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[1]
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
[2]
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
[3]
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
[4]
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
[5]
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.
[6]
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.
[7]
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
[8]
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.
[9]
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.
[10]
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
[11]
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.
[12]
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
[13]
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.
[14]
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”.
[16]
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:
[17]
(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
[18]
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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