How Has CEO Turnover Changed?
by
Steven N. Kaplan* and Bernadette A. Minton**
July 2011
Abstract
We study CEO turnover – both internal (board driven) and external (through takeover and bankruptcy) –
from 1992 to 2007 for a sample of large U.S. companies. Annual CEO turnover is higher than that
estimated in previous studies over earlier periods. Turnover is 15.8% from 1992 to 2007, implying an
average tenure as CEO of less than seven years. In the more recent period since 2000, total CEO turnover
increases to 16.8%, implying an average tenure of less than six years. Internal turnover is significantly
related to three components of firm stock performance – performance relative to industry, industry
performance relative to the overall market, and the performance of the overall stock market. The relations
are stronger in the more recent period since 2000. We find similar patterns for both forced and unforced
turnover, suggesting that some, if not most turnover labeled as unforced is actually not voluntary. The
turnover-performance sensitivity is modestly related to block shareholder ownership and board
independence.
Keywords: CEO turnover, board of directors, performance evaluation
JEL classification: G34
* University of Chicago Booth School of Business and NBER, ** Ohio State University. This research has been
supported by the Center for Research in Security Prices, by the Lynde and Harry Bradley Foundation and the Olin
Foundation through grants to the Center for the Study of the Economy and the State, and the Dice Center for
Research in Financial Economics. We thank Stuart Gillan, Chester Spatt, and seminar participants at the 2007 AFA
Meetings, Berkeley, NBER Corporate Governance Summer Institute, and the University of Chicago for helpful
comments. Address correspondence to Bernadette Minton, Fisher College of Business, The Ohio State University,
834 Fisher Hall, Columbus, OH 43210, minton_15@fisher.osu.edu.
I.
Introduction
In the last decade, corporate governance in the United States has come under great
scrutiny, if not attack. The corporate governance scandals at the turn of the century led to the
Sarbanes Oxley (SOX) legislation. Since the legislation, the criticism of corporate governance
has continued. CEOs are routinely criticized for being overpaid. Boards of directors are
commonly criticized as cronies of those overpaid CEOs. Jensen, Murphy and Wruck (2004)
document the increase in CEO pay since the 1970s. Bebchuk and Fried (2003) and Bebchuk and
Grinstein (2005) document a substantial increase in CEO pay accelerated after 1995. All three
papers criticize boards of directors for the increases in CEO pay and for not doing a good job
monitoring pay practices and CEOs.
While a great deal of work has focused on changes in CEO pay, recent changes in CEO
turnover and board behavior have received little attention. Earlier work and casual empiricism
suggest that the CEO’s job has become riskier over time. Khurana (2003) reports that CEO
turnover increased in the 1990s relative to the 1970s and 1980s. Murphy and Zabonjik (2004)
and Jensen et al. (2004) also report that turnover has increased in the 1990s, although the
magnitude they report is quite small – from 10% per year in the 1970s and 1980s to 11% in the
1990s. The samples in these papers do not go beyond the year 2000 so they are unable to
consider the period in which corporate governance and CEO performance and pay have been
subject to intense scrutiny.
In this paper, we study CEO turnover from 1992 to 2007 for a sample of large U.S.
companies. We consider turnover that occurs through takeover and bankruptcy as well as
turnover in ongoing companies. When takeovers and bankruptcies are taken into consideration,
the job of CEO in large U.S. companies appears more precarious than before, particularly since
1
2000. Annual CEO turnover is 15.8% from 1992 to 2007, implying an average tenure as CEO of
less than seven years. From 1992 to 1999, total CEO turnover averages about 12.6%, implying
an average CEO tenure of just under eight years. Since 2000, total CEO turnover increases to
about 16.8%, implying an average CEO tenure of about six years. Internal or board driven
turnover also rises substantially, increasing from 10.9% in the first part of the sample to 12.4% in
the latter part of the sample. Looked at another way, only 21.30% of CEOs in place in 1992
remained CEO in 1999, while only 16.35% of CEOs in place in 2000 remained CEO in 2007.
We then examine how turnover varies with firm performance. Previous work suggests a
modest relation between internal (board initiated) turnover and firm stock performance. (See
Murphy (1999) and Jensen et al. (2004)). We find stronger (and more significant) relations.
Internal turnover is related to three different components of total firm stock performance.
Turnover is sensitive to the stock performance of the firm relative to the industry, the stock
performance of the industry relative to the stock market (under certain specifications), and the
performance of the overall stock market. (Jenter and Kanaan (forthcoming) obtain similar results
for forced turnover.) The sensitivity to one standard deviation differences in each measure is
economically meaningful. We find similar results for both forced and unforced turnover.
We also find that internal turnover since 2000 is more strongly related to all three
measures of stock performance. In fact, the sensitivity to stock performance appears to be
greater than that in any of the periods between 1970 and 1995 studied in Murphy (1999).
Ironically, it appears that during the period in which boards have been criticized, boards have
become increasingly sensitive to firm stock performance.
We consider four possible explanations for factors that drive the changes in turnover and
turnover-performance sensitivity. There is some evidence that the turnover-performance
2
sensitivity is related to increases in block holdings and to director independence, but not to the
Gompers, Ishii and Metrick (2003) governance index or SOX legislation.
External turnover – turnover primarily related to mergers and acquisitions – in most
regression specifications is unrelated to stock performance, suggesting that, on average, the
takeovers are not disciplinary in nature.
As we discuss in more detail in the conclusion, our results have a number of implications.
First, CEO tenures have declined, suggesting the CEO job is more precarious than in the past.
When external takeovers are included, the average tenure of a CEO has declined to less than six
years since 2000. The recent tenures are substantially shorter than those reported in previous
work for the 1970s, 1980s, and 1990s. For individual CEOs, the shorter expected tenure likely
offsets some of the benefit of the increase in CEO pay over this period. This result is consistent
with Hermalin (2005) who presents a model that predicts increased board vigilance will be
associated with shorter CEO tenures (and higher CEO pay). The aforementioned relations with
more independent boards and blockholders also are consistent with the increased vigilance in
Hermalin’s model.
Second, our similar results for the turnover-performance sensitivities of forced and
unforced turnover suggest that a number of turnovers labeled as unforced are, in fact, not
voluntary. In subsequent work, partially motivated by our results, Jenter and Lewellen (2010)
find additional evidence consistent with this conclusion.
Third, the results suggest an evolving role for boards. In a sample from the 1980s,
Morck, Shleifer and Vishny (1989) find that internal turnover is related to industry-adjusted
performance while external turnover from hostile takeovers is related to industry performance.
They interpret this as indicating boards respond well to poor performance relative to the industry,
3
but do not respond well to poor industry performance. The external takeover market becomes
active in reaction to poor industry performance and a need for restructuring.
Our results suggest that boards respond not only to poor performance relative to the
industry, but also to poor industry performance and to poor market performance. One
interpretation of these results is that boards (perhaps in concert with shareholders) perform both
the role they performed in the 1980s and some of the role that hostile takeovers played then.
Fourth, the shorter expected CEO tenures and sensitivity of those tenures to stock
performance have implications for the measurement of CEO pay. The shorter expected tenures
suggest that the estimates of CEO pay used in most compensation studies may be overstated.
Finally, shorter CEO tenures, the greater sensitivity to stock performance, as well as
higher CEO pay may have created a greater incentive for CEOs to engage in earnings
management or manipulation.
This paper was written contemporaneously with Jenter and Kanaan (forthcoming) who
study related issues in a sample of CEO turnovers from 1993 to 2001. They focus on forced
CEO turnover, rather than all CEO turnover. Forced turnovers represent somewhere between
15% and 25% of total internal turnovers. As we do for forced and unforced turnover, they find
that forced CEO turnover is significantly related to industry-adjusted, industry, and market
returns. They focus most of their paper on verifying this effect for forced turnover and
explaining why boards might behave this way. They also study a larger sample of firms, but
over a shorter time period. Unlike us, they do not focus on the level of total turnover, the annual
variation in that turnover, and do not consider external turnovers. Given their shorter sample,
they also do not consider how turnover behavior changes over time.
4
Our paper also is related to that of Mikkelson and Partch (1997) who compare complete
management turnover in US companies in two five-year periods – the active takeover market of
1984 - 1988 and the less active market of 1989-1993. In the active takeover period, they find
that 39% of firms experience CEO turnover and 23% of firms experience complete management
turnover; in the less active period, 34% of firms experience CEO turnover while 16% of firms
experience complete management turnover. They find that the decline in turnover frequency is
more pronounced among poorly performing firms. They argue that the activity of the external
takeover market affects the “intensity of management discipline.” Our results suggest that the
intensity of management discipline has increased since the end of their sample period, and likely
exceeds the intensity of the active takeover period. Huson, Parrino, and Starks (2001) also
examine CEO turnover across sub-periods to see if the relation between performance and
turnover has changed over time. Using four six-year sub-periods between 1971 to 1994, they
document that while CEO turnover is negatively related to accounting performance and industryadjusted stock returns, the relations did not change significantly over time. Our analysis begins
at the end of their sample period and shows that, at least, during the 1992 to 2007 period the
relation between turnover and performance has changed.
The paper proceeds as follows. Section II describes our sample. Section III presents the
results for turnover levels. Section IV presents the turnover-performance regressions. Section V
summarizes the results and discusses their implications in more detail.
5
II.
Sample and Data
The sample of firms includes all Fortune 500 firms with data on both the Center for
Research in Security Prices (CRSP) tapes and Compustat files (research and current files). The
sample runs from fiscal-year end 1991 to fiscal-year-end 2007. We construct the sample using
the annual Fortune 500 lists from 1992 to 2008. Each year, Fortune ranks firms based on sales at
fiscal-year end and publishes the list in an April or May issue of the following year. For
example, fiscal-year end 1991 rankings are published in an April or May 1992 issue.
We follow the sample firms from the first year they appear on a Fortune list until the end
of the sample period or until the firm exits the sample because of a merger, acquisition or
delisting from a major stock exchange. Thus, we continue to follow a firm even if it falls out of
the Fortune 500. We identify CEO turnovers using the Fortune 500 and Fortune 1000 lists, 10K filings, proxy statements, Dun and Bradstreet’s Million Dollar Directory, the Wall Street
Journal and Lexis/Nexis business news searches.
III.
Turnover Levels
Turnover in a given fiscal year, T, means that the CEO in the spring of year T is no
longer the CEO by the following spring of year T+1. We measure turnover, therefore in the
years 1992 to 2007.
We consider two types of turnover. Standard or internal turnover is turnover that is
associated with a company’s board of directors. For standard turnover, a company remains
publicly-listed over the course of the year, but the CEO in the spring is no longer the CEO the
following spring. This is the turnover that is generally measured in studies of turnover. For
example, see Huson et al. (2001). Non-standard or external turnover is turnover due to a merger
6
or bankruptcy / delisting. We also consider the CEO to have been turned over if his or her
company is taken over by another company and he or she is not CEO of the combined company.
We view this as an instance of turnover because in many mergers the target CEO leaves the
combined company. In those instances in which the CEO target remains, the target CEO
generally experiences a reduction in pay and power. Total turnover is the sum of internal and
external turnover.
Table 1 presents the level of CEO turnover by year. For total turnover and standard
turnover we use two definitions of turnover. Definition (1) defines a turnover occurrence if a
new CEO is selected. Definition (2) defines a turnover occurrence in which the CEO dies as a
non-turnover event. Figure 1 presents total and standard turnover for all firms according to
definition (1) graphically.
There are three noteworthy patterns across the panels. First, total turnover levels are
substantially higher than those typically reported. Overall, total turnover under definition (1) is
15.8% over the entire sample period implying an average CEO tenure of 6.3 years. This is
substantially higher than that reported in Jensen, Murphy and Wruck (2004) and Murphy and
Zabonjik (2004) who study a different sample of large firms (from the Forbes lists) over three
decades from 1970 to 2000. They report turnover of 10.2% in the 1970s, 10.0% in the 1980s,
and 11.3% in the 1990s. All of these measures, however, are for standard or internal turnover.
For our sample period of 1992 to 2007, we obtain a standard turnover of 11.7%, similar to their
results for the 1990s. At 11.7%, the estimated average CEO tenure is 8.5 years, roughly two
years greater than the actual average tenure (that includes external takeover).
7
The second noteworthy pattern in table 1 is the time series variation in the levels of both
total and internal turnover. For example, using definition (1) total turnover is as low as 6.94% in
2003 (and only 9.35% in 1994), and as high as 26.32% in 2000 (and 21.37% in 1999).
Third, turnover increased significantly in the latter part of the sample. In the earlier
period from 1992 to 1996, total CEO turnover using definition (1) is 12.62% per year implying
an average tenure of 7.9 years. In the period from 1997 to 2002, total turnover increases to
19.15% per year, implying an average tenure of just 5.2 years. This period roughly coincides
with the large increase in CEO pay described in Bebchuk and Grinstein (2005). The period in
which CEO pay increased substantially coincides with a period in which CEO tenure decreases
substantially. It is worth adding that the increased level of turnover began well before 2002
(when the Enron and Worldcom scandals became apparent and Sarbanes-Oxley was passed). In
the more recent period from 2003 to 2007, total CEO turnover declines from the middle period to
14.70%, implying an average CEO turnover of 6.8 years. Internal or board driven turnover
follows a similar trend.
As stated previously, we continue to follow a firm once it is included in the Fortune 500,
even if it drops from the Fortune 500. This may make our results harder to compare with other
studies that restrict themselves to firms in the Fortune 500, S&P 500 or Forbes lists.
Accordingly Appendix table A1 examines turnover separately for firms in the Fortune 500 and
those not in the Fortune 500 in the particular year. The increase in turnover from the earlier part
of the sample to the latter part of the sample is consistent across both Fortune 500 and nonFortune 500 companies. While it appears that annual turnover is larger for non-Fortune 500
firms, annual tests of the differences in average turnover shows that the turnover across groups is
not different in all but three years.
8
Table 2 presents the results of probit regressions estimating the probability of CEO
turnover. The regression includes only an indicator variable equal to one if the year is 2000 or
later. This tests whether turnover in the later period (2000 to 2007) is statistically different from
that in the earlier period. We report the results for all firms for total turnover and standard
turnover using both definitions of turnover. The coefficient estimates on the indicator variable
are positive and statistically significant in all four regressions, suggesting that turnover is
significantly higher in the later period.
Table 3 presents the turnover data in a different way. We compare the fraction of the
CEOs in 1992 who are no longer CEOs in 1999 to the fraction of CEOs who are CEOs in 2000
and no longer CEOs in 2007. The table shows that 78.70% of CEOs in 1992 were no longer
CEOs in 1999, while over 83% of CEOs in 2000 were no longer CEOs by 2007. Again, this
result suggests that the job of CEO has become increasingly precarious over the sample period.
The turnover also is substantially greater than that measured by Mikkelsen and Partch
(1997) over two earlier five year periods. In the active takeover period from 1983 to 1988, they
find that 39% of firms experience CEO turnover (and 23% of firms experience complete
management turnover); in the less active period from 1989 to 1993, 34% of firms experience
CEO turnover (while 16% of firms experience complete management turnover). Unfortunately,
these results are not directly comparable because the sample in Mikkelsen and Partch consists of
smaller firms.
IV.
The Relation between Turnover and Performance
A. Internal Turnover
9
We estimate pooled annual probit regressions to examine the likelihood of internal CEO
turnover. In all of the probit regressions, the dependent variable is equal to one if a CEO turns
over and zero otherwise. Turnover is measured using definition (2) (i.e., deaths are coded as
non-turnover events). The tables report the marginal changes in the probability of internal CEO
turnover implied by the probit coefficient estimates that result from a unit change in the
explanatory variables. For indicator variables, the coefficient represents the change in the
probability associated with moving the indicator from 0 to 1. These marginal sensitivities,
labeled "ΔProb," are economically equivalent to coefficient estimates from ordinary least squares
estimation. In the discussion below, we focus on the significance of these marginal effects.
Robust standard errors to control for heteroskedasticity are reported in parentheses.
In all of the probit regressions, three proxies are used to measure stock market
performance. First, we measure market performance using the annual return on the S&P 500
index. Second, relative industry performance is measured at the two-digit SIC code level and
equals the difference between the return on the median firm in the industry and the return on the
S&P 500 index. Third, relative firm performance is measured as the industry-adjusted firm stock
return, which is equal to the firm stock return minus the return for the median firm in the same
two-digit SIC code. Returns are measured over the calendar year period. Lagged returns are
measured over the previous calendar year. For example, for companies in Fortune’s April 2006
issue, we measure stock returns for calendar year 2005 and lagged stock returns for calendar year
2004.
Table 4 reports the results for two sets of probit regressions. In panel A, we include
measures of stock market performance and an indicator variable equal to one if lagged CEO age
is greater than or equal to 60 (CEO age dummy). In the regressions in panel B, we add the
10
change in ROA as a measure of operating performance where ROA equals the sum of income
before extraordinary income plus interest and related expenses divided by total assets. We use
change in ROA because this measures the change in operating performance. For the two sets of
regressions, we report the results for the full sample period and five sub-periods: three five-year
periods, 1992 to 1996, 1997 to 2002, 2003 to 2007; and two longer periods, 1992 to 1999 and
2000 to 2007.
Table 4 shows that in the full sample regression all three components of stock
performance are significantly related to internal CEO turnover. Additionally, the negative
associations between stock performance and the likelihood of turnover are driven by the later
sub-periods.
Table 4 documents turnover increases with poor industry-adjusted stock performance
over the entire sample period and, particularly, in the latter sub-periods. For example, for the
2000 to 2007 sub-period, a one-standard deviation (35.4%) decline in a firm’s industry adjusted
stock return is associated with an increase of 3.2% in the mean likelihood of CEO turnover.
From a base turnover level of 12.55%, this change implies a likelihood of 9.35% for a CEO
whose firm performs one-standard deviation above the industry versus 15.75% for a CEO whose
firm performs one-standard deviation below the industry. These are economically meaningful
differences with 9.35% implying a tenure of 10.7 years and 15.75% implying a tenure of 6.3
years.
The reported marginal probabilities appear to be greater than the sensitivities reported in
Murphy (1999) for various sub-periods between 1970 and 1995. Yet, similar to Murphy (1999)
who finds that turnover is not related to industry-adjusted performance between 1990 and 1995,
11
panel A of table 4 shows that turnover is not statistically related to industry-adjusted
performance during the 1992 to 1996 period.
CEO turnover also is related to poor industry performance. Again, the negative relation
for the full sample period appears to be driven by the sub-period 1997 to 2002 if we split the
time period in thirds or by the 2000 to 2007 sub-period if we divide the period in half. For the
2000 to 2007 sub-period, a one-standard deviation (18.7%) decline in industry performance is
associated with a 2.7% increase in the mean likelihood of CEO turnover.
Lower overall market performance, as measured by the return on the S&P 500 index, is
also associated with a higher likelihood of internal CEO turnover for the full sample and the later
sub-periods. For the 2000 to 2007 sub-period a one-standard deviation (15%) decline in the S&P
500 index corresponds to an increase of 2.7% in mean probability of CEO turnover.
Surprisingly, the relations between CEO turnover and overall market performance, and
industry performance, respectively are positive and significant in the 1992 to 1996 sub-period.
One possible interpretation for these positive marginal probabilities is that CEOs left office after
good performance. This would be the case if they were voluntary turnovers. While forced
turnovers increased from the 1992 to 1996 sub-period to the 1997 to 2002 sub-period (from
about 12% to about 17%), this explanation is implausible because the great majority of turnovers
in both sub-periods are classified as voluntary.
Overall, the results in panel A indicate that the relation between internal CEO turnover
and (poor) stock market performance appears to have intensified. In the period from 2000 to
2007, all three sensitivities to stock performance – 3.2%, 2.7%, and 2.7%, respectively, for one
12
standard deviation changes in industry-adjusted, industry, and market performance – are
economically meaningful relative to average internal turnover of 12.55%1.
The second set of regressions in panel B of table 4 includes the change in return on assets
(ROA) in addition to the stock return variables. The results are qualitatively unchanged. The
change in ROA is significant during the full sample period from 1992 to 2007. While the
estimate is statistically significant, a one standard deviation increase in the change in ROA is
associated with only a 0.8 percent increase in the mean likelihood of CEO turnover.
In table 5, we add one year of lagged stock performance variables to the regressions.
Overall, the results in table 5 are consistent with those in table 4. For the entire period, internal
CEO turnover is significantly negatively related to industry-adjusted, industry, and overall
market stock performance in the current year. Turnover also is significantly negatively related to
industry-adjusted and industry performance stock performance in the previous year. Strangely,
turnover is significantly positively related to the lagged return on the S&P 500 (although the
positive coefficient on the lagged return is smaller in magnitude than the negative coefficient on
the contemporaneous return).2 As in the previous results, the regressions in table 5 indicate that
the turnover-performance relations are driven by the later sub-period.
To examine the change in the predicted probability associated with a change in the
current and lagged industry-adjusted performance, we first estimate the predicted probability of
turnover evaluated at the mean values of all the regressors. Next, we re-estimate the predicted
probability of turnover for current and lagged industry-adjusted stock returns evaluated at onestandard deviation below their means and for all other regressors evaluated at their means. For
1
The predicted likelihood calculated at the mean of the independent variables is 10.97% for the 200 to
2007 sub-period.
2
In unreported tests, we test whether the sum of the current and lagged market returns are statistically
different from zero. For the full sample period and the 2000 to 2007 sub-period, the sum is statistically
different from zero. It is not statistically different from zero for the 1992 to 1999 sub-period.
13
the full sample period, the result is an increase in the predicted probability of turnover of 5.18%.
Repeating the same procedure the 1992 to 1999 and 2000 to 2007 sub-periods results in
increases in the probability of turnover of 0.1% and 6.6%, respectively. Again, the sensitivity to
industry-adjusted performance for the 2000 to 2007 period appears to be greater than any of the
sensitivities reported in Murphy (1999). Similar exercises for market performance show that
similar to the results for industry-adjusted returns the relations between market performance and
turnover are greater in the 2000 to 2007 sub-period than in the 1992 to 1999 sub-period.
In contrast, when we evaluate the change in current and lagged industry performance we
find that one-standard deviation declines in industry performance are associated with larger
increases in the 1992 to 1999 sub-period than in the 2000 to 2007 sub-period. Specifically, a
one-standard deviation decline in current and lagged industry performance during the 1992 to
1999 sub-period is associated with a 5.00% increase in turnover. In contrast, a one-standard
deviation decline in current and lagged industry performance during the 2000 to 2007 sub-period
is associated with a 3.8% increase in turnover. Finally, one-standard deviation declines in
current and lagged market returns are associated with a 2.5% increase in turnover for using the
full-sample period.
Overall, the results in tables 4 and 5 suggest that since 2000, boards have been more
sensitive to poor stock performance. It is also worth noting that the economic magnitudes of the
effect are large. For the 2000 to 2007 period, the regressions in table 4 imply that a CEO whose
firm performs one standard deviation better than the industry has a 5.2% lower likelihood of
turnover while a CEO whose firm performs one standard deviation worse than the industry has a
cumulative 5.2% increase in the likelihood of turnover. From a base turnover level of 12.5%,
these imply likelihoods of 7.4% for the strong performer versus 17.8% for the poor performer.
14
These are economically meaningful differences with 7.4% implying a tenure of 13.5 years and
17.8% implying a tenure of 5.6 years.
Table 6 repeats the table 5 probit regressions for the full sample period and the 1992 to
1999 and 2000 to 2007 sub-periods for two sets of firms: firms in the S&P500 index and all
other Fortune 500 firms. We do this for two reasons. First, many papers on executive
compensation and corporate governance use the ExecuComp data set that includes only firms in
various S&P indices. It is possible there is a selection bias in these firms. Second, investors may
be more likely to pay attention to firms in the S&P 500 index, and, if so, these firms would be
more likely to be monitored by the press and institutional investors. Thus, the effect of stock
market performance might be different for these firms (Bertrand and Mullanianathan, 2001).
The coefficient patterns in table 6 are qualitatively similar for the two sets of firms except
for the 2000 to 2007 sub-period for which turnover for firms not in the S&P 500 index is not
statistically related to market performance. Turnover in both sets of firms is significantly related
to industry-adjusted and market stock performance over the entire sample period. As in the
sample overall, the relations for firm in the S&P 500 index are stronger in the more recent 2000
to 2007 period.
B. Internal Turnover and Governance Variables
The previous sections document an increase in CEO turnover and turnover-performance
sensitivity for large public companies in the U.S. In this section we consider four possible
sources of those increases – corporate governance (or shareholder rights), shareholder
blockholdings, board independence, and the SOX legislation.
15
Recent work has suggested that differences in corporate governance and shareholder
rights may have real effects. Gompers, Ishii and Metrick (2003) find that differences in
corporate governance and shareholder rights are related to stock returns. Masulis, Wang, and
Xie (2005) find that those differences in corporate governance are related to acquisition
behavior. In both papers, greater shareholder rights are associated with higher stock returns.
In this section, we examine the relation between turnover, stock performance and
governance. To do so, we use the GIM index developed by Gompers et al. (2003). They
categorize 24 charter provisions, bylaw provisions, and other firm-level rules associated with
corporate governance into five types: (1) Tactics for delaying hostile bidders, (2) voting rights,
(3) director/officer protection, (4) other takeover defenses, and (5) state laws. Their overall
index and the five component indices generally score one point for each provision that restricts
shareholder rights or increases managerial power. Thus, a higher index score represents greater
managerial power (weaker shareholder rights).
We estimate turnover regressions that interact stock performance with the measure of
governance. We used both a continuous measure of the GIM index as well as an indicator
variable equal to one if the firm’s GIM index is in the highest quintile that year and zero
otherwise. To the extent that the GIM index measures poor governance, the GIM index should
have a negative effect on the level of turnover (i.e., poorly governed firms should have less
turnover), while the interaction of the GIM index and stock performance should have a positive
effect on turnover (i.e., turnover at poorly governed firms should be less sensitive to poor
performance).
Table 7 presents results for probit regressions using the indicator variable for the highest
GIM index quintile. For the full sample period, the marginal probability associated with the
16
GIM index is positive and marginally significant. I.e., a high GIM index (fewer shareholder
rights) is associated with slightly higher CEO turnover, not less.
For the sample overall and for each sub-period, most of the interaction terms are not
statistically different from zero. For two coefficients, the GIM index interaction is significantly
negative. Turnover is significantly more sensitive to poor lagged industry-adjusted performance
for the high GIM index firms during the overall sample period and in the 2000 to 2007 subperiod. These are the opposite signs one would expect if the GIM index measured poor
governance.3
Overall, then, we interpret these results as finding that the GIM measures of governance
or shareholder rights do not have an appreciable relation to CEO turnover. The most one can say
is that the GIM measure is possibly associated with a somewhat faster response to poor industryadjusted performance. Our results are consistent with Bhagat and Bolton (2006) who also fail to
find a significant effect on turnover when they interact governance and performance.
Next we examine the relation between CEO turnover and blockholder ownership.
Institutional and blockholder ownership increase over the sample period. We focus on
blockholder ownership (where an institution owns at least 5% of a firm’s outstanding shares)
because blockholders have both the incentive and the ability to monitor. Cremers and Nair
(2005) find that blockholder ownership and governance affect corporate valuations in certain
circumstances. We follow Cremers and Nair (2005) and use the percentage of shares held in
each firm by the firm’s largest institutional blockholder where blockholders are shareholders
with greater than 5% ownership of the firm’s outstanding shares. Data on institutional
ownership are from Thomson-Reuters Institutional Holdings (13F) database.
3
Although not reported in a table, our results also are qualitatively similar when we interact stock
performance with the continuous measure of the GIM index.
17
Table 8 reports the mean and median block ownership and the presence of a blockholder
for our sample firms. The average holding of blockholders and fraction of firms with a
blockholder present increase over the sample period. During the 1992 to 1999 sub-period, the
average blockholder ownership is 9.6% while 57% of the firms have a blockholder present.
During the 2000 to 2007 sub-period, blockholder ownership averages 14.98% while almost 75%
of the firms have a blockholder present. The differences across sub-periods are statistically
significant.
Table 9 reports the results of probit turnover regressions that include the percent of total
blockholder ownership (at the end of the previous year) and the interactions of the continuous
measure and our three stock performance measures. As table 9 shows, the marginal probability
associated with the percent of total blockholder ownership while positive is not statistically
different from zero for the full sample or for either sub-period. The only interaction term that is
statistically significant is the interaction of block ownership and industry-adjusted stock returns
in the 2000 to 2007 sub-period. One interpretation of this result is that blockholders are
particularly active in firms that underperform their industries but only so in the latter time period.
This is somewhat suggestive of blockholders playing a role in the increase in industryadjusted turnover-performance sensitivity. These results are consistent with those in Brav et al.
(2008) who find increased CEO turnover associated with hedge fund activism and Del Guercio et
al. (2008) who find increased CEO turnover associated with institutional investor voting.
Third, we consider the role of independent directors. Weisbach (1988) finds that
turnover-performance sensitivities are greater for firms with more independent boards. And over
time, boards in the U.S. have become more independent. It is possible that this increased
independence has played a role in the changes in turnover. We obtain data on director
18
independence from the IRRC Directors database on WRDS. We use the variable director type to
classify directors as independent. The IRRC data are available only from 1996 on.
Table 8 reports the percent of independent directors, and the fraction of firms that do not
have a majority independent board. Similar to the rise in blockholders, the percent of
independent directors on a firm’s board increases over time. The percentage increases from 63%
to almost 72% from the 1992 to 1999 sub-period to the 2000 to 2007 sub-period. Moreover, the
fraction of firms without a majority independent board decreases from 24% during the 1992 to
1999 sub-period to 12% in the 2000 to 2007 sub-period.
Table 10 reports the results of probit turnover regressions that account for board
independence. We include a dummy variable that equals one if the firm does not have a majority
independent board. (The baseline, therefore, is a firm that does have a majority independent
board.) The results are qualitatively similar, but have a less natural interpretation when we use
the percentage of independent directors. We also interact this indicator variable with the stock
performance variables. We estimate the probit for the 1996 to 2007 period, the period over
which we have director data.
Table 10 indicates that the marginal probability associated with the no independent board
indicator variable, while negative, is not statistically significant. At the same time, two of the six
interaction terms are positive and statistically significant suggesting that non-independent boards
are associated with less turnover-performance sensitivity. Said another way, the results of the
second regression suggest that more independent boards are associated with more turnover and
more turnover sensitivity to poor performance.
In table 11, we examine whether the probability of CEO turnover is greater in the years
under the SOX legislation. We create an indicator variable equal to one for years 2003 and after
19
and zero otherwise. In the first regression, we include this indicator variable, current year
measures of performance, and interactions between the indicator variable and performance
variables. In the second regression we add the lagged performance measures and corresponding
interaction terms. In the last column of the table, we repeat the second regression for the 2000 to
2007 period.
In the first regression, CEO turnover is significantly higher during years under the SOX
legislation. The marginal positive marginal probability implies about a three percent increase in
turnover during these years. Additionally, the interaction term between the SOX indicator
variable and market performance is significantly negative implying a decrease in market
performance is associated with higher turnover during the years under the SOX legislation.
When we add the lagged variables, the marginal probability associated with the SOX indicator
variable is positive but no longer statistically significant in the full sample or the 2000 to 2007
sub-period. For the 2000 to 2007 sub-period, the interaction term between the indicator variable
and industry performance is positive and significant but the sum of the industry performance and
the interaction term is not statistically different from zero. We conclude that these results are
inconclusive.
Taken together, the governance variables are of mixed help in explaining the increase in
turnover and turnover-performance sensitivity in the latter half of our sample. While the GIM
measure and the SOX legislation do not reliably affect turnover, the presence of large
blockholders and independent boards are associated with greater turnover-performance
sensitivity. The findings in Jenter and Llewellen (2010) for a different sample are consistent
with this latter result.
20
C. Forced Turnover
Thus far, we have not distinguished between forced turnover and all other turnover.
Jenter and Kanaan (forthcoming) focus exclusively on forced turnover. As we do for all
turnover, they find that forced turnover is related to the three different measures of performance.
It is possible that our results are driven by the forced turnover in our sample. To examine
whether this is the case and whether performance is related differently to forced turnover and
standard internal turnover, we estimate multinomial logit (MNL) regressions.
We follow Huson, Parrino and Starks (2001) in classifying turnover as forced. (Jenter
and Kanaan (forthcoming) also use this classification scheme.) If an article in the business press
indicates that the CEO was fired, forced, or left following a policy disagreement or some other
equivalent, then turnover is defined as forced. For the remaining announcements, succession is
classified as forced when the CEO is under 60 and the first article reporting the announcement
does not report the reason for the departure as involving death, poor health or the acceptance of
another position elsewhere.
We present the regression results in table 12. The dependent variable categories in the
MNL estimations are unforced turnover, forced turnover, or no turnover. The table reports the
marginal effect of each regressor. The probability of forced turnover is significantly negatively
related to the three components of firm stock performance – firm performance relative to the
industry, the industry relative to the market, and the overall market – in the current year and to
industry-adjusted return in the previous year. The probability of unforced turnover is
significantly negatively related to firm stock performance relative to the industry and the overall
market in the current year, and to industry stock return and industry-adjusted stock return in the
21
previous year. As in the previous results, both type of turnover are positively related to lagged
market performance.
Overall, then, both forced turnover and unforced turnover are sensitive to all three types
of poor stock performance. This strongly suggests that a number of unforced turnovers are not
voluntary. In work that was partially motivated by our results, Jenter and Lewellen (2010) find
strong evidence consistent with this conclusion.
D. External Turnover
As discussed earlier, in addition to internal turnover, we examine external turnover.
Recall, non-standard or external turnover is turnover due to a merger or bankruptcy / delisting.
We consider the CEO to have been turned over in a merger if his or her company is taken over
by another company and he or she is not CEO of the combined company. We consider the CEO
to have been turned over in a bankruptcy if he or she is no longer CEO of the bankrupt company.
The incidence of external turnover is 4.7% per year over the sample period.
Table 13 reports probit regressions of the probability of external turnover as a function of
current stock market performance (columns 1 through 3) and current and lagged performance
(columns (4 through 6)). Unlike the results for internal turnover, in most specifications, external
turnover is unrelated to performance. When performance is significant, the marginal
probabilities are economically small and in most cases positive. For example, when we include
only current performance in the regressions, external turnover is positively related to market
performance in the earlier sub-period and to industry-adjusted stock performance in the full
sample period and later sub-period. One interpretation of the lack of results for external turnover
22
and performance is that, on average, mergers and acquisitions during this period were not
disciplinary in nature.
V.
Summary and Implications
In this paper, we examine the extent and determinants of internal and external CEO
turnover for a sample of large U.S. companies from 1992 to 2007. Total turnover, the sum of
internal and external turnover, is 15.84% from 1992 to 2007, implying an average CEO tenure of
less than seven years. In the more recent period from 2000 to 2007, total CEO turnover
increases to 16.78%, implying an average tenure of just under than six years. Internal or board
driven turnover also rises substantially in the latter part of the sample.
We then look at how turnover varies with firm stock performance. Previous work
suggests a modest relation between internal (board initiated) turnover and firm stock
performance. We find a stronger and significant relation between internal turnover and three
different components of firm stock performance – performance relative to the industry,
performance of the industry relative to the stock market, and the performance of the overall stock
market. (Jenter and Kanaan (forthcoming) obtain similar results for forced turnover.) The
sensitivities are economically meaningful. Both types of internal turnover – forced and
unforced are sensitive to all three types of poor stock performance.
Internal turnover after 2000 is more strongly related to all three measures of stock
performance. In fact, the sensitivity to stock performance appears to be greater than that in any
of the periods between 1970 and 1995 studied in Murphy (1999).
We next consider four possible explanations for or factors that drive the changes in
turnover and turnover-performance sensitivity. There is some evidence that the increases in
23
turnover and turnover-performance sensitivity are related to increases in blockholdings and
board independence. Turnover and turnover-performance sensitivity are not reliably related to
the Gompers, Ishii and Metrick (2003) governance index.
External turnover – turnover primarily related to acquisitions – also is significantly
related to all three measures of performance. As with internal turnover, the results are stronger
in the later sub-period.
Our results have several implications. First, they suggest that the CEO job is more
precarious than in the past. When external takeovers are included, the average tenure of a CEO
has declined to less than six years for the recent 1998 to 2005 period. The recent tenures are
substantially shorter than those reported in previous work for the 1970s, 1980s, and 1990s. The
shorter tenures appear to have continued out of sample.
For individual CEOs, the shorter expected tenure likely offsets some of the benefit of the
increase in CEO pay since the mid-1990s. For example, the annual pay of S&P 500 CEOs
roughly doubled in real terms from the 1992 – 1997 period to the 1998 – 2005 period. Our
estimates suggest that the total pay of an individual CEO over his or her entire expected term
increased by less than this because the expected tenure at the higher pay declined by one-quarter
to one-third.
This calculation would be inaccurate if severance agreements around internal turnover
and takeovers are both large and have increased over time. If, instead, the severance agreements
are small, then they do not have much of an effect on a CEOs total pay. Yermack (2006) and
Hartzell et al. (2004) study severance agreements, respectively, around internal and external
takeover events. In fact, the average and median magnitudes they report are modest. (They do
not study whether these payments have changed over time.) Severance agreements, therefore,
24
are unlikely to alter the conclusion that the job of CEO has become riskier and that the shorter
expected tenures of CEOs partially offset increases in CEO pay.
The coincidence of shorter CEO tenures and higher CEO pay is consistent with Hermalin
(2005) who presents a model that predicts increased board vigilance will be associated with both
outcomes. The relations with more independent boards and blockholders also are consistent with
the increased vigilance in Hermalin’s model.
Second, the similar results for the turnover-performance sensitivities of forced and
unforced turnover suggest that many unforced turnovers are not voluntary. This greater
incidence of involuntary turnover, in turn, implies both that boards do a better job of disciplining
poor management and that the CEO’s job is more precarious than is commonly believed.
Third, our results suggest an evolving role for boards. In a sample from the 1980s,
Morck, Shleifer and Vishny (1989) find that internal turnover is related to industry-adjusted
performance while external turnover from hostile takeovers is related to industry performance.
They interpret this as indicating boards respond well to poor performance relative to the industry,
but do not respond well to poor industry performance. The external takeover market becomes
active in reaction to poor industry performance and a need for restructuring.
Our results suggest that boards respond not only to poor performance relative to the
industry, but also to poor industry performance and to poor market performance. To the extent
that internal turnover has increased, boards also appear to monitor more frequently. One
interpretation of these results is that boards – possibly encouraged by large shareholders –
perform both the role they performed in the 1980s and the role that hostile takeovers played then.
The increased turnover associated with blockholdings and board independence is consistent with
this interpretation.
25
The result that boards do not index CEO turnover to the industry or the market is
noteworthy in light of criticisms of boards for not indexing CEO pay to the industry or the
market. Bebchuk and Fried (2003) interpret the lack of indexing of pay as a failure of
governance. Our results on turnover in conjunction with those in Morck et al. (1989) for the
earlier period provide an alternative explanation. When an industry or the overall economy
performs poorly, it is sometimes efficient for the board to bring on a new CEO to respond to the
new industry or market conditions. The recent (and out of sample) high turnover in the financial
services industry is consistent with this.
Fourth, the shorter expected CEO tenures and sensitivity of those tenures to stock
performance have implications for the measurement of CEO pay. The shorter expected tenures
suggest that the estimates of CEO pay based Standard and Poor’s ExecuComp data may be
overstated. While option grants typically have a ten-year life, ExecuComp uses a seven-year life
because “executives rarely wait until the expiration date to exercise their options.” This
adjustment assumes that CEOs will remain with the company for at least seven years. If a CEO
has an expected initial tenure of six years, the ExecuComp assumption will tend to overstate the
value of option grants every year of the CEO’s tenure with the overstatement increasing each
year. This assumes that CEOs forfeit unvested options and / or must exercise vested options
when they leave the company. For internal turnover, Yermack (2006) finds that this tends to be
the default policy for most companies and companies deviate from those policies in only 16% of
the internal turnovers he studies. ExecuComp also values restricted stock grants as fully vested
when, in fact, they usually vest over a period of time. This also will tend to overstate executive
compensation.
26
The sensitivity of turnover to performance implies that the vesting and effective life of
stock options are not independent of performance. The options of CEOs of companies that
perform poorly will both have a shorter effective life and will be worth less. The Black-Scholes
methodology does not take these correlations into account. This, in turn, implies that a proper
valuation of stock options – e.g., using a binomial tree approach – would incorporate these
correlations.
Finally, shorter CEO tenures, the greater sensitivity to stock performance, as well as
higher CEO pay may have created a greater incentive for CEOs to engage in earnings
management or manipulation.
27
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29
Table 1. CEO Turnover
CEO turnovers in publicly traded Fortune 500 companies between 1992 and year-end 2007. Total turnover is all
CEO turnover including turnover due to mergers and acquisitions and delistings from a major stock exchange.
Standard (internal) turnover excludes turnover due to mergers and acquisitions and delistings from a major stock
exchange. For total and standard turnover, turnover is measured in two ways: (1) and (2). (1) defines a turnover
occurrence if a new CEO is selected. (2) defines occurrences where the CEO dies as a non-turnover event. Data
are from annual Fortune 500 lists, 10-K filings, proxy statements, and the Wall Street Journal. Year denotes the
fiscal year-end for the sales data on which Fortune ranks firms. (i.e., 1992 corresponds to the 1993 April/May
Fortune list.)
Total Turnover
(1)
Standard (Internal) Turnover
(2)
(1)
(2)
Year
Number
of firms
N
1992
460
57
12.39%
57
12.39%
54
11.74%
54
11.74%
1993
486
57
11.73
57
11.75
49
10.10
49
10.10
1994
727
68
9.35
66
9.08
56
7.70
54
7.43
1995
741
113
15.25
113
15.25
92
12.42
92
12.42
1996
739
103
13.94
100
13.53
75
10.15
72
9.74
1997
736
113
15.35
111
15.08
68
9.24
66
8.97
1998
722
130
18.01
130
18.01
87
12.05
87
12.05
1999
716
153
21.37
153
21.37
101
14.11
101
14.11
2000
703
185
26.32
183
26.03
134
19.06
132
18.78
2001
683
97
14.20
97
14.20
63
9.22
63
9.22
2002
676
133
19.67
131
19.38
102
15.09
100
14.79
2003
663
46
6.94
46
6.94
34
5.13
34
5.13
2004
669
94
14.05
92
13.75
78
11.66
76
11.36
2005
679
127
18.70
126
18.56
94
13.84
93
13.70
2006
663
112
16.89
111
16.74
83
12.52
82
12.37
2007
652
110
16.87
107
16.41
84
12.88
81
12.42
Total
10,715
1,698
15.84%
1,680
15.67%
1,254
11.70%
1,236
11.54%
1992-1996
3,153
398
12.62
393
12.46
326
10.34
321
10.18
1997-2002
4,236
811
19.15
805
19.00
555
13.10
549
12.96
2003-2007
3,331
489
14.70
482
14.49
373
11.21
366
11.00
1992-1999
5,327
794
14.91%
787
14.77%
582
10.93%
575
10.79%
2000-2007
5,393
904
16.78
893
16.57
672
12.47
661
12.27
%
N
%
N
%
N
%
Figure 1
CEO turnovers in publicly traded Fortune 500 companies between 1992 and year-end 2007. Total turnover is all
CEO turnover including turnover due to mergers and acquisitions and delistings from a major stock exchange.
Standard (internal) turnover excludes turnover due to mergers and acquisitions and delistings from a major stock
exchange. For total and standard turnover, turnover is measured using method (1), which defines turnover if a new
CEO is selected.
Total and Standard CEO Turnover
1992-2007
30.00%
25.00%
20.00%
15.00%
10.00%
5.00%
0.00%
1992
1994
1996
1998
Total Turnover
2000
2002
2004
Standard Turnover
2006
Table 2. Turnover across periods
Probit regression estimates of the likelihood of CEO turnover during the period from 1992 to 2007 to test
whether the probability of turnover is higher in the 2000 to 2007 period. Total turnover is all CEO turnover
including turnover due to mergers and acquisitions and delistings from a major stock exchange. Standard
(internal) turnover excludes turnover due to mergers and acquisitions and delistings from a major stock
exchange. For total and standard turnover, turnover is measured in two ways: (1) and (2). (1) defines a turnover
occurrence if a new CEO is selected. (2) defines occurrences where the CEO dies in office as a non-turnover
event. The dependent variable equals one if the CEO turnovers and zero otherwise. ΔProb represents the change
in the probability associated with moving the indicator from 0 to 1. Robust standard errors to control for
heteroskedasticity are reported in parentheses. *** indicate significance at the 1% level.
Total Turnover
Variable
2000 or later
indicator variable
N
Pseudo R
(1)
(2)
(1)
(2)
ΔProb
(p-value)
ΔProb
(p-value)
ΔProb
(p-value)
ΔProb
(p-value)
0.01873***
(0.0071)
10,715
2
Standard (Internal) Turnover
0.0008
0.01800***
(0.0070)
0.0165**
(0.0065)
0.0158**
(0.0064)
10,715
10,272
10,272
0.0023
0.0008
0.0007
Table 3. CEO turnover
Number and percent of firms experiencing no turnover over a five-year period. Turnover is measured
using total turnover. Total turnover is all CEO turnover including turnover due to mergers and
acquisitions and delistings from a major stock exchange. Occurrences where the CEO dies in office is
defined as a non-turnover event.
Year
1992
Number of firms in the sample in 1992
460
Number of firms experiencing no turnover between 1992 and 1999
98
Percent of firms experiencing no turnover between 1992 and 1999
21.30%
Year
2000
Number of firms in the sample in 2000
703
Number of firms experiencing no turnover between 2000 and 2007
115
Percent of firms experiencing no turnover between 2000 and 2007
16.35%
Table 4. Probit regressions of the probability of internal CEO turnover on performance
Probit regression estimates of the likelihood of internal CEO turnover during the period from 1992 to 2007. Internal turnover excludes turnover due to mergers and
acquisitions and delistings from a major stock exchange. Occurrences where the CEO dies in office are defined as non-turnover events. The dependent variable equals one if
the CEO turnovers and zero otherwise. ΔProb measures the change in the probability of CEO turnover per unit change in the relevant explanatory variables. For indicator
variables, the coefficient represents the change in the probability associated with moving the indicator from 0 to 1. CEO age dummy equals 1 if lagged CEO age is greater
than or equal to 60 and zero otherwise. Robust standard errors to control for heteroskedasticity are reported in parentheses. *, **, and *** indicate significance at the 10%,
5% and 1% levels, respectively.
Panel A
1992 - 2007
ΔProb
(s.e)
1992-1996
ΔProb
(s.e)
1997 – 2002
ΔProb
(s.e)
Return on S&P 500
-0.1188***
(0.0203)
0.1121***
(0.0406)
-0.1477***
(0.0311)
Industry return – return
on S&P500
-0.0772***
(0.0163)
0.0700*
(0.0396)
Industry-adjusted stock
return
-0.0641***
(0.0106)
CEO age dummy
Variable
Number of obs
Pseudo R
2
2003 - 2007
ΔProb
(s.e.)
1992-1999
ΔProb
(s.e.)
2000 – 2007
ΔProb
(s.e.)
-0.3533***
(0.0722)
0.0891**
(0.0366)
-0.1823***
(0.0286)
-0.0963***
(0.0252)
-0.0463
(0.0385)
0.0071
(0.0244)
-0.1426***
(0.0242)
-0.0204
(0.0200)
-0.0818***
(0.0157)
-0.0818***
(0.0198)
-0.0387***
(0.0147)
-0.0917***
(0.0148)
0.1369***
(0.0081)
0.1255***
(0.0132)
0.1679***
(0.0139)
0.1112***
(0.0143)
0.1332***
(0.0106)
0.1415***
(0.0121)
9,982
2,947
3,903
3,132
4,937
5,045
0.0588
0.0600
0.0712
0.0591
0.0583
0.0712
Panel B
1992 - 2007
ΔProb
(s.e)
Variable
1992-1996
ΔProb
(s.e)
1997 – 2002
ΔProb
(s.e)
2003 - 2007
ΔProb
(s.e.)
1992-1999
ΔProb
(s.e.)
2000 – 2007
ΔProb
(s.e.)
Return on S&P 500
-0.1396***
(0.0215)
0.0454
(0.0499)
-0.1537***
(0.0325)
-0.3713***
(0.0745)
0.0160
(0.0429)
-0.1891***
(0.0299)
Industry return – return
on S&P500
-0.0820***
(0.0173)
0.0495
(0.0455)
-0.0948***
(0.0264)
-0.0426
(0.0405)
0.0082
(0.0267)
-0.1473***
(0.0253)
Industry-adjusted stock
return
-0.0586***
(0.0113)
-0.0157
(0.0230)
-0.0709***
(0.0166)
-0.0828***
(0.0207)
-0.0303*
(0.0162)
-0.0881***
(0.0157)
Change in ROA
-0.1594**
(0.0710)
-0.0974
(0.1399)
-0.3413***
(0.1034)
0.0287
(0.1335)
-0.2651**
(0.1044)
-0.0413
(0.0954)
CEO age dummy
0.1422***
(0.0081)
0.1326***
(0.0144)
0.1732***
(0.0142)
0.1137***
(0.0147)
0.1392***
(0.0113)
0.1452***
(0.0124)
9,375
2,624
3,714
3,037
4,523
4,852
0.0612
0.0537
0.0770
0.0590
0.0587
0.0714
Number of obs
Pseudo R
2
Table 5. Probit regressions of the probability of internal CEO turnover on performance and lagged performance
Probit regression estimates of the likelihood of internal CEO turnover during the period from 1992 to 2007. Internal turnover excludes turnover due to mergers and
acquisitions and delistings from a major stock exchange. Occurrences where the CEO dies in office are defined as non-turnover events. The dependent variable equals
one if the CEO turnovers and zero otherwise. ΔProb measures the change in the probability of CEO turnover per unit change in the relevant explanatory variables. For
indicator variables, the coefficient represents the change in the probability associated with moving the indicator from 0 to 1. CEO age dummy equals 1 if lagged CEO age
is greater than or equal to 60 and zero otherwise. Robust standard errors to control for heteroskedasticity are reported in parentheses. *, **, and *** indicate significance
at the 10%, 5% and 1% levels, respectively.
Variable
Return on S&P 500
Lagged return on S&P 500
Industry-return-return on
S&P500
Lagged industry returnreturn on S&P 500
Industry-adjusted return
Lagged industry-adjusted
stock return
CEO age dummy
Number of obs
Pseudo R2
1992-2007
ΔProb
(s.e.)
-0.2038***
(0.0278)
0.1103***
(0.0235)
-0.0500***
(0.0172)
-0.0630***
(0.0159)
-0.0646***
(0.0104)
-0.0618***
(0.0102)
0.1366***
(0.0081)
9,850
0.0686
1992-1996
ΔProb
(s.e.)
0.0229
(0.0664)
0.0437
(0.0449)
0.0853**
(0.0401)
-0.0683*
(0.0373)
-0.0202
(0.0201)
-0.0698***
(0.0210)
0.1252***
(0.0133)
2,886
0.0692
1997 – 2002
ΔProb
(s.e.)
-0.3204***
(0.0495)
0.2609***
(0.0530)
-0.0687***
(0.0248)
-0.0269
(0.0247)
-0.0822***
(0.0153)
-0.0597***
(0.0149)
0.1663***
(0.0139)
3,861
0.0866
2003-2007
ΔProb
(s.e.)
-0.3202***
(0.1144)
0.1221
(0.0750)
-0.0321
(0.0396)
-0.0616*
(0.0371)
-0.0802***
(0.0199)
-0.0593***
(0.0193)
0.1125***
(0.0144)
3,103
0.0652
1992-1999
ΔProb
(s.e.)
-0.0371
(0.0501)
0.1137***
(0.0363)
0.0347
(0.0244)
-0.1029***
(0.0256)
-0.0319**
(0.0144)
-0.0660***
(0.0155)
0.1331***
(0.0107)
4,859
0.0697
2000 – 2007
ΔProb
(s.e.)
-0.2484***
(0.0359)
0.1584***
(0.0332)
-0.1079***
(0.0246)
-0.0471**
(0.0207)
-0.0983**
(0.0147)
-0.0601***
(0.0134)
0.1395***
(0.0121)
4,991
0.0838
Table6. Probit regressions of the probability of internal CEO turnover on performance
Probit regression estimates of the likelihood of internal CEO turnover during the period from 1992 to 2007. Internal turnover excludes turnover due to mergers and
acquisitions and delistings from a major stock exchange. Occurrences where the CEO dies in office are defined as non-turnover events. The dependent variable equals
one if the CEO turnovers and zero otherwise. ΔProb measures the change in the probability of CEO turnover per unit change in the relevant explanatory variables. For
indicator variables, the coefficient represents the change in the probability associated with moving the indicator from 0 to 1. CEO age dummy equals 1 if lagged CEO age
is greater than or equal to 60 and zero otherwise. Robust standard errors to control for heteroskedasticity are reported in parentheses. *, **, and *** indicate significance
at the 10%, 5% and 1% levels, respectively.
Firms in the S&P 500
1992 - 2007
ΔProb
(s.e)
Variable
1992-1999
ΔProb
(s.e)
Firms not in the S&P 500
2000 – 2007
ΔProb
(s.e)
1992 - 2007
ΔProb
(s.e.)
1992-1999
ΔProb
(s.e.)
2000 – 2007
ΔProb
(s.e.)
Return on S&P 500
-0.2328***
(0.0364)
-0.0486
(0.0644)
-0.3055***
(0.0470)
-0.1602**
(0.0429)
-0.0067
(0.0791)
-0.1732
(0.0549)
Lagged return on S&P 500
0.1347***
(0.0303)
0.0849*
(0.0478)
0.2338***
(0.0425)
0.0656*
(0.0372)
0.1298**
(0.0548)
0.0555
(0.0533)
Industry return – return on
S&P500
-0.0625***
(0.0221)
0.0298
(0.0314)
-0.1359***
(0.0309)
-0.0314
(0.0276)
0.0424
(0.0385)
-0.0838**
(0.0404)
Lagged industry return –
return on S&P500
-0.0579***
(0.0209)
-0.0881***
(0.0338)
-0.0534**
(0.0273)
-0.0672***
(0.0244)
-0.1034***
(0.0392)
-0.0430
(0.0319)
Industry-adjusted stock
return
-0.0484***
(0.0149)
0.0028
(0.0195)
-0.1170***
(0.0212)
-0.0812**
(0.0146)
-0.0797**
(0.0212)
-0.0824***
(0.0198)
Lagged industry-adjusted
stock return
-0.0559***
(0.0147)
-0.0430**
(0.0215)
-0.0714***
(0.0198)
-0.0696***
(0.0141)
-0.0906***
(0.0224)
-0.0506***
(0.0179)
CEO age dummy
0.1625***
(0.0108)
0.1560***
(0.0141)
0.1690***
(0.0163)
0.0967***
(0.0120)
0.0974***
(0.0160)
0.0951***
(0.0178)
6,015
2,954
3,061
3,835
1,905
1,930
0.1104
0.0574
0.0772
0.0532
Number of obs
Pseudo R
2
0.0809
0.0760
Table 7. Probit regressions of internal CEO turnover for Fortune 500 firms on performance and
governance
Probit regression estimates of the likelihood of internal CEO turnover for Fortune 500 firms during the period 1992 to 2007.
Internal turnover excludes turnover due to mergers and acquisitions and delistings from a major stock exchange.
Occurrences where the CEO dies in office are defined as non-turnover events. The dependent variable equals one if the
CEO turnovers and zero otherwise. ΔProb measures the change in the probability of CEO turnover per unit change in the
relevant explanatory variables. For indicator variables, the coefficient represents the change in the probability associated
with moving the indicator from 0 to 1. Models are estimated with robust standard errors to control for heteroskedasticity.
CEO age dummy equals 1 if lagged CEO age is greater than or equal to 60 and zero otherwise. *, **, and *** indicate
significance at the 10%, 5% and 1% levels, respectively. Robust standard errors to control for heteroskedasticity are
reported in parentheses.
Variable
Return on S&P 500
Industry return – return
on S&P500
Industry-adjusted stock
return
Lagged return on S&P
500
Lagged industry return –
return on S&P500
Lagged industry-adjusted
stock return
G index
CEO age dummy
High G Index dummy
High G Index dummy
x(Return on S&P 500)
x(Industry return – return
on S&P500)
x(Industry-adjusted stock
return)
x(Lagged return on S&P
500)
x(Lagged industry return
– return on S&P500)
x(Lagged industryadjusted stock return)
x(G index)
x(CEO age dummy)
Number of obs.
Pseudo R2
Full Sample
ΔProb
(s.e.)
-0.2146***
(0.0315)
-0.0485**
(0.0196)
-0.0683***
(0.0119)
0.1314***
(0.0267)
-0.0656***
(0.0180)
-0.0529***
(0.0117)
0.0029*
(0.0016)
0.1358***
(0.0093)
0.0906
(0.1579)
0.1057
(0.0771)
0.0321
(0.0468)
0.0429
(0.0308)
-0.0915
(0.0636)
0.0153
(0.0468)
-0.0607*
(0.0326)
-0.0066
(0.0086)
0.0263
(0.0195)
9,213
0.0722
1992 – 1999
ΔProb
(s.e.)
-0.0499
(0.0563)
0.0346
(0.0275)
-0.0401**
(0.0161)
0.1316**
(0.0418)
-0.1077***
(0.0161)
-0.0632***
(0.0179)
0.0018
(0.0021)
0.1254***
(0.0120)
0.1233
(0.2793)
0.0207
(0.1412)
0.0413
(0.0684)
0.0660
(0.0454)
-0.0652
(0.0959)
0.0063
(0.0699)
-0.0170
(0.0517)
-0.0083
(0.0135)
0.0549**
(0.0317)
4,557
0.0728
2000-2007
ΔProb
(s.e.)
-0.2621***
(0.0408)
-0.1071***
(0.0281)
-0.0934***
(0.0171)
0.1803***
(0.0372)
-0.0492**
(0.0232)
-0.0457***
(0.0151)
0.0041
(0.003)
0.1455***
(0.0142)
0.0189
(0.1643)
0.1273
(0.0985)
0.0161
(0.0674)
0.0252
(0.0430)
-0.1158
(0.0906)
0.0087
(0.0624)
-0.0956**
(0.0425)
-0.0017
(0.0114)
0.0056
(0.0248)
4,656
0.0885
Table 8. Block ownership and Board of Directors
Block ownership and board independence for sample firms during the period 1992 to 2007. Institutional
ownership data are from 13-fililings. A block is defined as an institutional owner with greater than a
five percent ownership stake. Independent director data are taken from IRRC Directors database on
WRDS and proxy filings.
Block ownership
Year
Mean
Median
Blockholder
Present
Percent of firms
Percent of
independent directors
Mean
Median
Not an
independent Board
Percent of firms
1992
8.12%
5.02%
50.12%
1993
8.12
5.51
52.88
1994
8.56
5.25
52.82
1995
9.05
5.80
54.71
1996
9.42
6.08
56.97
61.5
63.64
28.22%
1997
10.08
6.37
57.75
63.38
66.67
25.42
1998
11.01
7.55
75.12
63.94
66.67
22.42
1999
11.48
8.35
62.74
65.09
66.67
21.57
2000
12.53
9.54
63.41
66.15
70.00
20.73
2001
12.55
10.54
66.29
67.39
70.00
18.99
2002
13.72
11.53
72.93
69.63
72.73
15.18
2003
13.32
11.33
73.00
71.45
75.00
12.06
2004
16.42
14.36
80.12
72.82
75.00
9.42
2005
16.54
14.83
79.23
73.90
77.78
7.85
2006
17.10
14.74
81.00
74.32
77.78
8.14
2007
17.92
15.38
78.68
80.45
81.82
1.42
Table 9. Probit regressions of internal CEO turnover for Fortune 500 firms on performance and block
ownership
Probit regression estimates of the likelihood of internal CEO turnover for Fortune 500 firms during the period 1992 to 2007.
Internal turnover excludes turnover due to mergers and acquisitions and delistings from a major stock exchange. Occurrences
where the CEO dies in office are defined as non-turnover events. The dependent variable equals one if the CEO turnovers
and zero otherwise. ΔProb measures the change in the probability of CEO turnover per unit change in the relevant
explanatory variables. For indicator variables, the coefficient represents the change in the probability associated with moving
the indicator from 0 to 1. Models are estimated with robust standard errors to control for heteroskedasticity. CEO age
dummy equals 1 if lagged CEO age is greater than or equal to 60 and zero otherwise. *, **, and *** indicate significance at
the 10%, 5% and 1% levels, respectively. Robust standard errors to control for heteroskedasticity are reported in
parentheses.
Variable
Full Sample
1992 – 1999
2000-2007
ΔProb
(s.e.)
ΔProb
(s.e.)
ΔProb
(s.e.)
Return on S&P 500
-0.2183***
(0.0394)
-0.0389
(0.6573)
-0.2672***
(0.0523)
Industry return –
return on S&P500
-0.0593**
(0.0244)
0.0288
(0.0327)
-0.1410***
(0.0359)
Industry-adjusted
stock return
-0.0450***
(0.0147)
-0.0522***
(0.0195)
-0.0865***
(0.0231)
Lagged return on S&P
500
0.1018***
(0.0329)
0.1436***
(0.0486)
0.1358***
(0.0472)
Lagged industry return
– return on S&P500
-0.0851***
(0.0226)
-0.1162***
(0.0341)
-0.0597**
(0.0304)
Lagged industryadjusted stock return
-0.0450***
(0.0150)
-0.0650***
(0.0213)
-0.0297
(0.0197)
Percent of total block
ownership
0.0116
(0.0300)
0.0847
(0.0903)
-0.0303
(0.0355)
CEO age dummy
0.1370***
(0.0081)
0.1339***
(0.0107)
0.1395***
(0.0121)
Percent of total block
ownership
x(Return on S&P 500)
0.0998
(0.2212)
-0.0270
(0.4471)
0.1133
(0.2844)
x(Industry return –
return on S&P500)
0.0792
(0.1311)
0.0443
(0.2080)
0.2303
(0.1769)
x(Industry-adjusted
stock return)
-0.0057
(0.0759)
0.1845
(0.1135)
-0.0721
(0.1072)
x(Lagged return on
S&P 500)
0.0998
(0.2212)
-0.2880
(0.3154)
0.1365
(0.2590)
x(Lagged industry
return – return on
S&P500)
0.1616
(0.1211)
0.1224
(0.2328)
0.0753
(0.1515)
x(Lagged industryadjusted stock return)
-0.1255
(0.0771)
-0.0055
(0.1377)
-0.2016**
(0.0958)
Number of obs.
9,848
4,857
4,991
0.0698
0.0711
Pseudo R
2
0.0859
Table 10. Probit regressions of internal CEO turnover for Fortune 500 firms on performance and
independent directors
Probit regression estimates of the likelihood of internal CEO turnover for Fortune 500 firms during the period 1996 to 2007.
Internal turnover excludes turnover due to mergers and acquisitions and delistings from a major stock exchange. Occurrences
where the CEO dies in office are defined as non-turnover events. The dependent variable equals one if the CEO turnovers
and zero otherwise. Independent director data are taken from IRRC Directors database on WRDS. No independent board
equals one if a majority of directors are not independent. ΔProb measures the change in the probability of CEO turnover per
unit change in the relevant explanatory variables. For indicator variables, the coefficient represents the change in the
probability associated with moving the indicator from 0 to 1. Models are estimated with robust standard errors to control for
heteroskedasticity. CEO age dummy equals 1 if lagged CEO age is greater than or equal to 60 and zero otherwise. *, **, and
*** indicate significance at the 10%, 5% and 1% levels, respectively. Robust standard errors are in parentheses.
Variable
1996 – 2007
1996-2007
ΔProb
(s.e.)
ΔProb
(s.e.)
Return on S&P 500
-0.2638***
(0.0311)
-0.2764***
(0.0336)
Industry return – return on S&P500
-0.0716***
(0.0189)
-0.0647*
(0.0206)
Industry-adjusted stock return
-0.0750***
(0.0116)
-0.0913***
(0.0130)
Lagged return on S&P 500
0.1356***
(0.0272)
0.1542***
(0.0293)
Lagged industry return – return on
S&P500
-0.0498***
(0.0172)
-0.0623***
(0.0189)
Lagged industry-adjusted stock return
-0.0600***
(0.0114)
-0.0724***
(0.0127)
CEO age dummy
0.1418***
(0.0097)
0.1418***
(0.0097)
No independent board indicator
variable
-0.0120
(0.0095)
-0.0147
(0.0125)
x(Return on S&P 500)
—
0.0572
(0.0871)
x(Industry return – return on S&P500)
—
-0.0442
(0.0485)
x(Industry-adjusted stock return)
—
0.0812***
(0.0295)
x(Lagged return on S&P 500)
—
-0.0877
(0.0778)
x(Lagged industry return – return on
S&P500)
—
0.0562
(0.0439)
x(Lagged industry-adjusted stock
return)
—
0.0506*
(0.0281)
No independent board indicator
variable
Number of obs.
Pseudo R
2
7,374
0.0777
7,374
0.0807
Table 11. Probit regressions of internal CEO turnover for Fortune 500 firms on performance and SOX
legislation
Probit regression estimates of the likelihood of internal CEO turnover for Fortune 500 firms during the period 1992 to 2005.
Internal turnover excludes turnover due to mergers and acquisitions and delistings from a major stock exchange. Occurrences
where the CEO is promoted to another CEO position, remains CEO of the delisting firm, is selected for a government
position, dies in office, or leaves office due to illness are defined as non-turnover events. The dependent variable equals one
if the CEO turnovers and zero otherwise. The SOX dummy equals one for years after 2002. ΔProb measures the change in
the probability of CEO turnover per unit change in the relevant explanatory variables. For indicator variables, the coefficient
represents the change in the probability associated with moving the indicator from 0 to 1. Models are estimated with robust
standard errors to control for heteroskedasticity. CEO age dummy equals 1 if lagged CEO age is greater than or equal to 60
and zero otherwise. *, **, and *** indicate significance at the 10%, 5% and 1% levels, respectively. p-values are in
parentheses.
Variable
Return on S&P 500
Full Sample
Full Sample
2000 - 2007
ΔProb
(s.e.)
ΔProb
(s.e.)
ΔProb
(s.e.)
-0.0917***
(0.234)
-0.1899***
(0.0335)
-0.4782***
(0.1944)
—
0.0801***
(0.0301)
0.2833***
(0.0750)
Industry return – return on
S&P500
-0.0585***
(0.0200)
-0.0474**
(0.0200)
-0.1386***
(0.0320)
Lagged industry return –
return on S&P500
—
-0.0747***
(0.0186)
-0.0245
(0.0286)
Industry-adjusted stock
return
-0.0581***
(0.0122)
-0.0586**
(0.0120)
-0.1090***
(0.0200)
Lagged industry-adjusted
stock return
—
-0.0620***
(0.0119)
-0.0557***
(0.0173)
CEO age dummy
0.1354***
(0.0081)
0.1362***
(0.0081)
0.1395***
(0.0121)
SOX dummy
0.0295***
(0.0109)
0.0174
(0.0181)
0.0448
(0.0327)
Lagged return on S&P 500
SOX dummy
x(Return on S&P 500)
-0.2834***
(0.0820)
-0.1520
(0.1275)
0.1308
(0.2315)
0.0515
(0.0862)
-0.1496
(0.1113)
0.0126
(0.0471)
0.1033*
(0.0539)
0.0069
(0.0440)
-0.0442
(0.0495)
-0.0266
(0.0248)
0.0224
(0.0298)
-0.0018
(0.0240)
-0.0092
(0.0273)
9,982
9,850
4,991
0.0606
0.0698
0.0866
x(Lagged return on S&P
500)
x(Industry return – return
on S&P500)
0.0080
(0.0461)
x(Lagged industry return –
return on S&P500)
x(Industry-adjusted stock
return)
-0.0291
(0.0249)
x(Lagged industryadjusted stock return)
Number of obs.
Pseudo R
2
Table 12. Multinominal logit regression estimates of the likelihood of no CEO turnover, unforced CEO
turnover and forced CEO turnover for Fortune 500 firms.
Multinominal logit regression estimates of the likelihood of no CEO turnover, non-forced CEO turnover and forced CEO
turnover for Fortune 500 firms during the period 1992 to 2007. ΔProb measures the change in the probability of the particular
choice per unit change in the relevant explanatory variables. For indicator variables, the coefficient represents the change in
the probability associated with moving the indicator from 0 to 1. Models are estimated with robust standard errors to control
for heteroskedasticity. CEO age dummy equals 1 if lagged CEO age is greater than or equal to 60 and zero otherwise. *, **,
and *** indicate significance at the 10%, 5% and 1% levels, respectively. Robust standard errors are in parentheses.
Variable
Unforced CEO turnover
Forced CEO turnover
ΔProb
(s.e.)
ΔProb
(s.e.)
Return on S&P 500
-0.1402***
(0.0237)
-0.0341***
(0.0084)
Lagged return on S&P 500
0.0761***
(0.0204)
0.0182***
(0.0069)
Industry return – return on
S&P500
-0.0202
(0.0144)
-0.0229***
(0.0052)
Lagged industry return – return on
S&P500
-0.0454***
(0.0134)
-0.0037
(0.0048)
Industry-adjusted stock return
-0.0285***
(0.0086)
-0.0288***
(0.0033)
Lagged industry-adjusted stock
return
-0.0399***
(0.0088)
-0.0130***
(0.0037)
CEO age dummy
0.1517***
(0.0079)
-0.0087***
(0.0018)
Pseudo R2 = 0.0878
Table 13. Probit regressions of the probability of external CEO turnover on performance
Probit regression estimates of the likelihood of external CEO turnover for Fortune 500 firms during the period 1992 to 2005. The dependent variable equals one if the
CEO turnovers and zero otherwise. ΔProb measures the change in the probability of CEO turnover per unit change in the relevant explanatory variables. For indicator
variables, the coefficient represents the change in the probability associated with moving the indicator from 0 to 1. Models are estimated with robust standard errors to
control for heteroskedasticity. CEO age dummy equals 1 if lagged CEO age is greater than or equal to 60 and zero otherwise. *, **, and *** indicate significance at the
10%, 5% and 1% levels, respectively. Robust standard errors to control for heteroskedasticity are reported in parentheses.
Variable
Return on S&P 500
Lagged return on S&P
500
Industry return – return
on S&P500
Lagged industry return –
return on S&P500
Industry-adjusted stock
return
Lagged industry-adjusted
stock return
CEO age dummy
Number of obs
Pseudo R
2
1992-2007
ΔProb
(s.e.)
1992-1999
ΔProb
(s.e.)
-0.0007
(0.0048)
0.0177**
(0.0073)
—
-0.0010
(0.0045)
—
0.0047**
(0.022)
—
—
0.0027
(0.0066)
—
0.0037
(0.0030)
—
2000 – 2007
ΔProb
(s.e.)
1992-1999
ΔProb
(s.e.)
2000 – 2007
ΔProb
(s.e.)
-0.0095
(0.0059)
0.0160
(0.0099)
-0.0105
(0.0067)
0.0125**
(0.0052)
0.0162**
(0.0075)
0.0168***
(0.0062)
-0.0072
(0.0058)
0.0015
(0.0044)
0.0051
(0.0052)
-0.0052
(0.0053)
—
-0.0068
(0.0029)
-0.0034
(0.0042)
-0.0094**
(0.0038)
0.0044*
(0.0026)
0.0042
(0.0021)
0.0034
(0.0027)
0.0033
(0.0024)
—
-0.0034
(0.0025)
-0.0023
(0.0033)
-0.0041
(0.0027)
0.0057**
(0.0029)
-0.0026
(0.0058)
—
1992-2007
ΔProb
(s.e.)
0.0027
(0.0081)
-0.000
(0.0020)
0.066
(0.0032)
0.0025
(0.0018)
0.0001
(0.0018)
8,842
4,400
4,442
8,719
4,325
0.0135
0.0268
0.0274
0.0250
0.0458
4,391
0.0449
Appendix Table A1. CEO Turnover
CEO turnovers in publicly traded Fortune 500 companies between 1992 and year-end 2007. Total turnover is all
CEO turnover including turnover due to mergers and acquisitions and delistings from a major stock exchange.
Standard (internal) turnover excludes turnover due to mergers and acquisitions and delistings from a major stock
exchange. For total and standard turnover, turnover is measured in two ways: (1) and (2). (1) defines a turnover
occurrence if a new CEO is selected. (2) defines occurrences where the CEO dies as a non-turnover event. Data are
from annual Fortune 500 lists, 10-K filings, proxy statements, and the Wall Street Journal. Year denotes the fiscal
year-end for the sales data on which Fortune ranks firms. (i.e., 1992 corresponds to the 1993 April/May Fortune
list.)
Panel A: Firms in the Fortune 500
Total Turnover
(1)
Year
Number
of firms
N
1992
443
53
1993
Standard (Internal) Turnover
(2)
%
(1)
(2)
N
%
N
%
N
%
11.96%
53
11.96%
53
11.96%
53
11.96%
458
52
11.35
52
11.35
44
9.61
44
9.61
6.60
31
6.60
470
31
22
4.68
22
4.68
1995
480
72
15.00
72
15.00
57
11.88
57
11.88
1996
473
54
10.99
52
10.99
41
8.67
39
8.25
1997
485
75
15.26
74
15.26
51
10.52
50
10.31
1998
484
88
18.97
88
18.97
63
13.02
63
13.02
1999
489
98
20.04
98
20.04
72
14.72
72
14.72
502
134
26.49
133
26.49
97
19.32
96
19.12
490
67
13.67
67
13.67
48
9.80
48
9.80
20.12
97
20.12
78
16.18
1994
2000
2001
2002
482
99
80
16.6%
2003
469
22
4.69
22
4.69
14
2.99
14
2.99
2004
475
72
14.95
71
14.95
62
13.05
61
12.84
2005
485
85
17.53
85
17.53
65
13.40
65
13.40
2006
478
74
15.27
73
15.27
57
11.92
56
11.72
2007
468
72
14.96
70
14.96
55
11.75
53
11.32
Total
7,631
1,148
15.04%
1,138
14.91%
881
11.55%
871
11.41%
1992-1996
2,324
262
11.27%
260
11.19%
217
9.34
215
9.25
1997-2002
2,932
561
19.13%
557
19.00%
411
14.02
407
13.88
2003-2007
2,375
325
13.68%
321
13.52%
253
10.65
249
10.48
1992-1999
3,783
523
13.83%
520
13.75%
403
10.66
400
10.58%
2000-2007
3,849
625
16.24
618
16.06
478
12.42
471
12.24
Panel B: Firms not in the Fortune 500
Total Turnover
(1)
Standard (Internal) Turnover
(2)
(1)
(2)
Year
Number
of firms
N
%
N
%
N
%
N
%
1992
17
4
23.53%
4
23.53%
1
5.88%
1
5.88%
1993
28
5
17.86
5
17.86
5
17.86
5
17.86
1994
257
37
14.40
35
13.6
34
13.23
32
12.45
1995
261
41
15.71
41
15.71
35
13.41
35
13.41
1996
265
49
18.49
48
18.11
34
12.83
33
12.48
1997
250
37
14.80
36
14.40
17
6.80
16
6.40
1998
237
41
17.30
41
17.30
24
10.13
24
10.13
1999
227
55
24.23
55
24.23
29
12.78
29
12.78
2000
201
51
25.37
50
24.88
37
18.41
36
17.91
2001
192
29
15.10
29
15.10
15
7.81
15
7.81
2002
194
34
17.53
34
17.53
22
11.34
22
11.34
2003
194
24
12.37
24
12.37
20
10.31
20
10.31
2004
194
22
11.34
21
10.82
16
8.25
15
7.73
2005
194
42
21.65
41
21.13
29
14.95
28
14.43
2006
185
38
20.54
38
20.54
26
14.05
26
14.05
2007
184
38
20.65
37
20.11
29
15.76
28
15.22
Total
3,080
547
17.76%
539
17.50%
373
12.11%
365
11.85%
1992-1996
828
136
16.43
133
16.06
109
13.16
106
12.80
1997-2002
1,301
247
18.99
245
18.83
144
11.07
2003-2007
951
164
17.25
161
16.93
120
12.62
142
117
10.91
12.30
1992-1999
1,542
269
17.44
265
17.19
179
11.61
175
11.35
2000-2007
1,538
278
18.08
274
17.82
194
12.61
190
12.35