# Forthcoming, Review of Financial Studies

Forthcoming, Review of Financial Studies

Electronic copy available at: http://ssrn.com/abstract=1699272

Co-opted Boards

Jeffrey L. Colesa, Naveen D. Danielb, Lalitha Naveenc

September 10, 2013

Forthcoming, Review of Financial Studies

Abstract We argue that not all independent directors are equally effective in monitoring top management. Specifically, directors who are appointed by the CEO are likely to have stronger allegiance to the CEO and will be weaker monitors. To examine this hypothesis, we propose and empirically deploy two new measures of board composition. Co-option is the fraction of the board comprised of directors appointed after the sitting CEO assumed office. Consistent with Co- option serving to measure board capture, as Co-option increases board monitoring intensity decreases: turnover-performance sensitivity diminishes; pay level increases but without a commensurate increase in pay-performance sensitivity; and investment in hard assets increases. Further analysis suggests that even independent directors who are co-opted are less effective monitors. Non-Co-opted Independence––the fraction of the board comprised of independent directors who were already on the board before the CEO assumed office––has more explanatory power for monitoring effectiveness than the traditional measure of board independence. JEL Classifications: G32; G34; K22 Keywords: Corporate governance; Board co-option; CEO entrenchment; Board composition; Board independence **__________________________________________________** a W. P. Carey School of Business, Arizona State University, Tempe, AZ., 85287, USA, jeffrey.coles@asu.edu bLeBow College of Business, Drexel University, Philadelphia, PA., 19104, USA, nav@drexel.edu cFox School of Business, Temple University, Philadelphia, PA., 19122, USA, lnaveen@temple.edu The authors are grateful to an anonymous referee, Renee Adams, Christa Bouwman, Vidhi Chhaochharia, Rachel Diana, Dave Denis, Diane Denis, Ben Hermalin, Yan Li, Antonio Macias, David Maber, John McConnell, Darius Palia, Raghu Rau, David Reeb, Oleg Rytchkov, Partha Sengupta, Mike Weisbach (the editor), Jun Yang, and seminar participants at Case Western Reserve University, Lehigh University, Northeastern University, Purdue University, Rutgers University, the Securities and Exchanges Commission, Villanova University, the 2008 American Financial Association meeting, the 2008 Conference on Corporate Governance and Fraud Prevention at George Mason University, the 2008 Financial Management Association meeting, the 2008 Summer Research Conference at Indian School of Business, the 2010 Weinberg Center for Corporate Governance Conference at the University of Delaware, the 2011 SFS Finance Cavalcade, and the 2011 Finance Down Under Conference at the University of Melbourne for helpful comments.

Electronic copy available at: http://ssrn.com/abstract=1699272

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- Introduction

The board of directors of a corporation is meant to perform the critical functions of

monitoring and advising top management (Mace (1971)). Conventional wisdom holds that

monitoring by the board is more effective when the board consists of majority of independent

directors. The empirical evidence on the connection between board independence and firm

performance, however, is mixed and weak, as is the evidence on the relation between board

independence and other organizational and governance attributes, such as managerial

ownership.1

One potential reason for the paucity of consistent, significant results is that many

directors are co-opted and the board is captured. In practice, CEOs are likely to exert

considerable influence on the selection of all board members, including non-employee directors.

Carl Icahn, activist investor, asserts quite directly (Business Week Online, 11/18/2005) that

“…members of the boards are cronies appointed by the very CEOs they’re supposed to be

watching.” Likewise, Finkelstein and Hambrick (1989) allege that CEOs can co-opt the board

by appointing “sympathetic” new directors. Hwang and Kim (2009) suggest that CEOs favor

appointees who share similar views or social ties or because there is some other basis for

alignment with the CEO.

Reflecting similar concerns about board capture, subsequent to the Sarbanes Oxley Act of

2002 (SOX) NYSE and Nasdaq adopted listing requirements that substantially reduced the direct

influence of the CEO in the nominating process. Nonetheless, CEOs are likely to continue to be

able to exert some influence on the board nomination process. At the very least, they approve

the slate of directors, and this slate is almost always voted in by shareholders (Hermalin and 1 See Coles, Daniel, and Naveen (2008), Adams, Hermalin, and Weisbach (2010), and Coles, Lemmon, and Wang (2011), for example.

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Weisbach (1998), Cai, Garner, and Walkling (2009)).2

In this paper, we propose and implement two new measures of board composition, which

we term Co-option and Non-Co-opted Independence. Co-option is meant to capture board

capture. Non-Co-opted Independence, on the other hand, is meant to refine the traditional

measure of board independence as a proxy for the monitoring effectiveness of the board.

We define Co-option as the ratio of the number of “co-opted” (or captured) directors,

meaning those appointed after the CEO assumes office, to board size. The idea is that such co-

opted directors, regardless of whether they are classified as independent using traditional

definitions, are more likely to assign their allegiance to the CEO because the CEO was involved

in their initial appointment. Our measure is meant to reflect the additional behavioral latitude

and managerial discretion afforded a CEO when that CEO has significant influence over some

directors on the board. A related interpretation of Co-option is that it captures the disutility to

the board from monitoring the CEO. Along these lines, Hermalin and Weisbach (1998), in their

model of CEO bargaining with the board, specify director utility as a function of, among other

things, a distaste for monitoring (κ in their model), which for a director is reflected in a “… lack

of independence, at least in terms of the way he or she behaves” (p. 101). Co-option can be

thought of as capturing director aversion to monitoring and lack of independence aggregated to

the board level. Intuitively, Co-option reflects what the CEO can get away with.

Co-option ranges from 0 to 1, with higher values indicating greater co-option and board

capture and greater insulation of the CEO from various efficiency pressures. In our sample,

mean Co-option is 0.47, indicating that on average nearly half of the directors on a board joined

the board after the CEO assumed office. 2 Of course, CEO influence on the nomination process is substantially lower in the relatively few instances where directors are put up for election by dissident shareholders in proxy fights.

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We predict that a CEO who has co-opted a greater fraction of the board will be less likely

to be fired following poor performance, will receive higher pay, will have lower sensitivity of

pay to performance, and will be able to implement preferred or pet projects even if they are

suboptimal from a shareholder-value perspective. Our findings generally are consistent with

these hypotheses.

First, we find that the sensitivity of forced CEO turnover to firm performance decreases

with co-option. For example, our parameter estimates indicate that CEO-turnover-performance

sensitivity is attenuated by about two-thirds for a one-standard-deviation increase in Co-option.

Second, we find that CEO pay levels increase with board co-option. Of course, higher pay being

associated with higher co-option is not symptomatic of entrenchment if it is compensation for

higher risk borne by the CEO through higher pay-performance sensitivity. Additional evidence,

however, suggests that this is not the case: we find that the sensitivity of CEO pay to firm

performance is generally unrelated to board co-option and even is negatively related to co-option

in some specifications. Finally, we find that investment in tangible assets (the ratio of capital

expenditure to assets) increases with co-option. This is consistent with the idea that CEOs who

have co-opted the board can invest in ways they otherwise would not. For example, in the

absence of effective board monitoring, executives are likely to satisfy their preferences for scale

and span of control, preferences that arise in larger firms for reasons of higher compensation,

control over more resources, and enhanced stature in the industry and community (Jensen

(1986)). Overall, the evidence on turnover, pay, and investment is consistent with the idea that

co-option reduces the monitoring effectiveness of the board.

In all specifications we control for the proportion of independent directors on the board

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(Independence), which traditionally has been understood to be a measure of board monitoring.3

We find that Independence has little power to explain CEO turnover-performance-sensitivity,

CEO pay, CEO pay-performance-sensitivity, and investment. If there were a statistical horse

race between Co-option and Independence, Co-option would appear to be more successful.

In light of this result, a natural question is whether independent directors who are co-

opted by the CEO are different in monitoring effectiveness from those who are not co-opted. To

address this question, we calculate the fraction of the board that is comprised of independent

directors appointed after the CEO assumed office (“Co-opted Independence”). Our results using

this measure as an explanatory variable are similar to what we find with Co-option. Specifically,

we find that Co-opted Independence is associated with lower sensitivity of CEO turnover to

performance, higher pay levels, lower sensitivity of pay to performance, and greater investment.

Thus, co-opted independent directors, though independent of the CEO in the conventional and

legal sense, behave as though they are not independent in the function of monitoring

management. This is likely to explain why the literature has not found consistent evidence with

respect to the monitoring effectiveness of independent directors.

To formally test the monitoring effectiveness of independent directors who are not co-

opted, we introduce a second new measure of board composition: Non-Co-opted Independence.

We define this measure as the fraction of the board comprised of independent directors who were

already on the board when the CEO assumed office. In our sample, mean Non-Co-opted

Independence is 0.35, indicating that on average about a third of the board is comprised of

independent directors who are truly independent, having not been co-opted by the CEO. Of

3 See, for example, Weisbach (1988), Byrd and Hickman (1992), Brickley, Coles, and Terry (1994), Dahya, McConnell, and Travlos (2002), Hermalin and Weisbach (2003), Dahya and McConnell (2007), Coles, Daniel, and Naveen (2008), and Dahya, Dimitrov, and McConnell (2008).

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course, on most issues the board faces, the majority rules, so there is a significant possibility that

the subset of independent directors who are not co-opted is not influential. Nonetheless,

consistent with our conjecture that independent directors who are not co-opted are the monitors

that matter, we find Non-Co-opted Independence is associated with higher sensitivity of CEO

turnover to performance, lower pay levels, higher sensitivity of pay to performance, and lower

investment.

In sum, not all independent directors are equally effective at monitoring. Those who are

co-opted by the CEO are associated with weaker monitoring, while the independent directors

who join the board before the CEO assumes office, that is, the directors who hired the CEO, are

associated with stronger monitoring.

Our results on board capture are robust to two alternative definitions of Co-option. Our

first alternative proxy, Tenure-Weighted Co-option (TW Co-option), accounts for the possibility

that directors appointed by the CEO become even more co-opted through time and that the

influence of co-opted directors increases with their tenure on the board.4 We define TW Co-

option as the sum of the tenure of co-opted directors divided by the total tenure of all directors,

so an increase likely indicates higher board co-option. Our second alternative proxy is designed

to address the possible concern that co-option increases mechanically with CEO tenure and that

our results on co-option may be capturing the effect of CEO tenure. We estimate Residual Co-

option as the residual from a regression of Co-option on CEO tenure. We similarly estimate

Residual TW Co-option as the residual from a regression of TW Co-option on CEO tenure. By

construction, these residual measures are uncorrelated with CEO tenure. We find qualitatively

similar results using these alternative definitions of co-option. 4 Per Nell Minow, quoted in Hymowitz and Green (2013), “What you want from directors is for them to really push the CEO for answers and, just by human nature, that gets harder the longer they’re on a board.”

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Our results also are robust to our best attempts to address endogeneity. All of our base-

case regressions include firm-fixed effects to control for biases introduced by unobserved, firm-

specific, time-invariant, omitted variables that are correlated with co-option. Endogeneity could

still arise, however, either because the omitted variable is not firm-specific or varies through

time, or because reverse causation runs from our firm policy variables, such as pay, to co-option.

We exploit exchange-rule changes enacted in 2002 to address such concerns. Since these rules

were adopted shortly after the passage of Sarbanes-Oxley (SOX), we refer to the post-rules

period as the post-SOX period. Firms that pre-SOX were not compliant with subsequent listing

requirements to have a majority of independent directors on the board chose to appoint new

independent directors (Linck, Netter, and Yang (2009)), thereby causing an exogenous increase

in board co-option for such firms. To isolate the causal impact of co-option, we apply a

modified difference-in-difference approach. We continue to find results on the effects of co-

option that by-and-large are consistent with the evidence described above.

- Motivation, Related Literature, and Hypotheses Development

2.1. CEO turnover-performance sensitivity

One of the key functions of the board is to evaluate the CEO and to replace him if his

performance is poor (Mace (1971)). While early studies find that the likelihood of CEO turnover

decreases in firm performance, subsequent studies suggest that this relation between turnover

and performance is weaker when the firm’s governance is weaker.5 Along similar lines,

Hermalin and Weisbach (2003) suggest that turnover-performance sensitivity is weaker if the

CEO captures the board. This implies that, for a given level of performance, CEOs of firms with 5 See Coughlan and Schmidt (1985), Warner, Watts, and Wruck (1988), Weisbach (1988), Huson, Parrino, and Starks (2001), Kang and Shivdasani (2005), and Kaplan and Minton (2012).

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more co-opted boards should be less likely to be fired. Thus, we expect that:

H1: All else equal, the sensitivity of forced CEO turnover to firm performance decreases

with co-option. 2.2. CEO pay level

A second important function of the board is to set the structure of CEO pay. Many

studies argue that entrenched CEOs and CEOs of firms with weaker monitoring receive higher

pay (Borokhovich, Brunarski, and Parrino (1997) and Core, Holthausen, and Larcker (1999)).

We extend this reasoning to argue that if co-opted boards are more sympathetic to the CEO, then

CEO pay should increase with co-option. This leads to our second hypothesis:

H2: All else equal, CEO pay level increases with co-option. 2.3. CEO pay-performance sensitivity

Pay contingent on performance is a means to align executive incentives with shareholder

interests (e.g., Jensen and Murphy (1990), Bizjak, Brickley, and Coles (1993)). Thus, we also

examine the impact of co-option on CEO pay-performance sensitivity (PPS or “delta”). Hartzell

and Starks (2003) show that the CEO pay-performance sensitivity is higher when institutions

hold more shares and argue that this is consistent with higher institutional holdings being good

for shareholders. Faleye (2007) finds lower PPS for CEOs of firms with staggered boards and

argues that staggered boards are associated with CEO entrenchment. Thus, we expect that, if co-

option results in lower efficiency pressures on the management team, then pay-performance

sensitivity should decrease in co-option.6

6 Empirically, the papers mentioned in this subsection use varying methodologies to capture PPS. For example, Hartzell and Starks (2003) use PPS from new option grants only as the dependent variable. Coles, Lemmon, and

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H3: All else equal, CEO pay-performance sensitivity decreases with co-option. 2.4. Investment policy

A long literature addresses managerial incentives to overinvest and to engage in empire

building. Jensen (1986, pg. 323), for example, notes that “growth increases managers’ power by

increasing the resources under their control. It is also associated with increases in managers’

compensation, because changes in compensation are positively related to the growth (see Kevin

Murphy (1985)).” Moreover, scale and span of control can enhance the stature of the CEO in the

industry and community. When the CEO has significant influence over some directors on the

board and, accordingly, is permitted additional behavioral latitude and managerial discretion,

such overinvestment is more likely. All else equal, co-option will be associated positively with

investment.

H4: All else equal, firm investment increases with co-option.

- Data and Summary Statistics

We start with the RiskMetrics database, with coverage of directors of S&P 500, S&P

MidCap, and S&P SmallCap firms over the period 1996-2010. RiskMetrics does not provide a

unique firm-level or director-level identifier over the entire time period. In the Appendix we

describe how we associate unique identifiers with each record on RiskMetrics.7 We obtain

Wang (2011) use the pay performance sensitivity derived from the total portfolio of accumulated stock and option holdings net of dispositions. Falaye (2007) uses Aggarwal and Samwick (1999) type regressions of changes in annual pay on dollar returns and interprets the coefficient on dollar returns as PPS. 7 RiskMetrics provides two different director identifiers, neither of which is fully populated for all directors. Between 23 – 27% of director-years have missing identifiers. We combine both to create a unique identifier for all director-year observations. Importantly, if only one of these identifiers is used, it will result in incorrect estimates of

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compensation data from Execucomp, accounting data from Compustat, and stock return data

from CRSP. We exclude firms incorporated outside the U.S. We define below our key

variables.

3.1. CEO forced turnover

The logic underlying our measure of co-option is most applicable for forced turnover.

Unfortunately, it is difficult to classify turnover as forced or voluntary. Very often, even forced

turnovers are reported to the press as voluntary. Nevertheless, we use an approximate

classification scheme, similar to that used in other papers (such as Denis and Denis (1995)) to

separate turnovers into forced or voluntary. We define Forced Turnover as one if the departing

CEO is less than 60 years old, and zero otherwise.

3.2. CEO pay

Our measure of CEO pay is total annual compensation (Execucomp variable TDC1).

This includes the value of annual stock option grants, salary and bonus, value of annual restricted

stock grants, other annual compensation, long-term incentive payouts, and all other

compensation. We discuss in the Appendix how the changes in compensation reporting

following FAS 123R and new SEC disclosure requirements affect the reporting of pay. We

compute an adjusted pay measure (discussed in more detail in the Appendix) that accounts for

these changes in reporting. Our results are similar using this adjusted pay measure.

3.3. CEO pay-performance sensitivity

Pay-performance sensitivity is estimated as the sensitivity of CEO wealth to stock price,

otherwise termed as CEO delta, based on the entire portfolio of stock and options held by the

CEO. Specifically, the semi-elasticity form of delta is the expected $ change in CEO wealth for board size, independence, co-option etc. Upon request, the authors can provide the unique director identifier that we create as well as the unique firm identifiers (GVKEY and PERMNO) for each record on RiskMetrics.

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a 1% change in stock price. We calculate delta using the approach of Core and Guay (2002) but

with adjustments to Execucomp data as specified in the Appendix. Also see Coles, Daniel, and

Naveen (2013) for details on data and on calculation of incentive measures in the presence of

changing financial reporting requirements and formats.

3.4. Investment

Our proxy for investment is capital expenditures scaled by book value of assets.

3.5. Co-option

Our principal measure of co-option is based on the number of directors elected after the

CEO takes office. We refer to such directors as “co-opted” directors.

sizeBoard directorsoptedCooptionCo #

This variable ranges from 0 to 1, with higher values indicating greater co-option.8

In some specifications, we use an alternative measure of co-option, Tenure-weighted Co-

option (TW Co-option), which is the sum of the tenure of co-opted directors divided by the total

tenure of all directors. Thus,

sizeboard

i i

sizeboard

i ii

Tenure

DummyDirectoroptedCoTenure optionCoTW

1

1

where Co-opted Director Dummyi equals 1 if the director ‘i’ is a co-opted director, and equals 0

otherwise. Tenurei refers to the tenure of the director ‘i’ on the board. This alternative measure

8 In contemporaneous work independent of ours, Morse, Nanda, and Seru (2011) develop a measure of CEO power based on three elements, one of which is similar to our measure of co-option. They show that more powerful CEOs (CEOs who have titles of Chairman, CEO, and President, CEOs of firms with insider-dominated boards, or CEOs with a greater proportion of directors appointed during their tenure) rig their pay contracts by increasing the weights on the better performing measures.

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accounts for the increase of influence of co-opted directors on board decisions through time, as

such directors work alongside the CEO and previously appointed directors. This measure

assumes that the greater the tenure of co-opted directors, the greater their influence on board

decisions. Again, this measure can vary from 0 to 1, with a higher value indicating greater board

capture.

Our third measure of co-option is Residual Co-option, which is defined as the residual

from a regression of Co-option on CEO tenure. Our final measure of co-option is Residual TW

Co-option, which is the residual from a regression of TW Co-option on CEO tenure. These two

measures remove the positive correlation between CEO tenure and co-option.

For each firm-year, RiskMetrics provides the date of the annual meeting and the slate of

directors up for election. The directors on the slate almost always obtain sufficient support to be

elected (Hermalin and Weisbach (1998) and Cai, Garner, and Walking (2009)). The majority of

the sample firms hold their annual meeting during the first 3 – 4 months of the fiscal year. Thus,

because these directors constitute the board for the majority of the fiscal year, we assign directors

on the slate at the annual meeting in a given fiscal year as the directors for that year.

For CEO turnover events, we are careful to identify the board in place before the CEO

was dismissed since this board is the one responsible for replacing the CEO. Thus the CEO

turnover date relative to the meeting date is important for our purpose. Figure 1 illustrates the

timeline. If a CEO turnover occurred after the annual meeting date, then the board that

determined the replacement was the board elected for that year. That is, turnover and co-option

are measured contemporaneously. If a CEO turnover occurred before the annual meeting date,

then the board responsible for replacing the CEO is the one elected in the previous year so we

use lagged measures of co-option in the turnover regression. In non-turnover years, since both

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the lagged and contemporaneous boards decide on the CEO’s ‘non-replacement,’ we use the

average of the lagged and contemporaneous values of co-option.

For regressions explaining variation in CEO pay, CEO delta, and investment, we use the

contemporaneous co-option measure, because this is based on the board that is in place for the

majority of the year and also because performance-based pay (which is a significant component

of overall pay) will be decided by the board at the end of the fiscal year.

3.6. Independence

Independence is the ratio of the number of independent directors on the board to total

board size. Independent directors are those who are neither inside nor grey directors (Weisbach

(1988), Byrd and Hickman (1992), Brickley, Coles, and Terry (1994)).

3.7. Summary statistics

Table 1 provides the summary statistics. To minimize the influence of outliers,

throughout the paper we winsorize all variables at the 1st and 99th percentiles.9 The average firm

in the sample is large, with sales of $5.3 billion. This is not surprising given that our sample is

S&P 1500 firms. The average board has about 10 directors. Co-option has a mean value of 0.47,

while mean Independence is 0.69. Thus, on average, although more than two-thirds of the

directors are technically independent, our calculations indicate that nearly half of the board has

been co-opted by the CEO. Average Tenure-Weighted (TW) Co-option is 0.31, implying that

while co-opted directors make up nearly half the board, their influence, after accounting for their

tenure on the board, is a bit lower at 31%. Not surprisingly, Co-option and TW Co-option are

similar, with a correlation of 0.93 (p <0.0001). Co-option and TW Co-option are dissimilar to

board independence (ρ = – 0.07 and ρ = – 0.09 respectively). 9 Our results are similar if we winsorize all variables at the 0.5 and 99.5 percentiles instead. Our results are also similar if we drop the observations in the top and bottom 0.5 percentiles from the analyses.

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The unconditional rate of forced turnover is 0.025. For comparison, the equivalent

number is 0.019 in Hazarika et al. (2012) (inferred from their Table 1) and is 0.030 in Mobbs

(2012). On average, CEOs receive $4.9 million in total annual compensation, have a delta of

$789,000, and have about 8 years of tenure. On average, investment is 5.2% of total book assets.

- Co-option and Monitoring Ineffectiveness: Empirical Results

4.1. Co-option and CEO turnover-performance sensitivity

Our first hypothesis, H1, is that the sensitivity of CEO turnover to performance decreases

with co-option. To test this, we estimate the following logistic regression:

ln[Prob(Forced Turnover)/(1 – Prob(Forced Turnover))] = α0 + α1 Co-option Performance + α2 Performance + α3 Co-option + α4 Independence + f(Other Controls) + ε1

Our proxy for performance is Prior Abnormal Return. For turnover years, this is

measured as the firm stock return (including dividends) in the year leading up to the actual date

of CEO turnover minus the value-weighted market return over that period. For non-turnover

years, this is measured as the stock return over the previous fiscal year minus the value-weighted

market return over that period. It is well-documented that, in practice, performance is negatively

related to the likelihood of CEO turnover, or that α2 is negative (Weisbach (1988), Warner,

Watts, and Wruck (1988), Parrino (1997), and Kaplan and Minton (2012)). Our hypothesis is

that turnover-performance sensitivity is attenuated by co-option, or that α1 is positive. All

specifications include Independence. Other control variables (Other Controls) include: firm size;

CEO tenure; and governance variables. The governance variables are: CEO ownership; CEO

duality, an indicator variable that equals 1 if the CEO has title of chairman also; outside director

ownership; GIM index, the governance index of Gompers, Ishii, and Metrick (2003); board size;

female director, an indicator variable that equals 1 if the firm has a female director on board; and

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(in some models) terms interacting governance variables with prior performance.10 We include

firm- fixed effects to control for any omitted firm-specific and time-invariant variables that are

correlated with co-option. We include year fixed effects to control for variation in common

influences through time. In general, our control variables are based on those in Adams and

Ferreira (2009), Hwang and Kim (2008), Fich and Shivdasani (2007), and Dittmar and Mahrt-

Smith (2007).

Table 2 reports the results. In Models 1 and 2, the key independent variable is the

interaction term of Co-option with Prior Abnormal Return. For each independent variable, we

report the coefficient estimates (Row 1), z-statistics (Row 2), and the marginal effects (Row 3).

We report the marginal effects because there is no ready economic interpretation of the

coefficients in non-linear regressions. The marginal effect is presented in semi-elasticity form.

For continuous variables, the marginal effect represents the percentage change in the probability

of Forced Turnover for a one unit change in the underlying variable, holding all other variables

at their mean values. For indicator variables, we report the percentage change in the probability

of Forced Turnover when the indicator variable moves from zero to one (holding other variables

at their mean values).11

Consistent with our hypothesis, the coefficient on the interaction term of Co-option and

Prior Abnormal Returns (α1) is positive and statistically significant (= 2.021, z-statistic = 3.4),

indicating that an increase in Co-option is associated with a decrease in the sensitivity of CEO

turnover to firm performance. To estimate the effect of the interaction term, we compute the

10 For the four CEO-related variables, the values correspond to the departing CEO in the year of turnover. Also, we do not include CEO age because Forced Turnover is automatically zero when the CEO is over 60. 11 Ai and Norton (2003) note that interpretation of interacted variables in non-linear models is not straight-forward. Stata (Version 11) has since introduced the margins statement which correctly computes the marginal effects in non- linear models with interaction terms. We use this statement to compute all reported marginal effects.

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marginal effect of Prior Abnormal Return at two different levels of Co-option: at the mean as

well as mean plus one standard deviation (holding all other variables at their mean values). The

difference indicates how the sensitivity of turnover to performance changes with co-option. As

can be seen in Model 1, the sensitivity of turnover to firm performance decreases by 0.856, from

–1.331 at the mean value of Co-option, to –0.476 when Co-option increases by one standard

deviation from its mean value (for ease of presentation in the table we report only the

difference). In other words, the sensitivity of turnover to performance goes down by almost two-

thirds when Co-option moves by one standard deviation from its mean value. If Co-option

increases even further to the maximum possible value of 1, then the sensitivity of forced turnover

to performance is even smaller (= –0.092; see the last row of Table 2).12 Thus, the results in

Model 1 are consistent with H1. Turnover-performance sensitivity decreases as co-option

increases.

In Model 1, we allow only Co-option to affect the turnover-performance sensitivity (that

is, we include only the interaction term of Co-option with Prior Abnormal Return). In Model 2

we allow all governance-related variables (Independence, CEO ownership, CEO duality, outside

director ownership, GIM index, board size, and female director) to affect the turnover-

performance sensitivity. Two results are worth noting. First, the coefficient on the interaction of

Co-option with Prior Abnormal Return remains significantly positive. Second, Independence

does not appear to have a significant impact on turnover-performance sensitivity. Board co-

option, rather than board independence, has explanatory power for turnover-performance

sensitivity.

12 In the model, α2 represents the effect of Prior Abnormal Return on Forced Turnover when Co-option is zero. When STATA reports the marginal effect of Prior Abnormal Return, however, it reports the total effect of Prior Abnormal Return on Forced Turnover at the mean of all variables.

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In Models 3 and 4, we use the same specifications as in Models 1 and 2 respectively, but

include TW Co-option rather than Co-option. The estimated coefficient on the interaction of TW

Co-option with Prior Abnormal Return remains significantly positive in both specifications. In

terms of economic significance, the results in Model 3 indicate that when TW Co-option

increases by one standard deviation from its mean value, the sensitivity of turnover to

performance changes from –1.539 to –0.577 (the table reports the difference = 0.962) . The last

row in the table shows that when TW Co-option increases to 1, the sensitivity of turnover to

performance is altered further to 0.213, which is positive. Results from Model 4 are similar.

A potential issue arises because our two co-option measures (Co-option and TW Co-

option) are positively correlated with CEO tenure. Thus, multicollinearity could be a concern.

To address this concern, we replace Co-option with Residual Co-option, which is the residual

from a regression of Co-option on CEO tenure. Model 5 reports the results. The coefficient on

the interaction of Residual Co-option with Prior Abnormal Returns is significantly positive,

indicating that the effect of Co-option on CEO turnover-performance sensitivity documented in

Model 1 is not due to the correlation between Co-option and CEO tenure. Finally, in Model 6,

we replace Co-option with Residual TW Co-option, which is the residual from a regression of

TW Co-option on CEO tenure. Once again, our results are similar to those in Model 3.13

In terms of the other control variables, our results across the various models show that

CEO duality is significantly negatively related to CEO turnover (as in Goyal and Park (2002)).

In contrast, the other governance variables, in general, are not consistently significant across the

13 We also estimate Models 5 and 6 including interactions of all governance variables with prior abnormal returns (as in Models 2 and 4). When we re-estimate Model 6 in this manner, the results are statistically and economically similar to our main results. When we re-estimate Model 5, the results are economically similar but statistically weaker. The sensitivity of turnover to performance decreases from –1.62 at the maximum value of Residual Co- option to –0.26 at the minimum value. The interaction of Residual Co-option with prior abnormal returns is positive, but is insignificant (p = 0.195).

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various specifications.

The number of observations is much smaller in our turnover regressions because the use

of firm-fixed effects means that firms that never had a forced turnover during the sample period

are excluded from the regression. To ensure that our results are not driven by any sample

selection, we estimate the same regression models without firm-fixed effects, but with industry-

fixed effects, and obtain very similar results for all six specifications on a much larger sample.

In all tables that follow, we report t-statistics based on standard errors adjusted for

heteroskedasticity and clustering at the firm level (Petersen (2009)). This option, however, is not

available for the fixed-effects logistic regression models in Table 2. As a robustness check, we

bootstrap the standard errors using 200 replications. We find qualitatively similar results using

the bootstrap.

Overall, the results indicate that, consistent with H1, turnover-performance sensitivity is

attenuated as measures of board co-option increase.

4.2. Co-option and CEO pay level

Our second hypothesis, H2, predicts that CEO pay increases with co-option. To test this,

we estimate regressions of CEO pay on co-option and controls.

CEO Pay = θ0 + θ1 Co-option + θ2 Independence + g(Other Controls) + ε2. Hypothesis H2 asserts that the coefficient on Co-option (θ1) will be positive. The control

variables, based on prior literature (see Murphy (1999) for a comprehensive review of CEO

compensation), include board independence, firm size, firm performance (both stock and

accounting), CEO tenure, governance variables, and firm and year dummies.14 We do not

14 The results are robust to using industry and year fixed-effects instead.

18

include CEO turnover years and require that the CEO’s tenure be at least one year. This is

because CEO pay in a turnover year is likely to reflect compensation only for part of the year.

Also, CEOs in their first year may receive higher than average stock compensation (to align their

incentives) and higher bonus (including signing bonuses). We use the logarithm of annual

compensation as the dependent variable because compensation data are skewed.15

Table 3 presents the results. In Model 1, the coefficient on Co-option is significantly

positive, implying that CEO pay increases with co-option.16 The coefficient of 0.223 on Co-

option indicates that moving from zero to full co-option would be associated with an increase in

CEO pay of 22.3%. A less extreme measure of economic significance is the change in pay when

Co-option increases by one standard deviation. In this case, we find that CEO pay increases by

7% relative to the mean pay. This corresponds to about $345,380 annually for the CEO.

In Model 2, we use TW Co-option rather than Co-option. As with Co-option, we find that

the coefficient on TW Co-option is significantly positive. Finally, in Models 3 and 4 we use

Residual Co-option and Residual TW Co-option. The results are similar. The coefficients on

both measures are significantly positive, indicating that co-option is associated with higher pay,

and this effect is not driven by the positive correlation between co-option and tenure.

Board independence has no explanatory power for CEO pay in two of the four

specifications. In the other two models, the coefficient on Independence is positive, which is

inconsistent with greater independence leading to better monitoring of rent extraction.17 For the

other control variables, as expected firm size and performance are strongly positively associated 15 We obtain similar results using unlogged compensation. 16 This result is consistent with Core, Holthausen, and Larcker (1999), who, using a sample of 495 firm-years over 1982-1984, find that CEO total pay is positively related to the proportion of the board composed of new outside (both independent and affiliated) directors. 17 As a robustness check, instead of using contemporaneous values of our co-option measures, we also use the average of the contemporaneous and the lagged values, since the lagged board may also be partly responsible for CEO compensation. Our results are robust to this change.

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with pay. Overall, the evidence is consistent with CEO pay increasing in co-option (H2).

4.3. Co-option and CEO pay-performance sensitivity

Pay-performance-sensitivity –– otherwise known as delta –– is seen as aligning the

incentives of managers with the interests of shareholders. Higher delta can mean that managers

will work harder or more effectively because managers share gains and losses. Thus, we now

examine the influence of co-option on CEO delta. The representative specification is

CEO Pay-Performance Sensitivity = γ0 + γ1 Co-option + γ2 Independence + h(Other Controls) + ε3.

Our control variables are based on the prior literature on the determinants of delta (Core and

Guay (1999) and Coles, Daniel, and Naveen (2006)) and the governance variables used in the

preceding regressions.

Table 4 presents the results. As in Table 3, our independent variables are Co-option

(Model 1), TW Co-option (Model 2), Residual Co-option (Model 3), and Residual TW Co-option

(Model 4). In Models 1 and 3, the estimated coefficients on Co-option and Residual Co-option

are negative (consistent with our hypothesis), but insignificant at conventional levels (p = 0.107

and 0.103 respectively). In Models 2 and 4, the estimated coefficient on TW Co-option and

Residual TW Co-option are negative and significant, albeit at the ten percent level. The

coefficient on Co-option in Model 1 indicates that when Co-option increases by one standard

deviation from its mean, pay-performance sensitivity decreases by 12% from its mean value.

When Co-option increases from zero to one, sensitivity of pay to performance decreases by

$296,485, or by 38% from its mean value.

The coefficient on board independence is negative and significant in Models 1 – 4. This

result, which is similar to the result in Coles, Lemmon, and Wang (2011), suggests that board

monitoring and CEO delta may well be substitutes in organization design.

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For robustness, as we do with CEO pay, we use the average of the contemporaneous and

the lagged values of the co-option measures instead of the contemporaneous values alone. Also,

we use industry-year fixed effects instead of firm-year fixed effects. The results in both cases

are similar to our base-case result, in that the coefficient on the co-option measures continues to

be negative but insignificant at conventional levels.

In sum, we find weak evidence in support of the hypothesis (H3) that higher co-option is

associated with lower CEO pay-performance sensitivity (PPS). CEO pay and PPS, however,

cannot be viewed as independent of each other. CEOs would demand higher pay if greater risk

is imposed on them in the form of higher PPS. Instead, if anything, co-option is associated with

lower exposure of CEO wealth to risk. Thus our finding that co-option is associated with higher

pay, but similar or even lower PPS, is consistent with co-opted boards adopting more liberal

compensation policies that are favorable to the CEO.

4.4. Co-option and investment

Hypothesis H4 proposes that co-option is positively associated with investment. We

examine this using the following specification:

Investment = μ0 + μ1 Co-option + μ2 Independence + j(Other Controls) + ε4.

The dependent variable is capital expenditure scaled by assets. In addition to board

independence, the other key independent variables are based on Coles, Daniel, and Naveen

(2006) and include vega, delta, cash compensation, CEO tenure, Tobin’s q, firm size, free cash

flow to assets, sales growth, leverage, and stock return.

Table 5 shows the results. In Model 1, we use Co-option as our key variable of interest.

The coefficient on Co-option is positive and statistically significant (= 0.005, p-value = 0.014).

In terms of economic significance, the coefficient indicates that when Co-option increases by one

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standard deviation, investment increases by 3% relative to the mean. When Co-option increases

from zero to one, investment increases by 10% relative to its mean value.

In Column 2, as the dependent variable we use TW Co-option instead of Co-option. Once

again, the coefficient on TW Co-option is positive and statistically significant. In the last two

columns we use Residual Co-option and Residual TW Co-option respectively. Our results are

similar in sign and significance.

In all specifications, we find that the fraction of independent directors is negatively

associated with investment. The results on the other control variables are consistent with prior

literature. Consistent with Coles et al. (2006), we find the coefficient on vega is negative

(although not significant at conventional levels), and the coefficient on delta is positive. Higher

Tobin’s q and higher free cash flow are associated with more investment.

As with CEO pay and pay-performance sensitivity, we confirm that the results are

qualitatively similar if we use the average of the contemporaneous and the lagged values of the

co-option measures instead of the contemporaneous values alone. When we use industry-year

fixed effects instead of firm-year fixed effects, however, we find that the coefficient on co-option

is not significant.

Overall, the results in this subsection support the hypothesis that CEOs that have captured

the board to a greater extent are able to invest more than otherwise would have been the case. At

this juncture, based on our results, we are unable to discern whether such investment, which

likely increases firm size and the economic span of control of top management, is necessarily

inconsistent with shareholder interests. On this question, however, in separate, independently

developed work, Pan, Wang, and Weisbach (2013) document that investment increases with the

extent of CEO control of the board, as proxied by a measure of co-option similar to ours. They

22

also find that the quality of investment (captured by the market reaction to acquisition

announcements) deteriorates over the CEO’s tenure and that this deterioration is related to the

CEO’s control of the board. Thus, the relation we document between CEO investment and Co-

option potentially arises because (Pan et al. (2013, abstract)) “… the CEO overinvests when he

gains more control over his board.”

- Endogeneity

Endogeneity is an important concern in any study on corporate governance (Coles,

Lemmon, and Wang (2011)). In particular, it is possible that both co-option and pay are high

due to an unobserved (and hence omitted) variable. Since we include firm-fixed effects in all our

specifications, we control for omitted variables that are firm-specific and time-invariant. If the

omitted variable is time-varying or not firm-specific, however, and is correlated with co-option,

this would cause the error term in the outcome equation to be correlated with co-option,

rendering OLS invalid. Another source of endogeneity is that both co-option and our variables

of interests, such as pay, are determined in equilibrium simultaneously. One solution would be a

valid instrument for the endogenous variable (Co-option). It is difficult, however, to find an

instrument that is related to co-option, but is not related to CEO pay or the other outcomes we

examine. As an alternative to firm-fixed-effects specifications, we turn to a natural experiment

to help us address endogeneity concerns.

We exploit the rules enacted in 2002 by the Nasdaq and NYSE, requiring all listed firms

to have a majority of independent directors on their board.18 Since these rules were adopted

shortly after the passage of SOX, we refer to the period following the proposal of the new stock 18 A detailed timeline is available in Chhaochharia and Grinstein (2007).

23

exchange rules (2002–2010) as the post-SOX period. Pre-SOX non-compliant firms were

required to increase board independence after implementation of the new listing requirements,

and these firms chose to add new independent directors onto the board (Linck, Netter, and Yang

(2009)). This resulted in an exogenous increase in co-option.19

To isolate the causal impact of co-option, we modify somewhat the Bertrand and

Mullainathan (2003) difference-in-difference (DID) methodology. The key difference is that we

allow for the possibility that SOX and associated exchange provisions have a direct effect on

turnover-performance-sensitivity, pay, pay-performance-sensitivity, and investment, as well as

an effect through co-option. This is because other regulations and political pressure arising from

SOX were likely to have affected monitoring through numerous channels.20 For example, under

SOX and the associated exchange provisions: complete independence was mandated for the

compensation, audit, and monitoring committees; a director with financial expertise was required

on the audit committee; in addition to their regular sessions, boards were required to meet

without management; CEO/CFO certification of accounting statements was required; and there

was a general increase in media scrutiny of all firms.

Because of this complication, we modify the typical DID setup to isolate the effect of co-

option (we term this the “clean” effect). The typical DID set up for examining pay, for example,

would be to regress pay on three dummy variables: Post-SOX, Non-Compliant, and the

interaction term Post-SOX × Non-Compliant, where Post-SOX is an indicator variable that

equals 1 if the year is 2002 or later, and equals 0 otherwise, and Non-Compliant is an indicator

variable that equals 1 if the firm was not in compliance in 2001, and equals 0 otherwise. Co-

19 We are particularly grateful to the referee for suggesting this specific line of attack and for shaping some of the other aspects of our approach to ameliorating endogeneity concerns. 20 Indicative evidence on the effects of SOX on pay and turnover is presented in Chhaochharia and Grinstein (2007), Carter, Lynch, and Zechman (2009), and Kaplan and Minton (2012).

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option is not included in the above specification, and the focus is on the coefficient on Post-SOX

× Non-Compliant. This coefficient, however, captures both the effect we want to isolate

(through the exogenous shock to co-option) and direct effect (through other channels) of SOX.

To assess the impact of co-option, we estimate the modified regression, which includes Co-

option and the interaction of Co-option with the three dummy variables:

Pay = β0 + β1 Co-option + β2 Post-SOX Co-option + β3 Non-Compliant Co-option + β4 Post-SOX Non-Compliant Co-option + β5 Post-SOX + β6 Non-Compliant + k(Other Controls) + ε5

The controls in the specification include the independent variables used in the pay regressions in

Table 3 and the individual dummies, as well as the interactions of all the independent variables

with the three key dummy variables: Post-SOX, Non-Compliant, and Post-SOX × Non-

Compliant.

Panel A of Table 6 provides an estimate of the sensitivity of pay to co-option for the four

subsamples of firms: compliant firms in the pre-SOX period, non-compliant firms in the pre-

SOX period, compliant firms in the post-SOX period, and non-compliant firms in the post-SOX

period. The effects are estimated by taking the partial derivative of Pay with respect to Co-

option in the equation above. As can be seen from the table, β1 and β1+β3 represent the

sensitivities for compliant and non-compliant firms respectively in the pre-SOX period. Both

sensitivities include the bias due to endogeneity. The sensitivity of Pay to Co-option for

compliant firms in the post-SOX period is given by β1 + β2 and this includes not only the effect

of bias but, in addition, the direct effects of SOX. The sensitivities for firms in all three groups

are subject to bias due to the standard set of reasons that give rise to the endogeneity problem.

We allow this bias to differ by whether the firm was compliant (superscript C) or not compliant

(superscript NC) pre-SOX, though we do restrict BiasC to be the same both pre- and post-SOX.

25

The subsample of primary interest is the non-compliant post-SOX group. This group

contains firms facing the exogenous shock to co-option. The sensitivity for this subsample (= β1

- β2 + β3 + β4) is contaminated by the SOX effects through channels other than co-option, and

thus represents the combined effect of both co-option and SOX on the variable of interest (=

“Clean + SOX”). As can be seen from the table, the typical DID estimate reported in the lower

right cell (β4) does not yield the clean estimate, but rather the negative of BiasNC. The “clean”

estimate, arising from the exogenous increase in co-option, forced on noncompliant firms

through a mandated increase in board independence, is given by β1 + β3 + β4.

Panel B of Table 6 provides the results. For brevity, we present only the clean estimates

for the total impact of co-option on each of the four variables of interest (turnover-performance

sensitivity, pay, pay-performance sensitivity, and investment). For ease of comparison, we

report results from the base-case regressions (Model 1 of Tables 2–5). In terms of the notation in

the regression specifications defined above, we report clean estimates of α1, θ1, γ1, and μ1.

For turnover and pay level, relative to the base case the estimates based on an exogenous

shock to co-option have the same sign and similar (though not quite as strong) statistical

significance. The clean estimate pertaining to the effect of co-option on CEO PPS, like that in

the base case, is statistically insignificant. The clean effect of co-option on investment policy is

still positive, but statistically weaker (t-statistic = 1.0 versus 2.5) than the estimated coefficient

from the base case.

- Are All Independent Directors Equally Relevant for Board Monitoring?

In this section, we examine whether monitoring effectiveness of directors varies

depending on whether or not they are independent and by whether or not they are co-opted.

6.1. Co-option: independent versus non-independent directors

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Our results thus far indicate that board capture is associated with weaker monitoring.

The measures of co-option used above, however, do not differentiate between directors who are

independent versus those that are not. Indeed, the notion that employee and affiliated directors

are co-opted is the basis for using board independence as a measure of monitoring in the first

place (e.g., Weisbach (1988) and Byrd and Hickman (1992)). The question remains as to

whether co-option blunts the monitoring effectiveness of independent directors. If we find that

co-opted directors who are independent are also weak monitors, then it would suggest that the

independence measure traditionally used in the literature does not capture the disposition of the

board to provide effective oversight and monitoring and can be improved. To examine this

question, we further refine Co-option. Co-opted Independence is defined as the proportion of the

board that consists of co-opted directors who are independent, while Co-opted Non-

Independence is defined as the proportion of the board that consists of co-opted directors who

are not independent. These two measures differentiate between directors who are employees or

affiliated versus those who are supposedly independent.

Table 7 documents the results. In Panel A, for ease of comparison, we reproduce our

base-case results on Co-option (Model 1 of Tables 2 – 5). We report the coefficients and

associated t-statistics only for our primary variables. Panels B and C report our results wherein

we replace Co-option by Co-opted Independence and Co-opted Non-Independence respectively.

In Panel B, we find that Co-opted Independence is associated with attenuated turnover-

performance sensitivity, higher pay, lower CEO delta, and higher investment. Per Panel C, Co-

opted Non-Independence is associated with attenuated turnover-performance sensitivity and

higher investment, but has no effect on pay or pay-performance sensitivity. Thus, our overall

results on co-option appear to be driven by independent co-opted directors, rather than by non-

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independent co-opted directors. We conclude that, once a director is co-opted, the independence

of the director does not matter from a monitoring perspective. This likely explains why the

literature has found little uniform evidence on the relation between board independence and

various measures of firm performance and structure.

6.2. Independence: co-opted versus non-co-opted directors

Our results to this point suggest that: (i) independent directors typically do not have an

effect on monitoring effectiveness in the presence of co-option (Tables 2 – 5), and (ii) co-opted

directors, even those that are independent, are weak monitors (Table 7). It is likely, therefore,

that only independent directors who are not co-opted by the CEO are effective monitors. To test

this formally, we introduce a second new measure of board composition, Non-Co-opted

Independence. We define this as the proportion of the board that consists of independent

directors who were already on the board when the CEO assumed office.

Panel A of Table 8 depicts the overlap and dissimilarity between our measures of co-

option and independence. As can be seen, the sum of Co-opted Independence and Co-opted

Non-Independence equals Co-option, while the sum of Co-opted Independence and Non-Co-

opted Independence equals Independence.

Figure 2 plots how the various board composition measures described above change over

CEO tenure. As expected, Co-option increases with CEO tenure. This is because in each

director election cycle the CEO has the opportunity to affect the nomination of directors to the

board. Independence, however, remains more or less constant (at around 69% in our sample).

Thus, while on the surface it appears that board independence is high, the composition of the

board as represented by co-option gradually tilts in the CEO’s favor over time. Further, a closer

look at the two components of Independence indicates that as CEO tenure increases, Co-opted

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Independence increases while Non-Co-opted Independence decreases. This arises as the CEO

replaces previously appointed independent with new independent directors. This suggests that

the monitoring effectiveness of the board weakens over the CEO’s tenure. We explore this issue

by estimating our base-case regressions with both Co-option and Independence replaced by Non-

Co-opted Independence as the key dependent variable.

Panel B of Table 8 reports the results. Consistent with the idea that independent directors

who are not co-opted are better monitors, we find Non-Co-opted Independence is associated with

higher sensitivity of CEO turnover to performance, lower pay levels, higher sensitivity of pay to

performance, and lower investment.

Overall, these results are consistent with non-co-opted directors being effective monitors.

Moreover, it appears that not all independent directors are the same. Differentiating among

independent directors by whether or not they are co-opted appears to be a more incisive way to

explain monitoring intensity of the board. Independent directors whose selection was influenced

by the CEO appear to be more sympathetic to the CEO. On the other hand, non-co-opted

independent directors appear to be effective monitors. Relative to aggregate board

independence, the representation of non-co-opted independent directors on the board appears to

be a sharper measure of monitoring effectiveness.

- Alternative Interpretations and Other Robustness Checks

7.1. Is Co-option capturing the effect of CEO tenure?

Figure 2 shows that Co-option increases over the CEO’s tenure. It is likely that CEO

power increases with tenure (e.g., see Weisbach (1988) and Ryan and Wiggins (2004)). Thus,

CEO tenure may be correlated with both power and Co-option and it is possible that our results

29

on the effect of co-option are due to the positive association between co-option and CEO tenure.

We perform three tests and conclude that CEO tenure is not causing our results.

First, our base case specifications include CEO tenure as an additional control variable in

all our regression specifications. Thus the effect of co-option that we document earlier is after

controlling for CEO tenure.

Second, in the specifications in Tables 2 – 5 (Model 1), instead of Co-option, we use

Residual Co-option, which is the residual from a regression of Co-option on CEO tenure. The

residual now no longer proxies for power arising from tenure but is a proxy for power related to

co-option of the board. We find that all results on Residual Co-option are similar to our results

on Co-option.21

Third, we drop Co-option from all specifications and use only tenure as our measure of

the CEO’s power over the board. If it is true that our results on Co-option somehow obtain only

because of the positive correlation between tenure and Co-option, and do not reflect the true

effect of board capture, then when we drop Co-option from the regressions, our results on tenure

should be similar to what we reported earlier with Co-option. That is, we should find that tenure

decreases CEO turnover-performance sensitivity, increases CEO pay, decreases CEO pay-

performance sensitivity, and increases investment. The results, however, are not supportive of

the idea that co-option is only capturing the effect of CEO tenure on monitoring.22 We find that

CEO tenure has a positive effect on turnover-performance sensitivity, similar to the effect of co-

option. In contrast to the effect of co-option, however, CEO tenure has no effect on pay or

21 The results are similar when we use Residual TW Co-option (the residual from a regression of TW Co-option on CEO tenure) instead. 22 In the interests of conciseness, we do not tabulate the results here or below. All results are available from the authors on request.

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