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Managerial Entrenchment and Earnings Smoothing
Francois Brochet fbrochet@stern.nyu.edu
Zhan Gao
zgao@stern.nyu.edu
May 2004 Key words: Earnings smoothing, Managerial Entrenchment, Job Security. Data Availability: Data are available from the sources indicated in the text. We thank April Klein, Joshua Ronen and Paul Zarowin for their comments. Usual disclaimers apply.
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Managerial Entrenchment and Earnings Smoothing
Abstract This paper investigates the association between earnings smoothing and managerial entrenchment. We primarily test the predictions of Fudenberg and Tirole (1995), who develop a model where managers smooth earnings because of job security concerns. Our findings support their predictions. Using the correlation between the change in accruals and cash flows, we find that firms whose managers are more entrenched exhibit less smooth earnings, ceteris paribus. Extensions provide additional insight into the role of discretionary accruals as well as investor clientele in the relation between smoothing and entrenchment.
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1. Introduction In this paper, we investigate the relation between earnings smoothing and
managerial entrenchment. Both concepts are extensively covered in the analytical and
empirical literature, in accounting as well as corporate finance. However, their
association is studied in an incomplete fashion: on one hand, researchers consider only
one side of earnings smoothing (the ‘opportunistic’ interpretation). On the other hand,
among the set of managerial entrenchment measures introduced by Berger et al. (1997),
some have a very ambiguous theoretical relationship to earnings smoothing. In a
framework that identifies how competing theories may explain univocal or equivocal
predictions, we analyze the relation between earnings smoothing measures and
managerial entrenchment proxies. Particularly, we test empirically the predictions of the
Fudenberg and Tirole (1995) model, which predicts that managers resort to earnings
smoothing in equilibrium if they are concerned about their job security, using managerial
entrenchment variables that relate specifically to job security. Ahmed et al. (2000) already
test this model, but using measures (for earnings smoothing and job security) that we
think do not correctly address the issue.
The methods to achieve earnings smoothing have been defined in different ways,
but the main idea is that it consists of manipulating reported earnings in order to make the
time-series stream of income appear less variable. Therefore, it involves upward and
downward manipulations, depending on whether managers consider the pre-smoothed
earnings relatively too low or too high. More importantly, researchers do not necessarily
agree upon the motives of smoothing. Ronen and Sadan (1981) consider it as a means for
managers to signal their private information about future earnings and provide investors
with more reliable current financial statements to forecast future cash flows. By contrast,
a radically yet prevalent view considers earnings smoothing as a subset of earnings
management, and as such an opportunistic behavior of managers at the expense of
shareholders and other claim holders of the firms (see, e.g., Leuz et al. (2003)). The main
focus of earnings smoothing research when attempting to explain why it may occur in
equilibrium has been managerial compensation. Healy (1985) shows that when managers
bonuses are capped and floored, managers smooth earnings to avoid being outside of the
interval where their compensation is increasing in earnings. In an indirectly related
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context, Agrawal and Knoeber (1996) or Rediker and Seth (1995) emphasize that prior
studies have failed to document a significant linkage between managerial ownership and
firm performance because of their focus on a single corporate governance variable.
Likewise, we argue that earnings smoothing needs to be related to a “bundle” of
corporate governance measures, that may be used as substitute devices. We build on past
research by using most variables identified by Berger et al. (1997) as the components of
managerial entrenchment. We do not make a unique prediction as to how managerial
entrenchment is associated with earnings smoothing, but attempt to identify categories
within the set of entrenchment variables that can measure directly what has been
documented in the analytical literature. Essentially, we believe that a number of
entrenchment variables correspond to the job security argument developed by Fudenberg
and Tirole (1995), who predict a positive association between concerns of dismissal or
shareholder intervention and earnings smoothing. We also consider a somewhat
competing theory (Dye (1988)), which predicts a positive relation between earnings
smoothing and managers’ horizon.
We use several earnings smoothing measures. Two of them are based on Myers
and Skinner (1999). Our analysis starts with examining managers’ smoothing behavior
around unsuccessful takeover attempts, as an exogenous shock to managerial
entrenchment (c.f. Berger et al. (1997)). An increase in smoothing post-shock earnings is
observed, consistent with the job security hypothesis. In the following regression
analyses, we further find that measures of earnings smoothing exhibit a significantly
negative association with entrenchment measures (high managerial stock ownership,
interlock situation), risk-taking incentives (stock option holdings) and short-term horizon
(CEO close to departure). The same evidence is obtained in a principal component factor
analysis, in which we construct a composite measure for managerial entrenchment.
However, both proxies are composed of variables which may reflect more the nature of
the underlying business of the firm than managerial use of accounting accruals to
influence the trend of reported earnings. To investigate further this point, we compute a
discretionary accrual measure and find that the results slightly differ from the previous
results. Namely, for both low and high levels of managerial ownership, managers smooth
earnings more when their stock holdings increase, consistent with the incentive alignment
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effect of stock ownership, under the common belief that investors prefer smooth earnings.
Contrarily, for the median level of ownership, the correlation becomes negative, as
predicted by job security argument. All results hold after controlling for industry and year
effects, as well as factors correlated with our earnings smoothing proxies.
This paper sheds light on the incomplete approach that past research has
undertaken when attempting to document explanations of earnings smoothing. This paper
is not aimed at discriminating between candidate theories. Rather, we point at the
importance of considering managerial incentives from a broader set of measures to avoid
documenting an association between earnings smoothing and an isolated managerial
entrenchment variable. We extend our analysis by controlling for investor clientele,
which may be of primary importance in this setting. Indeed, any earnings smoothing
theory depends on investors’ preferences. Ronen and Yaari (2002) distinguish two types
of shareholders: value maximizing owners (VMO) and price maximizing owners (PMO).
The former, because of their long-term horizon, have a preference for smoothed income
patterns that facilitate future cash flow predictions. The latter have a shorter-term horizon,
and will favor upward earnings manipulation in every state. Bushee (1998), using
institutional holdings data, classifies institutions into three categories: transient,
quasi-indexer and dedicated. The first category corresponds well to PMO, while the last
one can be considered VMO. Consistent with our predictions, the larger the stake of
transient (dedicated) investors in a firm-year, the less (more) managers smooth earnings.
Previous literature on earnings smoothing has provided several theoretical
explanations for why it may arise in equilibrium. Ronen and Sadan (1981) develop the
‘expectation conveyance’ hypothesis: managers, within the GAAP framework (which
excludes direct forecasts), use smoothing as a vehicle to convey their expectations.
Smoothing can be classificatory (assuming investors use ordinary income to form their
expectations) or inter-temporal (shifting income from or to future periods). The common
idea is that earnings have a permanent and a transitory component, and managers use
smoothing to prevent the latter from introducing noise into the perception by the market
of the permanent component. Opportunistic views of earnings smoothing have long
considered managerial compensation as the reason why managers resort to this technique.
Lambert (1984), in a traditional principal-agent with unobservable action framework,
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shows that optimal incentive scheme designed by rational investors for rational managers
induces earnings smoothing. As Lambert (1984), Dye (1988) shows that a risk-averse
manager who is precluded from borrowing and lending on the capital market has an
incentive to smooth his firm’s earnings, but refines the argument by demonstrating that
only managers with long-horizon motivations will smooth. Fudenberg and Tirole (1995)
depart from the managerial compensation argument by showing that managers who are
insensitive to monetary incentives (infinitely risk averse to income) but who enjoy a
private benefit from employment will smooth earnings to maximize their employment
period. Finally, an explanation of earnings smoothing widely accepted by empiricists who
try to document it as an opportunistic phenomenon is that managers want to lower the
claimholders’ perception of the variance of the underlying economic earnings of their
firm. This theory is central to Trueman and Titman’s (1988) paper, which additionally
shows that this smoothing has a positive impact on the firm’s market value.
Empirical research has built on this theory while introducing the idea of an
endogenous link between corporate governance and the quality of reported earnings.
Particularly, Leuz et al. (2003) show that earnings management (including smoothing)
decreases in investor protection, which reduces the incentives of insiders to conceal the
true economic performance of the firm. Leuz et al. (2003) use an international setting for
their study. Zarowin (1999) is one of the rare empirical papers testing and supporting the
private signaling argument: he finds that firms with greater smoothing have more
informative stock prices, i.e. which reflect a greater amount of the information about
future earnings and cash flows. The most relevant study to our topic is Ahmed et al.
(2000), who explicitly test the Fudenberg and Tirole (1995) model. DeFond and Park
(1997) already show that managers smooth income in consideration of both current and
future relative performance, but Ahmed et al. (2000) look more directly at job security
concerns of managers, proxied by the degree of competition in firms’ industries and
capital intensity, and find results consistent with the Fudenberg and Tirole (1995) model.
However, we think their job security concern proxies are very noisy and cannot properly
address the issue. Instead we use corporate governance measures from the Execucomp
database and carefully select variables that are directly related to managers’ entrenchment
and job security.
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The rest of the paper is organized as follows. Section 2 explains the hypothesis
development. Section 3 explains the sample selection process and addresses research
design issues. Section 4 reports the main results. Extension for the primary test is
presented in Section 5. We summarize the results in Section 6.
2. Hypothesis Development We categorize managerial entrenchment measures into three subgroups to
reconcile them with earnings smoothing theories and state predictions accordingly. We
attempt to motivate the tensions between several theories on the role of managerial
entrenchment when explaining its relation with earnings smoothing. Further detail is left
to the research design section.
The Fudenberg and Tirole (1995) model relates earnings smoothing to job
security concerns, predicting a positive association. Managerial entrenchment is directly
related to this concept, since an entrenched manager is by definition one that has little
concern about his being dismissed from the firm. Therefore, most managerial
entrenchment variables could be associated with a job security argument. Particularly,
interlock situations (when the CEO of company i sits on the board of company j and the
CEO of company j sits on the board of company i) should clearly be negatively related to
earnings smoothing according to the Fudenberg and Tirole (1995) argument. Other
variables lead to more ambiguous predictions, unless one is to prove that one theory
prevails. For example, CEO tenure is a measure of entrenchment (in other words, one can
argue that a new CEO has relatively low job security, as in Berger et al. (1997)), but a
CEO with more years of experience within the firm is more likely to be able to forecast
future earnings and smooth accordingly. This ability argument, though not our central
hypothesis, may weaken if not counterbalance the job security effect.
Managerial compensation, extensively studied in the context of earnings
management in the analytical and empirical literature, can be considered separately from
other managerial entrenchment measures. Managerial compensation is not modeled in the
Fudenberg and Tirole (1995) paper, which makes the strong assumption that managers
are infinitely risk averse, therefore do not respond to monetary incentives. This
assumption is not descriptive, so the association between managerial entrenchment and
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earnings smoothing cannot be analyzed solely under the Fudenberg and Tirole theoretical
framework. The main study documenting why and how smoothing arises because of
managers’ compensation is Healy (1985). Healy (1985) focuses on oil wildcatters whose
bonuses are an increasing function of reported earnings, but on a bounded interval, and
flat outside of the interval. Smoothing arises when actual earnings are outside of the
bonus interval. We, however, do not have access to bonus schemes of managers and
cannot document such smoothing behavior in our study. We choose to distinguish
compensation-related entrenchment measures to highlight their different implications
when trying to document smoothing. Following the seminal paper of Jensen and
Meckling (1976), managerial stock ownership has been considered as an incentive
alignment device, but can also be, at high levels, an entrenchment factor (Morck, Shleifer
and Vishny (1988)). A less equivocal entrenchment measure is CEO stock option
holdings. Stock options are aimed at inducing a higher risk taking investment behavior
from the manager, which results in more variable earnings. This particular example
illustrates the need to clarify which variables are considered when one attempts to link
managerial entrenchment (and – more generally – corporate governance) to earnings
smoothing (and – more generally – earnings management).
Finally, monitoring and investor clientele play a significant role with respect to
potential earnings smoothing. The monitoring argument uses the presence of
blockholders in the shareholding structure of firms as a deterrent to managerial
entrenchment (Shleifer and Vishny (1986)). It can however be taken to a broader
prospective, which is the investor clientele. Ronen and Yaari (2002) distinguish between
VMO and PMO. We consider blockholders as VMO, since investors with a large stake in
a firm’s outstanding shares are more likely to have a long-term investment horizon. This
particular subset of investors may not, however, be representative of the marginal
investor’s preferences. We extend this question by attempting to use Bushee’s (1998)
classification of institutions in order to refine our characterization of a firm’s
shareholding structure. Firms with high VM ownership are expected to smooth earnings
more than PMO driven firms.
Most of the points above lead us to a pragmatic approach: there are competing
views as to how earnings smoothing should relate to managerial entrenchment, so it is
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ultimately an empirical question. Therefore, we state the hypothesis in its alternative null
form:
H1: there is no significant association between managerial entrenchment and
earnings smoothing.
Managerial entrenchment measures lack time-series variation from year to year
for a given firm. Moreover, there is always a concern of endogenous determination of
those variables with earnings smoothing (Berger et al. (1997) or Gompers, Ishii and
Metrick (2003)) point out the same argument with respect to firm performance). Based on
Berger et al. (1997), we use unsuccessful takeover attempts as an exogenous shock to
managerial job security. Along the lines of the job security argument, takeover attempts
should act as a disciplinary threat from the corporate control market to managers of
undervalued firms who become concerned about their job security post-shock. In light of
this argument, we expect earnings smoothing to increase after an unsuccessful takeover
attempt. For consistency with the formulation of H1, we state our second hypothesis in its
alternative null form:
H2: managers experiencing an exogenous shock in their job security level do not
change their earnings smoothing behavior.
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3. Research Design Sample Selection
Our analysis uses data from COMPUSTAT Annual Industrial, EXECUCOMP, and
CDA Spectrum in the period from 1992 to 1999. Specially, financial data is retrieved
from COMPUSTAT Industrial; corporate governance measures are computed from
COMPUSTAT EXECOMP; institutional data is from CDA spectrum. Since the measures
for earnings smoothing need three-period-ahead data points, the sample period for
financial data is extended to 2002. Financial and utility companies (Two-digit SIC
between 47 and 60-67) are excluded because of government regulation. All observations
require non-missing variables in the sample period. Finally, all variables are censored at
the upper and lower 0.5% of their distributions. Our final sample consists of 2,497
firm-year observations for 1,435 firms.
Measures for Earnings Smoothing
Following Myers and Skinner (1999), Leuz, Nanda, and Wysocki (2000), and
Zarowin (2002), we use two proxies for earnings smoothing. The first one is �(�ACC,
�CFO), the correlation between changes in accruals and changes in cash flows from
operation (CFO). The second one is �NI/�CFO, the variance in net income relative to the
variance in CFO.
These two measures are conceptually appealing and computationally simple.
Though the nature of accrual accounting determines accruals normally to be negatively
correlated with cash flows (e.g. Dechow (1994)), the correlation becomes more negative
if managers intentionally adjust accrual accounts to mitigate income fluctuations, ceteris
paribus. Myers and Skinner (1999) verify the validity of this measure by showing that
firms attempting to sustain a series of consecutive earnings growth, which are
hypothesized to have strong incentives to smooth earnings, have more negative
correlation between changes in accruals and changes in CFO. The main criticism to this
measure is that it does not distinguish discretionary and non-discretionary accruals. In
accounting literature, the former has been long recognized more likely subject to
managers’ discretion, while the latter is mainly driven by a firm’s economic fundamentals,
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such as revenue generating process and technology.
The second measure, the volatility ratio of net income and CFO, emphasizes the
impact of earnings smoothing on volatility of CFO. Ceteris paribus, the lower the
volatility of net income relative to CFO, the more earnings smoothing managers may
engage in. The measure is subject to the same drawback as the first one.
Annual net income and CFO are COMPUSTAT#18 and #308, respectively.
Accruals are defined as the difference between net income and CFO. Ronen and Sadan
(1981) argue that managers smooth earnings in order to smooth their consumption. The
direct implication from their argument is that smoothed earnings reflect managers’ belief
about firm’s future performance. To capture the notion of belief on future, we use
three-year-ahead forward-looking data to compute the measures. For example, to
examine the effect of managerial entrenchment level in 1994 on manager’s earnings
smoothing behavior, �(�ACC, �CFO) uses changes in accruals and in CFO for
1995-1997. The longer period is not feasible given data constraints both in
EXECUCOMP (starting from 1992) and in COMPUSTAT Annual Industrial (Cash flow
data starts from 1987). The same method applies to �NI/�CFO.
Measures of Explanatory Variables
We include various measures to proxy for level of managerial entrenchment, built
on corporate governance literature.
Managerial compensation reflects CEOs’ entrenchment level. Following the
argument in Berger et al. (97), high level of fixed compensation is an indicator of
entrenched CEOs because un-entrenched CEOs may not be able to negotiate good
compensation for them. Fixed compensation is proxied by the sum of salary and bonus.
Excess fixed compensation is then defined as the difference between a specific CEO’s
fixed compensation and average of the industry where the firm belongs to. According to
the job security hypothesis, higher excess fixed compensation have negative coefficient
in the regression, implying entrenched managers engage in less earnings smoothing.
CEOs’ performance-based compensation is measured by stock option holdings,
the same as Berger et al. (1997). A CEO is regarded as entrenched if his compensation is
not sensitive to performance. Job security argument then predicts that positive correlation
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between stock option holdings and earning smoothing level will be observed. We
measure CEO stock option holdings as the percentage of exercisable options in common
shares.
Managerial ownership reflects managerial entrenchment since high managerial
ownership shields managers against other corporate governance. However, extra
complexity occurs because of nonlinearity between managerial ownership and
entrenchment. Morck et al. (1988) argue that low and high levels of managerial
ownership mean low agency costs because a low levels of managerial ownership helps
align interests of shareholders and managers, while managers with very high stock share
some characteristics of investors. Both situations can result in more smoothed earnings
under the common belief that investors prefer more stable earnings. Impact of managerial
entrenchment is most prominent for managers with median level of stock holdings.
Therefore, job security hypothesis predicts a positive coefficient for level of stock
holdings shareholdings, based on the standard argument. We adopt the measure in Morck
et al. (1988) and McConnell and Servaes (1990) to incorporate the nonlinearity issue.
Specifically,
Ceost_1 = managerial stock holding , if managerial stock holding <5%
5%, otherwise
0, if managerial stock holding < 5%
Ceost_2 = managerial stock holding minus 5%, if 5% ≤ stock holding ≤ 25%
20%, if managerial stock holding ≥ 25%
Ceost_3 = 0, if managerial stock holding < 25%,
managerial stock holding minus 25%, if managerial stock holding ≥ 25%
where managerial stock holding is percentage of common equity over a firm’s
outstanding shares. Job security hypothesis has no prediction on low and median levels of
managerial ownership, while predicting high level of managerial ownership to be
associated with low level of earnings smoothing.
The absence of effective monitoring mechanism is another characteristic of
increased managerial entrenchment. Thus, several measures related to firms’ internal
monitoring mechanism are included. The annual average of institutional holders of at
least 5 percent of common stock is added, motivated by the argument that large
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stockholders act as an important discipline power and keep CEOs from being entrenched.
Fewer large blockholders are predicted to result in less earnings smoothing. This measure
tends to bias downward since it only includes institutional investors.
If a CEO involves in a relationship requiring disclosure in the “Compensation
Committee Interlocks and Insider participation” section of the proxy, he may have more
influence on board of directors and therefore more entrenched. According to job security
hypothesis, an indicator of such interlock relation should have a positive coefficient in the
regression.
A CEO’s control over firm increases as his tenure lengthens. We include CEO
tenure for this concern. Tenure is measured as years of a CEO in office. The natural log
of tenure is used in analysis, based on the same concern as Berger et al. (1997) that CEO
power over corporate governance cumulates over time at a decreasing rate. We expect to
observe a negative coefficient of tenure.
Previous research also documents firms in competitive markets have greater
turnovers rates than their peers in monopolistic markets (for example, Fee and
Hadlock(2000)). Managers under threat of ousting have more incentive to smooth
earnings so that they can improve performance in “poor” years by the slack saved in
“good” years. Hence, Herfindahl-Hirschman index of competition is included as a
measure of product market competition. The positive coefficient of this measure is
consistent with job security hypothesis.
Dye (1988) shows that managers with short horizon distorts earnings to maximize
their contemporaneous benefits while those managers expecting staying long smooth
earnings against long-run trend of earnings. An indicator variable is set to be one if the
current fiscal year is less than three years before CEO’s retirement year. We predict that
the closer CEOs are to retirement, the less earnings smoothing occurs, to the extent that
our measures for earnings smoothing do capture managers’ belief of firms’ future
performance.
Some economic fundamentals may influence the inherent relation between
earnings (or equivalently, accruals) and cash flows. Accrual accounting has more
prominent role to mitigate cash flow fluctuation for a firm with volatile operation than it
does for a firm with stable operation. Revenue volatility then is included as a proxy for
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the volatility of a firm’s underlying operation, which is defined as standard deviation of
revenues in three periods, up to the current period. At last, we add size as a control,
believing that large firms can diversify their operations and generate more stable cash
flows, which results in less earnings smoothing attributed to accounting rule per se. Size
is measured as log of market capitalization.
Table 1 lists definition of dependent and explanatory variables for the analysis.
Descriptive statistics of these variables are presented in Table 2. Most observations have
negative SMTH1, consistent to the reversal nature of accruals. The median firm has
SMTH2 of 0.785, indicating cash flows are effectively smoothed, though without further
investigation, it’s hard to tell how much effect of smoothing can be attributed to
accounting rules or managerial concern to job security. Levels of CEO stock and stock
option holdings increase compared to the sample in Berger et al (1997), seemingly due to
the recent boom in incentive-based compensations. Table 3 further shows the sample
correlation between the variables. The two measures for earnings smoothing have
reasonably high correlation, implying they do capture the common characteristic in the
relation between reported earnings and cash flows. The correlations between dependent
and explanatory variables generally have the same sign as regression coefficient. The
explanatory variables are not highly correlated with each other, the evidence that they
only noisily capture different aspects of managerial entrenchment.
4. Empirical Results Earnings Smoothing after Exogenous Shock to Job Security
By examining how earnings smoothing measures change around exogenous shock
to managers’ job security, we can intuitively understand the relation between these two
variables. Following from the argument in Berger et al. (1997), managers are more
concerned with their job security in the aftermath of failed acquisition attempts.
Managers who ‘survive’ are more likely to resort to earnings smoothing, when faced with
strong demand from investors for consistent performance growth in the
post-acquisition-period.
We search firms experiencing unsuccessful takeover offers during 1995-1996, in
SDC Platinum. The measure for earning smoothing, SMTH1, is computed from annual
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and quarterly data in the period 1993-1999, though firms are not required to exist in the
whole period. Measures for quarterly data are introduced because the short-window
measure can better reveal delicate response of managers to exogenous shock. For
comparison purpose, control firms are randomly matched by 2-digit SIC and market
value at the beginning of the event year. The final sample of takeover firms consists of
797 firm-year observations for 96 firms (1624 firm-quarter observations for 96 firms).
Figure 1 plots how the level of earnings smoothing, measured by annual data,
responds to unsuccessful takeover offers. Specifically, mean values of SMTH1 are plotted
against time, where time 0 is the year unsuccessful takeover offers occur. Opposite to the
smoothing curves of control firms, SMTH1 drops after the event year, though not
statistically significant. Data from sample medians exhibits the similar pattern (not
shown). Figure 2 plots SMTH1 calculated by quarterly data. Before the event quarter
(t<=0) and far after the event quarter (t>4), the two curves for takeover firms and control
firms move in a similar pattern. However, in the period of three quarters after the
announcement of takeover tenders, the two curves diverge. Table 4 shows the comparison
of SMTH1 for takeover firms and controls over quarters around the event. The means of
SMTH1 for two groups are only significantly different up to 3 quarters after the takeover
event. One puzzling issue is the big peak for takeover firms at the event quarter. Such
peak is obviously inconsistent with job security hypothesis, which predicts managers
should actively smooth earnings after takeover offers, in order to satisfy investors’
demand to stable performance growth.
Regression Analysis: Earnings Smoothing and Managerial Entrenchment
Table 5 presents regression estimates of models, with SMTH1 and SMTH2 as
dependent variables. Three different models are used: pooled cross-sectional model
without and with year and industrial dummies.
The results in Table 5 generally support job security hypothesis that less
entrenched managers engage in more earnings smoothing. The parameter estimation is
robust to model specification and measures for dependent variables.
The regressions show a positive and economically significant association
between earnings smoothing proxies and high level of CEO ownership (CEOST_3),
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while insignificant relation for low and median levels of managerial ownership. The
inconsistency is hard to be explained in the current framework. We will explore this issue
in a model with alternative measure for earnings smoothing.
Our results show a significantly positive association between earning smoothing
and CEO vested option holdings. Under the premier that high stock option holdings, as an
indicator of performance-sensitive compensation, result in less managerial entrenchment,
this finding is inconsistent to the negative association predicted by job security argument.
Instead, it may better fit to the argument about risk-taking incentive of stock options.
That’s, stock options make volatile stock price more attractive to managers, since option
value increases with increased return volatility. Consequently, managers have less
incentive to smooth earnings because volatile earnings can cause more fluctuation in
stock price. It may also partially explain why in the regression with SMTH2 as dependent
variable, stock option holdings dominate stock holdings. We were unable to document
any significant association between the measures for CEOs’ excess compensation and
earnings smoothing.
CEO interlock relation, as an indicator for weak internal monitoring mechanism,
is positively correlated with earning smoothing measures, as job security hypothesis
predicts. However, number of blockholders, fails to show significant relation with
dependent variables.
The Herfindahl-Hirschman index (HH index), aimed at proxying for job market
competition faced by managers, is not robust to extra controls. It is partially because HH
index is an industry-specific variable. The indicator for CEO close to departure has a
positive coefficient, implying that managers with short horizon tend to smooth earnings
less. Finally, control variables behave normally in all regressions.
As low correlation among corporate governance variables in Table 3 shows, the
explanatory variables in the regressions at most noisily capture different features of
managerial entrenchment. In order to better assess job security pressure managers may be
faced with in reality, we construct a composite measure from the explanatory variables
available. Such a measure is expected to more comprehensively depict a CEO’s job
security concerns.
The composite measure is obtained from a principal component analysis, based on
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CEO stock holdings, CEO stock option holdings, excess compensation, number of
blockholders, close to departure, and CEO interlock. The results are present in Panel A of
Table 6. The first 4 or 5 principal components capture most of variances in the six raw
variables, 74.9% and 88.6%, respectively. We decide to use the first five principal
components to construct the composite measure. The scores of the composite measure
vary from -5.74 to 15.55. Sample firms are divided into deciles, based on their scores on
the composite measure.
Panel B of Table 6 shows the univariate test of means between two extreme
deciles with highest and lowest scores. Kruskal-Wallis non-parametric test shows firms in
the highest deciles, whose CEOs are faced with the least pressure of ousting threat,
significantly less smooth earnings than their counterparts in the lowest deciles, consistent
with the job security hypothesis. The regressions, using the composite measures, along
with other controls, generate similar results, as presented in Panel C of Table 6. However,
the correspondence between earnings smoothing measure and managerial entrenchment
scores are not strictly monotonic.
5. Model Extension Alternative Measures for Earnings Smoothing
The major criticism to the measures in the previous section is that they do not take
into account different components of accruals. It is well documented in accounting
literature that part of accruals, called “non-discretionary accruals,” are mainly determined
by a firm’s underlying economic process and less subject to managerial discretion. The
concrete examples include accruals directly related to production and real sales and
depreciation. Other categories of accruals, such as accruals from credit sales and
allowance for bad accounts, however, are more likely to be adjusted for manager’s
opportunistic purpose. Hence, a measure using discretionary accruals, instead of total
accruals, is more likely to reveal managers’ opportunistic behaviors. In the following
analysis, we recalculate the correlation by using discretionary accruals and CFO.
Following the literature, we obtain discretionary accruals for firm i in year t using
the residual from the cross-sectional Jones’ model (see Jones (1991), Dechow et al.
18
(1995)), estimated by two-digit SIC code and fiscal year:
TAiτ/Aiτ-1 = α1(1/Aiτ-1) + α2(∆REViτ - ∆RECiτ)/Aiτ-1 + α3(PPEiτ)/Aiτ-1 + �iτ (1)
where TA is total accruals (i.e., earnings before extraordinary items and discontinued
operations less operating cash flows); A is book value at the beginning of period t; ∆REV
is the change in revenues; ∆REC is the change in accounts receivable; PPE is gross
property, plant and equipment. �(�DACC, �CFO), the correlation between changes in
discretionary accruals and CFO, are calculated, following the same procedure in the
previous section.
Regression without and with industrial and year dummies are rerun by using our
new measure for earnings smoothing. The major difference occurs to CEO stock holdings.
As shown in Table 7, low and high levels of CEO stock holdings have significantly
positive coefficients, while median level of stock holdings has significantly negative
coefficients. The results fit well with job security hypothesis and agent theory. Other
variables generally provide consistent evidence to Table 5, such as CEO option holdings,
interlock relation, and close to departure. The controls generally lose the power in the
current model because the construction of dependent variables already takes in accounts
from revenues and sizes.
Managerial Behavior and Investor Clientele
The use of a variable that accounts for the number of blockholders in the
shareholding structure of a firm is a very simple attempt to capture the potential
monitoring power of those large blockholders. However, it is silent about the marginal
investor’s preferences, which are more likely to shed light on our research question. We
use Bushee’s (1998) classification of institutional investors into three categories that
exhibit distinct investing behavior to explore further the effect of shareholding structure
on earnings smoothing.
We summarize Bushee’s method to classify institutional investors based on past
investment behavior. The classification method combines factor and cluster analysis.
Based on prior research, nine variables are constructed from the 13-F SEC filings of
quarterly holdings by institutional investors. We use reported holdings across all
19
firm-quarters over our sample period (1992-1999). The variables are described in Table 7,
and include characteristics of institutions’ choices in terms of portfolio diversification,
turnover, and trading sensitivity to earnings news. The results of the factor analysis are
tabulated in Panel A. We use one more factor than Bushee, since three factors do not
explain enough of the variance in our sample. As Bushee, we can clearly interpret the
factors from their loadings on the variables. The first one (PTURN) measures portfolio
turnover, the second (MOMEN1) and fourth one (MOMEN2) are driven by momentum
trading, while the third one (BLOCK) is closest to the blockholder variable, for it is
characterized by high frequency of blockholding, low portfolio turnover and high
concentration. Using mean factor scores, we then perform a cluster analysis to classify
institutions into three categories. The three-cluster solution, as in Bushee (1998), yields
groups that can be defined as “quasi-indexer”, “transient” and “dedicated” institutions. As
reported in Panel B, “quasi-indexers” exhibit a trading pattern close to buy-and-hold
index strategies, with relatively low turnover and contrarian trading. Two thirds of the
sample fit into this cluster. “Dedicated” institutions hold larger stakes and have a very
low portfolio turnover. They represent a minority (9% of the sample) and are closest to
what Ronen and Saadi (2002) define as VMOs. Finally, “transient” institutions exhibit
high portfolio turnover and momentum trading. Untabulated results show that while the
two other categories are quite stable, about 40% of “transient” institutions switch clusters
from year to year. This is consistent with their characteristics.
We rerun the regressions as in Table 5 by replacing the blockholder measure with
the percentage of shares outstanding held respectively by quasi-indexer, transient and
dedicated. We run the model with each variable taken separately to read more clearly the
effect of each category of shareholders on firms’ earnings smoothing. Results can be
found in Table 8, where we report both the tests using normal and discretionary accruals.
Confirming Table 5, the coefficient on dedicated institutions is not significantly
different from zero, although the sign is as expected. By contrast, transient institutional
holdings are significantly associated with the two smoothing measures, positively as
expected. Indeed, ceteris paribus, the larger the portion of a firm’s shares held by
transient investors, the less accruals smooth earnings, since transient investors will
systematically prefer income increasing accruals (implicitly). This is consistent with
20
Ronen and Yaari (2002) who contend that VM firms will prefer more predictable,
smoother earnings, while PM firms will be driven by more short-term considerations,
therefore their accruals will exhibit a weaker correlation with their cash flows.
Untabulated results show that without industry and year fixed effects, the coefficient on
“dedicated” is significantly negative.
6. Conclusion Fudenburg and Tirole (1995) predict that managers resort to earnings smoothing if
they are concerned with their job security. Our results support their predictions. We find
evidence that level of earnings smoothing is affected by the degree of managerial
entrenchment. The results generally indicate that less entrenched managers seek to
smooth earnings more.
We examine cross-sectional relations between managerial entrenchment and
earnings smoothing, measured by the correlation between changes in total accruals and
changes in cash flows as well as the volatility ratio of net income and cash flows (Myers
and Skinner (1999)). The findings show that measures of earnings smoothing exhibit a
significantly negative association with entrenchment measures (high managerial stock
ownership, interlock situation), risk-taking incentives (stock option holdings) and
short-term horizon (CEO close to departure). The same evidence is obtained in a
principal component factor analysis, in which we construct a composite measure for
managerial entrenchment. An alternative measure using discretionary accruals generates
slightly different results, mainly concentrated on CEO stock option holdings. All results
hold after controlling for industry and year effects, as well as factors correlated with our
earnings smoothing proxies.
We extend our analysis by controlling for investor clientele, considering investors’
preferences should influence managers’ behavior to a substantial extant. Consistent with
Ronen and Yaari (2002)’s prediction, we find that the larger the stake of transient
(dedicated) investors in a firm-year, the less (more) managers smooth earnings.
21
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Working Paper. New York University.
23
Table 1: Variable Definition
Dependent Variable Abbreviation Definition Income smoothing Measure I
SMTH1 Correlation between changes in total accruals and cash flows from operation over the next years, excluding the current year
Income smoothing Measure II
SMTH2 Standard deviations of net income over standard deviation of cash flows from operation over the next years, excluding the current year
Explanatory Variable Abbreviation Definition CEO tenure Tenure Years in CEO position CEO stock holdings Ceost Shares owned by CEO / outstanding common
stock shares CEO option holdings Ceoopt Exercisable options held / outstanding common
stock shares Excess compensation Excomp Difference between a CEO’s fixed compensation
(salary plus bonus) and the industrial average Average number of blockholders(5%)
Block Average number of institutions owning 5% or more of shares outstanding
CEO Close to departure
Cls_dep Dummy variable set equal to 1 if the year when the CEO left position is less than three years from the current year; 0 otherwise
Interlock Intlock Dummy variable set equal to 1 if the CEO involves in a relationship requiring disclosure in the “Compensation Committee Interlocks and Insider Participation” section of the proxy; 0 otherwise.
Control Variable Abbreviation Definition Size Size Market value of equity at the beginning of the
fiscal year Revenue volatility Revvol Standard deviation of revenues over the next
years, excluding the current year Product market competition
HHind Herfindahl-Hirschman index of competition,
calculated as [ ]2
1
/�=
n
ii Ss , where si = firm i’s
sales, S = the sum of sales for all firms in the industry; n = the number of firms in the industry
24
Table 2: Descriptive Statistics
Variable N Mean Standard
deviation Q1 Median Q3
Smoothing Measures �(�ACC, �CFO) 6002 -0.596 0.589 -0.988 -0.908 -0.460 �NI/�CFO 6002 1.388 2.085 0.412 0.785 1.457
Managerial Entrenchment Excess compensation 6002 0.056 0.813 -0.480 -0.149 0.341 CEO option holdings 6002 0.007 0.010 0.001 0.004 0.009 CEO stock holdings 6002 0.036 0.069 0.001 0.006 0.030 CEO tenure 5560 8.313 7.707 3.000 6.000 11.000 Number of blockholders 4961 1.575 1.186 0.750 1.500 2.250 Product market competition
6002 0.056 0.050 0.035 0.044 0.066
Dummies Interlock 6002 0.116 0.320 0.000 0.000 0.000 Close to departure 3371 0.407 0.491 0.000 0.000 1.000
Controls Size 6002 3,714.4 10317.1 316.5 794.5 2,607.2 Revenue volatility 6002 492.3 1,244.7 45.5 122.1 378.1
The sample period is between 1992 and 1999. The definition of all variables refers to Table I.
25
Table 3: Correlation Matrix
SMTH1 SMTH2 Tenure Ceost Ceoopt Excomp Block Inv_dep Cls_dep Size Revvol HHind
SMTH1 0.338*** -.021 0.056*** -.029** 0.004 0.007 -.028** -.080*** 0.065*** -.024* -.001
SMTH2 0.571*** 0.003 0.026** -.017 -.013 -.001 -.015 -.045*** 0.068*** -.010 0.012
Tenure -.023* -.017 -.022* -.153*** -.099*** -.056*** 0.049*** 0.028** -.025 0.383*** 0.406***
Ceost 0.084*** 0.052*** -.053*** -.028** 0.143*** 0.007 0.037*** -.036*** 0.004 -.128*** -.154***
Ceoopt -.073*** -.054*** -.295*** 0.013 -.125*** 0.129*** 0.371*** -.001 -.030* -.092*** -.099***
Excomp 0.014 -.014 -.065*** 0.239*** -.012 -.067*** -.098*** 0.041*** 0.059*** -.151*** -.229***
Block -.003 -.004 -.095*** -.042*** 0.146*** -.069*** 0.135*** -.026** -.018 -.045*** -.050***
Inv_dep -.011 -.015 0.023* 0.035*** 0.442*** -.067*** 0.121*** 0.063*** 0.021 -.052*** -.041***
Cls_dep -.070*** -.079*** 0.060*** -.008 0.055*** 0.041*** -.003 0.031** -.021 0.008 -.061***
Size 0.078*** 0.066*** -.029* 0.018 -.021 0.045** -.018 0.045** -.016 -.043** 0.021
Revvol -.048*** -.033** 0.526*** -.218*** -.281*** -.098*** -.073*** -.026* 0.062*** -.076*** 0.562***
HHind 0.035*** 0.024* 0.593*** -.291*** -.378*** -.214*** -.076*** -.007 -.085*** 0.017 0.651***
Pearson correlations (Spearman correlations in the low triangle) between variables are shown. Significant at 1 percent (***), 5 percent (**), and 10 percent (*). The definition of all variables refers to Table I.
26
Table 4: Earnings smoothing around Exogenous Shock to Job Security
Quarterly SMTH1 �(�ACC, �CFO) Takeover Firms Control Firms
t # of Obs Mean # of Obs Mean
Right-sided Wilcoxon Test
(P-value)
Kruskal-Wallis Test (P-value)
-4 97 -0.588 174 -0.614 0.188 0.376 -3 101 -0.611 185 -0.587 0.366 0.731 -2 100 -0.633 191 -0.592 0.19 0.38 -1 101 -0.634 192 -0.636 0.129 0.258 0 96 -0.463 194 -0.69 0.011 0.023 1 98 -0.575 196 -0.694 0.024 0.048 2 100 -0.59 213 -0.674 0.01 0.019 3 104 -0.579 203 -0.606 0.166 0.332 4 99 -0.57 199 -0.636 0.148 0.295
The takeover sample represents 96 firms which experience unsuccessful tender offers in 1995-1996. Period 0 is the quarter when tender offers are announced. The control sample is matched by two-digit SIC and market value at the beginning of the event year. SMTH1 is calculated over fiscal quarters.
27
Table 5: Regression Analysis: Effect of Managerial Entrenchment on Earnings Smoothing
OLS regression coefficients for models of earnings smoothing. The sample consists of 2,497 firm-year observations from 1992 to 1999. For each of the two measures of earnings smoothing, the table shows estimates from models with and without industry and year dummies. SMTH1
�(�ACC, �CFO) SMTH2
�NI/�CFO Industry and Year Dummies No Yes No Yes Excess compensation 0.003 -0.014 -0.024 -0.04 (0.16) (-0.75) (-0.36) (-0.58) CEO option holdings 4.826*** 5.911*** 11.444** 12.527** (3.18) (3.86) (2) (2.15) CEO stock holdings-1 -1.151 -0.277 1.208 1.737 (-1.12) (-0.27) (0.31) (0.44) CEO stock holdings-2 -0.445 -0.305 -1.745 -1.611 (-0.99) (-0.68) (-1.03) (-0.94) CEO stock holdings-3 3.551*** 3.348*** 6.765 7.301 (3.01) (2.83) (1.52) (1.62) Blockholders 0.005 0.01 -0.023 -0.009 (0.51) (0.94) (-0.58) (-0.21) Interlock 0.061 0.073* 0.211 0.246* (1.58) (1.88) (1.45) (1.67) CEO tenure -0.004 -0.001 -0.024 0.002 (-0.26) (-0.53) (-0.46) (0.3) Product market -0.498** 0.528 -1.284 2.639 competition (-2.09) (1.19) (-1.43) (1.56) Close to departure 0.06** 0.044* 0.246*** 0.21** (2.56) (1.85) (2.78) (2.32) Revenue volatility -0.042*** -0.024** -0.165*** -0.107** (-4.09) (-2.1) (-4.22) (-2.52) Size 0.043*** 0.04*** 0.145*** 0.103** (3.53) (2.95) (3.13) (1.99) Adj R-Sq 0.0225 0.0683 0.0145 0.0389 F Value 5.794 4.518 4.070 2.943 Pr > F 0.000 0.000 0.000 0.000 *,**,*** indicate significance at the 0.10, 0.05 and 0.01 levels. Heteroscedasticity-consistent t-statistic values are shown in parentheses. All variables are described in Table 1, except:
28
Ceost_1: stock holdings if stock holdings <5%, 5% otherwise Ceost_2: 0 if stock holdings <5%, stock holdings minus 5% if 5% ≤ stock holdings ≤ 25%, 20% if stock holdings>25% Ceost_3: 0 if stock holdings<25%, stock holdings minus 25% if stock holdings ≥ 25% Industry dummies are defined at the two-digit SIC level.
29
Table 6: Regression Analysis: the Composite Measure for Managerial Entrenchment and Earnings Smoothing
Panel A: Principal Component Analysis �
Prin1 Prin2 Prin3 Prin4 Prin5 Prin6 Excess compensation -0.358 -0.6 -0.078 0.32 0.113 0.625 CEO stock holdings -0.251 0.655 0.198 -0.261 0.13 0.619 CEO option holdings 0.564 0.109 -0.255 0.239 0.726 0.143
Blockholders 0.64 -0.033 -0.119 -0.033 -0.612 0.447 Close to departure 0.242 -0.112 0.929 0.246 0.072 0.008
Interlock -0.148 0.431 -0.113 0.843 -0.253 -0.071 Cumulative Proportion
of Variance 0.219 0.428 0.592 0.749 0.886 1
The sample includes 2695 firm-year observations. All variables are standardized before computation. Panel B: Univariate Test for Measures of Earnings Smoothing over Extreme Deciles
Composite Measure Decilesa
Mean Score SMTH1b �(�ACC, �CFO)
SMTH2b �NI/�CFO
Lowest -2.60 -0.658 1.184 Highest 3.9 -0.484 1.988
Chi-Square for Kruskal-Wallis Test 9.46*** 8.67*** a: The composite measure consists of 5 principal components. The sample is divided into deciles based on scores of the composite measure. b: Mean of the dependent variable in the decile. Panel C: Regression Analysis: Using the Composite Measure
SMTH1 �(�ACC, �CFO)
SMTH2 �NI/�CFO
Industry and Year Dummies No Yes No Yes Composite Measure 0.021***
(4.05) 0.024***
(4.46) 0.070***
(3.60) 0.075***
(3.71) Size 0.047***
(4.61) 0.037***
(3.30) 0.156***
(4.15) 0.106** (2.56)
Revenue volatility -0.037*** (-3.80)
-0.020* (-1.94)
-0.152*** (-4.20)
-0.094** (-2.40)
HHind -0.579** (-2.57)
0.347 (0.82)
-1.503* (-1.79)
2.303 (1.45)
R2 0.02 0.06 0.02 0.04 *,**,*** indicate significance at the 0.10, 0.05 and 0.01 levels. Heteroscedasticity-consistent t-statistics are shown in parentheses. The composite measure of managerial entrenchment consists of 5 principal components. Refer to Table I for definition of all other variables.
30
Table 7: Regression Analysis: Alternative Measures for Earnings Smoothing and Managerial Entrenchment
OLS regression coefficients for models of earnings smoothing. The sample consists of 2,483 firm-year observations from 1992 to 1999. The table shows estimates from models with and without industry and year dummies. SMTH3 is the correlation between change in discretionary accruals and change in cash flows from operation. Discretionary accruals for firm i in year t are residuals from the following model, estimated by two-digit SIC code and fiscal year (see Jones [1991], Dechow et al. [1995]) :
TAiτ/Aiτ-1 = α1(1/Aiτ-1) + α2(∆REViτ - ∆RECiτ)/Aiτ-1 + α3(PPEiτ)/Aiτ-1 + �iτ where TA is total accruals; A is book value at the beginning of period t; ∆REV is change in revenues; ∆REC is change in accounts receivable; PPE is gross property, plant and equipment. SMTH3
�(�DACC, �CFO) Industry and Year Dummies No Yes Excess compensation 0.032 0.016 (1.46) (0.73) CEO option holdings 3.353* 1.763 (1.79) (0.94) CEO stock holdings-1 -1.938 -2.987** (-1.53) (-2.36) CEO stock holdings-2 1.15** 1.489*** (2.07) (2.71) CEO stock holdings-3 -2.549* -2.885** (-1.74) (-2) Blockholders 0.014 -0.005 (1.09) (-0.37) Interlock 0.07 0.089* (1.46) (1.89) CEO tenure 0 0.001 (-0.01) (0.47) Product market -1.314*** -0.519 competition (-4.44) (-0.96) Close to departure 0.026 -0.01 (0.88) (-0.35) Revenue volatility -0.04*** -0.006 (-3.14) (-0.45) Size 0.061*** 0.02 (3.98) (1.22) Adj R-Sq 0.0244 0.0921 F Value 6.164 5.839 Pr > F <.001 <.001 *,**,*** indicate significance at the 0.10, 0.05 and 0.01 levels. Heteroscedasticity-consistent t-statistics are shown in parentheses.
31
Table 8: Institutional Investor Portfolio Characteristics Panel A: Factor Analysis Variable Factor 1 Factor 2 Factor 3 Factor 4 APH 0.892 -0.000 -0.025 0.038 LBPH 0.905 -0.035 -0.002 0.033 HERF 0.567 0.003 0.477 -0.127 CONC -0.030 0.006 0.712 0.233 PT 0.019 0.005 -0.706 -0.005 LTPH 0.120 0.010 0.705 -0.082 NBCES -0.016 0.987 0.004 0.013 NTCES -0.016 0.987 0.006 0.015 NCCES 0.020 0.023 0.064 0.973 Variance Explained
30% 25% 12% 11%
Panel B: Cluster Analysis Mean Factor Scores Cluster % PTURN MOMEN1 BLOCK MOMEN2 Quasi-indexers 64.7 -0.194 0.004 -0.194 -0.236 Transient 27.6 0.322 0.074 -0.271 0.169 Dedicated 8.7 -0.544 0.011 1.389 -0.240 APH: Average stake size
ktkt NSTKw /� LBPH: Percent held in large blocks
ktktkt wPHw �� /)( HERF: Herfindahl measure of
concentration ktktkt wLBw �� /)(
CONC: Portfolio concentration )ln( 2ktPH�
PT: Portfolio turnover )/(|| 1, −+�∆� tkktkt www
LTPH: Percent held for two years ktktkt wLTw �� /)(
NBCES: Net buy sensitivity to earnings news
]}0|[]0|){[/1( <∆�−>∆� ktktktkt wRWEwRWEN
NTCES: Trading sensitivity to earnings news
||/)( ktktkt wRWEw ∆�∆�
NCCES: Net change in holdings based on earnings news ktktktktkt wRWEwRWEw ∆�<∆�−>∆� |/]}0|[]0|{[
where NSTKkt # of stocks owned by institution k at quarter t wkt Portfolio weight (shares held times stock price) in firm k at quarter t PHkt Percentage of total shares in firm k held by institution at quarter t LBkt 1 if PH>0, 0 otherwise LTkt 1 if institution held stock continuously for prior eight quarters, 0 otherwise RWEkt Seasonal random walk change in quarterly earnings per share of firm k at quarter t
(deflated by sales at quarter t-4)
32
Table 9: Regression Analysis: with Investor Clientele
OLS regression coefficients for models of earnings smoothing. The sample consists of 2,224 firm-year observations from 1992 to 1999. The table shows estimates from models with and without industry and year dummies. SMTH1 and SMTH3 are defined as in Table I and Table 7. Quasi-indexer, Transient and Dedicated, which are defined as the percentage of total shares outstanding held by each of the three groups identified in Table 8. SMTH1
�(�ACC, �CFO) SMTH3
�(�DACC, �CFO) (1) (2) (3) (4) (5) (6)
-0.01 -0.013 -0.01 0.01 0.008 0.009 Excess compensation (-0.53) (-0.69) (-0.55) (0.41) (0.34) (0.39)
5.553*** 5.499*** 5.52*** 2.768 2.76 2.743 CEO option holdings (3.33) (3.31) (3.31) (1.35) (1.34) (1.34)
-0.678 -0.484 -0.681 -3.08** -2.958** -3.057** Ceost_1 (-0.62) (-0.45) (-0.62) (-2.29) (-2.2) (-2.27)
-0.213 -0.225 -0.171 1.278** 1.247** 1.301** Ceost_2 (-0.45) (-0.48) (-0.36) (2.18) (2.14) (2.23)
3.307*** 3.213*** 3.213*** -2.546* -2.555* -2.613* Ceost_3 (2.72) (2.65) (2.64) (-1.7) (-1.71) (-1.75)
0.077* 0.08** 0.082** 0.112** 0.112** 0.116** Interlock (1.89) (1.98) -0.01 (2.24) (2.23) (2.31)
0.00 0.00 -0.002 0.016 0.017 0.015 CEO tenure (-0.03) (0.01) (-0.11) (0.86) (0.91) (0.82)
0.508 0.534 0.511 -0.547 -0.534 -0.541 Product market competition (1.05) (1.11) (1.06) (-0.92) (-0.9) (-0.91)
0.049** 0.046* 0.05** -0.018 -0.02 -0.017 Close to departure (1.96) (1.84) (2.01) (-0.57) (-0.65) (-0.55)
-0.03** -0.031*** -0.029** -0.009 -0.01 -0.008 Revenue volatility (-2.48) (-2.59) (-2.44) (-0.57) (-0.64) (-0.57)
0.05*** 0.033** 0.036** 0.026 0.023 0.016 Size (3.14) (2.39) (2.18) (1.34) (1.35) (0.8)
-0.488* -0.045 Quasi-indexer
(-1.81) (-0.14)
2.233*** 1.367* Transient
(3.91) (1.93)
-0.009 -0.299 Dedicated (-0.03) (-0.83)
Adj R-Sq 0.0683 0.0734 0.0669 0.0976 0.0992 0.0979 F Value 4.20 4.45 4.12 5.66 5.75 5.68 Pr > F 0.000 0.000 0.000 0.000 0.000 0.000
*,**,*** indicate significance at the 0.10, 0.05 and 0.01 levels. Heteroscedasticity-consistent t-statistics are shown in parentheses.
33
Figure 1. Earnings Smoothing around Exogenous Shock to Job Security. The figure shows mean level of the annual measure for earnings smoothing (SMTH1) for sample firms that experience an unsuccessful tender offer. Observations represent a sample of 797 firm-year observations for 96 firms. The control sample is matched by two-digit SIC and market value at the end of year -1.
34
Figure 2. Earnings Smoothing around Exogenous Shock to Job Security. The figure shows mean level of the quarterly measure for earnings smoothing (SMTH1) for sample firms that experience an unsuccessful tender offer. Observations represent a sample of 1624 firm-quarter observations for 96 firms. The control sample is matched by two-digit SIC and market value at the end of year -1.
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