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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.

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(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.