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Amsterdam Business School

“What is the impact of likelihood of dismissal on the

provision of performance-based compensation?”

MSc: Accountancy and Control

Track: Control

Thesis Supervisor: Dr. P. Kroos

Athanasios Koutras

ID: 10232214

Amsterdam, June 2012

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Contents

Contents...........................................................................................................................2

1. Introduction.......................................................................................................3

1.1. Background……………………………………………………….3

1.2. Research question………………………………………………....4

1.3. Motivation………………………………………………….……..4

2. Literature review and hypothesis…………....................................................5

2.1. Incentives and Sorting………………………………….………....5

2.2. Incentive compensation…………………………………………..6

2.3. Threat of dismissal………………………………………..………10

2.3.1. Why dismissal…………………………………...10

2.3.2. Firing cost and the termination incentive………..11

2.4. Key factors that affect the likelihood of dismissal and the influence of

Corporate Governance…………………………………..………...12

2.5. Relationship between performance-based compensation and threat of

dismissal……………………………………………………….….15

3. Research Design…….………………………………………………………...16

3.1. Sample selection………………………………………………….16

3.2. Empirical model………………………………………………….16

3.2.1. Dependent Variables…………………………….17

3.2.2. Independent variables…………………………...17

3.2.3. Control Variables………………………………..19

4. Findings………………………………………………………………………..21

4.1. Descriptive statistics……………………………………………..21

4.2. Empirical results……………………………………………...….24

5. Conclusion……………………………………………………………………..29

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Abstract

Prior studies have examined the relationship between the likelihood of dismissal and

performance. This study makes one step forward and attempts to detect if there is a

correlation between the threat of dismissal, used as incentive, and performance-based

compensation. The findings of the current paper demonstrate that there is a

complementary relationship between the CEO’s likelihood of dismissal and bonus

compensation, while they also show insignificant, though potential, evidence of a

substitute relation between the likelihood of dismissal and equity compensation.

1. Introduction

1.1 Background

Because of information asymmetry, owners of firms have limited information

regarding the actions of the managers. Therefore firms often use incentives to

encourage managers to take the desired actions that increase shareholders value, for

example through the threat of dismissal.

The threat of dismissal could be an incentive for the employees to increase their

performance and become more beneficial for the company in order not to be

dismissed. Particularly, the aforementioned incentive is much stronger when there are

other external factors which increase the cost of job loss, such as a higher

unemployment rate and a greater likelihood of a negative pay difference between the

old job and a prospective new job. According to previous research, dismissals have a

significant effect on productivity, but this relation is nonlinear (Kraft, 1991). This

means that on one hand, employees may be motivated from the possibility of

dismissal to perform better, but on the other hand the high risk of job loss could also

decrease their productivity. Many empirical studies have shown that there is a

negative relationship between performance and the probability of dismissal

(Weisbach (1988), Jensen and Murphy (1990), Kaplan (1994), Denis and Denis

(1995), Conyon (1998), and Chevalier and Ellison (1999).

Prior research distinguished several ways in which firms can provide incentives to

their employees. First, firms may provide monetary rewards if targets on predefined

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performance measures are achieved. Such rewards are bonuses, stock options,

restricted options and performance units (shares). Second, managers may experience

incentives because the threat of dismissal is basically a function of the likelihood of

dismissal and the corresponding cost of job loss.

Relatively, only a few research papers have looked into the question, how various

sources of incentives relate, and if incentives from compensation substitute or

complement those incentives that follow from the threat of dismissal. This study will

investigate the behaviour of the executives’ performance evaluators. The question

becomes whether they decrease the ex-ante incentive compensation that managers

face because it is assumed that the incentives of the likelihood of job dismissal are

sufficient with regard to the provision of effort-inducing incentives?

1.2. Research question

Taking into consideration the aforementioned, I will examine the following research

question:

“What is the impact of likelihood of dismissal on the provision of performance-based

compensation?”

1.3. Motivation

There are a lot of Wall Street Journal and other business publications, reporting the

job-termination of upper-level managers in the wake of poor performance. And while

chief executive officers (CEOs) used to be more often spared from the ranks of those

who lost their jobs, events over the last few years suggest a less secure future even for

chief executives. It seems that firms have the willingness to fire some of their

employees in the name of “good performance”. However, there is limited literature

regarding this particular topic. Most of the research has focused almost exclusively on

incentives provided by pay-for-performance schemes, while ignore the ability of the

firms to dismiss certain employees and increase in this way their performance-

inducing incentives. This research will constitute a contribution to previous research,

as it will examine the extent to which, the provision of performance-based

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compensation is affected by the threat of job-termination. In other words, the current

study will attempt to investigate how executive level managers’ compensation could

fluctuate due to the likelihood of dismissal.

Furthermore, as firms may be more inclined in recent years to fire executives

following poor performance, it is relevant for those firms to know whether different

incentives may be regarded as substitutes or complements. So, companies may gain

knowledge whether to increase or decrease bonuses, following an increase in the

likelihood of dismissal.

2. Literature Review and Hypothesis

2.1 Incentives and Sorting

Agency theory describes the relationship between the principal who delegates certain

tasks to the agent, who is responsible to complete this work. It explains their

differences in behaviour by stating that most of the time both parties have different

goals to meet and different attitudes toward risk. Adverse selection describes,

amongst others, the problems that principals encounter while inferring the quality of

the agent. Furthermore, the principal is not always able to fully observe the agent’s

actions and ability because of information asymmetry.

Agents always have more information than owners, regarding the firm’s performance

or even their own capabilities. Hence, the agent can use the informational advantage

to maximize his or her own benefit and interest, which leads to agency costs for the

principal. To minimize such consequences, most firms use a set of performance

measures to control agents’ activities and pressure them to increase their productivity.

They achieve that by measuring the progress of a manager toward a predefined

objective or goal, verifying ex-post whether managers have taken desired actions and

whether they are of sufficient quality. In addition managers face ex-ante incentives

when rewards or penalties are beforehand linked to performance measure outcomes.

In order for firms to improve the efficiency of these measures and realize a significant

increase in shareholders’ value, they provide a mix of incentives. One of these

incentives that will be examined in this study is the threat of dismissal.

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People being fired from their jobs, is not an uncommon feature in business practice.

Although dismissals have social and economic effects to the people got fired, there is

not much known regarding whether these people lost their jobs due to limited

capabilities or just because the board of directors tried to provide effort-inducing

incentives. Kwon (2003) was the one who tried to examine the threat of dismissal

from two different views: that of “incentive or sorting”. Both of them are costly for

the company. For the example of dismissal motivated by sorting, the firm has to

search and train new employees. In addition, when compensation committees use

dismissal as incentive device, this requires a strong commitment from the firm’s

board of directors, since they may have to fire a well qualified or highly experienced

executive because of some random events (causing the poor performance).

Overall, both models predict that the likelihood of dismissal decreases with good

performance and when the agent belongs to the category of “learning-by-doing”, the

average dismissal probability decreases over time. Indeed, Dikoli et al. (2008)

document how the (negative) relationship between performance and the likelihood of

dismissal becomes weaker as the tenure of the CEO increases.

2.2 Incentive Compensation

In general, the compensation committee of the board of directors in consultation with

the human resources, finance department and other third-party consultants, are

responsible for the compensation of the chief executive officer and other managers.

According to SEC (Securities & Exchange commission), the organizations are obliged

to include a Compensation Discussion & Analysis (CD&A) section in their annual

statement, in order to get shareholders’ approval for the compensation plan.

Shareholders can evaluate this program taking into consideration the company’s

compensation philosophy, total compensation awarded, elements of the pay package,

the peer groups used for comparative purposes in designing compensation and

measuring performance, performance metrics used to award variable pay, pay equity

between the CEO and other senior executives, stock ownership guidelines, clawback

policies, severance agreements, golden parachutes, and post-retirement compensation.

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A compensation program aims typically to: first, attract the right people for the job,

taking into account their skills, their experience and their ability to succeed in a

specific position. Second, retain the most efficient employees; otherwise they will

chase a better position in a competitive company that offers more appropriate

compensation for their talent. Third, provide them the right incentives to have a more

efficient performance. For example, encouraging those behaviors that are aligned with

the corporate strategy and discouraging the self-interested ones.

Many firms link compensation to performance by implementing performance-based

incentive programs at every level of the organization. Several economic theories state

that performance-based compensation increases a firm’s overall productivity by

attracting and retaining the more efficient employees (selection effect) and/or by

inducing employees to raise or better allocate their effort to increase their

performance (effort effect). According to the selection effect, a performance-based

compensation contract can be used as an ideal device that encourages less productive

employees to leave the firm, and on the other hand, motivates more productive

employees to join or remain with the firm. However, the impact of this effect on

employees’ behavior may not be instant because the employees themselves may not

be aware of their own capabilities, and may learn about them, only when they receive

feedback regarding their performance. Turning to the effort effect, a performance-

based compensation plan provides incentives to employees to increase their

performance by learning more efficient ways to deal with their daily tasks.

Banker, Lee, Potter and Srinivasan (2001) found that the improvements after the

implementation of such performance-based incentive plans are related to those

economic theories referring to employees’ behavior. They document that the

implementation of the plan leads to the attraction and retention of more productive

employees, supporting the hypothesis that a pay-for-performance plan acts as an

effective screening device by sorting employees by ability. Finally, the plan motivates

those employees that remain with the firm to continually increase their productivity,

suggesting that pay-for-performance provides incentives for a long-term effort.

Firms, instead of directly monitoring and supervising their employees’ behavior or

performance in a daily basis, rely on self-enforcing reward structures. According to

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Becker and Huselid (1992), the appeal of successively higher compensation motivates

employees to devote greater attention to organizational interests at all job levels and

discourages shirking. However, the main reason that firms are led to this kind of

compensation strategy is because they attempt in this way to align employees’ effort

with the organization’s interest. An employee can expand a great deal of effort, but if

it is not the right kind of effort, shirking exists.

Therefore, several tools are used by firms to compensate executives for their

increased performance. Many companies provide annual bonuses in the form of cash

to their employees to reward them for their annual performance when the company

exceeds pre-specified financial and non-financial targets. Additionally, other

companies also include such performance-based features in their stock-options

programs that require the firm to achieve specific targets in a certain period of time

before the executives realize any value from their grants. These features are especially

effective because the targets are more strongly aligned to the company’s strategy and

the executives are rewarded only if the firm’s performance is outstanding1. Jensen and

Murphy (1990a) suggest that “equity-based rather than cash compensation gives

managers the correct incentive to maximize firm value”. Moreover, as it is stated

from Zhou, the agent’s motivation problem occurs mainly because of the separation

of ownership and management. Hence, an efficient way for the principal to mitigate

this problem is to increase executive’s holding by awarding them with firm’s stock

option. Sometimes firms also encourage long-term equity ownership by requiring

their employees to hold this equity for several years to extend the decision horizon of

those employees.

Prior study of Elsila et al. (2009) measured executives’ incentives in terms of the

personal wealth they had invested in the company, and found that the ratio of CEO

ownership to personal wealth is positively correlated with both firm performance and

firm value. Moreover, it is worthwhile mentioning that Mehran (1995) in his research,

found, firstly, that firm performance is positively related to the percentage of

executive compensation that is equity-based, and, secondly, that firm performance is

positively related to the percentage of equity held by managers. These findings are

1 Equity grants by themselves are already a mean to align interests because managers are incentivized

to take actions that increase stock price.

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very interesting as they illustrate that besides the degree of incentive compensation;

also the type of incentives has an effect on managers’ incentives to take those actions

that increase firm value.

Last but not least, many companies also use several contractual agreements such as

severance agreements and golden parachutes to compensate executives for a potential

job-loss. A severance agreement provides payments upon future involuntary

terminations, except when the termination is ‘for cause’. Such a ‘cause’, which rarely

occurs, could be certain actions of the manager that are severely prohibited from the

contract (such as conviction of a felony). A severance pay is basically a way for the

board of directors to assess the manager’s achievements until the day that he or she

will leave the firm, and compensate him or her for them. Moreover it is a device to

motivate younger managers to undertake riskier projects that are aligned with the

shareholders interests. However, severance agreements weaken the incentives from

the likelihood of dismissal as they decrease the costs of job loss.

Furthermore, a significant number of corporations have also changed their executive

employment contracts to include additional compensation to executives when the

company undergoes some type of 'change in control' (e.g., purchase of a substantial

block of outstanding stock, a change in the majority of the Board of Directors, or

acquisition of the company by an unrelated party). These modifications have been

termed as 'Golden Parachutes'. According to Lambert and Larcker (1984), a golden

parachute adoption is associated with a statistically significant and positive stock

market reaction. On the other hand, because both severance pay and golden

parachutes occur when a CEO exits the firm, there are many people stating that it

represents a giveaway that cannot influence future firm performance. In addition,

some compensation packages go to executives who have failed, undermining in this

way the incentives from the threat of dismissal. However, it should be noted that

according to section 304 of the Sarbanes-Oxley Act, the US companies have the right

to reclaim compensation from the CEO and CFO if it is later proved that the bonuses,

were awarded after the earnings were being manipulated. This is referred to as

clawback provision and has been explicitly adopted by many large companies.

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2.3. Threat of dismissal

The current research focuses on the CEO turnover because the decision to dismiss a

CEO and replace him or her with someone else is one of the most crucial decisions

made by the board of directors. CEO turnover has long-term consequences for a

firm’s investment, operating and financing decisions. It is often assumed that if the

internal governance mechanisms and the external control market improve the

monitoring of executives, then the likelihood of dismissal of poorly performing

managers increases, and they are replaced by others who better represent

stockholders’ interests.

2.3.1. Why dismissal?

According to Kim (1996) a firm’s performance depends mainly on managers’ quality

and on random or unexpected events arising from chance. In other words, a company

can realize a significant decline in its performance either because the manager is not

capable or because it is facing a crisis (e.g., recession, etc.).

It is after assumed that forced management turnover tends to improve managerial

quality and hence the company’s performance. Here, all managers do not have the

same quality and therefore the board of directors attempts to measure their quality in

terms of realized performance. If performance is significantly poor, the directors

realize that the current manager is of low quality and they decide his or her

replacement with another one. However, sometimes performance is affected by bad

luck. Therefore, a change in management can lead to an increase in firm’s

performance for two reasons: the expected increment in manager quality is positive

and luck is also expected to revert to normal.

Furthermore, an alternative significant hypothesis for dismissal, based on the agency

theory of Holmstrom (1979), Shavell (1979), and Mirrlees (1976), is that of the

scapegoat. The scapegoat hypothesis is contradictory to the aforementioned

hypothesis of improved management. Here, it is assumed that all managers are of the

same quality, and the probability of poor performance arises only from chance or bad

luck. Taking into consideration that the managers’ capacities are the same, the

replacement of the incumbent manager will not improve the quality of the manager in

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charge. Despite that the quality will not improve following replacement, it still

provides incentives to the other employees to provide higher effort. So the dismissed

executive may be regarded as the scapegoat since this dismissal is not motivated by a

desire to improve managerial quality, but instead by the desire to provide effort-

inducing incentives to the remaining employees (Huson et al. 2003).

2.3.2. Firing cost and the termination incentive

The threat of dismissal is usually used by firms to motivate their employees to

increase their productivity. According to the research of Hallman et al. (1999), firms

threaten to fire those executives who perform poorly, and assuming that they do not

want to be fired, the threat of job loss gives them an incentive to perform well.

Furthermore, the subsequent employment prospects of the displaced managers of the

restatement firms are poorer than those of the displaced managers of control firms.

However, if the employees do not believe that the firm will actually fire them in the

event of poor performance, then the threat of job termination has no incentive power.

One reason that the employees might not believe that the firm will carry out the threat

of dismissal is that they (and firms) know that termination is costly. Many firms offer

golden employment contracts or severance agreements, especially to CEOs, that can

decrease or eliminate the probability of being punished for financial failure and

mitigate the adverse consequences of job loss. As it has already been mentioned

above, as these agreements aim to compensate managers for the job-loss or the

damage in their reputation after a turnover (almost none of these managers find a

position like the one they had before the termination), they pay all managers

independently of their performance and the value added for the firm and its

shareholders.

Finally, as the cost of firing increases and the termination incentive becomes less

effective, the firm must use more intense pay-for-performance incentives to motivate

its employees to provide the optimal level of effort. The most significant finding of

their research is that the pay-for-performance incentive and the termination incentive

are substitute incentive devices; as the cost of firing the employee increases and

therefore the power of the termination incentive decreases, firms have to provide

additional pay-for-performance incentives.

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2.4. Key factors that affect the determinants of likelihood of dismissal

A main stream of literature addressed the determinants of the likelihood of dismissal.

Some of the most recurring determinants will be briefly discussed in this section.

Tenure

According to prior research, executives’ likelihood of dismissal is influenced from

several factors. One of them is tenure. As it is mentioned in the paper (Kwon, 2003)

“the dismissal probability and the wage contract become less sensitive to the

performance as tenure increases”. In other words, this means that as tenure increases,

the manager becomes more familiar with the position or acquires more relevant

knowledge, the likelihood of dismissal declines and, at the same time, the average

wage rises because of the increase in human capital. It is also important to note that as

a manager’s tenure increases, the manager becomes more expensive to dismiss.

Furthermore, when a CEO remains in the same position for very long, develops

stronger bonds with the board of directors, which is the one that evaluates his or her

performance (if it is a two-tier board), and it is more difficult then to be dismissed.

Especially in the case of one-tier board the CEO is powerful as he is also the chairman

of the board. In such kind of boards the one who is responsible for CEO evaluation

regarding his or her performance is the CEO himself.

Age

Another factor that affects the probability of someone to be dismissed is age. The age

of a manager can play an important role in the compensation system as it influences

both the performance measures and his wage. According to Vancil (1987) “CEOs are

more likely to be fired when they are young than when they are closer to normal

retirement, while also suggests that managers between the ages of 50 and 60 are

unlikely to be dismissed subsequent to poor performance”. Additional research from

Warner et al. (1988) and Weisbach (1988), examined manager’s turnover in several

firms and for a broad period and found that there were only a few cases in which

boards mentioned performance as the main reason why the CEO had to be replaced. It

is also stated that most of them leave their position only after reaching normal

retirement age. The infrequent dismissals due to CEO’s poor performance do not, by

itself, imply the absence of incentives since even a low probability of job termination

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can provide incentives if the penalties associated with termination are sufficiently

severe (Jensen and Murphy, 1990).

Firm size

According to several studies, especially the research of Huson et al (2001), there is a

positive relationship between the likelihood of CEO turnover and firm size. It has

been proved that there is a higher probability for larger firms to appoint an insider to

replace an outgoing CEO (e.g Parrino, 1997). One reasonable explanation for this

finding could be that smaller firms have fewer senior managers that are suitably

qualified to replace the outgoing CEO and thus an outside candidate seems to be the

ideal solution for less complex organizations. However, smaller firms may not have

the budget to replace their CEOs with external candidates very often.

Zhou (2003) in an effort to combine the likelihood of dismissal with firm performance

documented an unexpected but interesting finding. “The probability of CEO turnover,

while almost unchanged related to performance of small firms, seems to be strongly

correlated with the performance of larger firms”. This observation seems inconsistent

with the finding of Jensen and Murphy (1990a). It is important to highlight the fact

that the above research was conducted in Canada and the similarities with the CEO’s

compensation in United States should not be surprising. ‘Given the extensive

economic (e.g., trade) and institutional (e.g., corporate, labour union) linkages that

have developed between Canada and the United States at both the macro and

microeconomic levels, we might reasonably expect significant cross-national

influences on compensation practices’ (Chaykowski and Lewis 1996, 2).

Industry homogeneity

Parrino (1997) demonstrates that in homogeneous industries the probability of CEO

turnover and outside replacements is higher because of the increased availability of

well-qualified outside candidates. DeFond and Park (1999) also finds evidence that

when the industries are highly competitive, the frequency of CEO turnover is

increased, compared to less competitive industries. That means that there is a high

correlation between industry competition and homogeneity.

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According to the studies of Farrell and Whidbee (2003) and Agrawal et al. (2001), the

board of directors is more likely to hire an outside candidate after they have forced the

previous CEO to be removed from his or her place. Furthermore, regarding historical

performance, it may influence the likelihood of CEO turnover and the type of

turnover, but on the other hand it does not have any considerable effect on the choice

of CEO’s replacement beyond its impact on the type of turnover.

Outside versus Inside directors

Last but not least, another crucial factor that has not been mentioned so far is the

evaluation of senior management and the enacting mechanisms to replace them, due

to poor performance, from the board. As it is well known, the board is made-up of

executive and non executive (outside) directors. Regarding Fama and Jensen (1983),

non executive directors are supposed to represent shareholders’ interests better. One

reason for this is that if their monitoring of the management team is not adequate, they

suffer reputation loss in the managerial labour market. Moreover Weibach (1988)

argues that inside directors cannot be more effective than outside ones because they

don’t want to challenge the CEO to whom their careers are tied. This means that

outside directors on the contrary with inside directors can more easily replace a poorly

performing CEO, while Borokhovich et al. (1996) reports that outside directors are

also more likely to replace a fired CEO with an executive from outside the firm.

Since the early 1970s, the percentage of outside directors on corporate boards seems

to have been increased. Bacon (1990) demonstrates that the percentage of outside

directors in manufacturing firms increased from 71 percent in 1972 to 86 percent in

1989. He also states that the number of board members at large firms decreased from

14 in 1972 to 12 in 1989. Finally, regarding the studies of Jensen (1993) and Yermack

(1996) it is reported that a more streamlined board is more efficient and can monitor

more effectively. In other words, a smaller board would reasonably be expected to

increase the negative relationship between firm performance and CEO turnover.

Turning back to the threat of dismissal part, Weisbach (1988) documents that “poor

stock-price performance increases the probability that the CEO will be replaced”;

this probability becomes more obvious if the percentage of outside directors is higher.

However, he also underlines the fact that even when, outside directors have little

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financial power in the firm, they also have little incentive to dismiss the CEO. “For

example, the CEO almost always determines the agenda and the information given to

the board. This limitation on information severely hinders the ability of even highly

talented board members to contribute effectively to the monitoring and evaluation of

the CEO and the company’s strategy”, Jensen (1993, p. 864). It also seems that non

executive directors have little time to collect information for the company’s operation

and they are only content with what the managers provide them with.

2.5. Relationship between performance-based compensation and threat of

dismissal

In summary, previous research supports that the threat of dismissal can be used as

incentive, to motivate managers to take those actions that increase the firm value.

However, this threat is also influenced by other factors. For example, severance

agreements weaken the costs of job loss and therefore weaken dismissal incentives. In

addition, managers who are already at the firm for a long time and possess a large

ownership stake may be, to some extent, shielded from the threat of dismissal. For

example, Denis et al. (1997) documented that “turnover is significantly less sensitive

to performance at high managerial ownership levels” and Dahya et al. (1998)

concluded that “managerial entrenchment effects occur at extremely low ownership

levels”.

This research will attempt to focus on the extent in which the provision of

performance-based incentives is affected by the threat of dismissal. A prior study by

Bushman, Dai and Wang (2008), illustrated that for retained CEOs, pay-performance-

sensitivity is decreasing in the likelihood of turnover. In other words, when the

probability of turnover is high enough, the CEO faces strong implicit incentives to

work harder and increase his or her performance and so requires less explicit

incentives. Furthermore, for CEOs who are retained in their position, incentive

compensation levels seem to decrease due to higher probability of dismissal. This is

suggesting that CEO could be forced to accept this downward revision of incentive

compensation as job termination pressure increases. This is also consistent with the

study of Gao et al. (2008), who documented that “compensation cuts can be a short-

term substitute for dismissal”.

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Given the aforementioned research, I expect that the effect-inducing incentives that

originate from performance-based compensation and the threat of dismissal act as

substitutes. However, incentives may also play a primary role for the selection of a

new executive (i.e., the selection effect of incentives) which be especially important

in the case of dismissal of an old executive and replacement by a new executive.

Finally, retention features of incentive compensation seem negatively associated with

the threat of dismissal. Overall, given the strongest emphasis put on the effort-effect

of incentives, I formulate my hypothesis as follows:

Hypothesis: The likelihood of dismissal is negatively associated with the provision of

performance-based compensation.

3. Research Design

3.1. Sample selection

The sample of firms used in this study includes all firms incorporated in the

Compustat Execucomp database for the year 2005. The coverage of the Execucomp

database roughly corresponds with the S&P 1500. I collected compensation data from

the Compustat Execucomp database. To compute my proxy for the likelihood of

dismissal, I collected data about the number of employees from the Compustat

industrial file. Data for my control variables are retrieved from the Compustat

databases. The combination of the data files is based on a firm’s code (gvkey) and

fiscal-year end. The need to combine different data files (Compustat-North America

and Execucomp), leads to a final sample size of 273 observations. This may, to some

extent, lead to a non-random sample which (at least) may have an effect on the

external validity of this study as there might be a selection bias towards large firms.

3.2. Empirical model

To examine how CEO compensation is influenced by the likelihood of dismissal I

solely focus on CEO flow compensation. Here, I distinguish between two important

parts of CEO flow compensation, i.e., cash bonus and equity grants. Therefore, I will

examine two different empirical models. The two regressions are as below:

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(1) BONUS_INC = ß0 + ß1*PERF + ß2*PERF*LIK_DIS1 + ß3*LIK_DIS1 + ß4*SIZE +

ß5*LEV + ß6*TEN + ß7*AGE + ß8*MTB + ß9VOL + ε

(2) EGRANTS = ß0 + ß1*PERF + ß2*PERF*LIK_DIS1 + ß3*LIK_DIS1 + ß4*SIZE +

ß5*LEV + ß6*TEN + ß7*AGE + ß8*MTB + ß9VOL + ε

However, as I used ROA (ACC_PERF) and the change in stock price

(MARKET_PERF) to measure the companies’ performance, as these both types of

performance measures are used most often in executive incentive plans, I also run the

aforementioned regressions including the above variables separately to each

regression each time.

In general, the relationship between performance and compensation would be

represented by the coefficient ß1. However, for my specific models I separate between

observations with a high likelihood of dismissal (i.e., LIK_DIS1=1) and observations

with a low likelihood of dismissal (i.e., LIK_DIS1=0). The relationship between

performance and compensation for CEOs that face a small likelihood of dismissal is

given by the coefficient ß1. The relationship between performance and compensation

for CEOs that face a high likelihood of dismissal is given by the sum of coefficients

(ß1 + ß2). Hence, the difference in the pay-for-performance relation between CEOs

that face a high likelihood of dismissal and those that face a small likelihood of

dismissal is represented by the coefficient ß2. On the basis of my hypothesis, I expect

that ß2<0.

3.2.1. Dependent variables

Regarding the first equation above, BONUS_INC is a dependent variable that

describes the payment that CEO receives in one year in the form of cash. It can be

measured as follows: Bonus / (salary + Bonus). Given that my hypothesis is focused

on the ex-ante bonus incentives but only ex-post bonus data can be retrieved, I will

control for actual performance in the respective year.

The second dependent variable of my research is EGRANTS. This illustrates the

equity grants that are offered to the CEO as compensation to his or her performance.

Equity incentives are awarded to align the interests of the CEO with that of the

shareholders. To determine the equity grants I used the amount of stock options and

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restricted stock that are awarded to the CEOs. To measure this variable, the amount of

equity grants must be divided by the total compensation (Equity grants / Total

Compensation). Both dependent variables describe the types of incentives that are

used by the firms in order to motivate CEOs, to increase their effort and subsequent

performance.

3.2.2. Independent variables

The first independent variable of interest in this study is the likelihood of dismissal.

Likelihood of dismissal (LIK_DIS) is proxied for in the following way. I use the

sensitivity of fluctuation in the number of people that are employed at a certain firm

to fluctuations in the performance of that firm as my proxy for the likelihood of

dismissal. So, I assume that in a firm where employees are more easily dismissed

following poor performance, also the CEO faces a greater threat of dismissal when the

performance is weak. I measure the likelihood of dismissal in the following way. I

compute the change in the number of employees and divide this by the change in

accounting performance (ROA)2. I do this for the period 1999-2004 and subsequently

compute the average value. I finally compose the dummy variable LIK_DIS which is

one if the value of the average sensitivity of the number of employees to performance

over the period 1999-2004 is higher than the median value in my sample; zero

otherwise.

The second independent variable of interest is performance. In order to measure

firm’s performance (PERF) I used two factors: the change in firm’s stock price and

the return on assets (ROA). To determine this fluctuation I took into account the stock

price at the end of the fiscal year minus the share price at the beginning of the fiscal

year, divided by the share price at the beginning of the fiscal year (SPt –SPt-1 / SPt-1).

Regarding the second variable that measures performance; most researchers use the

return on equity (ROE) as their primary measure of company performance. However,

ROE can be proved to be very risky. For example, companies, in an effort to keep

investors happy, can resort to financial strategies to artificially maintain a healthy

ROE - for a while - and hide in this way the deteriorating performance of the

business. Growing debt leverage and stock buybacks funded through accumulated

2 I take the absolute values

[19]

cash can help to maintain a company's ROE even though operational profitability is

eroding (http://blogs.hbr.org/bigshift/2010/03/the-best-way-to-measure-

compan.html/05/06/2012).

On the other hand, ROA shows how efficient management is at using its assets to

generate earnings or in other words, at converting its investments into profit. The

higher the return, the more efficient the management is in utilizing its asset base.

ROA is a better metric of financial performance than other profitability measures like

return on sales because it takes into consideration the assets used to support business

activities. Therefore, I considered ROA as a more suitable and reliable metric for

performance because it also illustrates whether the company is able to generate an

adequate return on these assets rather than simply showing robust return on sales.

Finally, turning back to my hypothesis, a change in ROA would indicate a change in

CEO’s performance. ROA is calculated by comparing net income to average total

assets.

3.2.3. Control variables

Firm size

Prior studies have illustrated a positive relationship between the likelihood of CEO

turnover and firm size. As it has already been mentioned in the paper, a CEO in a

large firm has higher probability to be dismissed compared to another one in a smaller

firm because there are more qualified senior managers to replace the outgoing CEO.

There is always the solution of an outside candidate, but smaller firms cannot afford

the cost of such replacement. To measure firm size (here illustrated as SIZE) factor, I

used the natural logarithm of the book value of total assets.

Age

As it has already been presented above, the CEO’s age plays a crucial role regarding

the likelihood of his dismissal due to low performance. Vancil (1987) states that the

probability of a CEO being fired is higher when he or she is young than when they are

between the age of 50 and 60, or closer to the retirement age. Furthermore, it is

assumed that an older CEO is more experienced than a young one, and hence his or

[20]

her power towards the board (particularly the compensation committee) will be

higher. CEO age (AGE) is defined as the age of the incumbent CEO rounded in full

years.

Tenure

According to previous research CEO tenure is a significant factor that affects both

compensation and likelihood of dismissal. A CEO’s long tenure could be indicative of

a powerful executive and, hence positively influence CEO’s compensation. Moreover,

long tenure decreases the likelihood of dismissal, because from the one hand the

human capital of CEO (knowledge regarding his/her position acquired) increases, but

on the other hand the cost to dismiss him/her is higher (Dikolli et al., 2008). The

Execucomp file provides all information regarding the start and termination dates for

CEOs, and can be used to compute CEO tenure. So, to compute the CEO tenure

(TEN) I deducted the date that he/she became CEO from the date that he/she left the

company as CEO (Date left as CEO – Date became CEO). However, because my

research focus only on the year 2005, this variable is truncated given that I do not

observe tenure following the year 2005.

Leverage

Leverage is used as a proxy for financial distress. Prior research showed that

distressed companies alter their compensation policies. For example, the study of

Matejka et al. (2009) illustrates that poorly performing firms change their incentive

compensation strategies (i.e., include more nonfinancial). Leverage (LEV) is

measured as follows: Total Long-term Debt / Total Assets.

Market-to-Book ratio

MTB-ratio is used to proxy for growth options. Firms with greater growth options

may face greater monitoring difficulty in which they may make greater use of

incentive compensation to address agency problems. MTB is defined as the ratio of a

numerator which is the sum of the market value of common stock and of a

denominator (book value of equity) which is the difference between total assets and

liabilities of the company.

[21]

Volatility

Finally, I used volatility as a control variable in my regression model. Greater

volatility implies greater risk imposed on managers which makes incentive

compensation more costly. To measure the volatility (VOL) of each company in 2005

I calculated the standard deviation of the accounting returns (specifically that of the

ROA) for the years 1999 until 2004.

4. Findings

In this section the descriptive statistics are discussed, followed by a discussion of the

results of the ordinary least squares (OLS) multivariate regression. It should be noted

that I repeated the analysis using a robust regression. I found that the results are less

reliable with respect to the sign and significance of the coefficient of interest (non-

tabulated), therefore, OLS regression’s results are presented.

4.1. Descriptive statistics

In this part of the study, Table 1 reports the descriptive statistics for the full sample.

The panel shows that the mean of CEO’s age is almost 58 years, while the mean of

CEO’s tenure is 8.1 years (which is similar with the average tenure that is illustrated

in prior studies). The average bonus is almost 0.5 which indicates that about half of

an executive’s cash compensation originates from bonuses. The average equity grants

is also about 0.5 which also shows that half of the executive’s cash compensation

comes from the equity that the executive is granted with. Regarding the MTB ratio

the mean is around 3.4 which suggests that the average firm has considerable growth

options (given that the market value of equity is more than three times the accounting

book value of equity). Turning to the performance variables, the mean of market

performance is 0.019, while the mean of ROA is 0.003.

[22]

Table 1: Descriptive statistics (full sample)

Variable Mean Std.Dev. 25% 50% 75%

BONUS_INC .438 .243 .288 .492 .609

EGRANTS .457 .240 .267 .458 .642

ACC_PERF .003 .054 -.013 .001 .016

MARKET_PERF .019 .357 -.185 -.028 .172

LIK_DIS1 .5 .501 0 .5 1

SIZE 7.706 1.547 6.557 7.636 8.791

LEV .167 .146 .023 .140 .271

TEN 8.145 7.203 3.167 6.255 10.844

AGE 57.736 7.223 53 59 63

MTB 3.358 4.240 1.741 2.467 3.492

VOL .043 .065 .010 .021 .045

Table 1: The table demonstrates the key variables that influence performance-based compensation. The sample

consists of US firms for the year 2005; Compustat/NorthAmerica/Execucomp merged datasets. BONUS_INC –

Dependent variable for the CEO’s bonus (cash) compensation; EGRANTS – Dependent variable for the CEO’s

equity compensation; ACC_PERF – Independent variable illustrating the change in the firm’s ROA for the year

2005; MARKET_PERF – Independent variable illustrating the change in the firm’s stock price for the year 2005;

LIK_DIS1 - The CEO’s likelihood of dismissal; SIZE – The size of the firm expressed by the value of the firm’s

total assets; LEV – The firm’s leverage in 2005; TEN – The CEO’s tenure in 2005; AGE – The age of the CEO in

2005; MTB – The firm’s market-to-book ratio for 2005; VOL – The firm’s volatility.

Table 2 shows the mean and median for the subsamples of a low likelihood of

dismissal (LIK_DIS=0) and a high likelihood of dismissal (LIK_DIS=1). The table

shows that firms that have a high likelihood of dismissal also provide stronger bonus

incentives. This suggests that the likelihood of dismissal and incentive compensation

may be regarded as complements instead of substitutes (note that I predicted that they

are substitutes in the sense that a decrease in one should lead to an increase in the

other).

In other words, the likelihood of dismissal is not sufficient by itself to serve as a

device to firms, so that they could decrease their executives’ compensation, without

influencing their total performance. With regard to the equity incentives, the table

shows that firms that have a low likelihood of dismissal provide more equity

compensation than those firms with a high likelihood of dismissal. This could be seen

as reasonable because firms would prefer to compensate an executive that they

[23]

believe he/she will be more efficient, with more long-term incentives (i.e., equity

grants) compared to one who faces a higher likelihood of dismissal (non-trustworthy).

Table 2: Descriptive statistics (By level of likelihood of dismissal)

LIK_DIS1=0 LIK_DIS1=1 Difference tests

Variable N Mean Median N Mean Median Mean Median

EGRANTS 137 0.460 0.479 136 0.454 0.432

BONUS_INC 137 0.374 0.4356 136 0.502 0.563 *** ***

MARKET_PERF 137 0.036 -0.044 136 -0.001 -0.011

ACC_PERF 137 0.009 0.007 136 -0.003 0 * **

SIZE 137 7.034 6.977 136 8.383 8.374 *** ***

LEV 137 0.162 0.124 136 0.172 0.148

TEN 137 7.942 6.003 136 8.351 7.003

AGE 137 56.818 59 136 58.662 58.5 **

MTB 137 3.260 2.609 136 3.457 2.394

VOL 137 0.062 0.032 136 0.025 0.015 *** ***

Table 2: EGRANTS – Dependent variable for the CEO’s equity compensation; BONUS_INC – Dependent variable for the

CEO’s bonus (cash) compensation; MARKET_PERF – Independent variable illustrating the change in the firm’s stock price for

the year 2005; ACC_PERF – Independent variable illustrating the change in the firm’s ROA for the year 2005; SIZE – The size of

the firm expressed by the value of the firm’s total assets; LEV – The firm’s leverage in 2005; TEN – The CEO’s tenure in 2005;

AGE – The age of the CEO in 2005; MTB – The firm’s market-to-book ratio for 2005; VOL – The firm’s volatility.

(*** p<0.01, ** p<0.05, * p<0.1)

However, after re-examining Table 2, one can observe that the difference between the

mean and the median of the firms with low likelihood of dismissal and those with

high likelihood of dismissal is not significant and therefore, the aforementioned

assumption cannot be strongly supported.

With respect to the control variables, larger firms, firms with a weaker accounting

performance, and less volatile firms have a greater likelihood of dismissal. It is worth

mentioning that the result regarding the firm size is in accordance with prior studies

that proved that there is a positive relation between the likelihood of CEO turnover

and firm size (Huson et al., 2001).

Table 3 shows the Pearson correlations. With respect to the dependent variables,

bonus incentives are positively correlated with performance, a high likelihood of

dismissal and firm size. In addition, bonus incentives are negatively correlated with

volatility. On the other hand, equity grants are negatively correlated with the

[24]

accounting performance (ROA), high likelihood of dismissal, tenure and age.

However, equity grants are positively related to market performance, firm size,

leverage, MTB ratio and volatility. Finally, none of the correlations are greater than

0.7, hence there is no concern for multicollinearity. The largest correlation is between

volatility and firm size (-0.494) which suggests that larger firms exhibit fewer

volatility in performance.

Table 3: Pearson correlation matrix

Variable 1 2 3 4 5 6 7 8 9 10 11

1. BONUS_INC 1.000 ** *** *** *** *** ** ***

2. EGRANTS -0.091 1.000 *** **

3. ACC_PERF 0.149 -0.027 1.000 *** * ** * *

4.MARKET_PERF 0.269 0.016 0.239 1.000 *** **

5. LIK_DIS1 0.263 -0.012 -0.113 -0.052 1.000 *** ** ***

6. SIZE 0.445 0.019 -0.061 -0.004 0.437 1.000 *** *** ***

7. LEV 0.095 0.067 -0.154 0.021 0.035 0.267 1.000 ** ***

8. TEN -0.039 -0.020 0.074 0.011 0.029 -0.074 -0.008 1.000 ***

9. AGE 0.159 -0.202 0.106 0.057 0.128 0.157 0.131 0.440 1.000 ***

10. MTB 0.133 0.150 -0.032 0.169 0.023 -0.078 -0.020 -0.013 -0.095 1.000 **

11. VOL -0.259 0.067 -0.102 0.132 -0.286 -0.494 -0.179 -0.047 -0.309 0.133 1.000

Table 3: BONUS_INC – Dependent variable for the CEO’s bonus (cash) compensation; EGRANTS – Dependent variable for the CEO’s equity

compensation; ACC_PERF – Independent variable illustrating the change in the firm’s ROA for the year 2005; MARKET_PERF – Independent

variable illustrating the change in the firm’s stock price for the year 2005; LIK_DIS1 - The CEO’s likelihood of dismissal; SIZE – The size of the firm

expressed by the value of the firm’s total assets; LEV – The firm’s leverage in 2005; TEN – The CEO’s tenure in 2005; AGE – The age of the CEO in

2005; MTB – The firm’s market-to-book ratio for 2005; VOL – The firm’s volatility. (*** p<0.01, ** p<0.05, * p<0.1)

4.2. Multivariate analysis

This section of the research illustrates the results of the regression models in an effort

to interpret the relationship between the likelihood of dismissal and performance-

based compensation.

It should be mentioned that in the regression of compensation on performance, I

expect the slope coefficient to be higher for CEOs that face a small likelihood of

dismissal than for those that face a high likelihood of dismissal. Furthermore, I

expect in both regressions (BONUS_INC and EGRANTS), where ß1 shows the

relationship between compensation and performance for CEOs that face low

likelihood of dismissal to be higher than the sum of the coefficients ß1+ ß2 that

[25]

describes the relationship between compensation and performance for CEOs that face

a higher likelihood of dismissal. Therefore I expect ß1+ ß2 < ß1, or alternatively, ß2 <0.

Bonus compensation

Table 4 shows the regression results of the relationship between the likelihood of

dismissal and bonus incentives. I distinguish between three models that first included

accounting performance or market performance separately and finally included them

both simultaneously. The results show that accounting performance is significantly

associated with the bonus for firms that have a low likelihood of dismissal (as

documented by ACC_PERF). However, the results also show that for firms that have

a strong likelihood of dismissal, the relationship between accounting performance and

bonus incentives is stronger due to the coefficient on ACC_PERF*LIK_DIS being

both positive and significant. The results for market performance do not show the

same. This makes sense as prior research has shown that bonus plans are more

strongly tied to accounting performance relative to market performance. So, overall

the results are significant in the opposite direction that was predicted. So, this

suggests that incentive compensation and likelihood of dismissal may be seen as

complements.

With respect to the control variables, firm size is positively associated with bonus

incentives. In addition, the MTB ratio and age of the CEO are also positively

associated with cash compensation. The model as a whole performs well. It is

significant given the F-value and an R2 of about 0.3 suggests that about 30% of the

variation regarding the bonus incentives is explained by the model.

[26]

Table 4: Coefficients resulted from the regression of the CEOs’ bonus compensation

Dependent Variable: BONUS_INC

Variables Coeff. t-stat. Coeff. t-stat. Coeff. t-stat.

Intercept -0.282** -2.00 -0.184 -1.31 -0.187 -1.34

ACC_PERF 0.716*** 2.82 - - 0.441* 1.70

ACC_PERF*LIK_DIS 1.753* 1.76 - - 1.659* 1.68

MARKET_PERF - - 0.173*** 4.10 0.152** 3.47

MARKET_PERF*LIK_DIS - - 0.008 0.11 0.002 0.02

LIK_DIS1 0.050* 1.71 0.040 1.40 0.052* 1.85

SIZE 0.061*** 5.76 0.057*** 5.49 0.057*** 5.48

LEV 0.025 0.27 -0.057 -0.63 0.001 0.02

TEN -0.002 -1.20 -0.002 -1.03 -0.002 -1.10

AGE 0.004* 1.72 0.003 1.44 0.003 1.35

MTB 0.010*** 3.15 0.007** 2.38 0.008** 2.45

VOL -0.037 -0.15 -0.338 -1.43 -0.234 -0.98

F-test(ß1+ ß2=0) 6.47** - 4.80**

F-test(ß3+ ß4=0) - 7.13*** 5.04**

Ν 273 273 273

R2 0.281 0.305 0.324

F-value 11.37*** 12.75*** 11.33***

Table 4: ACC_PERF – Independent variable illustrating the change in the firm’s ROA for the year 2005;

ACC_PERF*LIK_DIS – The correlation between the CEO’s likelihood of dismissal and the change in the firm’s

ROA; MARKET_PERF – Independent variable illustrating the change in the firm’s stock price for the year 2005;

MARKET_PERF*LIK_DIS – The correlation between the CEO’s likelihood of dismissal and the change in the

firm’s stock price; LIK_DIS1 - The CEO’s likelihood of dismissal; SIZE – The size of the firm expressed by the value

of the firm’s total assets; LEV – The firm’s leverage in 2005; TEN – The CEO’s tenure in 2005; AGE – The age of the

CEO in 2005; MTB – The firm’s market-to-book ratio for 2005; VOL – The firm’s volatility.

(*** p<0.01, ** p<0.05, * p<0.1)

Equity compensation

Here, I ran the regressions of equity grants (EGRANTS) in the same way as I did for

the regressions of bonus incentives (BONUS_INC), by using both performance

variables at the same time and then each variable separately each time. The results

from the run of these regressions are illustrated in Table 5.

[27]

Table 5: Coefficients resulted from the regression of the CEOs’ equity compensation.

Dependent Variable: EGRANTS

Variables Coeff. t-stat. Coeff. t-stat. Coeff. t-stat.

Intercept 0.758*** 4.84 0.761*** 4.77 0.753*** 4.71

ACC_PERF 0.155 0.55 - - 0.144 0.49

ACC_PERF*LIK_DIS -1.427 -1.29 - - -1.352 -1.20

MARKET_PERF - - 0.015 0.32 0.008 0.16

MARKET_PERF*LIK_DIS - - -0.056 -0.62 -0.035 -0.38

LIK_DIS1 -0.011 -0.29 -0.005 -0.15 -0.009 -0.27

SIZE 0.012 1.02 0.010 0.88 0.012 1.00

LEV 0.131 1.26 0.146 1.43 0.132 1.25

TEN 0.003 1.43 0.003 1.36 0.003 1.37

AGE -0.008** -3.49 -0.008** -3.39 -0.008** -3.39

MTB 0.008** 2.28 0.007** 2.16 0.008** 2.23

VOL 0.096 0.36 0.104 0.39 0.107 0.39

F-test(ß1+ ß2=0) 1.39 - 1.21

F-test(ß3+ ß4=0) - 0.28 0.12

Ν 273 273 273

R2 0.083 0.078 0.083

F-value 2.63*** 2.46 2.15 Table 5: ACC_PERF – Independent variable illustrating the change in the firm’s ROA for the year 2005;

ACC_PERF*LIK_DIS – The correlation between the CEO’s likelihood of dismissal and the change in the firm’s ROA;

MARKET_PERF – Independent variable illustrating the change in the firm’s stock price for the year 2005;

MARKET_PERF*LIK_DIS – The correlation between the CEO’s likelihood of dismissal and the change in the firm’s

stock price; LIK_DIS1 - The CEO’s likelihood of dismissal; SIZE – The size of the firm expressed by the value of the firm’s

total assets; LEV – The firm’s leverage in 2005; TEN – The CEO’s tenure in 2005; AGE – The age of the CEO in 2005;

MTB – The firm’s market-to-book ratio for 2005; VOL – The firm’s volatility. (*** p<0.01, ** p<0.05, * p<0.1)

Taking into consideration my hypothesis, both performance variables (Market

performance or Accounting performance) should be positively correlated to Equity

compensation. The results show that accounting performance is associated with the

equity grants for firms that have a low likelihood of dismissal (as documented by

EGRANTS), while they also demonstrate that for firms that have a strong likelihood

of dismissal, the relationship between accounting performance and equity grants is

negative, meaning that the likelihood of dismissal and equity incentives could be

interpreted as substitutes because the coefficient on ACC_PERF*LIK_DIS is

negative. However, none of the above assumptions regarding the equity compensation

can be either supported nor rejected, as the results are not significant. The main

significant results that are illustrated from the table are that MTB ratio is positively

[28]

correlated with equity incentives, while the CEO’s age is negatively associated with

equity incentives.

5. Conclusion

The general purpose of this research was to obtain useful information regarding how

the threat of dismissal impacts on the provision of the CEO’s performance-based

compensation. Prior studies have investigated the relationship between the likelihood

of dismissal and performance, while the current study also examines the level that

compensation could be influencing this relationship.

After collecting all necessary data for US firms, this research ended up with 273

firms, to measure all the aforementioned correlations. The main hypothesis of the

research stated that “The likelihood of dismissal is negatively associated with the

provision of performance-based compensation”. I tried to identify whether or not the

likelihood of dismissal serves as a complement or substitute to incentive

compensation (either by bonus incentives or by equity). However, according to the

regression results, I ended up with two different findings. With regard to the bonus

incentives I found that they, in relation to the likelihood of dismissal, may be seen as

complements (which do not support my hypothesis). On the other hand, the relation

between the likelihood of dismissal and equity compensation seem to be substitute, as

I predicted, however, while the results from the run of the regression were not

significant, I cannot support or reject my hypothesis.

The large but unavoidable number of missing observations due to the need of

merging different datasets did definitely play a significant role in these findings.

Most of the findings regarding the relationship between performance and

compensation (only bonuses) are in accordance with previous research that illustrated

a positive correlation.

To sum up, regardless of the findings one should always take into account all possible

limitations for undertaking such an empirical study, like those that have been

discussed above. However, this study presents a useful summary of prior, respective

to the topic of the threat of dismissal and performance, studies and shows that there is

[29]

a complementary relation between the likelihood of dismissal and bonus

compensation. Finally, it demonstrates results related to equity compensation (i.e.

equity grants), that could potentially lead to strong evidence to support the particular

research hypothesis after further investigation.

[30]

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