Firm performance following CEO turnover

EBS Universität für Wirtschaft und Recht
Thesis
To obtain the academic degree
Bachelor of Science
The effects of CEO turnover on firm performance
Name: Nicholas Fraser
Address: Eisenbahnstr. 10, Oestrich-Winkel, Germany
Submitted to: Professor Ulrich Hommel, PhD
Submission Date: April 11th, 2016

Table of Contents
List of Figures and Tables...........................................................................................................i
1 Introduction ........................................................................................................................1
2 Literature Review ...............................................................................................................4
2.1 CEO Influence on Performance ..................................................................................4
2.2 Incoming CEO Characteristics....................................................................................5
2.2.1 Internal versus External Candidates.................................................................5
2.2.2 Incoming CEO Age..........................................................................................8
2.2.3 CEO Monetary Incentives................................................................................9
2.2.4 Window-Dressing...........................................................................................10
2.3 Past Empirical Studies...............................................................................................11
2.3.1 Performance Measures ...................................................................................11
2.3.2 Previous Samples ...........................................................................................12
2.3.3 Test Variables.................................................................................................14
2.3.4 Conclusions....................................................................................................16
3 Research Design...............................................................................................................18
3.1 Sample.......................................................................................................................18
3.2 Methodology .............................................................................................................19
3.3 Additional Test Variables..........................................................................................20
4 Hypotheses.......................................................................................................................21
4.1 Question One.............................................................................................................21
4.2 Question Two............................................................................................................23
4.3 Question Three..........................................................................................................24
5 Results..............................................................................................................................25
5.1 Multiple Linear Regression.......................................................................................25
5.2 Robustness Checks....................................................................................................29
5.3 Incoming CEO Analysis............................................................................................32
6 Discussion........................................................................................................................33
6.1 Question One Results................................................................................................33
6.2 Question Two Results ...............................................................................................35
6.3 Question Three Results .............................................................................................36

6.4 Limitations ................................................................................................................37
7 Conclusion .......................................................................................................................38
References........................................................................................................................40

Turnover and Performance i
List of Figures and Tables
Table 1: Descriptive Statistics......................................................................................26
Table 2: Model 1 Summary..........................................................................................27
Table 3: Beta Coefficients of Model 1 .........................................................................27
Figure 1: Prior vs. Post Turnover Boxplot.....................................................................28
Figure 2: Normality of Residuals...................................................................................29
Figure 3: Cumulative Probability Plot...........................................................................30
Figure 4: Heteroskedasticity Check...............................................................................31
Table 4: Breusch-Pagan and Koenker Tests.................................................................31
Table 5: Multicollinearity Check..................................................................................32
Table 6: Model 2 Summary..........................................................................................33
Table 7 : Beta Coefficients of Model 2 .........................................................................33

Turnover and Performance 1
1 Introduction
So the captain has jumped ship or perhaps a mutiny has taken place, will you take what
plunder you have and disembark at the next port or get on board with the new
command. Investors often find themselves in this position when a company announces
the departure of their Chief Executive Officer (CEO). It is understandable to have
concerns about new leadership, but the CEO is only one person. What affect can one
person have on an established company? The aim of this paper is to determine if CEO
turnover warrants such concerns or if a change in leadership should be treated with
optimism. This study also provides an opportunity to look at new CEO characteristics
and their effect on firm performance following a turnover event.
CEOs have become very influential people in our society. Their control over the
company spills onto society as a whole. This influence on stakeholders can be seen very
clearly through CEOs like Steve Jobs, Larry Page, or Mark Zuckerberg. All of these
CEOs have been very involved with the direction of product innovations and their
decisions directly influence how we live. Steve Jobs has been credited for creating a
whole new industry with the innovative iPad (Nath, 2015). Similar statements can be
made about Zuckerberg and Facebook or Page and Google. This is not just a
phenomenon of modern technology companies: Henry Ford was famous for saying,
“Any customer can have a car painted any colour that he wants so long as it is black.”
Ford was of course referring to his Model T, which was only sold in black; in this way
Ford heavily influenced the aesthetics of American motorways in the early 20th century.
CEOs have become opinion leaders that frequently appear on news outlets and talk
shows. In addition to the aforementioned CEOs, names like Richard Branson, Elon
Musk, Bill Gates, Jack Welch, and Warren Buffet have all reached celebrity status.
Likely the most publicized example of CEO influence is Donald Trump’s 2016 United
States presidential bid: going against all political norms, Trump has managed to poise
himself as the Republican frontrunner. All of these leaders showcase the significance of
the CEO role.
It is easy to acknowledge the importance of the CEO role, but it is nearly impossible to
quantify its value. It is no wonder CEO income has ballooned and become a
controversial topic. The average person would be horrified by executive pay levels and

with good reason. Since 1978 CEO pay in the United States experienced a real increase
of 937%, in the same time period a typical worker’s pay has increased a mere 10%; this
means that today an average CEO is making about 269 times the amount that their
ordinary employees earn (Davis & Mishel, 2014). The difference in pay is very difficult
to justify, which raises several questions about the impact a CEO has on the company.
Coates and Kraakman (2010) defined the position well in saying “The CEO manages
the company, glorifying in its successes and taking the blame for its failures”. Being
glorified in successes is certainly evident through generous stock options and
performance pay. The blame aspect can also be seen through the high rates of CEO
turnover, which happens most frequently when firms underperform (Weisbach, 1995).
Given the conclusions from Weisbach (1995), executive pay could be indicative of the
pressure and scrutiny placed on the position.
There is very little variety when it comes to reasons for CEO dismissal. An
overwhelming amount of research indicates that poor firm performance drastically
increases the likelihood of CEO turnover. Research from Dikolli, Mayew, and Nanda
(2014) shows that firms who underperform analyst projections for four consecutive
quarters are between 89% and 222% more likely to replace their CEO than other firms.
To some this may seem reasonable, the company is failing so something has to change,
but what if the CEO is not at fault? For example Jenter and Kanaan (2011), found that
CEO turnover increases during market shocks and economic downturns. The CEO
cannot control the greater economy, yet they are held responsible for its decline.
Furthermore, will changing the CEO necessarily lead to improvements for the firm?
Clapham, Schwenk, and Caldwell (2005), found that CEO turnover was a common
factor in successful corporate turnarounds; however, the study determined that it was
not an essential element. The board of directors could be dismissing their CEO without
the express intention of improving firm performance. A turnover event signals to
stakeholders that improvements are coming. So the board may use dismissal in times
that do not call for such drastic action, but are necessary to quelle investor concerns.
Rhim, Peluchette, and Song (2006), blame the high rates of CEO turnover on
institutional investors that demand improved management practices. This idea might
suggest the turnover event is not in the firm’s best operational interest, but rather a short
term investment strategy. Current research is unclear whether the common practice of
dumping a CEO during tough times is founded. This study will look beyond the

announcement of CEO turnover to see if stakeholders can expect an improvement with
new leadership.
All reasons for CEO turnover, be it retirement, resignation, dismissal, or health
concerns, create a massive undertaking for the board of directors. CEO tenure has
ranged from 7.2 years to 11.3 years since 2002 (Schloetzer, Tonello, & Aguilar, 2015).
With nearly a decade of time leading the company, any successor will have long-term
effects on the firm’s direction. For this reason there are many things the board must
consider. A CEO turnover event is not an isolated incident, it often is accompanied by
changes among other executive employees; this essentially gives the board an
opportunity to realign management vision with shareholder interests (Schloetzer et al,
2015). The succession decision can add or destroy value for a firm. Investment analysts
will punish firms who do not have effective succession planning: in 2004, both
McDonald’s and Coca-Cola lost their CEO suddenly, only McDonald’s had a
permanent successor primed to take over and investors reacted accordingly (Intintoli,
2013). This indicates that succession decisions need to be proactive and on-going,
ideally with the assistance of the current CEO. Based on the gravity of the succession
decision, firm performance after a turnover event could also be interpreted as a measure
of the board’s competency.
There are many things to consider concerning a prospective CEO. It is important to
align the firm’s needs with the characteristics of the prospect. For example, when
determining if the firm should appoint an internal or external candidate they must
establish if they are on a steady path of growth or headed for trouble. While an internal
candidate may be counted on for continued success, an external candidate has been
shown to outperform their counterparts in times of trouble (Citron, Smith, & Speed,
2011). The age of an incoming CEO is an increasingly important topic. Research from
Elsaid and Ursel (2012), examined several patterns concerning new CEO age, one of
which is their propensity to risk. The board must acknowledge this relationship and
determine if their firm is in a position to take risks. A new CEO could also be an
opportunity to make changes to the compensation system. Performance pay may align
the CEO with shareholder goals, but its upper bound could lead to criticism as well as
unethical behaviour. Other matters like gender should also be considered while making
the CEO decision, although this factor has an economically insignificant effect on firm

value, the board must consider the social value of diverse leadership (D’Ewart, 2015).
Regardless of firm size if the board must consider all of these factors, the pool of viable
candidates will be small. It is important for the firm to make trade-offs and judge how
significant each factor is to future performance. In addition to the effects of turnover on
performance, this study will attempt to measure the influence new CEO characteristics
have on performance.
Literature on CEO turnover and firm performance make conflicting claims about the
benefits and drawbacks. Several empirical studies have been conducted, but they all are
substantially different from each other. To further complicate the topic, many papers
present evidence with opposing conclusions. The range of studies have core differences
in terms of the population samples, the observation period, the techniques for
performance measurement, and the criteria that qualifies a turnover. Section 2.3 will
take a more in depth look at the different studies that have taken place and the
conclusions they have produced. This inconsistency in research has left a gap that can
be filled with an overarching study that measures major global firms and makes broad
conclusions.
2 Literature Review
2.1 CEO Influence on Performance
The antecedent of this study would be to determine if the CEO has an effect on firm
performance at all. If evidence showed that CEOs are homogenous then there would be
no need to investigate the effects of CEO turnover, because a change could not lead to
any performance variation. In a leadership study by Thomas (1988), he claimed that the
CEO could only explain 3.9% of the variance in firm profits. This amount is fairly
insignificant, and makes it difficult to explain why certain CEOs obtain celebrity status.
It would also lead one to assume that a turnover event would be insignificant. In a much
more recent study Mackey (2005) completed a very comprehensive empirical analysis
that investigated different ways in which CEOs affect firm performance. Mackey
(2005), found that CEOs have control over firm direction including diversification,
mergers and acquisition, managerial appointments, firm level accounting practices, and
product strategies. This study claimed that 29.2% of variance in profitability could be

explained by the CEO. Mackey (2005), recognizes that her research shows a much
higher impact than many other studies which show leadership affects closer to 15%.
There is quite a bit of variation in research when it comes to how important the CEO
role is; however, the fact that an effect exists is consistent. The next step is to determine
which types of effects exist.
It is interesting to look at the different effects that result after changing a CEO, many of
which have conflicting influence on the overall performance of the firm. Many
empirical studies have provided a quantitative analysis of the turnover event, but failed
to discuss the underlying logic and psychological aspects. Before reviewing past
studies, the researcher will identify some of the reasoning behind the changes in firm
performance as well as characteristics of incoming CEOs that influence the post-
succession strategy.
2.2 Incoming CEO Characteristics
2.2.1 Internal versus External Candidates
A new CEO is much more willing to make necessary drastic changes when compared to
their predecessor. They can look at the firm objectively, without being influenced by
past decisions. They have less emotional attachment to firm assets and previous visions.
Weisbach (1995), found evidence supporting this idea: following a turnover event, the
likelihood of divesting poor-performing assets increases. The board of directors will
appoint someone who reflects their interests to the CEO position. In essence the
turnover event is a correction to the principal-agent problem, wherein the new CEO will
reverse decisions that were made out of managerial-interest by the previous regime
(Weisbach, 1995). Weisbach (1995), identifies some other areas that often change with
a new CEO including, personnel practices, marketing techniques, and general strategy
approaches. A tenured CEO would likely draw criticisms about their confidence in
decision making, if they carried out changes to the previous list of areas. Against logical
expectations, the decision to make major firm changes is not driven by poor
performance preceding the turnover event; major changes have been found after forced
CEO dismissals as well as turnovers caused by retirement or death (Pan & Wang, 2012).
Lausten (2002), provides evidence that the threat of turnover is a motivator for CEOs to
act in accordance with the desires of shareholders and by extension, of the board that

represents them. This evidence supports the idea that new CEOs reverse decisions that
were unfavourable to investors, thus increasing firm value. The ‘correction effect’
suggests that following a turnover event investors can expect an increase in firm
performance. The size of this effect would of course be dependent on the amount and
scale of decisions that have been made out of managerial interest, as well as how much
influence the old regime maintains over the new CEO.
The ability to make drastic changes after a turnover event is impeded by the connections
a new CEO has with the firm. If the new CEO is promoted from within they are less
likely to implement value-enhancing changes, because of their closeness with the
existing regime (Pan & Wang, 2012). This relationship has led to studies about the
benefit of CEO ‘outsiderness.’ Outsider CEOs are less influenced by the old
management team or any residual control the outgoing CEO maintains. Pan & Wang
(2012), also indicate that longer CEO tenure can lead to higher residual control after the
turnover event, and this can make it more difficult for new CEOs to make the necessary
corrections to firm strategy. From her research Karaevli (2007), finds that inside
executives with a long-tenure develop tunnel vision towards the existing firm vision.
Consistent with the research from Pan and Wang (2012), Karaevli (2007), finds that
company insiders have psychological commitments to the status quo and social
connections that make it increasingly difficult to enact much needed change. The
outsiderness effect is not limited to tenure within the firm. Karaevli (2007), also
identifies tenure inside a given industry as a barrier to change; within an industry,
leaders tend to have homogeneous perceptions that make it difficult to develop new
logic. The research supporting outsider appointments suggests that the correction effect
discussed above would be amplified by an external candidate.
For each benefit of appointing an outsider to the CEO position, there is a benefit to
insider appointment that rivals its advantages. If the board hires someone from within
this acts as a motivator for all managers inside the firm (Agrawal, Knoeber, &
Tsoulouhas, 2000). The promotion contest is a benefit to hiring insiders that cannot be
achieved through an outside hire. Assuming the pool of candidates inside and outside
the firm are equal in quality investors would maximize benefit by choosing an internal
candidate. This is consistent with Lazear and Rosen’s (1981), tournament theory;
according to these economists not only will managers in line for promotion increase

their performance efforts, all managers on lower levels will also be motivated to move
up within the firm. Based on the study by Agrawal et al. (2000), American firms highly
value internal candidates: approximately 80% of firms replaced their outgoing CEO
with a firm insider. Chan (1996), likens internal CEO promotion as a carrot
incentivizing all workers within the firm. If outside recruitment is included in new CEO
selection, the pool of candidates increases substantially. In this situation workers have
reduced chances of success and lose their ability to weigh the competition, this in turn
lowers their incentive to increase efforts in their work (Chan, 1996). The instinctive
benefit to appointing an internal candidate would be their firm- and industry-specific
knowledge. In theory, it would be a seamless transition to the new leadership with little
to no friction. One notable friction to an outsider appointment is animosity from senior
executives who were selected by the previous CEO (Karaevli, 2007). This hostility
could result in departure from the firm or resistance to change. The effect from a
promotion tournament is counter to the previous effect we discussed; this suggests firms
must be conscious of their own specific needs.
Despite the conflicting research on internal versus external candidates, there are some
situations where one option is clear. When a firm is having troubles, an outsider CEO is
more likely to perform better, while a stable or growing firm is more likely to perform
better with an insider CEO (Citron et al., 2011). It is evident from the research of
Citron et al. (2011), that an outsider CEO is the riskier option for the operational
performance of the firm, but Agrawal et al. (2000), claim that outside hires have a
stronger positive effect on stock performance. This type of discrepancy is what fuels
research into CEO turnover. For firms that are at polar extremes it is easy to classify
oneself as having troubles or in a period of growth. Hindsight also makes it much easier
to categorize firms. However, if a board waits until the firm is clearly having problems
to dismiss their CEO then it could be too late, and if the board waits until growth is
clear before preparing internal succession plans they may have missed their opportunity
to groom a candidate. In actuality it can be very difficult to assess firm needs. This is
among the many reasons why there is a need for a general evaluation of firm turnover
effects.

2.2.2 Incoming CEO Age
The average CEO age has not decreased substantially, it has only gone down three years
since 1980; the more noteworthy statistic is that CEOs under 47 have outperformed
their counterparts on the S&P 500 by over 6% (ceo.com, 2013). It would be a stretch to
use this information as evidence that young CEOs add more firm value. This number is
heavily influenced by the growth of technology firms, which for now are headed by
young CEOs. Age is an important factor to look at when considering successors,
unfortunately in most instances the board will select a CEO that resembles themselves
in age (Elsaid & Ursel, 2012). This finding strengthens the idea that a CEO turnover
event is used as an opportunity to realign the firm with shareholder interests. It is
valuable for firms to understand what the age of an incoming CEO could mean for firm
strategy. Based on the research examined it would be beneficial to have a diverse board
of directors, therefore CEO selection is based on firm needs without being biased by the
board’s demographics.
Young CEOs are characterized by their willingness to take risks. Elsaid and Ursel
(2012), found that corporate risk measures decrease as CEOs age. This is not
necessarily a negative trait, fast-paced industries would presumably be better off with a
leader who is energetic and willing to take chances. Some instances of risk taking are
acquisitions, where young CEOs are 4% more likely to initiate an offering, once
involved in acquisition talks young CEOs are 20% more likely to withdraw their offer,
and they are 10-15% more likely to restructure their firm (ceo.com, 2013). These
actions represent a leader who is open, honest, unapologetic, and brash. These qualities
can neither be classified as good nor bad, but rather the firm must consider if they are
fitting for the needs of their current situation. A firm aiming at a growth strategy should
strongly consider younger applicants. In a study by Zhang (2010), he finds that firm
growth as well as market value decline with CEO aging. While this certainly suggests
young CEOs are more expansionary, the results are not a clear indication that boards
should select young CEO replacements, because they are also synonymous with high
volatility. The relationship dynamics among senior executives must also be considered
when hiring a young CEO. There are countless articles and blogs that discuss how to
cope with an younger boss. The existence of so many self-help articles underscores how
uncomfortable older executives feel in this situation. With baby boomers opting to stay
on past retirement the likelihood of senior executives working under a young CEO is

only going to increase. Boards must then look for confidence and decisiveness in
younger CEOs in order to be effective among older subordinates.
Although there is a trend of younger leaders among major U.S. firms, the average age
still remains above 55; among their defining characteristics are experience, balanced
judgement, and the ability to manage people and processes (ceo.com, 2013). These
characteristics mitigate all of the pitfalls previously discussed about young CEOs. Issues
with subordinates would be minimized by skills in people management, and any
propensity to risk is softened by experience and balanced judgement. Zhang (2010),
focused her study on the benefits of young CEOs but recognized that past research has
indicated a reduction in volatility with older CEOs. Serfling (2013), found that older
CEOs reduce risk through secure investments and diversification. These conclusions
suggest that if a firm wants to pursue a conservative growth strategy they should appoint
an older CEO.
2.2.3 CEO Monetary Incentives
The topic of CEO compensation was touched on in the introduction. CEOs have become
a magnet for the dissatisfaction with societal wage gaps. Mackey (2005), investigates
whether CEOs are deserving of their exorbitant income, she discovered a very high rate
of performance variability controlled by the CEO, which might warrant their
compensation packages. Since CEOs can cause drastic improvements in firm
performance it is reasonable for them to receive huge compensation, but is high
compensation correlated with improved performance? According to an article in
Forbes, the highest-paid CEOs seem to have the worst performance in the three years
following (Adams, 2014).
One type of CEO monetary incentive is their stake in the firm. Ownership in the firm is
not limited to CEOs who are founders or inheritors of a family business: about one in
ten CEOs on the S&P 1500 voluntarily hold 5% or more of their company’s stock (von
Lilienfeld-Toal & Ruenzi, 2014). Given the size of the firms on this list, 5% would
represent a major stake. Changes in stock price will significantly affect the CEO's
personal wealth. In a study by von Lilienfeld-Toal and Ruenzi (2014), they discovered
that firms with a high portion of managerial ownership perform much stronger than

firms that do not. These CEOs would avoid any principal-agent problems, because their
heavy investment in the firm would balance managerial interests with owner interests.
The main focus of CEO monetary incentives is their compensation. It is reasonable to
expect that higher compensation would lead to stronger performance from the CEO. A
study from Coleman (2000), found that long-term compensation methods like stock or
stock options lead to improvements in firm performance. However, Coleman (2000)
also found that short-term compensation like salary had no relation to performance. This
study did not inspire much confidence in the pay-performance relationship of CEOs. If
anything, these conclusions are further evidence of ownership benefits. A more recent
study by Bradford (2015), could not find any significant relationship between CEO
compensation and firm performance, referring to the effect of compensation as
extremely minimal without any practical importance to performance. Even more
surprising is a study covered in a Forbes article that claims CEOs in the top 10% by
income, returned an average of 10% less to their shareholders when compared to
industry peers (Adams, 2014). By the conclusions found in these studies there is no
justification for the compensation level of CEOs.
2.2.4 Window-Dressing
The chain of accountability ends with the CEO, which forces them to look elsewhere to
lay the blame for decreasing performance. There is a long list of things to blame,
economic downturn, industry decline, aggressive competitors, or fickle consumers. A
convenient benefit for new CEOs is the ability to blame their predecessor for current
problems. A study on the effects of CEO turnover in Swedish firms found that in the
short-term there are negative performance effects associated with a change in the top
position (Friedl & Resebo, 2005). One of the explanations Friedl and Resebo (2005) put
forward for the results of their study is the desire for a new CEO to clean the slate; this
entails devaluing assets to more realistic levels, eliminating postponed expenses, and
revealing news that could damage the firm. The objective of this tactic is to avoid being
blamed for the mistakes of the past. This reasoning would indicate a decrease in firm
performance following the turnover event. To avoid this effect biasing the results of
their empirical study Pan and Wang (2012), measure CEO performance over a longer
period of time. Pan and Wang (2012) refer to it as “CEO window-dressing,” after the
initial period of poor performance, that is blamed on the previous regime, the new CEO

will have inflated improvements. Denis and Denis (1995), also make reference to CEO
window-dressing, however their reasoning has a counter effect to Friedl and Resebo
(2005). Denis and Denis (1995), recognize that new CEOs will sell poor performing
assets when they first enter the firm and the operating income from the sale of assets
will make initial performance appear higher. Although an extended time frame would
reduce the effect of CEO window-dressing it would also diminish the measurable
effects of the turnover event. An increased time interval would be influenced more by
market or industry changes.
2.3 Past Empirical Studies
Examining past empirical studies has allowed the researcher to control for aspects that
have biased previous results. The existing studies on CEO turnover events have
provided significant guidance for the methodology and data collection of this paper.
Past literature has gone in many different directions to address this topic and have come
to as many different conclusions. The following section will cover the decisions made
for previous analyses.
2.3.1 Performance Measures
A comprehensive measure of performance would require a thorough understanding of
the firm’s strategy and an accurate interpretation of accounting measures. In order to
compare performance across multiple companies, researchers have developed proxy
measures. Several empirical analyses use an event study methodology. Event studies
compare the amount of days that stocks outperformed their expectations before and after
the CEO turnover event (Hwang, 2013; Wilkes, 2014). In the case of Wilkes (2014), he
was able to compare stock performance to the performance of 12 portfolios that
adjusted for firm size, growth, and resource versus non-resource stock. These portfolios
were created for a previous study that like Wilkes’ (2014), only focused on South
Africa. Other researchers, who did not have the luxury of premade portfolios, used
existing indexes as a benchmark for performance. Hwang (2013), used the S&P 500
index, which was criticized by some for ignoring company size. Van Zyl (2007), used a
sector index to benchmark performance. This controlled for any industry specific
variance, but still did not adjust for firm size.

Rather than base performance on stock price, many researchers use accounting
measures. If firms have analyst forecasts available, the predicted performance can be
compared to actual performance in order to find deviation from what is expected.
Dikolli et al. (2014), used quarterly earnings forecasts as an indication of what the board
had expected, the difference in real performance determined whether the CEO had a
positive or negative effect on the firm. A similar system was used by Farrell and
Whidbee (2003), using one and five year forecasts. In a study by Huson, Malatesta, and
Parrino (2004), they used accounting ratios such as operating income over book assets
and operating income over sales to measure firm performance. They matched firms with
turnover events to firms that had similar performance in the same industry (Huson et al.,
2004). In this method the matched firm would control for all variables out of the firm’s
control, therefore differences could be attributed to the turnover event. For a more
complete analysis Huson et al. (2004), also tested turnover affects with unadjusted
performance measures and industry-adjusted performance measures, then compared the
results of all three.
The performance measurement in this study is most similar to Friedl and Resebo’s
(2010) study of Swedish firms. The researchers used stock price movements as their
indicator of firm performance; looking before and after the turnover event to see if there
was a significant change (Friedl & Resebo, 2010). This method differs from the event
study method because it does not count events, but rather looks at overall price changes.
The study uses a Swedish market index as a control variable for changes in overall
industry performance (Friedl & Resebo, 2010).
2.3.2 Previous Samples
The samples used in past CEO turnover research are perhaps the most inconsistent
aspect of the topic. There are major variations in location, size, years, and length of
observation periods. Some studies even use the performance of sports teams following
head coach dismissal to make conclusions about CEO turnover effects (Humphreys,
Paul, & Weinbach, 2011). Other studies take their samples around the turnover
announcement date (Setiawan, 2008). This method certainly shows the market reaction
to a turnover event, but this is a measure of investor predictions rather than the actual
effect of the turnover on firm performance. Although many samples were considered,

the decision for this study were heavily influenced by the information and tools
available. Below is an analysis of the samples in the four most relevant studies.
To collect their sample Denis and Denis (1995), examined firms in the 1984 Value Line
Investment Survey. There were 1689 firms monitored over a four year period, this
uncovered 1480 upper management changes (Denis & Denis, 1995). There is an
important distinction to make with this number, as it is not limited to CEO turnover. Of
the turnover events observed 908 had complete information for the study, and only 353
of these were the top executive (Denis & Denis, 1995). Denis and Denis (1995), were
very thorough in their event analysis: by reading the Wall Street Journal article for each
turnover, the researchers were able to identify the reason for departure, their previous
employment, and where they went after departure. Given the scope of the original
sample, this study has a lot of diversity in industry and firm size.
Huson et al. (2004), built on the work of Denis and Denis (1995) by expanding their
sample, they took CEOs that were listed in the Forbes annual compensation survey
from 1975-95. This source of this sample will limit the study to large firms. The length
of their time frame would capture more than enough turnover events. The researchers
created additional selection criteria to ensure the necessary information was available to
complete the study. The total number of successions observed, in accordance with the
criteria, was 1,344. Firm data was taken from Standard and Poor’s Compustat Database
(Huson et al., 2004). In this study financial data was collected for each turnover year
along with three years before and after (Huson et al., 2004). This study is unique and
valuable in large because of its comprehensive sample. However, because it focuses
solely on large firms it may be difficult to extrapolate conclusions to small- and
medium-sized firms.
The next study is limited to Sweden. Friedl and Resebo (2010), looked at companies
listed on the Swedish Stock Exchange between 1994 and 2009; however, because of
strict research criteria regarding firm size and stock continuity the data only includes
341 firms. The authors recognize that because corporate governance in Sweden restricts
CEO power, their sample would only make useful conclusions on the Swedish
population (Friedl & Resebo, 2010). In their paper Friedl and Resebo (2010), do not
indicate how many turnover events took place within the sample of 341 firms. Another

issue with this study is the observation interval: Friedl and Resebo (2010), only focus on
three years following the turnover event, neglecting any prior performance. It is logical
to believe performance preceding a turnover event has an effect on performance under
the new CEO, and should therefore be included.
Similar to the previous study Wilkes (2014), focused his study on firms from one
country, in this case South Africa with corporations listed on the Johannesburg Stock
Exchange. Over a five year period starting April 2007, there were 214 CEO turnover
events observed, which later were reduced to 143 that met research requirements
(Wilkes, 2014). Based on research from Dikolli et al. (2014), this study determined that
the optimal observation interval includes one year before the turnover event and one
year following. Although this study focused solely on South Africa and produced a
small sample, its recency adds value to the existing literature and has potential to
reinforce previous conclusions.
2.3.3 Test Variables
All of the studies relevant to this paper are focused on the succession effect. With slight
variations in methodology, they measure how the turnover event affects firm
performance. Most studies include other test variables that allow for additional
conclusions on the relationships between CEO characteristics and performance. The
paper by Friedl and Resebo (2010), was the only empirical study that did not include
CEO demographic variables because they focused on isolating the turnover effect by
involving many control variables. Some of these variables include, market performance,
GDP growth, industry performance, inflation, and currency exchange rate (Friedl &
Resebo, 2010).
A very common factor to consider is the previous location of the incoming CEO.
Companies in need of a replacement CEO would benefit from research on the positive
and negative impacts of hiring an external versus internal successor. In Wilkes’ (2014)
study of South African firms he collected information on both the incoming and
outgoing CEO regarding their previous work location. Farrell and Whidbee (1996),
focused their paper on the board of directors in relation to CEO turnover, so they
recorded information on the previous work location of board members rather than
CEOs. Most of the studies only ran tests on whether or not the incoming CEO was

internal or external (Denis & Denis, 1995; Huson et al., 2004). This information is the
most practical, since it could be used to advise boards on where to search for CEO
replacements.
The cause of CEO turnover only appeared as a test variable in two studies. This is likely
caused by the difficulty in collecting data. It is very rare for a firm to announce a
turnover event as termination. For this reason, it requires a detailed analysis of company
announcements and familiarity with corporate double speech to classify events
correctly. Huson et al. (2004), were able to label turnovers as forced or voluntary by
checking age and looking for specific statements in Wall Street Journal articles that
explained the reason for departure. The authors assume that CEOs who depart under 60
and without a clearly stated reason were terminated, but appeal to other articles in these
instances to reduce classification errors (Huson et al. 2004). In the study by Denis and
Denis (1995), they did not make any assumptions regarding the reason for turnover.
Similar to Huson et al. (2004), they used the Wall Street Journal to identify the reason
for departure, but in the case of Denis and Denis (1995), if there was no reason given
they listed the event as unknown. Denis and Denis (1995), were much more specific in
their reason for turnover classifications; their study included the labels, forced, poor
performance, pursued other interests, unexpected retirement, retirement, normal
succession, death/illness, took position elsewhere, no manager turnover, other, and no
reason given. This method of data collection is much more accurate, but it leaves many
turnover events classified as ‘no reason given.’ The 34% of events that did not have a
reason for departure represent a missed opportunity to strengthen the analysis (Denis &
Denis, 1995). Another possible reason for turnover is a company takeover; both Denis
and Denis (1995) and Huson et al. (2004) included a test variable for takeovers. This
could potentially be an important variable to measure because departures caused by
takeover would represent a completely distinct situation.
Certain variables were common across all studies. Age of incoming and outgoing CEO
was tested in almost all of the key studies observed, likely because it is a simple metric
to find and easily included in the formulation (Denis & Denis, 1995; Farrell & Whidbee,
1996; Huson et al., 2004; Wilkes, 2014). Tenure was included in many studies as well;
again this is likely because of its ease of access (Farrell & Whidbee, 1996; Huson et al.,
2004; Wilkes, 2014). Surprisingly the only study to include CEO ownership came from

Huson et al. (2004), who used the amount of stock held by the CEO as a test variable. In
the next section we will exam some of the significant conclusions made in past studies.
2.3.4 Conclusions
The first relationship that existing literature has identified was not the effect of CEO
turnover on firm performance, but rather the effect of firm performance on CEO
turnover. Countless empirical studies have been performed on what causes a CEO
turnover. Many of these studies overlap with the topic of performance following a
turnover event. Some of the papers used as references for this study have shown a
strong relationship between declining performance and CEO turnover (Denis & Denis,
1995; Dikolli et al., 2014; Huson et al., 2004; Wilkes, 2014). The studies which have
shown this relationship also indicate that it is consistent with evidence from other
research. Interestingly Wilkes (2014), found that strong and poor performing CEOs had
very similar tenures, less than a 0.2 year difference. Since there is a relationship
between CEO turnover and poor performance, but poor performers still work nearly as
long as strong performers this could indicate that the board does not rid poor performing
CEOs in a timely manner. Denis and Denis (1995), found additional evidence of poor
board monitoring; their research showed two-thirds of forced resignations were the
result of factors separate from board monitoring. The conclusions from these studies
suggest that boards should be more attentive to CEO performance.
Many of the studies covered a mixture of test variables; however, the conclusions were
surprisingly scarce. Wilkes (2014), was able to make a weak connection between tenure
and performance; this relationship was strengthened when the analysis was focused
solely on small corporations. Additionally Wilkes (2014), found evidence that younger
incoming CEOs (under 43) performed better than their counterparts, particularly in
small businesses. Huson et al. (2004), were also able to make some conclusions with
test variables: both the amount of shares held by the CEO and external employment
prior to succession positively affect firm performance. In the study from Wilkes (2014),
external appointments showed positive performance exceeding that of internal
appointments for medium and small firms, but in large corporations the performance
effect was negative. His evidence of external CEO effects on large companies conflicts
with the correction effect discussed in section 2.2.1. Presumably a large firm would
have more underperforming assets that an external CEO could divest, thus increasing

performance. Pan and Wang (2012), identify CEO window dressing as a solution for
this discrepancy. It is likely that the assets being divested are sold at a loss, therefore
decreasing the firm's value initially, but these decisions are necessary for long-term
prosperity.
The results of the key research question are inconsistent across all of the main studies in
the literature review. The most logical conclusion comes from Wilkes (2014), who
found that underperforming firms were more likely to improve following a turnover
event, and overperforming firms were more likely to worsen. Since most turnover
events are preceded by poor performance, Wilkes’ (2014) overall conclusion suggested
CEO turnover is beneficial to firm performance. This result is important because it
suggests that there are limitations to the benefits of CEO turnover: it can make a bad
firm good, but not a good firm better. Huson et al. (2004), used three different measures
of performance, discussed in section 2.3.1, each produced a different result. Unadjusted
performance showed a negative performance change following CEO turnover, control-
group adjusted showed a positive change, and industry-adjusted indicated positive
change, but was only significant at the 10% level (Huson et al., 2004). Since the control
group was created specifically for the study, it would be logical to accept its
conclusions. Friedl and Resebo (2010), were the only researchers to find a negative
relationship without any additional context. The study claims that following a turnover
event the firm performance is expected to go down. Since this study is based only on
Swedish firms there are some explanations for the conflicting results. Swedish firms
have stricter corporate governance which limits the amount of changes a CEO can
make, Swedish firms also have strong owners and influential boards impacting CEO
decisions (Friedl & Resebo, 2010). Counter to the study on Swedish firms, the results of
Denis and Denis’ (1995), show that there were significant improvements in firm
performance following CEO turnover: the effects were stronger among forced
resignations. The literature reviewed tends to point toward a positive improvement
following CEO turnover. However, the overarching studies are outdated, and the
modern studies have only focused on specific regions. More literature is needed on
larger markets with more recent data.

3 Research Design
3.1 Sample
This study will attempt to find overarching conclusions on the effects of CEO turnover
on firm performance. Therefore the population that our sample is pulled from includes
major publicly traded firms that have experienced a turnover event. The sample will
take firms from the S&P index. Presumably, large firms have more corporate
governance giving the CEO less freedom in decision making. This would indicate that
any conclusions on large firms would only increase in significance with smaller firms
Data for this study was collected from Compustat databases through the Wharton
Research Data Service (WRDS). Compustat offers comprehensive data sets on a host of
financial and industry topics. In order to measure the effect of CEO departure it was
necessary to collect information on both corporate executives and company stock
performance. Dating back to 1992, the ExecuComp database has statistics for more than
39,000 executives, coming from over 3,300 firms (WRDS, n.d.). In addition to
ExecuComp, the Centre for Research in Security Prices (CRSP) database was also used.
The CRSP has historical performance data on over 27,000 stocks (CRSP, n.d.).
Information was taken from both of these databases for every turnover event in the time
frame. The events on both databases were linked using turnover dates and stock
exchange ticker symbols.
For the purpose of this study data was collected on CEOs involved in a turnover event
between 2011 and 2015. These years returned a substantial sample size, as well as
avoided any effects from the 2008 financial crisis which had the potential to skew
results. Over the three years observed there were 555 CEOs returned, either in their final
year before a turnover or in their first year after a turnover. In order to be sure firms
were large enough and that there would be complete financial information the sample
only included S&P 500 companies that are listed on either the Nasdaq or New York
Stock Exchange (NYSE). Small firms are likely to return biased results, since potential
for growth is much higher and the role of the CEO has a stronger impact. Additional
examination of the data eliminated interim CEOs and any other workers who were
misclassified as CEO. The final sample included 366 CEOs and 260 firms.

3.2 Methodology
Previous literature and tests on this subject have provided a framework for the necessary
elements. Using information available and the guidance of past researchers an effective
methodology was developed.
The most crucial aspect of the study would be the measure of firm performance. Firm
strategies and changes in value are complex and can be measured using many variables.
For this study holding period stock returns including dividends will be used as a proxy
for changes in performance. Using the stock price as an indicator of firm performance is
generally accepted as a credible proxy (Wilkes, 2014). Some studies including Dikolli
et al (2014), have looked at earnings and other accounting measures as an indicator of
performance; however, these values can be altered by the incoming CEO through asset
devaluation or bookkeeping changes. In order to use stock price movements as a proxy
for firm performance we must assume that stock price is an accurate indication of a
company’s position. This assumption should not be an issue because all observed firms
are members of the S&P 500 list. Their size and exposure on either the Nasdaq or
NYSE are testaments to the amount of investor scrutiny that is placed on each firm.
Since there is greater attention given to the firms, it is logical to believe that their stock
price movements are accurate indicators of firm performance. This is essentially the
essence of the efficient markets theory.
Prior studies have monitored changes in firm performance over different observation
intervals and in some cases they only considered the years following the turnover event
(Wilkes, 2014). It would be ill-advised to ignore the performance of the firm prior to the
turnover event because the firm’s standing during this time would directly affect the
ability of the incoming CEO to manage the company. Using the average monthly return
over 12 months before and after the entrance of a new CEO allowed for fair comparison
of stock performance changes. Comparing an entire year of returns also avoids any
annual cyclical effects. Abnormal returns have been observed following the
announcement of CEO turnover (Kind & Schläpfer, 2010). In this study, no additional
attention will be given to announcement dates because this is not an indication of firm
performance, but rather an indication of what investors predict will happen to firm
performance.

The empirical analysis of this study will attempt to complete the formula,
𝑀𝑇𝐻 𝑅𝑒𝑡𝑢𝑟𝑛 = 𝛽0 + 𝛽1 × 𝑇𝑂𝑖 + 𝛽2 × 𝐴𝐺𝐸𝑖 + 𝛽3 × 𝐼𝑁𝐶𝑖 + 𝛽4 × 𝑂𝑊𝑁𝑖 + 𝛽5 × 𝑆𝑃𝑖
𝑇𝑂 = Incoming CEO indicator
𝐴𝐺𝐸 = Executive’s Age
𝐼𝑁𝐶 = Total Executive Compensation
𝑂𝑊𝑁 = Percentage of shares held by CEO
𝑆𝑃 = Month return of the S&P 500 index
This study will use SPSS to run a linear regression on the relationship between average
stock price and a variable indicating whether or not the CEO is incoming or outgoing
from the turnover event. Additional test variables will be included to determine if they
have an effect on the relationship. Conclusions will be based on the results from these
tests with supporting evidence from descriptive statistics.
As a supplementary aspect of the study we will determine if any characteristics are
particularly beneficial in incoming CEOs. Using many of the same variables with the
addition of previous employment the analysis will attempt to complete the formula,
𝑀𝑇𝐻 𝑅𝑒𝑡𝑢𝑟𝑛 = 𝛽0 + 𝛽1 × 𝐴𝐺𝐸𝑖 + 𝛽2 × 𝐼𝑁𝐶𝑖 + 𝛽3 × 𝑆𝑃𝑖 + 𝛽4 × 𝐿𝑂𝐶𝑖
𝐿𝑂𝐶 = Indicates whether the CEO was hired from outside the firm
*This test only includes incoming CEOs
To determine the strength of conclusions, several checks of robustness will be
performed through SPSS ensuring linear regression assumptions are met. Some key
assumptions that will be tested are normality of residuals, homoskedasticity of residuals,
the absence of multicollinearity, and the absence of autocorrelation.
3.3 Additional Test Variables
The dependent variable firm performance is discussed in detail in the methodology
section 3.2. The core independent variable that measures the key question of this study
is the CEO turnover event. This will be represented by a binary variable: 1 indicating

first year as the CEO and 0 indicating the final year before the turnover event. Common
across all empirical studies is an independent variable to control for changes in firm
performance that should not be credited to the turnover event. Some studies use
specifically created control portfolios (Huson et al., 2004; Wilkes, 2014), and others use
industry or market indexes to control for performance changes (Denis & Denis, 1995;
Friedl & Resebo, 2010). For this study the S&P 500 index was used to account for
performance changes caused by the economy as a whole. Since all of the observed firms
are members of the S&P 500, this measure is very fitting to control for the changes in
the appropriate markets.
Many of the additional test variables discussed in section 2.3.3 are examined in this
study also. The variables age, compensation, and ownership were all included to control
for effects that may have been incorrectly credited to turnover. They were also included
to check for any meaningful relationships that might spark interest. A variable that was
discussed in great detail in section 2.2.1 is internal versus external appointment. A
second regression will be completed to measure this effect on the performance of
incoming CEOs. The topic of internal versus external successions has been analyzed
quite frequently with mixed results. It will be interesting to measure how it affects this
study’s sample.
4 Hypotheses
Apart from the core hypothesis to be tested in this study there are two additional
questions that can be answered using the data that was collected. It would be interesting
to compare the data from this study to some of the post-turnover effects discussed in the
literature review.
4.1 Question One
The first hypothesis test will attempt to answer the question of this study. The test will
determine if firm performance is influenced by the turnover event. Additionally, the test
will indicate whether firm performance increases on average after a turnover event or
decreases.

H0: There is no significant change in firm performance prior to the CEO turnover event
compared to subsequent performance.
H1: The CEO turnover event leads to significant improvements in firm performance
over the previous leadership
The null hypothesis corresponds with the belief that a change in CEO is insignificant. If
no significant difference in stock performance is found in the year leading up to the
turnover event versus the subsequent year, this would provide evidence that the turnover
event has no effect on firm performance. This would also support the theory of CEO
homogeneity. Thomas (1988), claimed the CEO could only explain 3.9% of variation in
firm performance. This number seems surprisingly low considering the executive
powers held by the CEO. If research from Thomas (1988), is an accurate indication of
CEO homogeneity it is likely that the null hypothesis will not be rejected. The study by
Friedl and Resebo (2010), offers regional explanations for a CEO's inability to affect
change. In their research of Swedish firms the CEO was limited by strong corporate
governance, and influential founders and boards (Friedl & Resebo, 2010).
The alternative hypothesis agrees with the majority of literature examined for this study.
In section 2.2.1, CEO turnover was discussed as a solution to a company’s principal-
agent problem. Over the course of a CEO’s time in office, they will make many
decisions out of their own interests. The turnover event is an opportunity for the board
of directors to select a replacement that will reverse decisions unfavourable for
shareholders and therefore increase the firm’s value and performance. This correction
effect would support the alternative hypothesis. Additionally, through logic we can
accept that the incoming CEO will typically be younger than the outgoing CEO. In
section 2.2.2, an analysis of CEO age showed that younger leaders adopt a more
aggressive growth strategy. This idea was complemented by Zhang (2010), who found
evidence that not only does growth decline with CEO age, but also market value. While
there is a lot of evidence that strategy changes drive the benefits of CEO turnover, Rhim
et al. (2006), suggests a psychological reason for firm improvement. CEO turnover is
initiated by institutional investors who demand managerial change (Rhim et al., 2006).
This would cause an increase in stock price after the turnover event. This is an

alternative interpretation of the increase in stock performance, which credits satisfied
investors as the reason for an increase rather than the turnover event.
4.2 Question Two
The previous location of the incoming CEO has been discussed in nearly every study
that relates to firm performance following a turnover event. Location in this instance
refers to whether the incoming CEO was promoted from within the firm or an outside
hire. In the study by Karaevli (2007), there is the additional recognition of CEOs who
were hired from outside of the industry. Since CEO selection sets the long-term
direction of the firm, the question of whether to appoint an internal or external person
could be very important.
H0: There are no significant changes in firm performance between external and internal
CEO appointments.
H1: The benefits of either internal or external CEO appointment outway the benefits of
their counterpart.
The null hypothesis in this question has two very likely interpretations. The first is that
difference between external and internal hires is insignificant. This interpretation is
consistent with the null hypothesis in question one. If CEOs in general are homogenous
there previous employment location would not make a difference in performance. The
second interpretation is a bit more interesting and refers back to the discussion of
internal versus external candidates in section 2.2.1. There are different phenomena that
take place when an internal or external CEO is appointed, but both are positive on firm
performance. Recall that external applicants have the benefit of outsiderness. While
internal candidates are burdened with tunnel vision and psychological commitments to
the status quo, external candidates have the freedom to make value-enhancing changes
(Pan & Wang, 2012). Appointing an internal candidate has a motivational effect
discussed in Lazear and Rosen’s (1981) tournament theory, where they show that
promoting from within motivates all of the managers within the firm to exert more
effort. Managers being considered for the position are motivated to win the tournament
and lower managers are motivated to move up to gain the opportunity to compete in the

next tournament. The inclusion of external candidates in the tournament decreases the
likelihood of recognition for additional effort, luck also becomes more significant in the
tournament which leads to demotivation (Lazear & Rosen, 1981). The second
interpretation of the null hypothesis would exert that these effects among others cancel
each other out. So although there is a significant difference between internal and
external candidates, they have equal benefits overall.
The alternative hypothesis will measure if the performance benefits of external CEO
appointments are greater or weaker than internal appointments. In addition to the CEO
outsiderness effect and motivational effect discussed in the previous paragraph, we can
recognize previously discussed effects that benefit internal candidates. Looking back to
the literature review in section 2.2.1, other benefits to internal candidates are firm- and
industry-specific knowledge, as well as a greater likelihood of cooperation among
senior executives (Karaevli, 2007). Based on the review of past empirical studies it is
difficult to predict what this test will uncover. Both Huson et al. (1995), and Wilkes
(2014), found that external candidates perform better than their internal counterparts.
However, Wilkes (2014) explained that firm size reversed the effect of external
candidates making them perform worse than internal candidates in large firms. So
according to Wilkes (2014), this study will return superior results for internal
candidates, since only firms large enough to belong to the S&P 500 were included.
4.3 Question Three
By all accounts CEOs should have high motivation to succeed. They get extrinsic
motivation like money and praise, and intrinsic motivation from a sense of
accomplishment, independent direction and certainly challenging work. Perhaps it is the
presence of so many motivators that make it difficult to find a relationship between firm
performance and CEO monetary incentives. In Bradford’s (2015) study, he could not
find any relationship between performance and pay, but other studies have found
negative relationships (Adams, 2014), and positive relationships (Coleman, 2000).
Since the ExecuComp database allows us to pull data on both CEO compensation and
ownership this would be an interesting topic to explore.

H0: There is no relationship between firm performance and monetary incentives for
CEOs
H1: There is a significant (positive or negative) relationship between firm performance
and CEO monetary incentives.
The null hypothesis in this instance is going against conventional wisdom. If the firm
provides more financial incentives for the CEO, one would expect the CEO to exert
more effort. However, Douglas McGregor (1957), has told us “a satisfied need is not a
motivator of behaviour” (p. 24). This could be applied to a CEO’s need for money,
considering the average compensation for CEOs on our list is over ten million dollars
per year we can assume money is a satisfied need. This might explain why monetary
incentives do not lead to stronger firm performance.
The alternative hypothesis is the accepted practice in setting CEO compensation. CEO
compensation is approximately 269 times the pay of ordinary employees (Davis &
Mishel, 2014). The idea here is to align the CEO’s goals with the goals of investors. If
this is done correctly, von Lilien-Toal and Ruenzi (2015), has shown that managers are
able to effect strong firm performance in relation to their financial stake in the firm.
5 Results
5.1 Multiple Linear Regression
The tables and figures in this section will provide evidence for questions one and three.
In the results section of the paper the focus will be on observations in the data and
interpretations of the figures. The results will be connected to the study questions and
applied to theories in the discussion, section 6.

Table 1 Descriptive Statistics
S&P Adjusted Performance Before vs. After turnover
event Statistic Std. Error
Last year in
office
Mean -,0044 ,00129
95% Confidence
Interval for Mean
Lower Bound -,0070
Upper Bound -,0019
5% Trimmed Mean -,0035
Median -,0034
Std. Deviation ,01828
Minimum -,08
Maximum ,04
Range ,12
First year in
office
Mean ,0048 ,00148
95% Confidence
Interval for Mean
Lower Bound ,0019
Upper Bound ,0077
5% Trimmed Mean ,0041
Median ,0032
Std. Deviation ,01889
Minimum -,06
Maximum ,07
Range ,13
As seen in Table 1, there is a clear increase in S&P 500 adjusted firm performance in
the year following a turnover event opposed to the year preceding. There is no overlap
between the mean lower bound of the first year in office and upper bound of the last
year in office; this tells us that with a confidence level of 95% we can say that the
population means are not equal. Meaning, that following a turnover event investors can
expect an increase in firm performance all other factors held constant.

Table 2 Model 1 Summary
Model R R^2
Adjusted
R^2
Std. Error
of the
Estimate
Change Statistics
R^2
Change
F△ df1 df2
Sig. F
△
1 ,528
a
,278 ,268 ,01820925
8718338
,278 27,772 5 360 ,000
Model 1 is an OLS linear regression on the relationship between the dependent variable,
firm performance and the independent variables, turnover event, age, compensation,
ownership, and S&P 500 index return. As can be seen from adjusted R squared in Table
2, close to 27% of the variation in firm performance can be explained by the model.
Given the variety of variables that can influence stock prices, the researcher is satisfied
with how the model’s predicted results fit the actual results.
Table 3 Beta Coefficients of Model 1
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) -,030 ,011 -2,743 ,006
Dummy For New CEO ,010 ,002 ,234 4,502 ,000
Executive's Age ,000 ,000 ,088 1,711 ,088
Total Compensation 2,269E-7 ,000 ,075 1,680 ,094
Percentage of firm
ownership
,001 ,000 ,061 1,345 ,179
S&P 500 Avg Monthly
Return
1,491 ,150 ,450 9,945 ,000
Table 3, breaks down Model 1 by each of the test variables. As expected the S&P 500
return has the strongest influence over firm performance, in this study represented by
fluctuations in stock price. The average monthly return of the S&P 500 was included to
control for any economic changes that would have affected the firms in our sample.
Since its t-value is more than twice the nearest variable we can say this is a strong
control.

With an alpha of 5% only the control variable and the binary variable indicating a
turnover event are significant. Percentage of firm ownership and total compensation
have a very small effect on firm ownership, but should be excluded because they are
only significant at the 80% and 90% confidence level respectively.
Figure 1 Prior vs. Post Turnover Boxplot
Figure 1 is a graphical representation of the disparity between the firm performance
following a CEO turnover event (right) and the firm performance preceding a CEO
turnover event (left), as found in our sample. Fifty percent of the observation fall within
the shaded boxes, the group is divided equally by the median line in the middle. It is
easy to recognize that the first year in office plot is higher. One may point out the small
scale on the performance axis; however, it is important to keep in mind performance is
measured by average monthly return less that month’s S&P 500 index return.

5.2 Robustness Checks
The following are tests performed to validate the results previously discussed.
Successful tests would show that linear regression assumptions are met. This will
strengthen the conclusions of the study and interpretation of the data.
Figure 2 Normality of Residuals
As seen in Figure 2, the sum of squared residuals between model predicted results and
actual results follow a normal distribution. Given that we have a large sample size, 366
observations, normality of the residuals is not such an important assumption. However,
it still speaks to the confidence of the model.

Figure 3 Cumulative Probability Plot
The graph in Figure 3 also shows the normality of the residuals in the regression. The
solid line represents a normal distribution. There is strong evidence of normality in the
residuals, because all of the observed points are clustered around the solid line.

Figure 4 Heteroskedasticity Check
In order to check if the linear regression assumption of homoscedasticity was met,
Figure 4 was created to compare the predicted values with the observed values.
Homoskedasticity is characterized by equal variability across all values; this would
result in no discernible pattern in the graph. Figure 4 shows no evidence of
heteroskedasticity, in order to be certain the results were tested using the Breusch-Pagan
and Koenker tests below.
Table 4 Breusch-Pagan and Koenker Tests
Sample Predictors Test Sig.
Breusch-Pagan 366 5 4,437 0,4883
Koenker 366 5 2,521 0,7734
*H0: Model one is homoskedastic
Since the test statistic and significance levels in Table 4 are so high, we fail to reject the
null hypothesis. This tells us with high confidence that our regression model meets the
assumption of homoskedasticity.

Table 5 Multicollinearity Check
Model
Collinearity Statistics
Tolerance VIF
1 (Constant)
Dummy For New CEO ,740 1,350
Executive's Age ,753 1,328
Total Compensation ,993 1,007
Percentage of firm ownership ,990 1,010
S&P 500 Avg Monthly Return ,977 1,024
Several checks were performed to check for any multicollinearity among the
independent variables in the regression. Table 5 shows that every variable has a high
tolerance, this means that they have very little influence on all of the other variables.
The variance influence factors (VIF) make the same conclusion; even the most
conservative level of VIF to ignore multicollinearity is less than 2.5, which all of our
factors meet.
Although the table is not included, a check for the regression assumption of
autocollinearity was performed. Using SPSS the Durbin-Watson test returned a value of
2.238 which indicates a very low probability of correlation between residuals.
5.3 Incoming CEO Analysis
Of the 164 incoming CEOs that were observed in this study only 31 were hired from
outside of the firm. This is similar to the 80% level of internal appointments Agrawal et
al. (2000), found in their study. This aspect of the study is burdened with a small sample
to measure. The following information is used to determine if incoming CEO
characteristics have a significant effect on performance.

Table 6 Model 2 Summary
Model
R
R
Square
Adjusted
R Square
Std. Error of the
Estimate
First year in
office (Selected)
First year in office
(Unselected)
2 ,459
a
,464 ,211 ,191 ,018767005119265
a. Predictors: (Constant), Dummy for External, S&P 500 Avg Monthly Return, Total Compensation
, Executive's Age ; Dependent Variable: Average Monthly Return
A smaller portion of the variance in firm performance is explained by Model 2.
Table 7 Beta Coefficients of Model 2
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
2 (Constant) -,001 ,018 -,082 ,935
Executive's Age -5,181E-5 ,000 -,012 -,168 ,867
Total Compensation 3,385E-7 ,000 ,106 1,495 ,137
S&P 500 Avg Monthly
Return
1,474 ,230 ,454 6,403 ,000
Dummy for External -,001 ,006 -,008 -,107 ,915
a. Dependent Variable: Average Monthly Return
b. Selecting only cases for which Dummy For New CEO = First year in office
As seen in Table 7, the only factor that has a significant effect on firm performance is
the control factor for changes in the S&P 500 index. Compensation is the only other
variable that is close to showing a relationship, but it still is not significant at even the
90% confidence level.
6 Discussion
6.1 Question One Results
From the results, a highly significant positive relationship is found with performance
and CEO turnover. Following a turnover event a 0.01 increase in monthly return can be

expected holding all other factors constant. This may appear to be a small increase, but
this is quite substantial considering the scale we are using and the size of our sample
firms. The descriptive statistics in Table 1, show that firms with a first year CEO
perform much stronger than firms with a CEO in their final year. Through the lower and
upper mean bounds in Table 1, we are able to conclude with 95% confidence that
average post-turnover performance is higher than pre-turnover performance in our
population. This confidently shows that the population average return for firms
following a turnover event is higher than firms preceding a turnover event. Leading to
the result that turnover should be an optimistic sign for investors.
The results from this study are consistent with conclusions from key reference papers
like Huson et al. (2004), Denis and Denis (1995), and to some extent Wilkes (2014).
Wilkes (2014), found the opposite effect when observing firms that were performing
positively leading up to the turnover event, but looking at all firms together his results
mirrored this study. The study by Friedl and Resebo (2010), which was also a key
reference paper, came to an opposing conclusion. This was likely caused by their focus
solely on the Swedish market. Our results could not be biased by the window dressing
effect as described by Denis and Denis (1995), who claimed the sale of assets in the first
year can increase operating performance. This study uses stock price movements as a
measure of performance which would not be influenced by the sale of an asset. This was
an additional benefit of using stock price changes rather than accounting measures.
Based on the study results the idea of CEO homogeneity is rejected. Since changing the
CEO leads to an increase in firm performance, one must accept that CEOs are
influential. The results support the idea of a correction effect. Previous studies found
that a turnover event allows the new CEO to correct any decisions that were made out of
managerial interest, thus creating value for owners (Denis & Denis, 1995).
The idea of institutional investors demanding a change in management put forth by
Rhim et al. (2006) would be consistent with our results. Investors show their
dissatisfaction by divesting, once the board gets the message and invokes a turnover
event, investment increases and improves the performance measure this study used. If
this is the case, then our results do not indicate improved firm performance, only

improved investor satisfaction. In practice the increase in stock price is likely a
combination of improved firm performance and investor satisfaction.
The results from the study show the board of directors in a positive light. The increase
in firm value that was discovered following a turnover event adds credibility to the
decisions of the board. Although we cannot make conclusions on whether their
dismissal decisions are sound, a positive relationship between stock performance and
new CEOs, suggests that their replacement choices are sound.
6.2 Question Two Results
The second question of our study is limited to the CEOs who follow a turnover event.
As discussed in section 2.2.1, the previous location of a CEO candidate has a big effect
on the firm. In this study, through a regression analysis of incoming CEO characteristics
on firm performance, we attempt to quantify the value of CEO outsiderness against
motivational benefits of insider appointments. The results of the study returned a
relationship with a virtual significance of zero. There were many difficulties with the
data available, most notably the size. Our set of observations only includes 30 external
appointments out of a total set of 164 incoming CEOs. Additionally the firms observed
were not diverse. For example, in the study by Wilkes (2014), he found conflicting
results on the benefits of CEO previous location between large firms and firms that were
considered small or medium sized. Since only large firms were examined according to
the results of Wilkes (2014), the analysis should have shown a negative relationship
between external candidates and firm performance.
During the literature review two effects were examined regarding incoming CEO
previous location. Internal CEO appointments benefit the firm by motivating managers
to increase their performance efforts (Agrawal et al., 2000; Chan, 1996; Lazear &
Rosen, 1981). While external CEO appointments benefit the firm by bringing new ideas
and correcting past mistakes (Karaevli, 2007; Pan & Wang, 2012). It is very likely that
these effects, along with others that either benefit or harm firm performance have
normalized to an equal level. This is a possible reason why our regression returned no
relationship. This finding, or lack thereof, could indicate that the board of directors is
able to select an external or internal candidate at the appropriate time.

Apart from the theory that competing effects have equalized the benefits of external
versus internal appointment, there is the possibility that external and internal CEOs do
not have any significant differences. This idea is consistent with CEO homogeneity and
the study from Thomas (1988), which only credited CEOs with 3.9% of the variation in
firm performance. Although our study cannot disprove the idea that external and
internal candidates are similar, it goes against the vast majority of literature reviewed in
section 2.2.1.
6.3 Question Three Results
The results of our study show a weak relationship between compensation and firm
performance in Model 1. However, there is not enough evidence to reject the null
hypothesis. In our first model the relationship between total compensation and firm
performance is significant only at the 90% confidence level. The beta coefficient for this
variable is 2.269*10^(-7). This seems miniscule, but the variable is measured in
thousands of dollars. If the sample’s mean CEO compensation--nearly 11 million
dollars--is used for an example it would increase performance by 0.0024 all other
factors held constant. This test was mainly intended to give an indication of the
relationship between firm performance and CEO compensation. Of course there are
diminishing returns to CEO compensation. If the results of our study are taken without
proper interpretation it would suggest that CEO pay increases are perpetually beneficial.
Furthermore, in Model the results become even less significant.
In Model 2, the significance level diminishes, but still remains positive. The data from
Model 2, is more relevant for our purpose. If a strong relationship was found between
incoming CEO performance and compensation, this would indicate to the compensation
committee in a firm that higher financial incentive makes CEOs more successful. Since
the results are not significant, the firm should not expect higher firm performance with
increased financial incentives. The relationship between performance and ownership has
even weaker significance than compensation, and this is likely the most relevant
financial incentive. Total compensation is influenced by the simultaneity bias between
stock options and firm performance, while the portion of firm ownership is not.

This study shows results opposing the Forbes article by Adams (2014), who claimed the
CEOs with the highest compensation belong to lower performing firms. On the other
hand the study does not go so far as to agree with the results from Coleman (2000), or
von Lilienfeld-Toal and Ruenzi (2014), who found positive relationships between
compensation and ownership respectively. The lack of confidence in our results does
not allow us to reject the null hypothesis making our results follow the example of
Bradford (2015), who could not find a relationship between firm performance and CEO
compensation.
6.4 Limitations
There is a sample selection bias that limits the conclusions that can be made on the
benefits of the turnover event. The study did not consider the performance of firms that
were neither leading up to a turnover event nor following one. Therefore, our
conclusions do not suggest to a board of directors that dismissing the CEO in struggling
times will lead to improved firm performance. This conclusion would require an
analysis of comparable firms who choose to keep their CEO on board. This study can
only suggest to stakeholders that a CEO turnover event is a credible signal for future
improvements in firm performance.
An additional limitation is caused by the absence of the reason for departure. Separating
firms by the cause of the turnover event would lead to more definitive conclusions.
Since every reason for departure would likely have its own unique effect, the
measurements in this study will not be effective in specific situations. Instead this study
makes overarching conclusions on turnover events as a whole. For example, a firm may
be performing exceptionally well and their CEO is headhunted or retires, the next CEO
would find it difficult to maintain the high performance levels and likely cause a
decrease in performance. The model in this study would make an incorrect prediction of
the change in performance. On the other side of the argument the existence of this
situation in our sample may have decreased the positive turnover effect we have
concluded on.
The results of this study are also limited by any omitted variables that were not
considered or that were too difficult to include. For example industry-specific portfolios

would have been a better control variable for performance changes that the firm was not
responsible for. When a firm experiences a turnover there are many other changes that
take place simultaneously. The turnover of other key management positions would of
course affect performance. This limitation does not allow the study to credit the total
performance change on the CEO alone, but rather the entire turnover event and every
change that comes with it.
One criticism of the study by Hwang (2013), was his use of the S&P 500 as a control
for industry growth. This was the same control factor used in this study, so it too must
face the criticism of not considering small- and medium-size firms. However, early on
in the study the assumption was made that a relationship between CEO turnover and
firm performance in large firms would only become more significant with smaller firms.
This assumption was based on the idea of increased significance of the CEO role in
small firms, more opportunities for growth, and less control by corporate governance.
Although there is some logic behind this assumption, it is still only an estimation of the
extrapolated effects. In order to make credible statements about the relationship between
performance and CEO turnover in small- and medium-sized firms a new sample would
need to be drawn.
7 Conclusion
This paper presents evidence supporting a positive relationship between CEO turnover
and firm performance. The purpose of this analysis was to determine how investors
ought to react after a CEO turnover announcement. Without given further specification
on the firm or CEO this study argues that turnover events should be treated with
optimism. Although questions two and three did not come to any significant
conclusions, the results have still been telling. The insignificance of monetary
incentives on CEOs is evident in the results of this study. Basic organizational
behaviour theories like Maslow’s hierarchy of needs and McGregor’s x-y theory are
likely the best way to approach motivating CEOs. None of the CEOs in our sample are
in financial need, so it is only reasonable to assume money is not an effective motivator
for them. The performance benefits of internal versus external CEO appointments are
specific to firm needs. For this reason our results could not find the slightest relationship

between these variables. In order to identify when it is best to appoint an internal or
external candidate, research must look at a firm’s weaknesses and opportunities.
After examining the existing literature and previous studies as well as working through
this study on the relationship between CEO turnover and firm performance, there should
not be any further analysis of this relationship in the general sense. It has been shown in
several different environments and through different methods that CEO turnover
follows poor performance and leads to improved performance when aggregated cases
are tested. Further analysis should narrow the scope of the study and examine patterns
of specific situations.
In order to improve the role of the board of directors, future research should focus on
relationships between firm needs and CEO characteristics. The literature review
uncovered certain relationships that can benefit board decision making, but there is
much more that can be done. A relationship between young CEOs and aggressive
growth strategies has been discovered as well as a relationship between external
candidates and firm transformation. These and similar relationships should be studied.
Additional research in timing for CEO dismissal would also benefit the board. This
study has found poor performance leading up to CEO turnover; further research could
help reduce the decline in performance before a turnover event by identifying signals of
deterioration in CEO usefulness.

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