, in the untabulated first-stage regression the IVs are statistically

significant (at the 5% level) in predicting the firm’s likelihood to encounter litigation.

24

To ascertain whether the results from the original regression models are driven by

selection bias, I employ the Hausman (1978) Test to examine whether the key independent

variable LAWSUITt=0 exhibits endogeneity (Feng, Li, and McVay, 2009; Larcker and

Rusticus, 2010). In the first stage regression I include SEGt-1 and RISKINDQ as IVs, the

residual from which is included in the original regression as an additional explanatory

variable.12 If the coefficient on this additional variable is significant, the Hausman test rejects

the null position of no endogeneity. The residual variable in the untabulated results is not

significant at the 10% level, indicating that the null hypothesis of no endogeneity cannot be

rejected.13

In the untabulated second-stage results from the Heckman Selection Model,

LAWSUITt=0 remains negative and statistically significant (at the 5% level) in predicting

RETOP3t(0,+2),t(-1,+2) and REEMPLOYt(0,+2),t(-1,+2), consistent with the original empirical findings.

Similarly, in the second-stage regression predicting ∆DIRECTt(0,+2), the estimated coefficient

of LAWSUITt=0 is significant and positive (at the 5% level). Further, the persistent statistical

insignificance of the Inverse Mills Ratio (lambda) at the 10% level supports the view that the

original results are not driven by any selection bias.

To address the exclusion criteria (Larcker and Rusticus, 2010; Lennox, Francis, and Wang, 2012), I regress the

second-stage dependent variables, RETOP3t(0,+2),t(-1,+2) / REEMPLOYt(0,+2),t(-1,+2) and ∆DIRECTt(0,+2),t(-1,+2), on the

instrumental variables as regressors. Both SEGt-1 and RISKINDQ are not statistically significant at the 10%

level, providing support for the a priori view to justify the exclusion of the IVs from the second-stage

regressions. 12 An alternative specification uses the fitted LAWSUIT*t=0 rather than the residuals from the first regression

(Larcker and Rusticus, 2010, 191), and produces identical results. 13 As pointed out by Larcker and Rusticus (2010), an Over-Identifying Restriction Test is required as a

prerequisite to a valid Hausman Test, where the number of instrumental variables exceeds the endogenous

variables (as it does in this case). Accordingly, I run the Over-Identifying Restriction Test by regressing the

second-stage residual on all exogenous variables, including IVs (Feng, Li, and McVay, 2009; Larcker and

Rusticus, 2010), to determine the appropriateness of the instruments. If the instruments are valid, the R2 from

this model should be close to zero and not statistically significant (Larcker and Rusticus, 2010). In the

untabulated results, the R2 from the model is <0.001 and not significantly different from zero, thus providing

support for the choice of the instruments.

25

5.6. Probability of CEO Turnover

A condition precedent of a CEO finding reemployment is that he must depart from his

original employer. Conversely, a CEO must have remained at his existing employer for the

change in outside directorships data to be available. Prior studies have modeled the

probability of CEOs being displaced following legal allegations (Burks, 2010; Niehaus and

Roth, 1999; Karpoff, Lee, and Martin, 2008b). In order to account for the role of the

probability of CEO turnover in the original regressions, I re-run the regressions predicting

CEO reemployment prospects and loss of outside directorships, by including an additional

explanatory variable TURNOVER_FITt=0. TURNOVER_FITt=0 represents the predicted

likelihood of CEO turnover as estimated from a separate regression over the entire dataset.14

In the untabulated results, after including TURNOVER_FITt=0 as an explanatory variable in

the models predicting ∆DIRECTt(0,+2),t(-1,+2), RETOP3t(0,+2),t(-1,+2) and REEMPLOYt(0,+2),t(-1,+2), the

estimated coefficient and statistical significance of the key independent variables remain

consistent with those discussed in the preceding section.

6. Lawsuit-specific Characteristics

In the US federal judicial system, filed lawsuits vary significantly in economic scale

and legal merit. I further investigate the roles of these lawsuit-specific characteristics in

predicting the reputational penalties experienced by the CEOs of the sued companies. In this

section, I re-run Equations (1) and (3) over a sub-sample of the dataset, comprising only firm-

years with at least one lawsuit filed during the (0,+2) period. In order to examine the roles of

lawsuit merit, as proxied by outcomes, all lawsuit filings (not restricted to settled lawsuits)

14 The following regression is run to estimate the likelihood of CEO turnover and to generate the fitted value of

the dependent variable:

0807

061514131201)2,1(),2,0(%

tt

tttttttt

TENUREEXECOWN

CEOAGEOUTSIDEBSIZEROALogTALAWSUITTURNOVER

26

are included in this robustness analysis. In lieu of the LAWSUITt=0 variable, I include the

following test variables to examine the roles of lawsuit characteristics:

Firstly, I capture the economic magnitude of a lawsuit by observing the amount of

monetary compensation sought by the plaintiff(s). The test variable DEMANDALL–t=0 is

calculated as the cumulative sum of demands for compensation in all lawsuits filed against

the company during the (0,+2) period, scaled by firm size (total assets) at the beginning of

year 0. Larger lawsuits are more likely to be followed by CEO reputational penalties, ceteris

paribus.

Second, I use lawsuit outcomes as an indicator of the legal merit of the claims (Eisenberg

and Lanvers, 2009; Cox, Thomas, and Bai, 2008), in order to distinguish frivolous lawsuits

from meritorious ones. Building upon Baum et al. (2009) and Eisenberg and Lanvers (2009),

who classify lawsuits as settled or not settled, I further differentiate lawsuit outcomes into the

following categories: lawsuits dismissed by the court,15 lawsuits settled by agreements,16

lawsuits receiving court judgments,17 and lawsuits with other indeterminable outcomes.18 In

the regression analysis, DISMISSAL constitutes the omitted category. Three lawsuit outcome

variables, SETTLEALL–t=0, JUDGMENTALL–t=0 and OTHERALL–t=0, each denotes the number of

lawsuits filed which end in settlements, court judgments, or other dispositions, respectively.19

15 The following lawsuit outcomes recorded in the PACER database are grouped into the DISMISSAL category:

‘Dismissed - Lack of Jurisdiction’, ‘Dismissed – Other’, and ‘Dismissed - Want of Prosecution’. Lawsuits that

are voluntarily dismissed or dismissed due to settlement are not included in this category, but are included in the

‘SETTLE’ category. 16 The SETTLE category includes lawsuits which are recorded in PACER as having been dismissed voluntarily

or because of settlements, any arbitrated outcomes, and consent judgments. 17 The following lawsuit outcomes recorded in the PACER database are grouped into the JUDGMENT category:

‘Judgment - Court Trial’, ‘Judgment - Directed Verdict’, ‘Judgment - Jury Verdict’, ‘Judgment - Motion Before

Trial’, ‘Judgment - Non-Jury Trial’, and ‘Judgment - Other’. 18 The OTHER category consists of lawsuits that are neither dismissed, nor settled, nor court adjudicated, but

end in another non-terminating outcome, such as lawsuits that are ‘consolidated’ or ‘transferred/remanded’ to

another jurisdiction. 19 These broad categories of lawsuit outcomes do not account for the specific terms of each lawsuit’s

termination, such as the actual content of a settlement agreement reached by the plaintiffs and defendants. In this

paper I do not attempt to compute a more detailed measure of the defendants’ degree of victory in the lawsuits

(for example a scalar measure based on the terms of the settlement or court judgment) for two reasons. First,

because of the confidential nature of settlements, the terms of most settlement contracts are not available to the

public. Second, even assuming full data availability, considerable difficulty lies in the process of transforming

27

Compared to dismissed lawsuits, which imply weak merits or inappropriate jurisdiction,

lawsuits with all other types of outcome are expected to be followed by more significant

reputational penalties for the CEOs.

Third, I interact the economic magnitude of the lawsuits (DEMANDALL–t=0) with their

legal merit proxied by outcomes (SETTLEALL–t=0, JUDGMENTALL–t=0 and OTHERALL–t=0), since

larger lawsuits, which are proven to be more meritorious, are more likely to be followed by

reputational penalties for CEOs of the sued firms.

Data on demands for compensation and litigation outcome is collected from the Public

Access to Court Electronic Records (PACER) Database, by downloading individual court

dockets for all sample lawsuits. The results from the regressions predicting reemployment are

reported in Table 7. The results from regressions predicting the change in outside

directorships are reported in Table 8.

[Insert Table 7]

As reported in Table 7, in predicting the reemployment prospects of CEOs departing

from sued firms, the economic magnitude of lawsuits (DEMANDALL–t=0) is not statistically

significant, nor are the interaction terms when DEMANDALL–t=0 is interacted with lawsuit

outcomes. Amongst the lawsuit outcome variables, the estimated coefficient of OTHERALL–t=0

is negative and significant at the 5% level in predicting both RETOP3t(0,+2),t(-1,+2) and

REEMPLOYt(0,+2),t(-1,+2). This indicates that lawsuits that are more drawn out, with non-

terminating outcomes such as ‘transfer/remand’ to another jurisdiction, are more likely to be

followed by impaired reemployment prospects for the CEOs departing from the sued firms.

the terms of the judgments and settlements, which are qualitative in nature and specific to the facts of each case,

into quantitative measures that could be generalized and compared across all lawsuits. Any attempt at this

process would inevitably introduce substantial subjectivity into the data and, hence, compromise accuracy. For

these reasons, individual variations from lawsuit to lawsuit, in terms of their outcomes and the degrees of

victory for the defendant companies, are not captured by the study design.

28

These results indicate that, in the executive labor market, the reputational penalties associated

with lawsuits are significantly determined by the legal merit, but not economic scale, of the

lawsuits. CEOs tend to face more significant impediments in gaining reemployment after

their companies encounter lawsuits which are long-lasting and jurisdictionally complicated,

regardless of their size.

Similarly, as reported in Table 8, the magnitude of the pecuniary demands for

compensation (DEMANDALL–t=0) remains statistically insignificant in predicting the number of

outside directorships gained or lost by the CEOs, indicating that the economic scale of the

litigation alone does not determine the reputational penalties to follow. SETTLEALL–t=0, which

captures the number of lawsuits settled by the sued companies, is positive and significant at

the 5% level in predicting ∆DIRECTt(0,+2),t(-1,+2). Additionally, amongst the interaction

variables, the estimated coefficient of DEMAND*JUDGMENTALL–t=0 is also positive and

significant at the 1% level in both Models (1) and (2). These results indicate that, in the

executive labor market governing the supply and demand of outside directors, CEOs with the

following types of litigation experience are regarded favorably: (i) CEOs who have dealt with

meritorious lawsuits, as evidenced by their eventual settlements, or alternatively (ii) CEOs

who have defended frivolous lawsuits in court (resulting in court judgments), whilst

successfully withstanding the pressure exerted by the large claims for compensation by the

plaintiffs.

[Insert Table 8]

29

7. Conclusion

This study investigates the changes in reputation experienced by CEOs of companies

following a variety of lawsuits. The results provide a number of significant insights into the

way in which the executive labor market operates to impose such reputational changes.

Outside the realm of securities fraud allegations which have formed the focus of

existing research, this paper documents that CEOs do experience declines in reputation

following non-fraud corporate lawsuits, even when the alleged wrongdoing is not perpetrated

against shareholders but against other external stakeholders. When a CEO departs from the

sued company within the two-year period following the lawsuit, she faces impaired prospects

of finding comparable reemployment elsewhere. This evidence contributes to existing

literature by indicating that any post-litigation increase in turnover has real disciplinary

effects on the displaced CEOs. On the other hand, if the CEOs remain with their existing

employers, they suffer no additional impairment in reputation in the director labor market;

their litigation experience is sometimes even regarded favorably, as evidenced by the

marginal increase in outside board seats.

In addition, the executive labor market takes into consideration the legal merit of the

lawsuits, but does not respond significantly to the economic scale of the claims. CEO

reemployment prospects are particularly grim when their companies encounter lawsuits

which are of sufficient merit not to be dismissed by court, and are drawn out or complicated

so as not to be settled or resolved by court judgments. On the other hand, CEOs who have

experience of dealing with meritorious lawsuits, or with frivolous lawsuits with large

pecuniary claims, appear to be viewed favorably in the director labor market, experiencing a

net gain in the number of outside directorships.

30

Importantly, the poorer reemployment prospects for departing CEOs are primarily

associated with contractual lawsuits. In contrast, there is no evidence of any reputational

penalty following environmental lawsuits. There is some evidence to suggest that following

IP lawsuits, CEOs are rewarded with an increase in the number of outside board seats, most

likely because their IP litigation experience is viewed as a desirable quality in a director. This

empirical evidence rejects the ‘idealistic’ view that politically sensitive allegations lead to

significant reputational penalties, in favor of the more ‘cynical’ alternative, that sued

companies and their executive officers are only penalized when the legal disputes are filed by

parties with direct contractual power to increase the cost of operations of the accused

company.

In summary, the results show that the executive labor market forces impose reputational

penalties on CEOs who depart from sued companies in the form of impaired career

progression. The operation of the market forces is sufficiently sophisticated to process

litigation-specific information including the merit of the allegations. However,

notwithstanding this, the executive labor market systematically fails to penalize CEOs whose

companies face socially sensitive allegations such as environmental violations. Given the

absence of such market-based reputational penalties to deter corporate executives, arguably

lawmakers should consider harsher legal penalties for managers in the event of proven

violations, in the hope of influencing corporate cultures and behaviors in the future.

31

8. Appendix 1: Variable Definitions

Variable Name Variable Definition

Dependent Variables

)2,0(3

tRETOP Dummy variable which takes on a value of one if the CEO, who departs from the company during

the (0,+2) period relative to year 0, subsequently obtains reemployment as the CEO, president, or

chairman of the board at another S&P 1,500 company, and zero otherwise.

)2,1(3

tRETOP Dummy variable which takes on a value of one if the CEO, who departs from the company during

the (-1,+2) period relative to year 0, subsequently obtains reemployment as the CEO, president, or

chairman of the board at another S&P 1,500 company, and zero otherwise.

)2,0( tREEMPLOY Dummy variable which takes on a value of one if the CEO, who departs from the company during

the (0,+2) period relative to year 0, subsequently obtains reemployment at another S&P 1,500

company, as a senior executive officer (including vice president, chief financial officer, chief

operating officer), or as a non-executive member of the board; and zero otherwise.

)2,1( tREEMPLOY Dummy variable which takes on a value of one if the CEO, who departs from the company during

the (-1,+2) period relative to year 0, subsequently obtains reemployment at another S&P 1,500

company, as a senior executive officer (including vice president, chief financial officer, chief

operating officer), or as a non-executive member of the board; and zero otherwise.

)2,0(

tDIRECT The change in the number of outside directorships on the boards of other companies held by the

CEO during the (0,+2) period relative to year 0.

)2,1(

tDIRECT The change in the number of outside directorships on the boards of other companies held by the

CEO during the (-1,+2) period relative to year 0.

Key Independent Variables (Litigation)

0tLAWSUIT Litigation as represented by two alternative measures: first, a dummy variable which is assigned a

value of one if there is one or more lawsuits filed against the company during the year (0,+2)

period that result in settlement, and zero otherwise; second, a continuous variable measuring the

number of lawsuits filed against the company during the year (0,+2) period that result in

settlement.

0tENV Environmental litigation as represented by two alternative measures: first, a dummy variable

which is assigned a value of one if there is one or more environmental lawsuits filed against the

company during the year (0,+2) period that result in settlement, and zero otherwise; second, a

continuous variable measuring the number of environmental lawsuits filed against the company

during the year (0,+2) period that result in settlement.

0tANT Antitrust litigation as represented by two alternative measures: first, a dummy variable which is

assigned a value of one if there is one or more antitrust lawsuits filed against the company during

the year (0,+2) period that result in settlement, and zero otherwise; second, a continuous variable

measuring the number of antitrust lawsuits filed against the company during the year (0,+2) period

that result in settlement.

0tIP Intellectual property litigation as represented by two alternative measures: first, a dummy variable

which is assigned a value of one if there is one or more intellectual property lawsuits filed against

the company during the year (0,+2) period that result in settlement, and zero otherwise; second, a

continuous variable measuring the number of intellectual property lawsuits filed against the

company during the year (0,+2) period that result in settlement.

0tCON Contractual litigation as represented by two alternative measures: first, a dummy variable which is

assigned a value of one if there is one or more contractual lawsuits filed against the company

during the year (0,+2) period that result in settlement, and zero otherwise; second, a continuous

variable measuring the number of contractual lawsuits filed against the company during the year

(0,+2) period that result in settlement.

32

Variable Name Variable Definition

Control Variables

1tLogTA Natural logarithm of the book value of total assets at the end of year -1 as a control for firm size.

1tROA Returns on total assets ratio for the company for the year -1, calculated as the net profit in year -1

divided by the total assets of the company as at the end of year -1, as a control for firm

performance.

1%

tOUTSIDE The proportion of independent directors on the board, calculated as the number of independent

directors over the total number of directors as at the end of year -1, as a control for board

independence.

0tCEOAGE

Continuous variable representing the age of the CEO in year 0.

0tGENDER Dummy variable which takes on the value of one if the CEO is female, and zero otherwise.

0tINTERNAL Dummy variable which takes on a value of one if the CEO has been employed by his current

company for 12 months or longer prior to his appointment as the CEO, and zero otherwise, as a

control for internally appointed CEOs.

0tEXECOWN

The percentage of total ordinary shares outstanding owned by the CEO at the time of the lawsuit

filing in year 0.

0tTENURE The number of years during which the CEO has served the company in his or her current capacity

as at year 0.

1tNUMDIR The number of existing seats on the boards of other companies held by the CEO as at year 0.

0tRETAIN Dummy variable which takes on a value of one if the CEO has been retained by his company in

another capacity of employment for 12 months or longer upon ceasing to be its CEO, and zero

otherwise.

0tRESIGN Dummy variable which takes on a value of one if the official reason for the CEO turnover is that

the CEO has resigned, and zero otherwise.

Instrumental Variables

1tSEG The number of business segments of the company as at the end of year -1 as reported in the

Compustat Segment Database, as a control for organizational complexity.

1tRISKINDQ Dummy variable which takes on a value of one, if the two-digit Standard Industry Classification

(SIC) code of the company falls into the top quartile of the most litigious industries as observed

during the sampling period 2000-2007, and zero otherwise.

Lawsuit-Specific Characteristics

0tALLDEMAND

The cumulative sum of all demands for compensation filed against the public company during the

(0,+2) period, scaled by the total assets of the company at the beginning of year 0, as a measure of

the economic magnitude of the lawsuit(s).

0tALLDISMISSAL

The number of lawsuits filed against the company during the (0,+2) period that end in dismissal

(the omitted category in the regression analysis).

0tALLSETTLE

The number of lawsuits filed against the company during the (0,+2) period that end in settlement.

0tALLJUDGMENT

The number of lawsuits filed against the company during the (0,+2) period that end in a court

judgment.

0tALLOTHER

The number of lawsuits filed against the company during the (0,+2) period that end in a manner of

disposition other than dismissal, settlement, and court judgments.

33

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36

Tables

Table 1 Filing of Corporate Litigation by Year and by Category

Panel A: All lawsuit filings

YEAR TOTAL ENV ANT IP CON

Number Percentage Number Percentage Number Percentage Number Percentage Number Percentage

2000 1842 10.90% 47 0.28% 262 1.55% 393 2.33% 1140 6.75%

2001 1927 11.40% 58 0.34% 330 1.95% 392 2.32% 1147 6.79%

2002 2214 13.10% 36 0.21% 313 1.85% 463 2.74% 1402 8.30%

2003 2116 12.52% 51 0.30% 265 1.57% 455 2.69% 1345 7.96%

2004 2065 12.22% 41 0.24% 219 1.30% 502 2.97% 1303 7.71%

2005 2348 13.89% 54 0.32% 341 2.02% 463 2.74% 1490 8.82%

2006 2245 13.28% 181 1.07% 207 1.22% 531 3.14% 1326 7.85%

2007 2144 12.69% 47 0.28% 225 1.33% 590 3.49% 1282 7.59%

Total 16,901 100.00% 515 3.05% 2162 12.79% 3789 22.42% 10,435 61.74%

This table reports the total number of lawsuits filed against the S&P1,500 companies in the US federal courts during each year in the 2000-2007 sampling period and in each lawsuit category.

ENV denotes environmental lawsuits (PACER lawsuit code 893). ANT denotes antitrust lawsuits (PACER lawsuit code 410). IP denotes intellectual property lawsuits, including patent and

trademark litigation (PACER lawsuit codes 830 and 840). CON denotes contractual lawsuits (PACER lawsuit codes 140, 150, 190, 195, and 196). Source: Public Access to Court Electronic

Records (PACER) database.

37

Panel B: Settled Lawsuits

YEAR TOTAL ENV ANT IP CON

Number Percentage Number Percentage Number Percentage Number Percentage Number Percentage

2000 1123 11.28% 34 0.34% 121 1.21% 270 2.71% 698 7.01%

2001 1199 12.04% 43 0.43% 149 1.50% 271 2.72% 736 7.39%

2002 1312 13.17% 33 0.33% 104 1.04% 299 3.00% 876 8.80%

2003 1276 12.81% 41 0.41% 103 1.03% 300 3.01% 832 8.35%

2004 1234 12.39% 34 0.34% 94 0.94% 324 3.25% 782 7.85%

2005 1361 13.67% 35 0.35% 118 1.18% 310 3.11% 898 9.02%

2006 1216 12.21% 36 0.36% 76 0.76% 353 3.54% 751 7.54%

2007 1238 12.43% 35 0.35% 95 0.95% 351 3.52% 757 7.60%

Total 9,959 100.00% 291 2.92% 860 8.64% 2,478 24.88% 6,330 63.56%

This table reports the number of settled lawsuits against the S&P1,500 companies in the US federal courts during each year in the 2000-2007 sampling period and in each lawsuit category.

Lawsuit settlement is defined in accordance with Eisenberg and Lanvers (2009)’s settlement rate which proxies the plaintiff’s litigation success. ENV denotes environmental lawsuits (PACER

lawsuit code 893). ANT denotes antitrust lawsuits (PACER lawsuit code 410). IP denotes intellectual property lawsuits, including patent and trademark litigation (PACER lawsuit codes 830 and

840). CON denotes contractual lawsuits (PACER lawsuit codes 140, 150, 190, 195, and 196). Source: Public Access to Court Electronic Records (PACER) database.

38

Table 2 Univariate Analysis (Mean and Median) for Lawsuit and Control Samples

Lawsuit

(Mean)

Control

(Mean)

Difference in

Mean

Lawsuit

(Median)

Control

(Median)

Difference in

Median N (Lawsuit) N (Control) N (Total)

RETOP3(0,+2) 0.051 0.038 0.013 0.000 0.000 0.000 314 583 897

RETOP3(-1,+2) 0.044 0.045 -0.001 0.000 0.000 0.000 389 710 1099

DIRECT(0,+2) 0.072 0.047 0.025 0.000 0.000 0.000 1330 2343 3673

DIRECT(-1,+2) 0.128 0.056 0.072*** 0.000 0.000 0.000 1134 2041 3175

log(TA) 8.331 7.383 0.947*** 8.271 7.263 1.007*** 1330 2343 3673

ROA 0.057 0.051 0.006*** 0.051 0.048 0.003* 1330 2343 3673

%OUTSIDE 0.688 0.677 0.010* 0.714 0.700 0.014** 1330 2343 3673

CEOAGE 55.228 55.315 -0.087 55.000 55.000 0.000 1330 2343 3673

GENDER 0.013 0.017 -0.004 0.000 0.000 0.000 1330 2343 3673

INTERNAL 0.663 0.616 0.047*** 1.000 1.000 0.000 1330 2343 3673

EXECOWN 1.682 2.544 -0.862*** 0.241 0.413 -0.172*** 1330 2343 3673

TENURE 6.965 8.068 -1.104*** 5.000 6.000 -1.000*** 1330 2343 3673

RETAIN 0.165 0.131 0.034 0.000 0.000 0.000 389 710 1099

RESIGN 0.216 0.273 -0.057** 0.000 0.000 0.000 389 710 1099

NUMDIR 0.638 0.504 0.135*** 0.000 0.000 0.000 1330 2343 3673

This table reports the results from the univariate analysis of the dependent and control variables, including results from the ANOVA F-test of the difference in mean and the Chi-square test of

the difference in median. Firm-years are divided into the lawsuit sample and the control sample, on the basis of whether any lawsuit is filed against the company which subsequently results in

settlement as defined by Eisenberg and Lanvers (2009) to proxy the plaintiff’s litigation success. RETOP3(0,+2) and RETOP3(-1,+2) equal the value of one if a CEO who departs from the

company during the (0,+2) period and (-1,+2) period, respectively, subsequently gains reemployment as the CEO, president, or chairman of the board at another S&P 1,500 company, and zero

otherwise. ∆DIRECT(0,+2) and ∆DIRECT(-1,+2) denote the change in the number of outside directorships held by the CEO on the boards of other companies over the (0,+2) period and (-1,+2)

period, respectively. LAWSUIT (dummy) equals the value of one if one or more lawsuit(s) is filed against the company during the (0,+2) period. LAWSUIT (continuous) denotes the number of

lawsuits filed against the company during the (0,+2) period. Log(TA) equals the natural log of total assets at the end of year -1. ROA equals the returns on total assets for year -1. %OUTSIDE

denotes the proportion of independent directors on the board in year -1. CEOAGE equals the age of the CEO. GENDER equals one if the CEO is female and zero otherwise. INTERNAL equals

one if the CEO is internally appointed (having been employed at the company for 12 months or more prior to his or her appointment) and zero otherwise. EXECOWN denotes the stock

ownership of the company’s common shares by the CEO. TENURE equals the number of years over which the CEO has been serving in his/her current capacity. RETAIN equals the value of

one if the CEO has been retained by his company in another capacity of employment for 12 months or longer upon ceasing to be its CEO, and zero otherwise. RESIGN equals the value of one if

the official reason for the CEO turnover is that the CEO has resigned, and zero otherwise. NUMDIR denotes the number of outside directorships already held by the CEO as at year 0.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

39

Table 3 CEO Reemployment Prospects

LAWSUIT (dummy) LAWSUIT (continuous) LAWSUIT (dummy) LAWSUIT (continuous)

Dependant Variable RETOP3

(0,+2)

RETOP3

(-1,+2)

RETOP3

(0,+2)

RETOP3

(-1,+2)

RETOP3

(0,+2)

RETOP3

(-1,+2)

RETOP3

(0,+2)

RETOP3

(-1,+2)

Models (1) (2) (3) (4) (5) (6) (7) (8)

constant -4.001*** -3.356*** -4.018*** -3.260*** -4.322*** -3.535*** -4.507*** -3.715***

(0.001) (0.001) (0.001) (0.001) (0.000) (0.000) (0.000) (0.000)

LAWSUIT (dummy) -0.253 -0.403**

(0.173) (0.013)

LAWSUIT (continuous) -0.017 -0.025

(0.465) (0.258)

ENV (dummy) -0.213 -0.299

(0.636) (0.438)

ANT (dummy) -0.244 -0.166

(0.521) (0.619)

IP (dummy) 0.269 0.211

(0.169) (0.213)

CON (dummy) -0.332* -0.428**

(0.094) (0.016)

ENV (continuous) -0.162 -0.218

(0.607) (0.519)

ANT (continuous) 0.048 0.078

(0.794) (0.622)

IP (continuous) 0.172** 0.168***

(0.011) (0.006)

CON (continuous) -0.213** -0.246***

(0.025) (0.005)

log(TA) 0.252*** 0.257*** 0.250*** 0.245*** 0.281*** 0.282*** 0.288*** 0.283***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

ROA 1.586 1.571* 1.566 1.508* 1.483 1.432 1.101 1.085

(0.106) (0.075) (0.110) (0.083) (0.129) (0.101) (0.263) (0.216)

%OUTSIDE -0.311 -0.424 -0.324 -0.429 -0.479 -0.560 -0.634 -0.673

(0.634) (0.439) (0.621) (0.432) (0.470) (0.311) (0.353) (0.237)

CEOAGE 0.013 0.003 0.012 0.001 0.016 0.003 0.020 0.007

(0.458) (0.853) (0.480) (0.947) (0.375) (0.835) (0.272) (0.629)

GENDER 1.135*** 1.112*** 1.072*** 0.982*** 1.127*** 1.006*** 1.060*** 0.953***

(0.003) (0.001) (0.005) (0.003) (0.004) (0.003) (0.007) (0.004)

INTERNAL -0.527*** -0.425*** -0.541*** -0.431*** -0.560*** -0.438*** -0.542*** -0.410**

(0.005) (0.008) (0.004) (0.006) (0.003) (0.006) (0.005) (0.012)

TENURE -0.537** -0.646*** -0.507** -0.624*** -0.537** -0.647*** -0.504** -0.620***

(0.020) (0.001) (0.026) (0.001) (0.020) (0.001) (0.030) (0.001)

EXECOWN -0.825* -0.054 -0.840** -0.048 -0.851** -0.062 -0.753* -0.061

(0.050) (0.459) (0.048) (0.508) (0.048) (0.423) (0.074) (0.427)

RETAIN -0.549* -0.423 -0.618* -0.508* -0.654* -0.521* -0.558* -0.457

(0.095) (0.133) (0.062) (0.072) (0.056) (0.074) (0.094) (0.110)

RESIGN 0.596*** 0.547*** 0.612*** 0.552*** 0.673*** 0.596*** 0.631*** 0.568***

(0.004) (0.002) (0.003) (0.001) (0.002) (0.001) (0.004) (0.002)

YEARLY DUMMIES YES YES YES YES YES YES YES YES

n 897 1099 897 1099 897 1099 897 1099

Adj. R2 0.210 0.166 0.206 0.154 0.222 0.174 0.252 0.201

F-Stat 10.06 13.11 9.93 13.08 7.43 9.76 7.67 10.01

(p-value) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

This table reports the results from probit model regressions estimating the reemployment prospects of CEOs subsequent to settled

lawsuits. RETOP3(0,+2) and RETOP3(-1,+2) equal the value of one if a CEO who departs from the company during the (0,+2) period

and (-1,+2) period, respectively, subsequently gains reemployment as the CEO, president, or chairman of the board at another S&P

1,500 company, and zero otherwise. LAWSUIT (dummy) equals the value of one if one or more lawsuit(s) is filed against the company

during the (0,+2) period which results in settlement (as defined by Eisenberg and Lanvers (2009) to proxy the plaintiff’s litigation

40

success). LAWSUIT (continuous) denotes the number of lawsuits filed against the company, which result in settlement, during the

(0,+2) period. ENV, ANT, IP, CON (dummy) equal one if any environmental, antitrust, intellectual property, and contractual lawsuits,

respectively, are filed against the company during the (0,+2) period, which result in settlement, and zero otherwise. ENV, ANT, IP,

CON (continuous) denote the number of environmental, antitrust, intellectual property, and contractual lawsuits, respectively, against

the company during the (0,+2) period, which result in settlement. Log(TA) equals the natural log of total assets at the end of year -1.

ROA equals the returns on total assets for year -1. %OUTSIDE denotes the proportion of independent directors on the board in year -1.

CEOAGE equals the age of the CEO. GENDER equals one if the CEO is female and zero otherwise. INTERNAL equals one if the

CEO is internally appointed (having been employed at the company for 12 months or more prior to his or her appointment) and zero

otherwise. EXECOWN denotes the stock ownership of the company’s common shares by the CEO. TENURE equals the number of

years over which the CEO has been serving in his/her current capacity. RETAIN equals the value of one if the CEO has been retained

by his company in another capacity of employment for 12 months or longer upon ceasing to be its CEO, and zero otherwise. RESIGN

equals the value of one if the official reason for the CEO turnover is that the CEO has resigned, and zero otherwise. The sample

consists of the Standard & Poor’s 1,500 firms, divided into the litigation and control samples on the basis of whether any lawsuit is

filed against the firm in the (0,+2) period which results in settlement. The numbers in parentheses below the coefficient estimates are p-

values.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

41

Table 4 Loss of Outside Directorships

LAWSUIT (dummy) LAWSUIT (continuous) LAWSUIT (dummy) LAWSUIT (continuous)

Dependant Variable ∆DIRECT

(0,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(0,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(0,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(0,+2)

∆DIRECT

(-1,+2)

Models (1) (2) (3) (4) (5) (6) (7) (8)

constant -0.006 -0.175* 0.009 -0.149 0.012 -0.167 0.003 -0.167

(0.954) (0.095) (0.924) (0.166) (0.898) (0.119) (0.973) (0.118)

LAWSUIT (dummy) 0.038** 0.104***

(0.041) (0.000)

LAWSUIT (continuous) 0.002 0.005

(0.324) (0.184)

ENV (dummy) 0.030 0.002

(0.472) (0.967)

ANT (dummy) 0.004 -0.037

(0.937) (0.506)

IP (dummy) 0.023 0.080***

(0.311) (0.002)

CON (dummy) 0.037* 0.082***

(0.066) (0.000)

ENV (continuous) 0.016 -0.010

(0.435) (0.667)

ANT (continuous) 0.014** 0.017***

(0.025) (0.005)

IP (continuous) 0.000 0.004

(0.986) (0.678)

CON (continuous) -0.003 0.001

(0.296) (0.917)

log(TA) 0.004 0.015** 0.004 0.019** 0.001 0.013* 0.007 0.022***

(0.543) (0.043) (0.482) (0.013) (0.844) (0.098) (0.300) (0.005)

ROA -0.018 0.017 -0.003 0.063 -0.024 -0.003 -0.003 0.061

(0.881) (0.896) (0.978) (0.633) (0.840) (0.982) (0.977) (0.645)

%OUTSIDE 0.141** 0.263*** 0.137** 0.254*** 0.141** 0.267*** 0.130** 0.247***

(0.011) (0.000) (0.014) (0.000) (0.011) (0.000) (0.019) (0.000)

CEOAGE 0.001 0.002 0.001 0.002 0.001 0.003 0.001 0.002

(0.584) (0.146) (0.605) (0.174) (0.613) (0.125) (0.606) (0.140)

GENDER -0.105 0.040 -0.108 0.033 -0.107 0.034 -0.107 0.034

(0.179) (0.544) (0.169) (0.625) (0.173) (0.607) (0.173) (0.621)

INTERNAL 0.015 0.015 0.014 0.012 0.015 0.016 0.014 0.012

(0.447) (0.498) (0.466) (0.581) (0.427) (0.460) (0.481) (0.579)

EXECOWN -0.002 -0.004** -0.002 -0.004** -0.002 -0.004** -0.002 -0.004**

(0.188) (0.026) (0.167) (0.020) (0.165) (0.021) (0.181) (0.023)

TENURE -0.006*** -0.007*** -0.006*** -0.007*** -0.006*** -0.007*** -0.006*** -0.008***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

NUMDIR -0.153*** -0.285*** -0.152*** -0.282*** -0.152*** -0.284*** -0.152*** -0.283***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

PERIOD FIXED

EFFECT YES YES YES YES YES YES YES YES

n 3673 3175 3673 3175 3673 3175 3673 3175

Adj. R2 0.061 0.156 0.061 0.151 0.061 0.157 0.061 0.152

F-Stat 15.14 35.61 14.95 34.28 12.96 30.48 13.02 29.37

(p-value) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

This table reports the results from the OLS regressions estimating the change in the number of CEO outside directorships subsequent to

settled lawsuits. ∆DIRECT(0,+2) and ∆DIRECT(-1,+2) denote the change in the number of outside directorships held by the CEO on

the boards of other companies over the (0,+2) period and (-1,+2) period, respectively. LAWSUIT (dummy) equals the value of one if

one or more lawsuit(s) is filed against the company during the (0,+2) period which results in settlement (as defined by Eisenberg and

Lanvers (2009) to proxy the plaintiff’s litigation success). LAWSUIT (continuous) denotes the number of lawsuits filed against the

company, which result in settlement, during the (0,+2) period. ENV, ANT, IP, CON (dummy) equal one if any environmental, antitrust,

intellectual property, and contractual lawsuits, respectively, are filed against the company during the (0,+2) period, which result in

settlement, and zero otherwise. ENV, ANT, IP, CON (continuous) denote the number of environmental, antitrust, intellectual property,

42

and contractual lawsuits, respectively, against the company during the (0,+2) period, which result in settlement. Log(TA) equals the

natural log of total assets at the end of year -1. ROA equals the returns on total assets for year -1. %OUTSIDE denotes the proportion

of independent directors on the board in year -1. CEOAGE equals the age of the CEO. GENDER equals one if the CEO is female and

zero otherwise. INTERNAL equals one if the CEO is internally appointed (having been employed at the company for 12 months or

more prior to his or her appointment) and zero otherwise. EXECOWN denotes the stock ownership of the company’s common shares

by the CEO. TENURE equals the number of years over which the CEO has been serving in his/her current capacity. NUMDIR denotes

the number of outside directorships already held by the CEO as at year 0. The numbers in parentheses below the coefficient estimates

are p-values.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

43

Table 5 CEO Reemployment Prospects (Individual Lawsuit Categories)

IP (dummy) IP (continuous) Contractual (dummy) Contractual (continuous)

Dependant Variable RETOP3

(0,+2)

RETOP3

(-1,+2)

RETOP3

(0,+2)

RETOP3

(-1,+2)

RETOP3

(0,+2)

RETOP3

(-1,+2)

RETOP3

(0,+2)

RETOP3

(-1,+2)

Models (1) (2) (3) (4) (5) (6) (7) (8)

constant -4.987*** -3.495*** -4.978*** -3.448*** -3.856*** -3.074*** -3.940*** -3.162***

(0.002) (0.004) (0.002) (0.004) (0.007) (0.008) (0.006) (0.007)

IP 0.022 -0.121 0.066 -0.014

(0.944) (0.647) (0.682) (0.922)

CON -0.373 -0.529** -0.298* -0.383**

(0.148) (0.025) (0.090) (0.022)

log(TA) 0.271*** 0.269*** 0.271*** 0.269*** 0.288*** 0.279*** 0.292*** 0.282***

(0.001) (0.000) (0.001) (0.000) (0.000) (0.000) (0.000) (0.000)

ROA 0.406 0.390 0.360 0.374 -0.440 -0.318 -0.407 -0.287

(0.720) (0.685) (0.751) (0.697) (0.686) (0.743) (0.708) (0.766)

%OUTSIDE -1.106 -0.814 -1.128 -0.846 0.164 0.027 0.117 0.006

(0.248) (0.259) (0.235) (0.239) (0.851) (0.970) (0.895) (0.994)

CEOAGE 0.028 0.004 0.028 0.003 -0.003 -0.011 -0.001 -0.010

(0.234) (0.826) (0.234) (0.851) (0.884) (0.504) (0.962) (0.576)

GENDER 1.213** 1.170*** 1.208** 1.130*** 0.785 0.654 0.721 0.593

(0.023) (0.007) (0.022) (0.007) (0.156) (0.197) (0.193) (0.244)

INTERNAL -0.313 -0.232 -0.318 -0.232 -0.406* -0.291 -0.413* -0.294

(0.217) (0.245) (0.209) (0.244) (0.085) (0.137) (0.083) (0.136)

TENURE -0.184 -0.387* -0.179 -0.382* -0.380 -0.519** -0.397 -0.537**

(0.527) (0.087) (0.536) (0.091) (0.160) (0.020) (0.147) (0.017)

EXECOWN -1.252* -0.070 -1.237* -0.071 -0.554 -0.012 -0.568 -0.014

(0.069) (0.379) (0.071) (0.379) (0.236) (0.857) (0.228) (0.837)

RETAIN -0.376 -0.303 -0.391 -0.327 -0.622 -0.677 -0.568 -0.657

(0.418) (0.410) (0.392) (0.370) (0.206) (0.121) (0.249) (0.137)

RESIGN 0.791*** 0.614*** 0.789*** 0.611*** 0.443* 0.412* 0.453* 0.420*

(0.008) (0.007) (0.008) (0.008) (0.100) (0.062) (0.093) (0.058)

YEARLY DUMMIES YES YES YES YES YES YES YES YES

n 505 613 505 613 595 731 595 731

Adj. R2 0.239 0.152 0.240 0.151 0.204 0.163 0.213 0.173

F-Stat 8.69 13.78 8.72 13.81 11.43 15.87 11.14 15.33

(p-value) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

This table reports the results from probit model regressions estimating CEO reemployment prospects, by employing a restricted sub-

sample to examine individual lawsuit categories in turn. IP (dummy) equals one if any intellectual property lawsuits are filed against

the company during the (0,+2) period which result in settlement, and zero otherwise. IP (continuous) denotes the number of intellectual

property against the company during the (0,+2) period which result in settlement. In the re-estimation of the regressions examining IP

lawsuits, a restricted sample is used that excludes firm-years which experience any other category of lawsuits during the (0,+2) period.

CON (dummy) equals one if any contractual lawsuits are filed against the company during the (0,+2) period which result in settlement,

and zero otherwise. CON (continuous) denotes the number of contractual lawsuits filed against the company during the (0,+2) period

which result in settlement. In the re-estimation of the regressions examining contractual lawsuits, a restricted sample is used that

excludes firm-years which experience any other category of lawsuits during the (0,+2) period. RETOP3(0,+2) and RETOP3(-1,+2)

equal the value of one if a CEO who departs from the company during the (0,+2) period and (-1,+2) period, respectively, subsequently

gains reemployment as the CEO, president, or chairman of the board at another S&P 1,500 company, and zero otherwise. Log(TA)

equals the natural log of total assets at the end of year -1. ROA equals the returns on total assets for year -1. %OUTSIDE denotes the

proportion of independent directors on the board in year -1. CEOAGE equals the age of the CEO. GENDER equals one if the CEO is

female and zero otherwise. INTERNAL equals one if the CEO is internally appointed (having been employed at the company for 12

months or more prior to his or her appointment) and zero otherwise. EXECOWN denotes the stock ownership of the company’s

common shares by the CEO. TENURE equals the number of years over which the CEO has been serving in his/her current capacity.

RETAIN equals the value of one if the CEO has been retained by his company in another capacity of employment for 12 months or

longer upon ceasing to be its CEO, and zero otherwise. RESIGN equals the value of one if the official reason for the CEO turnover is

that the CEO has resigned, and zero otherwise. The numbers in parentheses below the coefficient estimates are p-values.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

44

Table 6 Loss of Outside Directorships (Individual Lawsuit Categories)

Environmental Antitrust Intellectual Property Contractual

Dependant Variable ∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

∆DIRECT

(-1,+2)

Key Independent Variable ENV

(dummy)

ENV

(continuous)

ANT

(dummy)

ANT

(continuous)

IP

(dummy)

IP

(continuous)

CON

(dummy)

CON

(continuous)

Models (1) (2) (3) (4) (5) (6) (7) (8)

constant -0.118 -0.123 -0.121 -0.133 -0.126 -0.101 -0.217** -0.186*

(0.350) (0.330) (0.338) (0.293) (0.286) (0.393) (0.046) (0.089)

ENV 0.141* 0.109

(0.099) (0.128)

ANT 0.107 0.066

(0.490) (0.248)

IP 0.075** 0.014

(0.016) (0.295)

CON 0.070*** 0.023**

(0.005) (0.015)

log(TA) 0.022** 0.022** 0.023** 0.023** 0.026*** 0.026*** 0.030*** 0.029***

(0.034) (0.031) (0.024) (0.028) (0.007) (0.007) (0.000) (0.001)

ROA 0.154 0.154 0.105 0.105 0.081 0.101 0.221* 0.229*

(0.284) (0.285) (0.479) (0.477) (0.555) (0.463) (0.080) (0.070)

%OUTSIDE 0.045 0.047 0.073 0.066 0.092 0.091 0.143** 0.134*

(0.567) (0.551) (0.360) (0.403) (0.195) (0.201) (0.040) (0.053)

CEOAGE 0.002 0.002 0.002 0.002 0.001 0.001 0.003* 0.003

(0.232) (0.225) (0.362) (0.267) (0.497) (0.624) (0.096) (0.104)

GENDER -0.087 -0.087 -0.084 -0.083 -0.028 -0.029 -0.076 -0.077

(0.330) (0.330) (0.339) (0.345) (0.750) (0.737) (0.449) (0.446)

INTERNAL 0.036 0.036 0.037 0.040 0.050** 0.049** -0.004 -0.007

(0.189) (0.192) (0.182) (0.152) (0.047) (0.049) (0.880) (0.785)

EXECOWN -0.004* -0.004* -0.004* -0.004* -0.004** -0.004** -0.002 -0.002

(0.064) (0.063) (0.053) (0.055) (0.039) (0.030) (0.281) (0.268)

TENURE -0.005** -0.005** -0.004* -0.004** -0.004** -0.004** -0.008*** -0.008***

(0.018) (0.018) (0.076) (0.048) (0.019) (0.027) (0.000) (0.000)

NUMDIR -0.271*** -0.270*** -0.278*** -0.279*** -0.275*** -0.274*** -0.290*** -0.289***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

PERIOD FIXED EFFECT YES YES YES YES YES YES YES YES

n 1705 1705 1688 1688 2022 2022 2580 2580

Adj. R2 0.148 0.147 0.152 0.155 0.157 0.155 0.153 0.153

F-Stat 18.38 18.34 18.77 19.18 23.12 22.80 28.49 28.47

(p-value) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

This table reports the results from the OLS regressions estimating the change in the number of CEO outside directorships subsequent to

settled lawsuits, by employing a restricted sub-sample to examine individual lawsuit categories in turn. For the examination of

environmental, antitrust, intellectual property, and contractual lawsuits, respectively, the restricted sample includes only firm-years

with that particular type of lawsuit that ends in settlement, and excludes any firm-year with lawsuits filed and settled in the other

categories. ENV, ANT, IP, CON (dummy) equal one if any environmental, antitrust, intellectual property, and contractual lawsuits,

respectively, are filed against the company during the (0,+2) period which result in settlement, and zero otherwise. ENV, ANT, IP,

CON (continuous) denote the number of environmental, antitrust, intellectual property, and contractual lawsuits, respectively, filed

against the company during the (0,+2) period which result in settlement. ∆DIRECT(-1,+2) denotes the change in the number of outside

directorships held by the CEO on the boards of other companies over the (-1,+2) period. Log(TA) equals the natural log of total assets

at the end of year -1. ROA equals the returns on total assets for year -1. %OUTSIDE denotes the proportion of independent directors

on the board in year -1. CEOAGE equals the age of the CEO. GENDER equals one if the CEO is female and zero otherwise.

INTERNAL equals one if the CEO is internally appointed (having been employed at the company for 12 months or more prior to his or

her appointment) and zero otherwise. EXECOWN denotes the stock ownership of the company’s common shares by the CEO.

TENURE equals the number of years over which the CEO has been serving in his/her current capacity. NUMDIR denotes the number

of outside directorships already held by the CEO as at year 0. The numbers in parentheses below the coefficient estimates are p-values.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

45

Table 7 Litigation Characteristics and CEO Reemployment Prospects

RETOP3 REEMPLOY

Dependant Variable RETOP3(0,+2) RETOP3(-1,+2) REEMPLOY(0,+2) REEMPLOY(-1,+2)

Models (1) (2) (3) (4)

constant -11.606*** -10.148*** -9.116*** -8.146***

(0.000) (0.000) (0.001) (0.000)

DEMAND -7.363 -7.453 -6.644 -7.085

(0.225) (0.172) (0.241) (0.174)

SETTLE -0.039 -0.064 -0.051 -0.077

(0.589) (0.362) (0.481) (0.275)

JUDGMENT -0.008 0.013 -0.048 -0.023

(0.963) (0.939) (0.796) (0.899)

OTHER -0.846** -0.780** -0.841** -0.772**

(0.015) (0.013) (0.015) (0.014)

DEMAND*SETTLE 1.634 1.562 1.501 1.510

(0.306) (0.306) (0.339) (0.333)

DEMAND*JUDGMENT -3.225 -2.667 -2.816 -2.506

(0.494) (0.563) (0.553) (0.602)

DEMAND*OTHER -6.664 -5.286 -5.492 -4.426

(0.571) (0.650) (0.645) (0.721)

log(TA) 0.781*** 0.716*** 0.763*** 0.712***

(0.000) (0.000) (0.000) (0.000)

ROA 9.073*** 9.655*** 9.899*** 10.449***

(0.001) (0.000) (0.000) (0.000)

%OUTSIDE -0.177 -0.590 -0.914 -1.228

(0.871) (0.557) (0.380) (0.203)

CEOAGE 0.065** 0.054* 0.031 0.025

(0.046) (0.066) (0.272) (0.329)

GENDER 2.418*** 2.343*** 2.114*** 2.121***

(0.000) (0.000) (0.001) (0.000)

INTERNAL -1.333*** -1.245*** -1.121*** -1.093***

(0.000) (0.000) (0.001) (0.001)

TENURE -1.602*** -1.417*** -1.405*** -1.288***

(0.002) (0.002) (0.003) (0.003)

EXECOWN -1.702** -1.575** -1.776** -1.660**

(0.050) (0.043) (0.046) (0.039)

RETAIN -1.146** -1.055** -1.218** -1.134**

(0.021) (0.021) (0.016) (0.015)

RESIGN 1.277*** 1.107*** 1.299*** 1.174***

(0.001) (0.001) (0.001) (0.000)

YEARLY DUMMIES YES YES YES YES

n 543 665 543 665

Adj. R2 0.466 0.446 0.468 0.452

F-Stat 2.73 3.17 2.81 3.23

(p-value) 0.000 0.000 0.000 0.000

This table reports the results from probit regressions estimating CEO reemployment prospects by employing lawsuit-specific

characteristics as independent variables. The regressions are estimated over a subsample of firm-years with any lawsuit filings (not

restricted to settled lawsuits in the final litigation sample). RETOP3(0,+2) and RETOP3(-1,+2) equal the value of one if a CEO who

departs from the company during the (0,+2) period and (-1,+2) period, respectively, subsequently gains reemployment as the CEO,

president, or chairman of the board at another S&P 1,500 company, and zero otherwise. REEMPLOY(0,+2) and REEMPLOY(-1,+2)

equal the value of one if a CEO who departs from the company during the (0,+2) period and (-1,+2) period, respectively, subsequently

gains reemployment at another S&P 1,500 company as a senior executive officer (including vice president, chief financial officer, chief

operating officer) or as a non-executive member of the board, and zero otherwise. DEMAND equals the sum of all demands for

pecuniary compensation filed against the company during the (0,+2) period, scaled by firm size (total assets) at the beginning of year 0.

SETTLE denotes the number of lawsuits filed against the company during the (0,+2) period, which eventually end in settlement.

JUDGMENT denotes the number of lawsuits filed against the company during the (0,+2) period, which eventually end in a court

judgment. OTHER denotes the number of lawsuits filed against the company during the (0,+2) period, which eventually end in a

manner of disposition other than dismissal, settlement, and court judgments. ROA equals the returns on total assets for year -1.

%OUTSIDE denotes the proportion of independent directors on the board in year -1. CEOAGE equals the age of the CEO. GENDER

equals one if the CEO is female and zero otherwise. INTERNAL equals one if the CEO is internally appointed (having been employed

at the company for 12 months or more prior to his or her appointment) and zero otherwise. EXECOWN denotes the stock ownership of

the company’s common shares by the CEO. TENURE equals the number of years over which the CEO has been serving in his/her

current capacity. RETAIN equals the value of one if the CEO has been retained by his company in another capacity of employment for

12 months or longer upon ceasing to be its CEO, and zero otherwise. RESIGN equals the value of one if the official reason for the

CEO turnover is that the CEO has resigned, and zero otherwise. The numbers in parentheses below the coefficient estimates are p-

values.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

46

Table 8 Litigation Characteristics and Outside Directorships

Overall Lawsuits

Dependant Variable

∆DIRECT

(0,+2)

∆DIRECT

(-1,+2)

Models (1) (2)

constant 0.229 0.238 (0.270) (0.318) DEMAND 0.001 -0.007 (0.725) (0.165) SETTLE 0.019** 0.023** (0.019) (0.024) JUDGMENT 0.001 -0.007 (0.912) (0.618) OTHER -0.008 -0.000 (0.344) (0.983) DEMAND*SETTLE -0.004 0.001 (0.413) (0.924) DEMAND*JUDGMENT 0.007*** 0.009*** (0.003) (0.000) DEMAND*OTHER 0.002 -0.007 (0.791) (0.284) log(TA) -0.001 0.016 (0.927) (0.328) ROA -0.294 -0.143 (0.328) (0.676) %OUTSIDE 0.074 0.266** (0.535) (0.050) CEOAGE -0.002 -0.000 (0.557) (0.960) GENDER 0.154 0.269 (0.415) (0.292) INTERNAL -0.006 -0.029 (0.884) (0.528) TENURE 0.001 0.003 (0.772) (0.488) EXECOWN 0.036 -0.044 (0.327) (0.388) NUMDIR -0.257*** -0.570*** (0.000) (0.000) PERIOD FIXED EFFECT YES YES

n 2393 2047 Adj. R2 0.101 0.310 F-Stat 12.64 40.95 (p-value) 0.000 0.000

This table reports the results from OLS regressions estimating the change in the number of outside directorships held by the CEO by

employing lawsuit-specific characteristics as independent variables. The regressions are estimated over a subsample of firm-years with

any lawsuit filings (not restricted to settled lawsuits in the final litigation sample). ∆DIRECT(0,+2) and ∆DIRECT(-1,+2) denote the

change in the number of outside directorships held by the CEO on the boards of other companies over the (0,+2) period and (-1,+2)

period, respectively. DEMAND equals the sum of all demands for pecuniary compensation filed against the company during the (0,+2)

period, scaled by firm size (total assets) at the beginning of year 0. SETTLE denotes the number of lawsuits filed against the company

during the (0,+2) period, which eventually end in settlement. JUDGMENT denotes the number of lawsuits filed against the company

during the (0,+2) period, which eventually end in a court judgment. OTHER denotes the number of lawsuits filed against the company

during the (0,+2) period, which eventually end in a manner of disposition other than dismissal, settlement, and court judgments. ROA

equals the returns on total assets for year -1. %OUTSIDE denotes the proportion of independent directors on the board in year -1.

CEOAGE equals the age of the CEO. GENDER equals one if the CEO is female and zero otherwise. INTERNAL equals one if the

CEO is internally appointed (having been employed at the company for 12 months or more prior to his or her appointment) and zero

otherwise. EXECOWN denotes the stock ownership of the company’s common shares by the CEO. TENURE equals the number of

years over which the CEO has been serving in his/her current capacity. NUMDIR denotes the number of outside directorships already

held by the CEO as at year 0. The numbers in parentheses below the coefficient estimates are p-values.

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.